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Sample records for biologically inspired model

  1. Bio-inspired motion estimation – From modelling to evaluation, can biology be a source of inspiration?

    OpenAIRE

    Tlapale, Émilien; Kornprobst, Pierre; Masson, Guillaume; Faugeras, Olivier; Bouecke, Jan,; Neumann, Heiko

    2010-01-01

    We propose a bio-inspired approach to motion estimation based on recent neuroscience findings concerning the motion pathway. Our goal is to identify the key biological features in order to reach a good compromise between bio-inspiration and computational efficiency. Here we choose the neural field formalism which provides a sound mathematical framework to describe the model at a macroscopic scale. Within this framework we define the cortical activity as coupled integro-differential equations ...

  2. 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...

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

    Science.gov (United States)

    Knuuttila, Tarja; Loettgers, Andrea

    2013-06-01

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

  4. Biologically Inspired Model for Visual Cognition Achieving Unsupervised Episodic and Semantic Feature Learning.

    Science.gov (United States)

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

    2016-10-01

    Recently, many biologically inspired visual computational models have been proposed. The design of these models follows the related biological mechanisms and structures, and these models provide new solutions for visual recognition tasks. In this paper, based on the recent biological evidence, we propose a framework to mimic the active and dynamic learning and recognition process of the primate visual cortex. From principle point of view, the main contributions are that the framework can achieve unsupervised learning of episodic features (including key components and their spatial relations) and semantic features (semantic descriptions of the key components), which support higher level cognition of an object. From performance point of view, the advantages of the framework are as follows: 1) learning episodic features without supervision-for a class of objects without a prior knowledge, the key components, their spatial relations and cover regions can be learned automatically through a deep neural network (DNN); 2) learning semantic features based on episodic features-within the cover regions of the key components, the semantic geometrical values of these components can be computed based on contour detection; 3) forming the general knowledge of a class of objects-the general knowledge of a class of objects can be formed, mainly including the key components, their spatial relations and average semantic values, which is a concise description of the class; and 4) achieving higher level cognition and dynamic updating-for a test image, the model can achieve classification and subclass semantic descriptions. And the test samples with high confidence are selected to dynamically update the whole model. Experiments are conducted on face images, and a good performance is achieved in each layer of the DNN and the semantic description learning process. Furthermore, the model can be generalized to recognition tasks of other objects with learning ability.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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

  10. Biologically inspired coupled antenna beampattern design

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-12-15

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

  11. Biological Inspiration in Human Centred Robotics

    Institute of Scientific and Technical Information of China (English)

    HU Huo-sheng; LIU Jin-dong; Calderon Carlos A

    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.

  12. Biologically inspired autonomouse system; Seibutsugata jiritsu system

    Energy Technology Data Exchange (ETDEWEB)

    Yuta, S. [Tsukuba Univ., Ibaraki (Japan)

    1996-04-10

    The intelligence robot was begun to try to make up a machine to imitate the human intelligent actions as a model of human thoughts. However, robots created with the results of traditional artificial intelligence based on the logical knowledge impression and logic judgement have been found to be unable to realize the usual actions conducted by humans and animals even though having superior brains or remembrances. Research on `The biological inspired autonomous robots` in the intelligence robots, aims to peruse a method to realize on a machine not for high class intelligence capable to execute logical thoughts down by human but for intelligence corresponding to ability response to environment autonomously and to live in a given environment which is had even by animals except human being. Here is examined on the non-human biological type robot and its intelligence under a center of research on the biological inspired autonomous system in the intelligence robots, and is outlined on their research field. 2 refs., 1 fig.

  13. 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.

  14. 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.

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

    Science.gov (United States)

    Ghodrati, Masoud; Khaligh-Razavi, Seyed-Mahdi; Ebrahimpour, Reza; Rajaei, Karim; Pooyan, Mohammad

    2012-01-01

    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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. A Biologically Inspired CMOS Image Sensor

    NARCIS (Netherlands)

    Sarkar, M.

    2011-01-01

    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

  2. Biology-Inspired Autonomous Control

    Science.gov (United States)

    2011-08-31

    of, and perhaps will not be tolerated in, manmade critical systems. Although this paper does not directly address questions of ethics associated...political, ethical , and moral issues associated with the use of autonomous systems in warfare will be debated long after the technology hurdles to...accessible discussion on the interplay of biochemistry, genetics and embryology in animal evolution; Wagner, 2005 describes biological concepts of

  3. 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.

  4. 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

  5. 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.

  6. Biology-inspired Architecture for Situation Management

    Science.gov (United States)

    Jones, Kennie H.; Lodding, Kenneth N.; Olariu, Stephan; Wilson, Larry; Xin, Chunsheng

    2006-01-01

    Situation Management is a rapidly developing science combining new techniques for data collection with advanced methods of data fusion to facilitate the process leading to correct decisions prescribing action. Current research focuses on reducing increasing amounts of diverse data to knowledge used by decision makers and on reducing time between observations, decisions and actions. No new technology is more promising for increasing the diversity and fidelity of observations than sensor networks. However, current research on sensor networks concentrates on a centralized network architecture. We believe this trend will not realize the full potential of situation management. We propose a new architecture modeled after biological ecosystems where motes are autonomous and intelligent, yet cooperate with local neighborhoods. Providing a layered approach, they sense and act independently when possible, and cooperate with neighborhoods when necessary. The combination of their local actions results in global effects. While situation management research is currently dominated by military applications, advances envisioned for industrial and business applications have similar requirements. NASA has requirements for intelligent and autonomous systems in future missions that can benefit from advances in situation management. We describe requirements for the Integrated Vehicle Health Management program where our biology-inspired architecture provides a layered approach and decisions can be made at the proper level to improve safety, reduce costs, and improve efficiency in making diagnostic and prognostic assessments of the structural integrity, aerodynamic characteristics, and operation of aircraft.

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

    Science.gov (United States)

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

    2015-11-01

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

  8. Biologically Inspired Intercellular Slot Synchronization

    Directory of Open Access Journals (Sweden)

    Alexander Tyrrell

    2009-01-01

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

  9. 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.

  10. Biologically inspired intelligent decision making

    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

  11. On the Optimum Architecture of the Biologically Inspired Hierarchical Temporal Memory Model Applied to the Hand-Written Digit Recognition

    Science.gov (United States)

    Štolc, Svorad; Bajla, Ivan

    2010-01-01

    In the paper we describe basic functions of the Hierarchical Temporal Memory (HTM) network based on a novel biologically inspired model of the large-scale structure of the mammalian neocortex. The focus of this paper is in a systematic exploration of possibilities how to optimize important controlling parameters of the HTM model applied to the classification of hand-written digits from the USPS database. The statistical properties of this database are analyzed using the permutation test which employs a randomization distribution of the training and testing data. Based on a notion of the homogeneous usage of input image pixels, a methodology of the HTM parameter optimization is proposed. In order to study effects of two substantial parameters of the architecture: the patch size and the overlap in more details, we have restricted ourselves to the single-level HTM networks. A novel method for construction of the training sequences by ordering series of the static images is developed. A novel method for estimation of the parameter maxDist based on the box counting method is proposed. The parameter sigma of the inference Gaussian is optimized on the basis of the maximization of the belief distribution entropy. Both optimization algorithms can be equally applied to the multi-level HTM networks as well. The influences of the parameters transitionMemory and requestedGroupCount on the HTM network performance have been explored. Altogether, we have investigated 2736 different HTM network configurations. The obtained classification accuracy results have been benchmarked with the published results of several conventional classifiers.

  12. 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.

  13. Sensory architectures for biologically inspired autonomous robotics.

    Science.gov (United States)

    Higgins, C M

    2001-04-01

    Engineers have a lot to gain from studying biology. The study of biological neural systems alone provides numerous examples of computational systems that are far more complex than any man-made system and perform real-time sensory and motor tasks in a manner that humbles the most advanced artificial systems. Despite the evolutionary genesis of these systems and the vast apparent differences between species, there are common design strategies employed by biological systems that span taxa, and engineers would do well to emulate these strategies. However, biologically-inspired computational architectures, which are continuous-time and parallel in nature, do not map well onto conventional processors, which are discrete-time and serial in operation. Rather, an implementation technology that is capable of directly realizing the layered parallel structure and nonlinear elements employed by neurobiology is required for power- and space-efficient implementation. Custom neuromorphic hardware meets these criteria and yields low-power dedicated sensory systems that are small, light, and ideal for autonomous robot applications. As examples of how this technology is applied, this article describes both a low-level neuromorphic hardware emulation of an elementary visual motion detector, and a large-scale, system-level spatial motion integration system.

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

    Science.gov (United States)

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

    2014-04-01

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

  15. 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.

  16. Synthetic biology, inspired by synthetic chemistry.

    Science.gov (United States)

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

    2012-07-16

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

  17. 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...

  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. Dynamical Systems and Control Theory Inspired by Molecular Biology

    Science.gov (United States)

    2014-10-02

    in both bacterial and eukaryotic signaling pathways. A common theme in the systems biology literature is that certain systems whose output variables...AFRL-OSR-VA-TR-2014-0282 DYNAMICAL SYSTEMS AND CONTROL THEORY INSPIRED BY MOLECULAR BIOLOGY Eduardo Sontag RUTGERS THE STATE UNIVERSITY OF NEW JERSEY...Standard Form 298 (Re . 8-98) v Prescribed by ANSI Std. Z39.18 DYNAMICAL SYSTEMS AND CONTROL THEORY INSPIRED BY MOLECULAR BIOLOGY AFOSR FA9550-11-1-0247

  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. Self-organization, embodiment, and biologically inspired robotics.

    Science.gov (United States)

    Pfeifer, Rolf; Lungarella, Max; Iida, Fumiya

    2007-11-16

    Robotics researchers increasingly agree that ideas from biology and self-organization can strongly benefit the design of autonomous robots. Biological organisms have evolved to perform and survive in a world characterized by rapid changes, high uncertainty, indefinite richness, and limited availability of information. Industrial robots, in contrast, operate in highly controlled environments with no or very little uncertainty. Although many challenges remain, concepts from biologically inspired (bio-inspired) robotics will eventually enable researchers to engineer machines for the real world that possess at least some of the desirable properties of biological organisms, such as adaptivity, robustness, versatility, and agility.

  5. Kirigami artificial muscles with complex biologically inspired morphologies

    Science.gov (United States)

    Sareh, Sina; Rossiter, Jonathan

    2013-01-01

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

  6. 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.

  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. 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.

  9. 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.

  10. A Biologically-Inspired Symmetric Bidirectional Switch

    Science.gov (United States)

    Song, Kahye; Chang, Shyr-Shea; Roper, Marcus; Kim, Hyejeong; Lee, Sang Joon

    2017-01-01

    Stimuli-sensitive hydrogels have been intensively studied because of their potential applications in drug delivery, cell culture, and actuator design. Although hydrogels with directed unidirectional response, i.e. capable of bending actuated by different chemical components reaction in response to several stimuli including water and electric fields, these hydrogels are capable of being actuated in one direction only by the stimulus. By contrast the challenge of building a device that is capable of responding to the same cue (in this case a temperature gradient) to bend in either direction remains unmet. Here, inspired by the structure of pine cone scales, we design a temperature-sensitive hydrogel with bending directed an imposed fishing line. The layers with same PNIPAAm always shrinks in response to the heat. Even the layers made with different chemical property, bends away from a warm surface, whether the warm surface is applied at its upper or lower boundary. To design the bending hydrogel we exploited the coupled responses of the hydrogel; a fishing line intercalating structure and change its construction. In addition to revealing a new capability of stimulus sensitive hydrogels, our study gives insight into the structural features of pine cone bending. PMID:28068391

  11. Biologically Inspired Robots to Assist Areonauts on the Martian Surface

    Science.gov (United States)

    Scott, G. P.; Saaj, C. M.

    Long before humans set foot on the surface of Mars, significant exploration of the surface will have been completed. Orbital spacecraft have certainly helped provide information about the surface to date, but significant advances are made through surface-based exploration. Not only does this include the Viking landers of years past, but also current and next generation mobile robots traversing the surface with scientific experiments for humans to better learn about this mostly unexplored environment. Many robotic vehicles have been proposed in recent years to assist astronauts on planetary surfaces. Only a few of these vehicles, or some aspects therein, have been inspired from biological creatures. With regards to the vehicle's locomotion system, looking into biologically inspired concepts is incredibly important because of the expectation of these astronauts exploring more complex terrain than current wheeled robotic explorers have yet traversed. This paper will review a number of robotic systems designed to assist Mars areonauts (astronauts specifically exploring Mars) before proposing a multi-purpose legged microrover assistant. This vehicle has a biologically inspired locomotion system which provides the capability to follow the areonauts over the most complex Martian terrain, or even traverse areas too complex for the areonaut to negotiate, in order to perform on-the-spot scientific experimentation as needed. The results of the biologically inspired vehicle's capability to traverse Mars terrain, both with regards to tractive capability in soil and ability to access more hostile terrain than its wheeled or tracked counterparts, will also be presented.

  12. 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…

  13. Trusted computation through biologically inspired processes

    Science.gov (United States)

    Anderson, Gustave W.

    2013-05-01

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

  14. Semiconductor Devices Inspired By and Integrated With Biology

    Energy Technology Data Exchange (ETDEWEB)

    Rogers, John [University of Illinois

    2012-04-25

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

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

    Science.gov (United States)

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

    2013-12-01

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

  16. Bits from Brains for Biologically-Inspired Computing

    Directory of Open Access Journals (Sweden)

    Michael eWibral

    2015-03-01

    Full Text Available Inspiration for artificial biologically-inspired computing is often drawn from neural systems. This article shows how to analyze neural systems using information theory with the aim of obtaining constraints that help to identify the algorithms run by neural systems and the information they represent. Algorithms and representations identified this way may then guide the design of biologically inspired computing systems. The material covered includes the necessary introduction to information theory and to the estimation of information theoretic quantities from neural recordings. We then show how to analyze the information encoded in a system about its environment, and also discuss recent methodological developments on the question of how much information each agent carries about the environment either uniquely, or redundantly or synergistically together with others. Last, we introduce the framework of local information dynamics, where information processing is partitioned into component processes of information storage, transfer, and modification -- locally in space and time. We close by discussing example applications of these measures to neural data and other complex systems.

  17. 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.

  18. 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 ...

  19. 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...

  20. 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.

  1. Platensimycin and platencin: Inspirations for chemistry, biology, enzymology, and medicine.

    Science.gov (United States)

    Rudolf, Jeffrey D; Dong, Liao-Bin; Shen, Ben

    2016-11-16

    Natural products have served as the main source of drugs and drug leads, and natural products produced by microorganisms are one of the most prevalent sources of clinical antibiotics. Their unparalleled structural and chemical diversities provide a basis to investigate fundamental biological processes while providing access to a tremendous amount of chemical space. There is a pressing need for novel antibiotics with new mode of actions to combat the growing challenge of multidrug resistant pathogens. This review begins with the pioneering discovery and biological activities of platensimycin (PTM) and platencin (PTN), two antibacterial natural products isolated from Streptomyces platensis. The elucidation of their unique biochemical mode of action, structure-activity relationships, and pharmacokinetics is presented to highlight key aspects of their biological activities. It then presents an overview of how microbial genomics has impacted the field of PTM and PTN and revealed paradigm-shifting discoveries in terpenoid biosynthesis, fatty acid metabolism, and antibiotic and antidiabetic therapies. It concludes with a discussion covering the future perspectives of PTM and PTN in regard to natural products discovery, bacterial diterpenoid biosynthesis, and the pharmaceutical promise of PTM and PTN as antibiotics and for the treatment of metabolic disorders. PTM and PTN have inspired new discoveries in chemistry, biology, enzymology, and medicine and will undoubtedly continue to do so.

  2. 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...

  3. 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.

  4. Biologically Inspired Self-Stabilizing Control for Bipedal Robots

    Directory of Open Access Journals (Sweden)

    Woosung Yang

    2013-02-01

    Full Text Available Despite recent major advances in computational power and control algorithms, the stable and robust control of a bipedal robot is still a challenging issue due to the complexity and high nonlinearity of robot dynamics. To address the issue an efficient and powerful alternative based on a biologically inspired control framework employing neural oscillators is proposed and tested. In a numerical test the virtual force controller combined with the neural oscillator of a humanoid robot generated rhythmic control signals and stable bipedal locomotion when coupled with proper impedance components. The entrainment nature inherent to neural oscillators also achieved stable and robust walking even in the presence of unexpected disturbances, in that the centre of mass (COM was successfully kept in phase with the zero moment point (ZMP input trajectory. The efficiency of the proposed control scheme is discussed alongside simulation results.

  5. 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.

  6. 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.

  7. 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 ...

  8. 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.

  9. 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

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

    Directory of Open Access Journals (Sweden)

    Zlatogor Minchev

    2005-12-01

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

  11. 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.

  12. Classification of biological cells using bio-inspired descriptors

    OpenAIRE

    Bel Haj Ali, Wafa; Giampaglia, Dario; Barlaud, Michel; Piro, Paolo; Nock, Richard; Pourcher, Thierry

    2012-01-01

    International audience; This paper proposes a novel automated approach for the categorization of cells in fluorescence microscopy images. Our supervised classification method aims at recognizing patterns of unlabeled cells based on an annotated dataset. First, the cell images need to be indexed by encoding them in a feature space. For this purpose, we propose tailored bio-inspired features relying on the distribution of contrast information. Then, a supervised learning algorithm is proposed f...

  13. 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

  14. A cognitive computational model inspired by the immune system response.

    Science.gov (United States)

    Abdo Abd Al-Hady, Mohamed; Badr, Amr Ahmed; Mostafa, Mostafa Abd Al-Azim

    2014-01-01

    The immune system has a cognitive ability to differentiate between healthy and unhealthy cells. The immune system response (ISR) is stimulated by a disorder in the temporary fuzzy state that is oscillating between the healthy and unhealthy states. However, modeling the immune system is an enormous challenge; the paper introduces an extensive summary of how the immune system response functions, as an overview of a complex topic, to present the immune system as a cognitive intelligent agent. The homogeneity and perfection of the natural immune system have been always standing out as the sought-after model we attempted to imitate while building our proposed model of cognitive architecture. The paper divides the ISR into four logical phases: setting a computational architectural diagram for each phase, proceeding from functional perspectives (input, process, and output), and their consequences. The proposed architecture components are defined by matching biological operations with computational functions and hence with the framework of the paper. On the other hand, the architecture focuses on the interoperability of main theoretical immunological perspectives (classic, cognitive, and danger theory), as related to computer science terminologies. The paper presents a descriptive model of immune system, to figure out the nature of response, deemed to be intrinsic for building a hybrid computational model based on a cognitive intelligent agent perspective and inspired by the natural biology. To that end, this paper highlights the ISR phases as applied to a case study on hepatitis C virus, meanwhile illustrating our proposed architecture perspective.

  15. Inspiring Integration in College Students Reading Multiple Biology Texts

    Science.gov (United States)

    Firetto, Carla

    2013-01-01

    Introductory biology courses typically present topics on related biological systems across separate chapters and lectures. A complete foundational understanding requires that students understand how these biological systems are related. Unfortunately, spontaneous generation of these connections is rare for novice learners. These experiments focus…

  16. 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

  17. 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.

  18. The berkeley wavelet transform: a biologically inspired orthogonal wavelet transform.

    Science.gov (United States)

    Willmore, Ben; Prenger, Ryan J; Wu, Michael C-K; Gallant, Jack L

    2008-06-01

    We describe the Berkeley wavelet transform (BWT), a two-dimensional triadic wavelet transform. The BWT comprises four pairs of mother wavelets at four orientations. Within each pair, one wavelet has odd symmetry, and the other has even symmetry. By translation and scaling of the whole set (plus a single constant term), the wavelets form a complete, orthonormal basis in two dimensions. The BWT shares many characteristics with the receptive fields of neurons in mammalian primary visual cortex (V1). Like these receptive fields, BWT wavelets are localized in space, tuned in spatial frequency and orientation, and form a set that is approximately scale invariant. The wavelets also have spatial frequency and orientation bandwidths that are comparable with biological values. Although the classical Gabor wavelet model is a more accurate description of the receptive fields of individual V1 neurons, the BWT has some interesting advantages. It is a complete, orthonormal basis and is therefore inexpensive to compute, manipulate, and invert. These properties make the BWT useful in situations where computational power or experimental data are limited, such as estimation of the spatiotemporal receptive fields of neurons.

  19. 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.

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

    Science.gov (United States)

    Raney, David L.; Slominski, Eric C.

    2003-01-01

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

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

    DEFF Research Database (Denmark)

    Goldschmidt, Dennis; Wörgötter, Florentin; Manoonpong, Poramate

    2014-01-01

    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...

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

    Science.gov (United States)

    Abdulrahim, Mujahid

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

  3. 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...

  4. 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.

  5. Advances in isothermal amplification: novel strategies inspired by biological processes.

    Science.gov (United States)

    Li, Jia; Macdonald, Joanne

    2015-02-15

    Nucleic acid amplification is an essential process in biological systems. The in vitro adoption of this process has resulted in powerful techniques that underpin modern molecular biology. The most common tool is polymerase chain reaction (PCR). However, the requirement for a thermal cycler has somewhat limited applications of this classic nucleic acid amplification technique. Isothermal amplification, on the other hand, obviates the use of a thermal cycler because reactions occur at a single temperature. Isothermal amplification methods are diverse, but all have been developed from an understanding of natural nucleic acid amplification processes. Here we review current isothermal amplification methods as classified by their enzymatic mechanisms. We compare their advantages, disadvantages, efficiencies, and applications. Finally, we mention some new developments associated with this technology, and consider future possibilities in molecular engineering and recombinant technologies that may develop from an appreciation of the molecular biology of natural systems.

  6. 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.

  7. 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.

  8. Muon anomalous magnetic moment in string inspired extended family models

    CERN Document Server

    Kephart, T W

    2002-01-01

    We propose a standard model minimal extension with two lepton weak SU(2) doublets and a scalar singlet to explain the deviation of the measured anomalous magnetic moment of the muon from the standard model expectation. This scheme can be naturally motivated in string inspired models such as E_6 and AdS/CFT.

  9. Dynamical Systems and Control Theory Inspired by Molecular Biology

    Science.gov (United States)

    2011-02-20

    is odd) steady states, there never are more than 2n − 1 steady states, that for parameters near the standard Michaelis - Menten quasi-steady state...conditions, there are at most n + 1 steady states and that for parameters far from the standard Michaelis - Menten quasi-steady state conditions, there is at...moments for certain stochastic kinetics : We have recently started research into stochastic aspects in systems biology. Deterministic mod- els

  10. 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

  11. Chemical biology--identification of small molecule modulators of cellular activity by natural product inspired synthesis.

    Science.gov (United States)

    Hübel, Katja; Lessmann, Torben; Waldmann, Herbert

    2008-07-01

    The aim of this tutorial review is to introduce the reader to the concept, synthesis and application of natural product-inspired compound collections as an important field in chemical biology. This review will discuss how potentially interesting scaffolds can be identified (structural classification of natural products), synthesized in an appropriate manner (including stereoselective transformations for solid phase-bound compounds) and tested in biological assays (cell-based screening as well as biochemical in vitro assays). These approaches will provide the opportunity to identify new and interesting compounds as well as new targets for chemical biology and medicinal chemistry research.

  12. 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.

  13. A Biologically-Inspired Neural Network Architecture for Image Processing

    Science.gov (United States)

    1990-12-01

    findings, in accord with other research cited here, were obtained from cortical measurements or, 15 adult cats and 12 kittens , all anesthetized (9...software models on a Cray computer. Furthermore, care should be taken to avoid exceeding machine memory capacity when running intensive processes

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

    Science.gov (United States)

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

    2016-10-01

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

  15. 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.

  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. 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.

  18. 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.

  19. 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.

  20. E6 inspired supersymmetric models with exact custodial symmetry

    Science.gov (United States)

    Nevzorov, Roman

    2013-01-01

    The breakdown of E6 gauge symmetry at high energies may lead to supersymmetric models based on the standard model gauge group together with extra U(1)ψ and U(1)χ gauge symmetries. To ensure anomaly cancellation the particle content of these E6 inspired models involves extra exotic states that generically give rise to nondiagonal flavor transitions and rapid proton decay. We argue that a single discrete Z˜2H symmetry can be used to forbid tree-level flavor changing transitions, as well as the most dangerous baryon and lepton number violating operators. We present 5D and 6D orbifold grand unified theory constructions that lead to the E6 inspired supersymmetric models of this type. The breakdown of U(1)ψ and U(1)χ gauge symmetries that preserves E6 matter parity assignment guarantees that ordinary quarks and leptons and their superpartners, as well as the exotic states which originate from 27 representations of E6, survive to low energies. These E6 inspired models contain two dark matter candidates and must also include additional TeV scale vectorlike lepton or vectorlike down-type quark states to render the lightest exotic quark unstable. We examine gauge coupling unification in these models and discuss their implications for collider phenomenology and cosmology.

  1. E6 inspired SUSY models with exact custodial symmetry

    CERN Document Server

    Nevzorov, R

    2012-01-01

    The breakdown of E_6 gauge symmetry at high energies may result in supersymmetric (SUSY) models based on the Standard Model (SM) gauge group together with extra U(1)_{\\psi} and U(1)_{\\chi} gauge symmetries. To ensure anomaly cancellation the particle content of these E_6 inspired models involves extra exotic states that can give rise to non--diagonal flavour transitions and rapid proton decay. We argue that a single discrete \\tilde{Z}^{H}_2 symmetry can be used to forbid tree--level flavor-changing transitions and the most dangerous baryon and lepton number violating operators. We present 5D and 6D orbifold GUT models that can lead to the E_6 inspired SUSY models of this type. The breakdown of U(1)_{\\psi} and U(1)_{\\chi} gauge symmetries that preserves E_6 matter parity assignment guarantees that the exotic states which originate from 27_i representations of E_6 as well as ordinary quark and lepton states survive to low energies. The considered E_6 inspired models contain at least two dark-matter candidates a...

  2. 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 $\

  3. 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

  4. 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...

  5. 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

  6. 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.

  7. 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...

  8. 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...

  9. Laboratory of Biological Modeling

    Data.gov (United States)

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

  10. 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.

  11. Bio-inspired evolutionary oral tract shape modeling for physical modeling vocal synthesis.

    Science.gov (United States)

    Howard, David M; Tyrrell, Andy M; Murphy, Damian T; Cooper, Crispin; Mullen, Jack

    2009-01-01

    Physical modeling using digital waveguide mesh (DWM) models is an audio synthesis method that has been shown to produce an acoustic output in music synthesis applications that is often described as being "organic," "warm," or "intimate." This paper describes work that takes its inspiration from physical modeling music synthesis and applies it to speech synthesis through a physical modeling mesh model of the human oral tract. Oral tract shapes are found using a computational technique based on the principles of biological evolution. Essential to successful speech synthesis using this method is accurate measurements of the cross-sectional area of the human oral tract, and these are usually derived from magnetic resonance imaging (MRI). However, such images are nonideal, because of the lengthy exposure time (relative to the time of articulation of speech sounds) required, the local ambient acoustic noise associated with the MRI machine itself and the required supine position for the subject. An alternative method is described where a bio-inspired computing technique that simulates the process of evolution is used to evolve oral tract shapes. This technique is able to produce appropriate oral tract shapes for open vowels using acoustic and excitation data from two adult males and two adult females, but shapes for close vowels that are less appropriate. This technique has none of the drawbacks associated with MRI, because all it requires from the subject is an acoustic and electrolaryngograph (or electroglottograph) recording. Appropriate oral tract shapes do enable the model to produce excellent quality synthetic speech for vowel sounds, and sounds that involve dynamic oral tract shape changes, such as diphthongs, can also be synthesized using an impedance mapped technique. Efforts to improve performance by reducing mesh quantization for close vowels had little effect, and further work is required.

  12. [Total synthesis of biologically active alkaloids using bio-inspired indole oxidation].

    Science.gov (United States)

    Ishikawa, Hayato

    2015-01-01

    Many tryptophan-based dimeric diketopiperazine (DKP) alkaloids including WIN 64821 and ditryptophenaline, which exhibit fascinating biological activities, have been isolated from fungi. These alkaloids possess a unique architecture; therefore several total syntheses of these compounds have been accomplished via bio-inspired reactions. Despite these elegant strategies, we were convinced that a more direct bio-inspired solution for the preparation of tryptophan-based DKP alkaloids was possible because in a true biosynthesis, direct dimerization of tryptophan occurs in aqueous media without incorporation of a protecting group on the substrates. Thus we developed direct bio-inspired dimerization reactions in aqueous, acidic media, along with a novel biomimetic pathway, to provide C2-symmetric and non-symmetric dimeric compounds from commercially available amine-free tryptophan derivatives using Mn(OAc)3, VOF3, and V2O5 as one-electron oxidants. In addition, concise two-pot or three-step syntheses of the naturally occurring dimeric DKP alkaloids (+)-WIN 64821, (-)-ditryptophenaline, and (+)-naseseazine B were accomplished with total yields of 20%, 13%, and 20%, respectively. The present synthesis has several noteworthy features: 1) the tryptophan-based C2-symmetric and non-symmetric dimeric key intermediates can be prepared on a multigram scale in one step; 2) the developed oxidation reaction was carried out in aqueous, acidic solution without deactivation of the metal oxidants; 3) protection of the primary amine can be avoided by salt formation in aqueous acid; 4) for the total two-pot operation, the reaction media are environmentally friendly water and ethanol; 5) satisfactory total yields are obtained compared with previously reported syntheses.

  13. Dark matter in a constrained E 6 inspired SUSY model

    Science.gov (United States)

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

    2016-12-01

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

  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. 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.

  16. 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.

  17. 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.

  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. 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...

  20. Modified Chaplygin gas inspired inflationary model in braneworld scenario

    Science.gov (United States)

    Jawad, Abdul; Rani, Shamaila; Mohsaneen, Sidra

    2016-05-01

    We investigate the modified Chaplygin gas inspired inflationary regime in the brane-world framework in the presence of standard and tachyon scalar fields. We consider the intermediate inflationary scenario and construct the slow-roll parameters, e-folding numbers, spectral index, scalar and tensor power spectra, tensor to scalar ratio for both scalar field models. We develop the ns - N and r - N planes and concluded that ns˜eq96^{+0.5}_{-0.5} and r≤0.0016 for N˜eq60^{+5}_{-5} in both cases of scalar field models as well as for all values of m. These constraints are consistent with observational data such as WMAP7, WMAP9 and Planck data.

  1. 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.

  2. 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

  3. 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

  4. 16th International Conference on Hybrid Intelligent Systems and the 8th World Congress on Nature and Biologically Inspired Computing

    CERN Document Server

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

    2017-01-01

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

  5. 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).

  6. 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.

  7. dNSP: a biologically inspired dynamic Neural network approach to Signal Processing.

    Science.gov (United States)

    Cano-Izquierdo, José Manuel; Ibarrola, Julio; Pinzolas, Miguel; Almonacid, Miguel

    2008-09-01

    The arriving order of data is one of the intrinsic properties of a signal. Therefore, techniques dealing with this temporal relation are required for identification and signal processing tasks. To perform a classification of the signal according with its temporal characteristics, it would be useful to find a feature vector in which the temporal attributes were embedded. The correlation and power density spectrum functions are suitable tools to manage this issue. These functions are usually defined with statistical formulation. On the other hand, in biology there can be found numerous processes in which signals are processed to give a feature vector; for example, the processing of sound by the auditory system. In this work, the dNSP (dynamic Neural Signal Processing) architecture is proposed. This architecture allows representing a time-varying signal by a spatial (thus statical) vector. Inspired by the aforementioned biological processes, the dNSP performs frequency decomposition using an analogical parallel algorithm carried out by simple processing units. The architecture has been developed under the paradigm of a multilayer neural network, where the different layers are composed by units whose activation functions have been extracted from the theory of Neural Dynamic [Grossberg, S. (1988). Nonlinear neural networks principles, mechanisms and architectures. Neural Networks, 1, 17-61]. A theoretical study of the behavior of the dynamic equations of the units and their relationship with some statistical functions allows establishing a parallelism between the unit activations and correlation and power density spectrum functions. To test the capabilities of the proposed approach, several testbeds have been employed, i.e. the frequencial study of mathematical functions. As a possible application of the architecture, a highly interesting problem in the field of automatic control is addressed: the recognition of a controlled DC motor operating state.

  8. 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.

  9. The Capra Research Program for Modelling Extreme Mass Ratio Inspirals

    CERN Document Server

    Thornburg, Jonathan

    2011-01-01

    Suppose a small compact object (black hole or neutron star) of mass $m$ orbits a large black hole of mass $M \\gg m$. This system emits gravitational waves (GWs) that have a radiation-reaction effect on the particle's motion. EMRIs (extreme--mass-ratio inspirals) of this type will be important GW sources for LISA; LISA's data analysis will require highly accurate EMRI GW templates. In this article I outline the "Capra" research program to try to model EMRIs and calculate their GWs \\textit{ab initio}, assuming only that $m \\ll M$ and that the Einstein equations hold. Here we treat the EMRI spacetime as a perturbation of the large black hole's "background" (Schwarzschild or Kerr) spacetime and use the methods of black-hole perturbation theory, expanding in the small parameter $m/M$. The small body's motion can be described either as the result of a radiation-reaction "self-force" acting in the background spacetime or as geodesic motion in a perturbed spacetime. Several different lines of reasoning lead to the (s...

  10. 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...

  11. A multispecies exclusion model inspired by transcriptional interference

    Science.gov (United States)

    Ghosh, Soumendu; Bameta, Tripti; Ghanti, Dipanwita; Chowdhury, Debashish

    2016-12-01

    We introduce exclusion models of two distinguishable species of hard rods with their distinct sites of entry and exit under open boundary conditions. In the first model both species of rods move in the same direction whereas in the other two models they move in the opposite direction. These models are motivated by the biological phenomenon known as transcriptional interference. Therefore, the rules for the kinetics of the models, particularly the rules for the outcome of the encounter of the rods, are also formulated to mimic those observed in transcriptional interference. By a combination of mean-field theory and computer simulation of these models we demonstrate how the flux of one species of rods is completely switched off by the other. Exploring the parameter space of the model we also establish the conditions under which switch-like regulation of two fluxes is possible; from the extensive analysis we discover more than one possible mechanism of this phenomenon.

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

    Directory of Open Access Journals (Sweden)

    Linsen Xu

    2013-10-01

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

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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. 

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Topological data analysis of biological aggregation models.

    Science.gov (United States)

    Topaz, Chad M; Ziegelmeier, Lori; Halverson, Tom

    2015-01-01

    We apply tools from topological data analysis to two mathematical models inspired by biological aggregations such as bird flocks, fish schools, and insect swarms. Our data consists of numerical simulation output from the models of Vicsek and D'Orsogna. These models are dynamical systems describing the movement of agents who interact via alignment, attraction, and/or repulsion. Each simulation time frame is a point cloud in position-velocity space. We analyze the topological structure of these point clouds, interpreting the persistent homology by calculating the first few Betti numbers. These Betti numbers count connected components, topological circles, and trapped volumes present in the data. To interpret our results, we introduce a visualization that displays Betti numbers over simulation time and topological persistence scale. We compare our topological results to order parameters typically used to quantify the global behavior of aggregations, such as polarization and angular momentum. The topological calculations reveal events and structure not captured by the order parameters.

  5. Validation of systems biology models

    NARCIS (Netherlands)

    Hasdemir, D.

    2015-01-01

    The paradigm shift from qualitative to quantitative analysis of biological systems brought a substantial number of modeling approaches to the stage of molecular biology research. These include but certainly are not limited to nonlinear kinetic models, static network models and models obtained by the

  6. The Capra Research Program for Modelling Extreme Mass Ratio Inspirals

    Science.gov (United States)

    Thornburg, Jonathan

    2011-02-01

    Suppose a small compact object (black hole or neutron star) of mass m orbits a large black hole of mass M ≫ m. This system emits gravitational waves (GWs) that have a radiation-reaction effect on the particle's motion. EMRIs (extreme-mass-ratio inspirals) of this type will be important GW sources for LISA. To fully analyze these GWs, and to detect weaker sources also present in the LISA data stream, will require highly accurate EMRI GW templates. In this article I outline the ``Capra'' research program to try to model EMRIs and calculate their GWs ab initio, assuming only that m ≪ M and that the Einstein equations hold. Because m ≪ M the timescale for the particle's orbit to shrink is too long for a practical direct numerical integration of the Einstein equations, and because this orbit may be deep in the large black hole's strong-field region, a post-Newtonian approximation would be inaccurate. Instead, we treat the EMRI spacetime as a perturbation of the large black hole's ``background'' (Schwarzschild or Kerr) spacetime and use the methods of black-hole perturbation theory, expanding in the small parameter m/M. The particle's motion can be described either as the result of a radiation-reaction ``self-force'' acting in the background spacetime or as geodesic motion in a perturbed spacetime. Several different lines of reasoning lead to the (same) basic O(m/M) ``MiSaTaQuWa'' equations of motion for the particle. In particular, the MiSaTaQuWa equations can be derived by modelling the particle as either a point particle or a small Schwarzschild black hole. The latter is conceptually elegant, but the former is technically much simpler and (surprisingly for a nonlinear field theory such as general relativity) still yields correct results. Modelling the small body as a point particle, its own field is singular along the particle worldline, so it's difficult to formulate a meaningful ``perturbation'' theory or equations of motion there. Detweiler and Whiting found

  7. Real-Time Biologically Inspired Action Recognition from Key Poses Using a Neuromorphic Architecture

    Science.gov (United States)

    Layher, Georg; Brosch, Tobias; Neumann, Heiko

    2017-01-01

    Intelligent agents, such as robots, have to serve a multitude of autonomous functions. Examples are, e.g., collision avoidance, navigation and route planning, active sensing of its environment, or the interaction and non-verbal communication with people in the extended reach space. Here, we focus on the recognition of the action of a human agent based on a biologically inspired visual architecture of analyzing articulated movements. The proposed processing architecture builds upon coarsely segregated streams of sensory processing along different pathways which separately process form and motion information (Layher et al., 2014). Action recognition is performed in an event-based scheme by identifying representations of characteristic pose configurations (key poses) in an image sequence. In line with perceptual studies, key poses are selected unsupervised utilizing a feature-driven criterion which combines extrema in the motion energy with the horizontal and the vertical extendedness of a body shape. Per class representations of key pose frames are learned using a deep convolutional neural network consisting of 15 convolutional layers. The network is trained using the energy-efficient deep neuromorphic networks (Eedn) framework (Esser et al., 2016), which realizes the mapping of the trained synaptic weights onto the IBM Neurosynaptic System platform (Merolla et al., 2014). After the mapping, the trained network achieves real-time capabilities for processing input streams and classify input images at about 1,000 frames per second while the computational stages only consume about 70 mW of energy (without spike transduction). Particularly regarding mobile robotic systems, a low energy profile might be crucial in a variety of application scenarios. Cross-validation results are reported for two different datasets and compared to state-of-the-art action recognition approaches. The results demonstrate, that (I) the presented approach is on par with other key pose based

  8. Issues in Biological Shape Modelling

    DEFF Research Database (Denmark)

    Hilger, Klaus Baggesen

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

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

    Indian Academy of Sciences (India)

    BHASKAR JYOTI HAZARIKA; D K CHOUDHURY

    2017-03-01

    We use Wentzel–Kramers–Brillouin (WKB) approximation for calculating the slope and curvature of Isgur–Wise function in a QCD-inspired potential model. This work is an extension of the approximation methods to the QCD-inspired potential model. The approach hints at an effective range of distance for calculating the slope and curvature of Isgur–Wise function. Comparison is also made with those of Dalgarno method and variationallyimproved perturbation theory (VIPT) as well as other models to show the advantages of using WKB approximation.

  10. Isgur-Wise function in a QCD-inspired potential model with WKB approximation

    Science.gov (United States)

    Hazarika, Bhaskar Jyoti; Choudhury, D. K.

    2017-03-01

    We use Wentzel-Kramers-Brillouin (WKB) approximation for calculating the slope and curvature of Isgur-Wise function in a QCD-inspired potential model. This work is an extension of the approximation methods to the QCD-inspired potential model. The approach hints at an effective range of distance for calculating the slope and curvature of Isgur-Wise function. Comparison is also made with those of Dalgarno method and variationally improved perturbation theory (VIPT) as well as other models to show the advantages of using WKB approximation.

  11. 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.

  12. 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...

  13. 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.

  14. 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.

  15. High Energy (-p)p and pp Elastic Scatterings in QCD Inspired Model

    Institute of Scientific and Technical Information of China (English)

    LU Juan; MA Wei-Xing; HE Xiao-Rong

    2007-01-01

    We propose QCD inspired model to calculate (p)p and pp elastic scatterings at high energies in this paper.A calculation for total cross section of (p)p and pp is performed in which the contributions from gluon-gluon,quark-quark,and gluon-quark interactions are included.Our results show that the QCD inspired model gives a perfect fit to experimental data of total cross section both for (p)p and pp elastic scatterings at the whole energy region where experimental data existed at FNAL and CERN.

  16. 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...

  17. Modeling the Heat Capacity of Spider Silk Inspired Di-block Copolymers

    Science.gov (United States)

    Huang, W.; Krishnaji, S.; Kaplan, D.; Cebe, P.

    2011-03-01

    We synthesized and characterized a new family of di-block copolymers based on the amino acid sequences of Nephila clavipes major ampulate dragline spider silk, having the form HABn and HBAn (n=1-6), comprising an alanine-rich hydrophobic block, A, a glycine-rich hydrophilic block, B, and a histidine tag, H. Using temperature modulated differential scanning calorimetry (TMDSC), we captured the effect of bound water acting as a plasticizer for copolymer films which had been cast from water solution and dried. We determined the water content by thermogravimetry and used the weight loss vs. temperature to correct the mass in TMDSC experiments. Our result shows that non-freezing bound water has a strong plasticization effect which lowers the onset of the glass transition by about 10circ; C. The reversing heat capacities, Cp(T), for temperatures below and above the glass transition were also characterized by TMDSC. We then calculated the solid state heat capacities of our novel block copolymers below the glass transition (Tg) based on the vibrational motions of the constituent poly(amino acid)s, whose heat capacities are known from the ATHAS Data Bank. Excellent agreement was found between the measured and calculated values of the heat capacity, showing that this model can serve as a standard method to predict the solid state Cp for other biologically inspired block copolymers. Support was provided from the NSF CBET-0828028 and the MRI Program under DMR-0520655 for thermal analysis instrumentation.

  18. 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.

  19. The DCA:SOMe Comparison A comparative study between two biologically-inspired algorithms

    CERN Document Server

    Greensmith, Julie; Aickelin, Uwe

    2010-01-01

    The Dendritic Cell Algorithm (DCA) is an immune-inspired algorithm, developed for the purpose of anomaly detection. The algorithm performs multi-sensor data fusion and correlation which results in a 'context aware' detection system. Previous applications of the DCA have included the detection of potentially malicious port scanning activity, where it has produced high rates of true positives and low rates of false positives. In this work we aim to compare the performance of the DCA and of a Self-Organizing Map (SOM) when applied to the detection of SYN port scans, through experimental analysis. A SOM is an ideal candidate for comparison as it shares similarities with the DCA in terms of the data fusion method employed. It is shown that the results of the two systems are comparable, and both produce false positives for the same processes. This shows that the DCA can produce anomaly detection results to the same standard as an established technique.

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

    Science.gov (United States)

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

    2015-07-06

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

  1. Aristotelian-Inspired Model for Curtailing Academic Dishonesty in the United States

    Science.gov (United States)

    Sanders, Maria A.

    2012-01-01

    This dissertation explores the growing epidemic of academic dishonesty in the United States in order to propose an Aristotelian-inspired model for developing moral character to curtail this epidemic. The task is laid out in four parts. Chapter one responds to the problem of "akrasia," adopting a modified version of Devin Henry's…

  2. 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.

  3. Simulations of a supersymmetry inspired model on a fuzzy sphere

    Energy Technology Data Exchange (ETDEWEB)

    Volkholz, J. [Humboldt-Universitaet, Berlin (Germany). Inst. fuer Physik; Bietenholz, W. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC

    2007-11-15

    We present a numerical study of a two dimensional model of the Wess-Zumino type. We formulate this model on a sphere, where the fields are expanded in spherical harmonics. The sphere becomes fuzzy by a truncation in the angular momenta. This leads to a finite set of degrees of freedom without explicitly breaking the space symmetries. The corresponding field theory is expressed in terms of a matrix model, which can be simulated. We present first numerical results for the phase structure of a variant of this model on a fuzzy sphere. The prospect to restore exact supersymmetry in certain limits is under investigation. (orig.)

  4. 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.

  5. 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...

  6. Simulations of a supersymmetry inspired model on a fuzzy sphere

    OpenAIRE

    2008-01-01

    We present a numerical study of a two dimensional model of the Wess-Zumino type. We formulate this model on a sphere, where the fields are expanded in spherical harmonics. The sphere becomes fuzzy by a truncation in the angular momenta. This leads to a finite set of degrees of freedom without explicitly breaking the space symmetries. The corresponding field theory is expressed in terms of a matrix model, which can be simulated. We present first numerical results for the phase structure of a v...

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

    NARCIS (Netherlands)

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

    2016-01-01

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

  8. 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.

  9. Design and characterization of a biologically inspired quasi-passive prosthetic ankle-foot.

    Science.gov (United States)

    Mooney, Luke M; Lai, Cara H; Rouse, Elliott J

    2014-01-01

    By design, commonly worn energy storage and release (ESR) prosthetic feet cannot provide biologically realistic ankle joint torque and angle profiles during walking. Additionally, their anthropomorphic, cantilever architecture causes their mechanical stiffness to decrease throughout the stance phase of walking, opposing the known trend of the biological ankle. In this study, the design of a quasi-passive pneumatic ankle-foot prosthesis is detailed that is able to replicate the biological ankle's torque and angle profiles during walking. The prosthetic ankle is comprised of a pneumatic piston, bending spring and solenoid valve. The mechanical properties of the pneumatic ankle prosthesis are characterized using a materials testing machine and the properties are compared to those from a common, passive ESR prosthetic foot. The characterization spanned a range of ankle equilibrium pressures and testing locations beneath the foot, analogous to the location of center of pressure within the stance phase of walking. The pneumatic ankle prosthesis was shown to provide biologically appropriate trends and magnitudes of torque, angle and stiffness behavior, when compared to the passive ESR prosthetic foot. Future work will focus on the development of a control system for the quasi-passive device and clinical testing of the pneumatic ankle to demonstrate efficacy.

  10. [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.

  11. QCD-inspired determination of NJL model parameters

    CERN Document Server

    Springer, Paul; Rechenberger, Stefan; Rennecke, Fabian

    2016-01-01

    The QCD phase diagram at finite temperature and density has attracted considerable interest over many decades now, not least because of its relevance for a better understanding of heavy-ion collision experiments. Models provide some insight into the QCD phase structure but usually rely on various parameters. Based on renormalization group arguments, we discuss how the parameters of QCD low-energy models can be determined from the fundamental theory of the strong interaction. We particularly focus on a determination of the temperature dependence of these parameters in this work and comment on the effect of a finite quark chemical potential. We present first results and argue that our findings can be used to improve the predictive power of future model calculations.

  12. a Markov-Process Inspired CA Model of Highway Traffic

    Science.gov (United States)

    Wang, Fa; Li, Li; Hu, Jian-Ming; Ji, Yan; Ma, Rui; Jiang, Rui

    To provide a more accurate description of the driving behaviors especially in car-following, namely a Markov-Gap cellular automata model is proposed in this paper. It views the variation of the gap between two consequent vehicles as a Markov process whose stationary distribution corresponds to the observed gap distribution. This new model provides a microscopic simulation explanation for the governing interaction forces (potentials) between the queuing vehicles, which cannot be directly measurable for traffic flow applications. The agreement between empirical observations and simulation results suggests the soundness of this new approach.

  13. 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.

  14. Relativistic Effects in a QCD Inspired quark model and the necessity of a short distance scale

    CERN Document Server

    Pathak, Krishna Kingkar

    2010-01-01

    We study the masses and decay constants of heavy light flavoured mesons in a QCD Inspired Quark model. We modify the relativistic correction procedure by introducing a short distance scale r0 in analogy with relativistic Hydrogen atom and estimate the values of masses and decay constants of heavy-light mesons. Necessity of a short distance scale r0 \\leq 10-3 - 10-5 fm in the model is indicated. Keywords: heavy- light mesons, masses, decay constants

  15. 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.

  16. Biological System Behaviours and Natural-inspired Methods and Their Applications to Supply Chain Management

    OpenAIRE

    Fan, Xuemei; Zhang, Shujun; Hapeshi, Kevin; Ynag, Y

    2014-01-01

    People have learnt from biological system behaviours and structures to design and develop a number of different kinds of optimisation algorithms that have been widely used in both theoretical study and practical applications in engineering and business management. An efficient supply chain is very important for companies to survive in global competitive market. An effective SCM (supply chain management) is the key for implement an efficient supply chain. Though there have been considerable am...

  17. 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.

  18. 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

  19. 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.

  20. 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...

  1. Teaching biology with model organisms

    Science.gov (United States)

    Keeley, Dolores A.

    The purpose of this study is to identify and use model organisms that represent each of the kingdoms biologists use to classify organisms, while experiencing the process of science through guided inquiry. The model organisms will be the basis for studying the four high school life science core ideas as identified by the Next Generation Science Standards (NGSS): LS1-From molecules to organisms, LS2-Ecosystems, LS3- Heredity, and LS4- Biological Evolution. NGSS also have identified four categories of science and engineering practices which include developing and using models and planning and carrying out investigations. The living organisms will be utilized to increase student interest and knowledge within the discipline of Biology. Pre-test and posttest analysis utilizing student t-test analysis supported the hypothesis. This study shows increased student learning as a result of using living organisms as models for classification and working in an inquiry-based learning environment.

  2. 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.

  3. 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.

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

    Science.gov (United States)

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

    2011-05-01

    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 many biological organisms reduce the high dimensionality of their action space by generating movements through linear superposition of a rather small number of stereotypical combinations of simultaneous movements of many joints, to which we refer as kinematic synergies in this paper. We show that by constructing two suitable non-linear kinematic synergies for the lower part of the body of a humanoid robot, balance control can in fact be reduced to a linear control problem, at least in the case of relatively slow movements. We demonstrate for a variety of tasks that the humanoid robot HOAP-2 acquires through this approach the capability to balance dynamically against unforeseen disturbances that may arise from external forces or from manipulating unknown loads.

  5. 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.

  6. Sources of CP violation from E{sub 6} inspired heterotic string model

    Energy Technology Data Exchange (ETDEWEB)

    Boussahel, M.; Mebarki, N. [Departement de physique Faculte des sciences Universite de M' sila 28000 (Algeria); Laboratoire de Physique Mathematique et Subatomique Mentouri University, Constantine (Algeria)

    2012-06-27

    Sources of the weak CP violation from the SU{sub L}(3)x SU{sub R}(3)x SU{sub c}(3) subgroup of the E{sub 6} inspired heterotic string model are discussed. It is shown that the number of the Cabibo-Kobayachi-Maskawa like matrices depends on the spontaneous breakdown of the E{sub 6} gauge symmetry and/or supersymmetry.

  7. 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...

  8. Industry Cluster's Adaptive Co-competition Behavior Modeling Inspired by Swarm Intelligence

    Science.gov (United States)

    Xiang, Wei; Ye, Feifan

    Adaptation helps the individual enterprise to adjust its behavior to uncertainties in environment and hence determines a healthy growth of both the individuals and the whole industry cluster as well. This paper is focused on the study on co-competition adaptation behavior of industry cluster, which is inspired by swarm intelligence mechanisms. By referencing to ant cooperative transportation and ant foraging behavior and their related swarm intelligence approaches, the cooperative adaptation and competitive adaptation behavior are studied and relevant models are proposed. Those adaptive co-competition behaviors model can be integrated to the multi-agent system of industry cluster to make the industry cluster model more realistic.

  9. 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.

  10. Development in a biologically inspired spinal neural network for movement control

    NARCIS (Netherlands)

    van Heijst, JJ; Vos, JE; Bullock, D

    1998-01-01

    In two phases, we develop increasingly complex neural network models of spinal circuitry that self-organizes into networks with opponent channels for the control of an antagonistic muscle pair. The self-organization is enabled by a Hebbian learning rule operating during spontaneous activity present

  11. 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.…

  12. Ratio of Real to Imaginary for pp and (p)p Elastic Scatterings in QCD Inspired Model

    Institute of Scientific and Technical Information of China (English)

    LU Juan; MA Wei-Xing; HE Xiao-Rong

    2007-01-01

    We use the QCD inspired model to analyze the ratio of the real to the imaginary for pp and 5p elastic scatterings. A calculation for the ratio of the real to the imaginary is performed in which the contributions from gluongluon interaction, quark-quark interaction, quark-gluon interaction, and odd eikonal profile function are included. Our results show that the QCD inspired model gives a good fit to the LHC experimental data.

  13. A biologically inspired psychometric function for accuracy of visual identification as a function of exposure duration

    DEFF Research Database (Denmark)

    Petersen, Anders; Andersen, Tobias

    in modelling human performance in whole and partial report tasks in which multiple simultaneously presented letters are to be reported (Shibuya & Bundesen, 1988). Therefore, we investigated visual letter identification as a function of exposure duration. On each trial, a single randomly chosen letter (A......The psychometric function of letter identification is typically described as a function of stimulus intensity. However, the effect of stimulus exposure duration on letter identification remains poorly described. This is surprising because the effect of exposure duration has played a central role......-Z) was presented at the centre of the screen. Exposure duration was varied from 5 to 210 milliseconds. The letter was followed by a pattern mask. Three subjects each completed 54,080 trials in a 26-Alternative Forced Choice procedure. We compared the exponential, the gamma and the Weibull psychometric functions...

  14. 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.

  15. 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...

  16. 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

  17. 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.

  18. Nuclear Slope Parameter Of pp and (-p)p Elastic Scattering in QCD Inspired Model

    Institute of Scientific and Technical Information of China (English)

    MA Shan-Jun; LU Juan; LU Hai-Liang; MA Wei-Xing; FAN Hong-Yi; HE Xiao-Rong

    2008-01-01

    Based on the quaxk-gluon structure of nucleon and the possible existence of Odderon in strong interaction process due to gluon self-interaction, the elastic scatterings of pp and pp at high energies axe studied. The contributions from individual terms of quark-quark, gluon-gluon interactions, quaxk-gluon interference, and the Odderon terms to the nuclear slope parameter B(s) are analyzed. Our results show that the QCD inspired model gives a good fit to the LHC experimental data of the nucleax slope parameter.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-05-10

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

  20. 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.

  1. 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.

  2. Searching for features of a string-inspired inflationary model with cosmological observations

    Science.gov (United States)

    Cai, Yi-Fu; Ferreira, Elisa G. M.; Hu, Bin; Quintin, Jerome

    2015-12-01

    The latest Planck results show a power deficit in the temperature anisotropies near ℓ≈20 in the cosmic microwave background (CMB). This observation can hardly be explained within the standard inflationary Λ -cold-dark-matter (Λ CDM ) scenario. In this paper we consider a string theory inspired inflationary model (axion monodromy inflation) with a step-like modulation in the potential which gives rise to observable signatures in the primordial perturbations. One interesting phenomenon is that the primordial scalar modes experience a sudden suppression at a critical scale when the modulation occurs. By fitting to the CMB data, we find that the model can nicely explain the ℓ≈20 power deficit anomaly as well as predict specific patterns in the temperature-polarization correlation and polarization autocorrelation spectra. Though the significance of the result is not sufficient to claim a detection, our analysis reveals that fundamental physics at extremely high energy scales, namely, some effects inspired by string theory, may be observationally testable in forthcoming cosmological experiments.

  3. Inspired Responses

    Science.gov (United States)

    Steele, Carol Frederick

    2011-01-01

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

  4. 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].

  5. 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.

  6. Searching for Features of a String Inspired Inflationary Model with Cosmological Observations

    CERN Document Server

    Cai, Yi-Fu; Hu, Bin; Quintin, Jerome

    2015-01-01

    The latest Planck results show a power deficit in the temperature anisotropies near $\\ell \\approx 20$ in the cosmic microwave background (CMB). This observation can hardly be explained within the standard inflationary $\\Lambda$-cold-dark-matter ($\\Lambda$CDM) scenario. In this Letter we consider a string theory inspired inflationary model (axion monodromy inflation) with a step-like modulation in the potential which gives rise to observable signatures in the primordial perturbations. One interesting phenomenon is that the primordial scalar modes experience a sudden suppression at a critical scale when the modulation occurs. By fitting to the CMB data, we find that the model can nicely explain the $\\ell \\approx 20$ power deficit anomaly as well as predict specific patterns in the temperature-polarization correlation and polarization autocorrelation spectra. Though the significance of the result is not sufficient to claim a detection, our analysis reveals that fundamental physics at extremely high energy scales...

  7. Biology-oriented synthesis of a natural-product inspired oxepane collection yields a small-molecule activator of the Wnt-pathway.

    Science.gov (United States)

    Basu, Sudipta; Ellinger, Bernhard; Rizzo, Stefano; Deraeve, Céline; Schürmann, Markus; Preut, Hans; Arndt, Hans-Dieter; Waldmann, Herbert

    2011-04-26

    In Biology Oriented Synthesis the scaffolds of biologically relevant compound classes inspire the synthesis of focused compound collections enriched in bioactivity. This criterion is met by the structurally complex scaffolds of natural products (NPs) selected in evolution. The synthesis of NP-inspired compound collections approaching the complexity of NPs calls for the development of efficient synthetic methods. We have developed a one pot 4-7 step synthesis of mono-, bi-, and tricyclic oxepanes that resemble the core scaffolds of numerous NPs with diverse bioactivities. This sequence entails a ring-closing ene-yne metathesis reaction as key step and makes productive use of polymer-immobilized scavenger reagents. Biological profiling of a corresponding focused compound collection in a reporter gene assay monitoring for Wnt-signaling modulation revealed active Wntepanes. This unique class of small-molecule activators of the Wnt pathway modulates the van-Gogh-like receptor proteins (Vangl), which were previously identified in noncanonical Wnt signaling, and acts in synergy with the canonical activator protein (Wnt-3a).

  8. Proofs of the Technical Results Justifying a Biologically Inspired Algorithm for Reactive Navigation of Nonholonomic Robots in Maze-Like Environments

    CERN Document Server

    Matveev, Alexey S; Savkin, Andrey V

    2011-01-01

    We present technical results justifying a method for guidance of a Dubins-like vehicle with saturated control towards a target in a steady simply connected maze-like environment. The vehicle always has access to to the target relative bearing angle and the distance to the nearest point of the maze if it is within the given sensor range. The proposed control law is composed by biologically inspired reflex-level rules. Mathematically rigorous analysis of this law is provided; its convergence and performance are confirmed by computer simulations and experiments with real robots.

  9. Statistical Mechanics-Inspired Modeling of Heterogeneous Packet Transmission in Communication Networks.

    Science.gov (United States)

    Sarkar, S; Mukherjee, K; Ray, A; Srivastav, A; Wettergren, T A

    2012-08-01

    This paper presents the qualitative nature of communication network operations as abstraction of typical thermodynamic parameters (e.g., order parameter, temperature, and pressure). Specifically, statistical mechanics-inspired models of critical phenomena (e.g., phase transitions and size scaling) for heterogeneous packet transmission are developed in terms of multiple intensive parameters, namely, the external packet load on the network system and the packet transmission probabilities of heterogeneous packet types. Network phase diagrams are constructed based on these traffic parameters, and decision and control strategies are formulated for heterogeneous packet transmission in the network system. In this context, decision functions and control objectives are derived in closed forms, and the pertinent results of test and validation on a simulated network system are presented.

  10. 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.

  11. 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.

  12. 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.

  13. A class of LQC-inspired models for homogeneous, anisotropic cosmology in higher dimensional early universe

    Science.gov (United States)

    Rama, S. Kalyana

    2016-12-01

    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.

  14. 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

  15. Quasifixed point scenarios and the Higgs mass in the E6 inspired supersymmetric models

    Science.gov (United States)

    Nevzorov, R.

    2014-03-01

    We analyze the two-loop renormalization group (RG) flow of the gauge and Yukawa couplings within the E6 inspired supersymmetric models with extra U(1)N gauge symmetry under which right-handed neutrinos have zero charge. In these models, single discrete Z stretchy="false">˜2H symmetry forbids the tree-level flavor-changing transitions and the most dangerous baryon and lepton number violating operators. We consider two different scenarios A and B that involve extra matter beyond the minimal supersymmetric Standard Model contained in three and four 5+5¯ representations of SU(5), respectively, plus three SU(5) singlets which carry U(1)N charges. In scenario A, the measured values of the SU(2)W and U(1)Y gauge couplings lie near the fixed points of the RG equations. In scenario B, the contribution of two-loop corrections spoils the unification of gauge couplings, resulting in the appearance of the Landau pole below the grand unification scale MX. The solutions for the Yukawa couplings also approach the quasifixed points with increasing their values at the scale MX. We calculate the two-loop upper bounds on the lightest Higgs boson mass in the vicinity of these quasifixed points and compare the results of our analysis with the corresponding ones in the next-to-minimal supersymmetric Standard Model. In all these cases, the theoretical restrictions on the Standard-Model-like Higgs boson mass are rather close to 125 GeV.

  16. 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.

  17. 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”.

  18. 基于生物刺激神经网络的多机器人编队方法%Multi-robot formation based on biological inspired neural network

    Institute of Scientific and Technical Information of China (English)

    仰晓芳; 倪建军

    2013-01-01

    Multi-robot formation control is an important issue in the multi-robot cooperation field. It is a hot and difficult problem to achieve multi-robot dynamic formation while making them move toward the same target. Concerning this problem, a new biological inspired neural network based approach for multi-robot formation was proposed in this paper. In the proposed approach, a leader-referenced formation model was used to calculate the virtual target location for each robot in real-time, and a biological neural network was used to realize multi-robot navigation. Finally, some simulation experiments were carried out. The experimental results show that the proposed approach has some good performances, such as the real-time obstacle avoidance, keeping formation and moving toward the same target. Furthermore, multi-robots can change the formation quickly, which proves the real-time and intelligence of the proposed approach.%多机器人编队控制是多机器人协作领域的重要研究内容之一,如何实现多机器人朝同一目标移动的同时保持队形是多机器人编队的一个热点和难点问题.针对这一问题,提出一种新的基于生物刺激神经网络的多机器人动态编队方法,采用基于leader-referenced编队模型实时计算各机器人的虚拟目标位置,利用生物刺激神经网络进行机器人导航.最后进行仿真实验,实验结果表明该方法在实现多机器人实时避障并保持队形的同时,朝同一目标移动,而且可以很快实现队形变换,具有较好的实时性和灵活性.

  19. Building multivariate systems biology models

    NARCIS (Netherlands)

    Kirwan, G.M.; Johansson, E.; Kleemann, R.; Verheij, E.R.; Wheelock, A.M.; Goto, S.; Trygg, J.; Wheelock, C.E.

    2012-01-01

    Systems biology methods using large-scale "omics" data sets face unique challenges: integrating and analyzing near limitless data space, while recognizing and removing systematic variation or noise. Herein we propose a complementary multivariate analysis workflow to both integrate "omics" data from

  20. Quasi-fixed point scenarios and the Higgs mass in the E6 inspired SUSY models

    CERN Document Server

    Nevzorov, R

    2013-01-01

    We analyse the renormalization group (RG) flow of the gauge and Yukawa couplings within the E6 inspired supersymmetric (SUSY) models with extra U(1)_{N} gauge symmetry under which right-handed neutrinos have zero charge. In these models single discrete \\tilde{Z}^{H}_2 symmetry forbids the tree-level flavor-changing transitions and the most dangerous baryon and lepton number violating operators. We argue that the measured values of the SU(2)_W and U(1)_Y gauge couplings lie near the quasi-fixed points of the RG equations in these models. The solutions for the Yukawa couplings also approach the quasi-fixed points with increasing their values at the Grand Unification scale. We calculate the two-loop upper bounds on the lightest Higgs boson mass in the vicinity of these quasi-fixed points and compare the results of our analysis with the corresponding ones in the NMSSM. In all these cases the theoretical restrictions on the SM-like Higgs boson mass are rather close to 125 GeV.

  1. 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.

  2. 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.

  3. 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.

  4. 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...

  5. An insect-inspired model for visual binding II: functional analysis and visual attention.

    Science.gov (United States)

    Northcutt, Brandon D; Higgins, Charles M

    2017-04-01

    We have developed a neural network model capable of performing visual binding inspired by neuronal circuitry in the optic glomeruli of flies: a brain area that lies just downstream of the optic lobes where early visual processing is performed. This visual binding model is able to detect objects in dynamic image sequences and bind together their respective characteristic visual features-such as color, motion, and orientation-by taking advantage of their common temporal fluctuations. Visual binding is represented in the form of an inhibitory weight matrix which learns over time which features originate from a given visual object. In the present work, we show that information represented implicitly in this weight matrix can be used to explicitly count the number of objects present in the visual image, to enumerate their specific visual characteristics, and even to create an enhanced image in which one particular object is emphasized over others, thus implementing a simple form of visual attention. Further, we present a detailed analysis which reveals the function and theoretical limitations of the visual binding network and in this context describe a novel network learning rule which is optimized for visual binding.

  6. 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...

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. Integrating interactive computational modeling in biology curricula.

    Science.gov (United States)

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

    2015-03-01

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

  12. 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

  13. 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.

  14. Biological transportation networks: Modeling and simulation

    KAUST Repository

    Albi, Giacomo

    2015-09-15

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

  15. Modeling growth in biological materials

    OpenAIRE

    Jones, Gareth Wyn; Chapman, S. Jonathan

    2012-01-01

    The biomechanical modeling of growing tissues has recently become an area of intense interest. In particular, the interplay between growth patterns and mechanical stress is of great importance, with possible applications to arterial mechanics, embryo morphogenesis, tumor development, and bone remodeling. This review aims to give an overview of the theories that have been used to model these phenomena, categorized according to whether the tissue is considered as a continuum object or a collect...

  16. 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.

  17. 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.

  18. 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...

  19. 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.

  20. Biologically inspired highly durable iron phthalocyanine catalysts for oxygen reduction reaction in polymer electrolyte membrane fuel cells.

    Science.gov (United States)

    Li, Wenmu; Yu, Aiping; Higgins, Drew C; Llanos, Bernard G; Chen, Zhongwei

    2010-12-08

    In the present work, we have designed and synthesized a new highly durable iron phtalocyanine based nonprecious oxygen reduction reaction (ORR) catalyst (Fe-SPc) for polymer electrolyte membrane fuel cells (PEMFCs). The Fe-SPc, with a novel structure inspired by that of naturally occurring oxygen activation catalysts, is prepared by a nonpyrolyzing method, allowing adequate control of the atomic structure and surface properties of the material. Significantly improved ORR stability of the Fe-SPc is observed compared with the commercial Fe-Pc catalysts. The Fe-SPc has similar activity to that of the commercial Fe-Pc initially, while the Fe-SPc displays 4.6 times higher current density than that of the commercial Fe-Pc after 10 sweep potential cycles, and a current density that is 7.4 times higher after 100 cycles. This has been attributed to the incorporation of electron-donating functional groups, along with a high degree of steric hindrance maintaining active site isolation. Nonprecious Fe-SPc is promising as a potential alternative ORR electrocatalyst for PEMFCs.

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

    DEFF Research Database (Denmark)

    Sandborg-Petersen, Ulrik

    2011-01-01

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

  2. 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.

  3. 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

    2016-02-18

    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.

  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. 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...

  6. Introduction to stochastic models in biology

    DEFF Research Database (Denmark)

    Ditlevsen, Susanne; Samson, Adeline

    2013-01-01

    be exposed to influences that are not completely understood or not feasible to model explicitly. Ignoring these phenomena in the modeling may affect the analysis of the studied biological systems. Therefore there is an increasing need to extend the deterministic models to models that embrace more complex...... variations in the dynamics. A way of modeling these elements is by including stochastic influences or noise. A natural extension of a deterministic differential equations model is a system of stochastic differential equations (SDEs), where relevant parameters are modeled as suitable stochastic processes......, or stochastic processes are added to the driving system equations. This approach assumes that the dynamics are partly driven by noise....

  7. 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.

  8. Biomimetic bio-inspired biomorph sustainable? An attempt to classify and clarify biology-derived technical developments.

    Science.gov (United States)

    Speck, Olga; Speck, David; Horn, Rafael; Gantner, Johannes; Sedlbauer, Klaus Peter

    2017-01-24

    Over the last few decades, the systematic approach of knowledge transfer from biological concept generators to technical applications has received increasing attention, particularly because marketable bio-derived developments are often described as sustainable. The objective of this paper is to rationalize and refine the discussion about bio-derived developments also with respect to sustainability by taking descriptive, normative and emotional aspects into consideration. In the framework of supervised learning, a dataset of 70 biology-derived and technology-derived developments characterised by 9 different attributes together with their respective values and assigned to one of 17 classes was created. On the basis of the dataset a decision tree was generated which can be used as a straightforward classification tool to identify biology-derived and technology-derived developments. The validation of the applied learning procedure achieved an average accuracy of 90.0%. Additional extraordinary qualities of technical applications are generally discussed by means of selected biology-derived and technology-derived examples with reference to normative (contribution to sustainability) and emotional aspects (aesthetics and symbolic character). In the context of a case study from the building sector, all aspects are critically discussed.

  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. Functional model of biological neural networks.

    Science.gov (United States)

    Lo, James Ting-Ho

    2010-12-01

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

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

    Science.gov (United States)

    Coveney, Peter V; Fowler, Philip W

    2005-09-22

    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 examples of systems biology, are modelled by sets of nonlinear coupled differential equations, which have to be solved numerically. A major difficulty with this approach is that all the parameters within these equations are not usually known. Coupled models that include biomolecular detail could help solve this problem. Coupling models across large ranges of length- and time-scales is central to describing complex systems and therefore to biology. Such coupling may be performed in at least two different ways, which we refer to as hierarchical and hybrid multiscale modelling. While limited progress has been made in the former case, the latter is only beginning to be addressed systematically. These modelling methods are expected to bring numerous benefits to biology, for example, the properties of a system could be studied over a wider range of length- and time-scales, a key aim of systems biology. Multiscale models couple behaviour at the molecular biological level to that at the cellular level, thereby providing a route for calculating many unknown parameters as well as investigating the effects at, for example, the cellular level, of small changes at the biomolecular level, such as a genetic mutation or the presence of a drug. The modelling and simulation of biomolecular systems is itself very computationally intensive; we describe a recently developed hybrid continuum-molecular model, HybridMD, and its associated molecular insertion algorithm, which point the way towards the

  14. 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

  15. 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.

  16. 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)

  17. 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

  18. Performance optimization of a leagility inspired supply chain model: a CFGTSA algorithm based approach

    OpenAIRE

    Chan, Felix T S; Kumar, Vikas

    2009-01-01

    Lean and agile principles have attracted considerable interest in the past few decades. Industrial sectors throughout the world are upgrading to these principles to enhance their performance, since they have been proven to be efficient in handling supply chains. However, the present market trend demands a more robust strategy incorporating the salient features of both lean and agile principles. Inspired by these, the leagility principle has emerged, encapsulating both lean and agile features....

  19. Performance variation due to stiffness in a tuna-inspired flexible foil model.

    Science.gov (United States)

    Rosic, Mariel-Luisa N; Thornycroft, Patrick J M; Feilich, Kara L; Lucas, Kelsey N; Lauder, George V

    2017-01-17

    Tuna are fast, economical swimmers in part due to their stiff, high aspect ratio caudal fins and streamlined bodies. Previous studies using passive caudal fin models have suggested that while high aspect ratio tail shapes such as a tuna's generally perform well, tail performance cannot be determined from shape alone. In this study, we analyzed the swimming performance of tuna-tail-shaped hydrofoils of a wide range of stiffnesses, heave amplitudes, and frequencies to determine how stiffness and kinematics affect multiple swimming performance parameters for a single foil shape. We then compared the foil models' kinematics with published data from a live swimming tuna to determine how well the hydrofoil models could mimic fish kinematics. Foil kinematics over a wide range of motion programs generally showed a minimum lateral displacement at the narrowest part of the foil, and, immediately anterior to that, a local area of large lateral body displacement. These two kinematic patterns may enhance thrust in foils of intermediate stiffness. Stiffness and kinematics exhibited subtle interacting effects on hydrodynamic efficiency, with no one stiffness maximizing both thrust and efficiency. Foils of intermediate stiffnesses typically had the greatest coefficients of thrust at the highest heave amplitudes and frequencies. The comparison of foil kinematics with tuna kinematics showed that tuna motion is better approximated by a zero angle of attack foil motion program than by programs that do not incorporate pitch. These results indicate that open questions in biomechanics may be well served by foil models, given appropriate choice of model characteristics and control programs. Accurate replication of biological movements will require refinement of motion control programs and physical models, including the creation of models of variable stiffness.

  20. Macromodeling for analog design and robustness boosting in bio-inspired computing models

    Science.gov (United States)

    Cuadri, J.; Linan, G.; Roca, E.; Rodriguez-Vazquez, A.

    2005-06-01

    Setting specifications for the electronic implementation of biological neural-network-like vision systems on-chip is not straightforward, neither it is to simulate the resulting circuit. The structure of these systems leads to a netlist of more than 100.000 nodes for a small array of 100x150 pixels. Moreover, introducing an optical input in the low level simulation is nowadays not feasible with standard electrical simulation environments. Given that, to accomplish the task of integrating those systems in silicon to build compact, low power consuming, and reliable systems, a previous step in the standard analog electronic design flux should be introduced. Here a methodology to make the translation from the biological model to circuit-level specifications for electronic design is proposed. The purpose is to include non ideal effects as mismatching, noise, leakages, supply degradation, feedthrough, and temperature of operation in a high level description of the implementation, in order to accomplish behavioural simulations that require less computational effort and resources. A particular case study is presented, the analog electronic implementation of the locust"s Lobula Giant Movement Detector (LGMD), a neural structure that fires a collision alarm based on visual information. The final goal is a collision threat detection vision system on-chip for automotive applications.

  1. 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.

  2. 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.

  3. The neuroscience of vision-based grasping: a functional review for computational modeling and bio-inspired robotics.

    Science.gov (United States)

    Chinellato, Eris; Del Pobil, Angel P

    2009-06-01

    The topic of vision-based grasping is being widely studied in humans and in other primates using various techniques and with different goals. The fundamental related findings are reviewed in this paper, with the aim of providing researchers from different fields, including intelligent robotics and neural computation, a comprehensive but accessible view on the subject. A detailed description of the principal sensorimotor processes and the brain areas involved is provided following a functional perspective, in order to make this survey especially useful for computational modeling and bio-inspired robotic applications.

  4. 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.

  5. 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

  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. 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.

  8. Higgs and Dark Matter Physics in the Type-II Two-Higgs-Doublet Model inspired by E_6 GUT

    CERN Document Server

    Ko, P; Yu, Chaehyun

    2015-01-01

    We study Higgs and dark matter physics in the type-II two-Higgs-doublet model (2HDM) with an extra U(1)_H gauge symmetry, inspired by the E_6 grand unified theory (GUT). From the viewpoint of the bottom-up approach, the additional U(1)_H gauge symmetry plays a crucial role in avoiding the tree-level flavor changing neutral currents mediated by neutral Higgs bosons in general 2HDMs. In the model with U(1)_H gauge symmetry, which has Type-II Yukawa couplings, we have to introduce additional chiral fermions that are charged under the U(1)_H gauge symmetry as well as under the Standard-Model (SM) gauge symmetry in order to cancel chiral gauge anomalies. For the U(1)_H charge assignment and the extra matters, we adopt the ones inspired by the E_6 GUT: the extra quark-like and lepton-like fermions with the non-trivial U(1)_H charges. We discuss their contributions to the physical observables, such as the measurements of Higgs physics and electro-weak interactions, and investigate the consistency with the experiment...

  9. 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.

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

    Science.gov (United States)

    Dimas, Leon S; Buehler, Markus J

    2014-07-07

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

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. Optimal control of inspired perfluorocarbon temperature for induction of hypothermia by total liquid ventilation in juvenile lamb model.

    Science.gov (United States)

    Nadeau, Mathieu; Sage, Michael; Praud, Jean-Paul; Tissier, Renaud; Walti, Herve; Micheau, Philippe; Nadeau, Mathieu; Sage, Michael; Praud, Jean-Paul; Tissier, Renaud; Walti, Herve; Micheau, Philippe; Sage, Michael; Micheau, Philippe; Praud, Jean-Paul; Nadeau, Mathieu; Walti, Herve; Tissier, Renaud

    2016-08-01

    Mild hypothermia is well known for its therapeutic value in cardio- and neuroprotection. Many recent experimental studies have shown that the swiftness of the cooling offered by total liquid ventilation (TLV) holds great promise in achieving maximal therapeutic effect. TLV is an emerging ventilation technique in which the lungs are filled with breathable liquids, namely perfluorocarbons (PFCs). A liquid ventilator ensures subject ventilation by periodically renewing a volume of oxygenated, CO2-free and temperature-controlled breathable PFC. The substantial difference between breathing air and liquid is related to the fact that PFCs have over 500 times the volumetric thermal capacity of air 100% relative humidity. The PFC-filled lungs thus turn into an efficient heat exchanger with pulmonary circulation. The objective of the present study was to compute a posteriori the optimal inspired PFC temperature for ultrafast induction of mild hypothermia by TLV in a juvenile lamb experimentation using direct optimal control. The continuous time model and the discretized cycle-by-cycle model are presented. The control objectives of the direct optimal control are also presented and the results are compared with experimental data in order to validate the improved control performances. The computed direct optimal control showed that the inspired PFC temperature command can be improved to avoid temperature undershoots without altering the cooling performances.

  19. 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.

  20. Biological Aging - Criteria for Modeling and a New Mechanistic Model

    Science.gov (United States)

    Pletcher, Scott D.; Neuhauser, Claudia

    To stimulate interaction and collaboration across scientific fields, we introduce a minimum set of biological criteria that theoretical models of aging should satisfy. We review results of several recent experiments that examined changes in age-specific mortality rates caused by genetic and environmental manipulation. The empirical data from these experiments is then used to test mathematical models of aging from several different disciplines, including molecular biology, reliability theory, physics, and evolutionary biology/population genetics. We find that none of the current models are consistent with all of the published experimental findings. To provide an example of how our criteria might be applied in practice, we develop a new conceptual model of aging that is consistent with our observations.

  1. 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.

  2. 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

  3. Heuristic approaches to models and modeling in systems biology

    NARCIS (Netherlands)

    MacLeod, Miles

    2016-01-01

    Prediction and control sufficient for reliable medical and other interventions are prominent aims of modeling in systems biology. The short-term attainment of these goals has played a strong role in projecting the importance and value of the field. In this paper I identify the standard models must m

  4. (HBCU) Development and Application of a Biologically Inspired Methodology for the Optimized, Multi-Disciplinary and Multi-Objective Design of Air Vehicles

    Science.gov (United States)

    2013-05-01

    Approach to Modeling Morphogenesis Using Control Theory” Sao Paulo Journal of Mathematical Sciences (5) 281315. (b) N. Y. Kawabata , M.Sc., University of...Summer 2010, advisor: M.H. Kobayashi. Dissertation available from UHM library. 4. N. Y. Kawabata , M.Sc., University of Hawaii at Manoa, “A Biologically

  5. Biologically Inspired Self-assembling Synthesis of Bone-like Nano-hydroxyapatite/PLGA- (PEG-ASP)n Composite: A New Biomimetic Bone Tissue Engineering Scaffold Material

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    A new biomimetic bone tissue engineering scaffold material, nano-HA/ PLGA-( PEG- ASP )n composite, was synthesized by a biologically inspired self assembling approach. A novel biodegradable PLGA( PEG-ASP ) n copolymer with pendant amine functional groups and enhanced hydrophilicity was synthesized by bulk ring-opening copolymerization by DL-lactide( DLLA ) and glycolide( GA ) with Aspartic acid ( ASP )-Polyethylene glycol( PEG ) alt-prepolymer. A Three-dimensional, porous scaffold of the PLGA-( PEG-ASP )n copolymer was fabricated by a solvent casting, particulate leaching process. The scaffold was then incubated in modified simulated body fluid ( mSBF ) . Growth of HA nanocrystals on the inner pore surfaces of the porous scaffold is confirmed by calcium ion binding analyses, SEM, mass increase measurements and quantification of phosphate content within scaffolds . SEM analysis demonstrated the nucleation and growth of a continuous bonelike, low crystalline carbonated HA nanocrystals on the inner pore surfawes of the PLGA-( PEG-ASP)n scaffolds. The amount of calcium binding, total mass and the mass of pbosphate on experimental PLGA-( PEG- ASP )n scaffolds at different incubation times in mSBF was significantly greater than that of control PLGA scaffolds . This nano-HA/ PLGA- ( PEG-ASP )n composite shows some features of natural bone both in main composition and hierarchical microstructure. The ASPPEG alt-prepolymer modified PLGA copolymer provide a controllable high surface density and distribution of anionic functional groups which would enhauce nucleation and growth of bonelike mineral following exposure to mSBF. This biomimetic treatment provides a simple method for surface funetionalization and subsequent mineral nucleation and self-assembling on biodegradable polymer scaffolds for tissue engineering.

  6. Modeling delayed processes in biological systems

    Science.gov (United States)

    Feng, Jingchen; Sevier, Stuart A.; Huang, Bin; Jia, Dongya; Levine, Herbert

    2016-09-01

    Delayed processes are ubiquitous in biological systems and are often characterized by delay differential equations (DDEs) and their extension to include stochastic effects. DDEs do not explicitly incorporate intermediate states associated with a delayed process but instead use an estimated average delay time. In an effort to examine the validity of this approach, we study systems with significant delays by explicitly incorporating intermediate steps. We show that such explicit models often yield significantly different equilibrium distributions and transition times as compared to DDEs with deterministic delay values. Additionally, different explicit models with qualitatively different dynamics can give rise to the same DDEs revealing important ambiguities. We also show that DDE-based predictions of oscillatory behavior may fail for the corresponding explicit model.

  7. 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...

  8. BIOLOGICALLY INSPIRED HARDWARE CELL ARCHITECTURE

    DEFF Research Database (Denmark)

    2010-01-01

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

  9. Biologically Inspired Artificial Haircell Sensors

    Science.gov (United States)

    2008-06-23

    degree at the University of Illinois. James A. Liburdy, J.R. Welty Professor of Mechanical engineering, Oregon State University Daniel R. Morse...patent disclosure None. Honors/Awards James A. Liburdy, promoted to J.R. Welty Professor of Mechanical engineering, Oregon State University

  10. Spherical Cancer Models in Tumor Biology

    Directory of Open Access Journals (Sweden)

    Louis-Bastien Weiswald

    2015-01-01

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

  11. 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.

  12. 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.

  13. Documentation of TRU biological transport model (BIOTRAN)

    Energy Technology Data Exchange (ETDEWEB)

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

    1980-01-01

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

  14. Modeling the Biological Diversity of Pig Carcasses

    DEFF Research Database (Denmark)

    Erbou, Søren Gylling Hemmingsen

    for 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......This thesis applies methods from medical image analysis for modeling the biological diversity of pig carcasses. The Danish meat industry is very focused on improving product quality and productivity by optimizing the use of the carcasses and increasing productivity in the abattoirs. In order...... to achieve these goals there is a need for more detailed information about pig carcasses in relation to measures of quality. Non-invasive imaging such as X-ray Computed Tomography (CT) can provide this very detailed information discerning the major tissue types. Medical image analysis provides the tools...

  15. 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.

  16. 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 ...

  17. 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.

  18. 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.

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

    Directory of Open Access Journals (Sweden)

    Víctor López-Jaquero

    2016-10-01

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

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

    Science.gov (United States)

    López-Jaquero, Víctor; Rodríguez, Arturo C.; Teruel, Miguel A.; Montero, Francisco; Navarro, Elena; Gonzalez, Pascual

    2016-01-01

    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. PMID:27754371

  1. 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...... that modulates the parameters of the locomotor central pattern generators. We present phonotactic performance results of the simulated lizard-salamander hybrid robot....

  2. 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.

  3. 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.

  4. 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.

  5. Anti-icing property of bio-inspired micro-structure superhydrophobic surfaces and heat transfer model

    Science.gov (United States)

    Liu, Yan; Li, Xinlin; Jin, Jingfu; Liu, Jiaan; Yan, Yuying; Han, Zhiwu; Ren, Luquan

    2017-04-01

    Ice accumulation is a thorny problem which may inflict serious damage even disasters in many areas, such as aircraft, power line maintenance, offshore oil platform and locators of ships. Recent researches have shed light on some promising bio-inspired anti-icing strategies to solve this problem. Inspired by typical plant surfaces with super-hydrophobic character such as lotus leaves and rose petals, structured superhydrophobic surface are prepared to discuss the anti-icing property. 7075 Al alloy, an extensively used materials in aircrafts and marine vessels, is employed as the substrates. As-prepared surfaces are acquired by laser processing after being modified by stearic acid for 1 h at room temperature. The surface morphology, chemical composition and wettability are characterized by means of SEM, XPS, Fourier transform infrared (FTIR) spectroscopy and contact angle measurements. The morphologies of structured as-prepared samples include round hump, square protuberance and mountain-range-like structure, and that the as-prepared structured surfaces shows an excellent superhydrophobic property with a WCA as high as 166 ± 2°. Furthermore, the anti-icing property of as-prepared surfaces was tested by a self-established apparatus, and the crystallization process of a cooling water on the sample was recorded. More importantly, we introduced a model to analyze heat transfer process between the droplet and the structured surfaces. This study offers an insight into understanding the heat transfer process of the superhydrophobic surface, so as to further research about its unique property against ice accumulation.

  6. Towards Bio-Inspired Chromatic Behaviours in Surveillance Robots

    Directory of Open Access Journals (Sweden)

    Sampath Kumar Karutaa Gnaniar

    2016-09-01

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

  7. 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...

  8. A nonlinear scalar model of extreme mass ratio inspirals in effective field theory I. Self force through third order

    CERN Document Server

    Galley, Chad R

    2010-01-01

    The motion of a small compact object in a background spacetime is investigated in the context of a model nonlinear scalar field theory. This model is constructed to have a perturbative structure analogous to the General Relativistic description of extreme mass ratio inspirals (EMRIs). We apply the effective field theory approach to this model and calculate the finite part of the self force on the small compact object through third order in the ratio of the size of the compact object to the curvature scale of the background (e.g., black hole) spacetime. We use well-known renormalization methods and demonstrate the consistency of the formalism in rendering the self force finite at higher orders within a point particle prescription for the small compact object. This nonlinear scalar model should be useful for studying various aspects of higher-order self force effects in EMRIs but within a comparatively simpler context than the full gravitational case. These aspects include developing practical schemes for highe...

  9. Model checking biological systems described using ambient calculus

    DEFF Research Database (Denmark)

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

    2005-01-01

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

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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…

  15. 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).

  16. 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.

  17. 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.

  18. 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.

  19. 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.

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

    Science.gov (United States)

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

    2017-04-01

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

  1. Hydrodynamic surrogate models for bio-inspired micro-swimming robots

    CERN Document Server

    Tabak, Ahmet Fatih

    2013-01-01

    Research on untethered micro-swimming robots is growing fast owing to their potential impact on minimally invasive medical procedures. Candidate propulsion mechanisms of robots are based on flagellar mechanisms of micro organisms such as rotating rigid helices and traveling plane-waves on flexible rods. For design and control of swimming robots, accurate real-time models are necessary to compute trajectories, velocities and hydrodynamic forces acting on robots. Resistive force theory (RFT) provides an excellent framework for the development of real-time six degrees-of-freedom surrogate models for design optimization and control. However the accuracy of RFT-based models depends strongly on hydrodynamic interactions. Here, we introduce interaction coefficients that only multiply body resistance coefficients with no modification to local resistance coefficients on the tail. Interaction coefficients are obtained for a single specimen of Vibrio Algino reported in literature, and used in the RFT model for compariso...

  2. 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

  3. 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.

  4. 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.

  5. Modelling biological and chemically induced precipitation of calcium phosphate in enhanced biological phosphorus removal systems.

    Science.gov (United States)

    Barat, R; Montoya, T; Seco, A; Ferrer, J

    2011-06-01

    The biologically induced precipitation processes can be important in wastewater treatment, in particular treating raw wastewater with high calcium concentration combined with Enhanced Biological Phosphorus Removal. Currently, there is little information and experience in modelling jointly biological and chemical processes. This paper presents a calcium phosphate precipitation model and its inclusion in the Activated Sludge Model No 2d (ASM2d). The proposed precipitation model considers that aqueous phase reactions quickly achieve the chemical equilibrium and that aqueous-solid change is kinetically governed. The model was calibrated using data from four experiments in a Sequencing Batch Reactor (SBR) operated for EBPR and finally validated with two experiments. The precipitation model proposed was able to reproduce the dynamics of amorphous calcium phosphate (ACP) formation and later crystallization to hydroxyapatite (HAP) under different scenarios. The model successfully characterised the EBPR performance of the SBR, including the biological, physical and chemical processes.

  6. 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).

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

    Science.gov (United States)

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

    2016-01-01

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

  8. Cosmological perturbations in SFT inspired non-local scalar field models

    Energy Technology Data Exchange (ETDEWEB)

    Koshelev, Alexey S. [Vrije Universiteit Brussel and The International Solvay Institutes, Theoretische Natuurkunde, Brussels (Belgium); Vernov, Sergey Yu. [Instituto de Ciencias del Espacio (ICE/CSIC) and Institut d' Estudis Espacials de Catalunya (IEEC), Bellaterra, Barcelona (Spain); Lomonosov Moscow State University, Theoretical High Energy Physics Division, Skobeltsyn Institute of Nuclear Physics, Moscow (Russian Federation)

    2012-10-15

    We study cosmological perturbations in models with a single non-local scalar field originating from the string field theory description of the rolling tachyon dynamics. We construct the equation for the energy density perturbations of the non-local scalar field and explicitly prove that for the free field it is identical to a system of local cosmological perturbation equations in a particular model with multiple (maybe infinitely many) local free scalar fields. We also show that vector and tensor perturbations are absent in this set-up. (orig.)

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

    Science.gov (United States)

    Skinner, Brian

    2016-09-01

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

  10. Doubly heavy baryons in a quark model with AdS/QCD inspired potential

    CERN Document Server

    Giannuzzi, Floriana

    2009-01-01

    The spectrum of doubly heavy baryons, hadrons made up of two heavy quarks and one light quark, is computed through a potential model with relativistic kinematics. The expression for the $Q\\bar Q$ potential comes from the AdS/QCD correspondence.

  11. Gravitational Wave Tests of Strong Field General Relativity with Binary Inspirals: Realistic Injections and Optimal Model Selection

    CERN Document Server

    Sampson, Laura; Yunes, Nicolas

    2013-01-01

    We study generic tests of strong-field General Relativity using gravitational waves emitted during the inspiral of compact binaries. Previous studies have considered simple extensions to the standard post-Newtonian waveforms that differ by a single term in the phase. Here we improve on these studies by (i) increasing the realism of injections and (ii) determining the optimal waveform families for detecting and characterizing such signals. We construct waveforms that deviate from those in General Relativity through a series of post-Newtonian terms, and find that these higher-order terms can affect our ability to test General Relativity, in some cases by making it easier to detect a deviation, and in some cases by making it more difficult. We find that simple single-phase post-Einsteinian waveforms are sufficient for detecting deviations from General Relativity, and there is little to be gained from using more complicated models with multiple phase terms. The results found here will help guide future attempts t...

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

    Science.gov (United States)

    Mello, Clayton S.; de Melo, J. P. B. C.; Frederico, T.

    2017-03-01

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

  14. 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.

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

    OpenAIRE

    Ziyu Ren; Kainan Hu; Tianmiao Wang; Li Wen

    2016-01-01

    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 morphol...

  16. Financial price dynamics and agent-based models as inspired by Benoit Mandelbrot

    Science.gov (United States)

    LeBaron, Blake

    2016-12-01

    This short note draws some connections between Mandelbrot‗s empirical legacy, and the interdisciplinary work that followed in finance. Much of this work is now labeled econophysics, but some has always been more in the realm of economics than physics. In a few areas the overlap is even becoming quite complete as in market microstructure. I will also give some ideas about the various successes and failures in this area, and some directions for the future of agent- based modeling in particular.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

    Paula, Goa 403 004, India. Phone: +91 0832 2450624, Fax: +91 0832 2450606, e-mail: mjudith@nio.org Introduction In India, classroom education in biology does not generally include an exercise in which the data can be used to develop models.... This has hampered exposure to quantitative tools in biology, much to the disadvantage of students. The purpose of this note is to report an exercise we carried out to expose traditional biologists educated in India to mathematical modelling of biological...

  1. 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

  2. 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.

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

    Science.gov (United States)

    Bahia, C. A. S.; Broilo, M.; Luna, E. G. S.

    2016-04-01

    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 (¯pp) total cross sections, σpp,\\bar{pp}tot(s), obtained using the CTEQ6L1 parton distribution function, are consistent with the recent data from the TOTEM experiment.

  4. 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).

  5. 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.

  6. 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.

  7. Analytic modeling of tidal effects in the relativistic inspiral of binary neutron stars.

    Science.gov (United States)

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

    2010-12-31

    To detect the gravitational-wave (GW) 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 present the two longest (to date) general-relativistic simulations of equal-mass binary neutron stars with different compactnesses, C=0.12 and C=0.14, and compare them with a tidal extension of the effective-one-body (EOB) model. The typical numerical phasing errors over the ≃22   GW cycles are Δϕ≃±0.24   rad. By calibrating only one parameter (representing a higher-order amplification of tidal effects), the EOB model can reproduce, within the numerical error, the two numerical waveforms essentially up to the merger. By contrast, the third post-Newtonian Taylor-T4 approximant with leading-order tidal corrections dephases with respect to the numerical waveforms by several radians.

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

    Science.gov (United States)

    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

  9. Modeling of Biological Intelligence for SCM System Optimization

    OpenAIRE

    Shengyong Chen; Yujun Zheng; Carlo Cattani; Wanliang Wang

    2012-01-01

    This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing c...

  10. 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 $E_{6}$.

  11. 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.

  12. Multi-scale modelling and simulation in systems biology.

    Science.gov (United States)

    Dada, Joseph O; Mendes, Pedro

    2011-02-01

    The aim of systems biology is to describe and understand biology at a global scale where biological functions are recognised as a result of complex mechanisms that happen at several scales, from the molecular to the ecosystem. Modelling and simulation are computational tools that are invaluable for description, prediction and understanding these mechanisms in a quantitative and integrative way. Therefore the study of biological functions is greatly aided by multi-scale methods that enable the coupling and simulation of models spanning several spatial and temporal scales. Various methods have been developed for solving multi-scale problems in many scientific disciplines, and are applicable to continuum based modelling techniques, in which the relationship between system properties is expressed with continuous mathematical equations or discrete modelling techniques that are based on individual units to model the heterogeneous microscopic elements such as individuals or cells. In this review, we survey these multi-scale methods and explore their application in systems biology.

  13. Obstacle Avoidance Method for a Group of Humanoids Inspired by Social Force Model

    Directory of Open Access Journals (Sweden)

    Ali Sadiyoko

    2015-12-01

    Full Text Available This paper presents a new formulation for obstacle and collision behavior on a group of humanoid robots that adopts walking behavior of pedestrian crowd. A pedestrian receives position information from the other pedestrians, calculate his movement and then continuing his objective. This capability is defined as socio-dynamic capability of a pedestrian. Pedestrian’s walking behavior in a crowd is an example of a sociodynamics system and known as Social Force Model (SFM. This research is trying to implement the avoidance terms in SFM into robot’s behavior. The aim of the integration of SFM into robot’s behavior is to increase robot’s ability to maintain its safety by avoiding the obstacles and collision with the other robots. The attractive feature of the proposed algorithm is the fact that the behavior of the humanoids will imitate the human’s behavior while avoiding the obstacle. The proposed algorithm combines formation control using Consensus Algorithm (CA with collision and obstacle avoidance technique using SFM. Simulation and experiment results show the effectiveness of the proposed algorithm.

  14. 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.

  15. Learning from nature: Nature-inspired algorithms

    DEFF Research Database (Denmark)

    Albeanu, Grigore; Madsen, Henrik; Popentiu-Vladicescu, Florin

    2016-01-01

    During last decade, the nature has inspired researchers to develop new algorithms. The largest collection of nature-inspired algorithms is biology-inspired: swarm intelligence (particle swarm optimization, ant colony optimization, cuckoo search, bees' algorithm, bat algorithm, firefly algorithm etc...... on collective social behaviour of organisms, researchers have developed optimization strategies taking into account not only the individuals, but also groups and environment. However, learning from nature, new classes of approaches can be identified, tested and compared against already available algorithms....... This work reviews the most effective nature-inspired algorithms and describes learning strategies based on nature oriented thinking. Examples and the benefits obtained from applying nature-inspired strategies in test generation, learners group optimization, and artificial immune systems for learning...

  16. Model for biological communication in a nanofabricated cell-mimic driven by stochastic resonance

    Energy Technology Data Exchange (ETDEWEB)

    Karig, David K [ORNL; Siuti, Piro [ORNL; Dar, Roy D. [University of Tennessee, Knoxville (UTK); Retterer, Scott T [ORNL; Doktycz, Mitchel John [ORNL; Simpson, Michael L [ORNL

    2011-01-01

    Cells offer natural examples of highly efficient networks of nanomachines. Accordingly, both intracellular and intercellular communication mechanisms in nature are looked to as a source of inspiration and instruction for engineered nanocommunication. Harnessing biological functionality in this manner requires an interdisciplinary approach that integrates systems biology, synthetic biology, and nanofabrication. Recent years have seen the amassing of a tremendous wealth of data from the sequencing of new organisms and from high throughput expression experiments. At the same time, a deeper fundamental understanding of individual cell function has been developed, as exemplified by the growth of fields such as noise biology, which seeks to characterize the role of noise in gene expression. The availability of well characterized biological components coupled with a deeper understanding of cell function has led to efforts to engineer both living cells and to create bio-like functionality in non-living substrates in the field of synthetic biology. Here, we present a model system that exemplifies the synergism between these realms of research. We propose a synthetic gene network for operation in a nanofabricated cell mimic array that propagates a biomolecular signal over long distances using the phenomenon of stochastic resonance. Our system consists of a bacterial quorum sensing signal molecule, a bistable genetic switch triggered by this signal, and an array of nanofabricated cell mimic wells that contain the genetic system. An optimal level of noise in the system helps to propagate a time-varying AHL signal over long distances through the array of mimics. This noise level is determined both by the system volume and by the parameters of the genetic network. Our proposed genetically driven stochastic resonance system serves as a testbed for exploring the potential harnessing of gene expression noise to aid in the transmission of a time-varying molecular signal.

  17. 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...

  18. 3D printed, bio-inspired prototypes and analytical models for structured suture interfaces with geometrically-tuned deformation and failure behavior

    Science.gov (United States)

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

    2014-12-01

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

  19. 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...

  20. Highly eccentric inspirals into a black hole

    Science.gov (United States)

    Osburn, Thomas; Warburton, Niels; Evans, Charles R.

    2016-03-01

    We model the inspiral of a compact stellar-mass object into a massive nonrotating 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 ˜0.8 and initial separations as large as p ˜50 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 ˜0.1 radians or better. The difference between self-force models and inspirals computed in the radiative approximation is quantified.

  1. Spatial Modeling Tools for Cell Biology

    Science.gov (United States)

    2006-10-01

    Capillary blood flow is shown circling both sides of the cell and entering from the bottom part of the figure. Species are transported in and out of...replication molecules, mitochondria – in which most of he cell energy metabolism takes place, endoplasmic reticula – build of complex membranes... part of the cell biology problem. Numerical solutions of even large scale ODE systems are very fast (seconds to minutes on powerful PCs). Numerical

  2. Synthetic biology of minimal living cells: primitive cell models and semi-synthetic cells.

    Science.gov (United States)

    Stano, Pasquale

    2010-09-01

    This article summarizes a contribution presented at the ESF 2009 Synthetic Biology focused on the concept of the minimal requirement for life and on the issue of constructive (synthetic) approaches in biological research. The attempts to define minimal life within the framework of autopoietic theory are firstly described, and a short report on the development of autopoietic chemical systems based on fatty acid vesicles, which are relevant as primitive cell models is given. These studies can be used as a starting point for the construction of more complex systems, firstly being inspired by possible origins of life scenarioes (and therefore by considering primitive functions), then by considering an approach based on modern biomacromolecular-encoded functions. At this aim, semi-synthetic minimal cells are defined as those man-made vesicle-based systems that are composed of the minimal number of genes, proteins, biomolecules and which can be defined as living. Recent achievements on minimal sized semi-synthetic cells are then discussed, and the kind of information obtained is recognized as being distinctively derived by a constructive approach. Synthetic biology is therefore a fundamental tool for gaining basic knowledge about biosystems, and it should not be confined at all to the engineering side.

  3. 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.

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

    Science.gov (United States)

    Phair, Robert D

    2014-11-05

    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.

  5. Sustainable model building the role of standards and biological semantics.

    Science.gov (United States)

    Krause, Falko; Schulz, Marvin; Swainston, Neil; Liebermeister, Wolfram

    2011-01-01

    Systems biology models can be reused within new simulation scenarios, as parts of more complex models or as sources of biochemical knowledge. Reusability does not come by itself but has to be ensured while creating a model. Most important, models should be designed to remain valid in different contexts-for example, for different experimental conditions-and be published in a standardized and well-documented form. Creating reusable models is worthwhile, but it requires some efforts when a model is developed, implemented, documented, and published. Minimum requirements for published systems biology models have been formulated by the MIRIAM initiative. Main criteria are completeness of information and documentation, availability of machine-readable models in standard formats, and semantic annotations connecting the model elements with entries in biological Web resources. In this chapter, we discuss the assumptions behind bottom-up modeling; present important standards like MIRIAM, the Systems Biology Markup Language (SBML), and the Systems Biology Graphical Notation (SBGN); and describe software tools and services for handling semantic annotations. Finally, we show how standards can facilitate the construction of large metabolic network models.

  6. 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...

  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. 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.

  9. 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.

  10. 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...

  11. Mathematical and computational modeling in biology at multiple scales

    OpenAIRE

    Tuszynski, Jack A; Winter, Philip; White, Diana; Tseng, Chih-Yuan; Sahu, Kamlesh K.; Gentile, Francesco; Spasevska, Ivana; Omar, Sara Ibrahim; Nayebi, Niloofar; Churchill, Cassandra DM; Klobukowski, Mariusz; El-Magd, Rabab M Abou

    2014-01-01

    A variety of topics are reviewed in the area of mathematical and computational modeling in biology, covering the range of scales from populations of organisms to electrons in atoms. The use of maximum entropy as an inference tool in the fields of biology and drug discovery is discussed. Mathematical and computational methods and models in the areas of epidemiology, cell physiology and cancer are surveyed. The technique of molecular dynamics is covered, with special attention to force fields f...

  12. Structure learning for Bayesian networks as models of biological networks.

    Science.gov (United States)

    Larjo, Antti; Shmulevich, Ilya; Lähdesmäki, Harri

    2013-01-01

    Bayesian networks are probabilistic graphical models suitable for modeling several kinds of biological systems. In many cases, the structure of a Bayesian network represents causal molecular mechanisms or statistical associations of the underlying system. Bayesian networks have been applied, for example, for inferring the structure of many biological networks from experimental data. We present some recent progress in learning the structure of static and dynamic Bayesian networks from data.

  13. 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.

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

    Directory of Open Access Journals (Sweden)

    Simeonidis Evangelos

    2010-11-01

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

  15. 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

  16. 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.

  17. 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…

  18. Biological models for automatic target detection

    Science.gov (United States)

    Schachter, Bruce

    2008-04-01

    Humans are better at detecting targets in literal imagery than any known algorithm. Recent advances in modeling visual processes have resulted from f-MRI brain imaging with humans and the use of more invasive techniques with monkeys. There are four startling new discoveries. 1) The visual cortex does not simply process an incoming image. It constructs a physics based model of the image. 2) Coarse category classification and range-to-target are estimated quickly - possibly through the dorsal pathway of the visual cortex, combining rapid coarse processing of image data with expectations and goals. This data is then fed back to lower levels to resize the target and enhance the recognition process feeding forward through the ventral pathway. 3) Giant photosensitive retinal ganglion cells provide data for maintaining circadian rhythm (time-of-day) and modeling the physics of the light source. 4) Five filter types implemented by the neurons of the primary visual cortex have been determined. A computer model for automatic target detection has been developed based upon these recent discoveries. It uses an artificial neural network architecture with multiple feed-forward and feedback paths. Our implementation's efficiency derives from the observation that any 2-D filter kernel can be approximated by a sum of 2-D box functions. And, a 2-D box function easily decomposes into two 1-D box functions. Further efficiency is obtained by decomposing the largest neural filter into a high pass filter and a more sparsely sampled low pass filter.

  19. 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 t...

  20. 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...

  1. 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 ...

  2. Holography inspired stringy hadrons

    Science.gov (United States)

    Sonnenschein, Jacob

    2017-01-01

    Holography inspired stringy hadrons (HISH) is a set of models that describe hadrons: mesons, baryons and glueballs as strings in flat four dimensional space-time. The models are based on a "map" from stringy hadrons of holographic confining backgrounds. In this note we review the "derivation" of the models. We start with a brief reminder of the passage from the AdS5 ×S5 string theory to certain flavored confining holographic models. We then describe the string configurations in holographic backgrounds that correspond to a Wilson line, a meson, a baryon and a glueball. The key ingredients of the four dimensional picture of hadrons are the "string endpoint mass" and the "baryonic string vertex". We determine the classical trajectories of the HISH. We review the current understanding of the quantization of the hadronic strings. We end with a summary of the comparison of the outcome of the HISH models with the PDG data about mesons and baryons. We extract the values of the tension, masses and intercepts from best fits, write down certain predictions for higher excited hadrons and present attempts to identify glueballs.

  3. Clay Bells: Edo Inspiration

    Science.gov (United States)

    Wagner, Tom

    2010-01-01

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

  4. Synthetic biology between challenges and risks: suggestions for a model of governance and a regulatory framework, based on fundamental rights.

    Science.gov (United States)

    Colussi, Ilaria Anna

    2013-01-01

    This paper deals with the emerging synthetic biology, its challenges and risks, and tries to design a model for the governance and regulation of the field. The model is called of "prudent vigilance" (inspired by the report about synthetic biology, drafted by the U.S. Presidential Commission on Bioethics, 2010), and it entails (a) an ongoing and periodically revised process of assessment and management of all the risks and concerns, and (b) the adoption of policies - taken through "hard law" and "soft law" sources - that are based on the principle of proportionality (among benefits and risks), on a reasonable balancing between different interests and rights at stake, and are oriented by a constitutional frame, which is represented by the protection of fundamental human rights emerging in the field of synthetic biology (right to life, right to health, dignity, freedom of scientific research, right to environment). After the theoretical explanation of the model, its operability is "checked", by considering its application with reference to only one specific risk brought up by synthetic biology - biosecurity risk, i.e. the risk of bioterrorism.

  5. 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.

  6. Parameter estimation and model selection in computational biology.

    Directory of Open Access Journals (Sweden)

    Gabriele Lillacci

    2010-03-01

    Full Text Available A central challenge in computational modeling of biological systems is the determination of the model parameters. Typically, only a fraction of the parameters (such as kinetic rate constants are experimentally measured, while the rest are often fitted. The fitting process is usually based on experimental time course measurements of observables, which are used to assign parameter values that minimize some measure of the error between these measurements and the corresponding model prediction. The measurements, which can come from immunoblotting assays, fluorescent markers, etc., tend to be very noisy and taken at a limited number of time points. In this work we present a new approach to the problem of parameter selection of biological models. We show how one can use a dynamic recursive estimator, known as extended Kalman filter, to arrive at estimates of the model parameters. The proposed method follows. First, we use a variation of the Kalman filter that is particularly well suited to biological applications to obtain a first guess for the unknown parameters. Secondly, we employ an a posteriori identifiability test to check the reliability of the estimates. Finally, we solve an optimization problem to refine the first guess in case it should not be accurate enough. The final estimates are guaranteed to be statistically consistent with the measurements. Furthermore, we show how the same tools can be used to discriminate among alternate models of the same biological process. We demonstrate these ideas by applying our methods to two examples, namely a model of the heat shock response in E. coli, and a model of a synthetic gene regulation system. The methods presented are quite general and may be applied to a wide class of biological systems where noisy measurements are used for parameter estimation or model selection.

  7. 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.

  8. 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.

  9. Preservice Biology Teachers' Conceptions About the Tentative Nature of Theories and Models in Biology

    Science.gov (United States)

    Reinisch, Bianca; Krüger, Dirk

    2016-11-01

    In research on the nature of science, there is a need to investigate the role and status of different scientific knowledge forms. Theories and models are two of the most important knowledge forms within biology and are the focus of this study. During interviews, preservice biology teachers (N = 10) were asked about their understanding of theories and models. They were requested to give reasons why they see theories and models as either tentative or certain constructs. Their conceptions were then compared to philosophers' positions (e.g., Popper, Giere). A category system was developed from the qualitative content analysis of the interviews. These categories include 16 conceptions for theories (n tentative = 11; n certain = 5) and 18 conceptions for models (n tentative = 10; n certain = 8). The analysis of the interviews showed that the preservice teachers gave reasons for the tentativeness or certainty of theories and models either due to their understanding of the terms or due to their understanding of the generation or evaluation of theories and models. Therefore, a variety of different terminology, from different sources, should be used in learning-teaching situations. Additionally, an understanding of which processes lead to the generation, evaluation, and refinement or rejection of theories and models should be discussed with preservice teachers. Within philosophy of science, there has been a shift from theories to models. This should be transferred to educational contexts by firstly highlighting the role of models and also their connections to theories.

  10. BayesMD: flexible biological modeling for motif discovery

    DEFF Research Database (Denmark)

    Tang, Man-Hung Eric; Krogh, Anders; Winther, Ole

    2008-01-01

    We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fashion. A mixture of Dirichlets is used as prior over nucleotide probabilities in binding sites. It is trained on trans......We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fashion. A mixture of Dirichlets is used as prior over nucleotide probabilities in binding sites. It is trained...

  11. 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.

  12. Adaptive neural-based fuzzy modeling for biological systems.

    Science.gov (United States)

    Wu, Shinq-Jen; Wu, Cheng-Tao; Chang, Jyh-Yeong

    2013-04-01

    The inverse problem of identifying dynamic biological networks from their time-course response data set is a cornerstone of systems biology. Hill and Michaelis-Menten model, which is a forward approach, provides local kinetic information. However, repeated modifications and a large amount of experimental data are necessary for the parameter identification. S-system model, which is composed of highly nonlinear differential equations, provides the direct identification of an interactive network. However, the identification of skeletal-network structure is challenging. Moreover, biological systems are always subject to uncertainty and noise. Are there suitable candidates with the potential to deal with noise-contaminated data sets? Fuzzy set theory is developed for handing uncertainty, imprecision and complexity in the real world; for example, we say "driving speed is high" wherein speed is a fuzzy variable and high is a fuzzy set, which uses the membership function to indicate the degree of a element belonging to the set (words in Italics to denote fuzzy variables or fuzzy sets). Neural network possesses good robustness and learning capability. In this study we hybrid these two together into a neural-fuzzy modeling technique. A biological system is formulated to a multi-input-multi-output (MIMO) Takagi-Sugeno (T-S) fuzzy system, which is composed of rule-based linear subsystems. Two kinds of smooth membership functions (MFs), Gaussian and Bell-shaped MFs, are used. The performance of the proposed method is tested with three biological systems.

  13. 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.

  14. 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...

  15. Insect-Inspired Micropump: Flow in a Tube with Local Contractions

    OpenAIRE

    2015-01-01

    A biologically-inspired micropumping model in a three-dimensional tube subjected to localized wall constrictions is given in this article. The present study extends our previous pumping model where a 3D channel with a square cross-section is considered. The proposed pumping approach herein applies to tubular geometries and is given to mimic an insect respiration mode, where the tracheal tube rhythmic wall contractions are used/hypothesized to enhance the internal flow transport within the ent...

  16. Modeling of biological intelligence for SCM system optimization.

    Science.gov (United States)

    Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

    2012-01-01

    This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

  17. 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.

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

    Science.gov (United States)

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

    2016-01-29

    Biological networks play a key role in determining biological function and therefore, an understanding of their structure and dynamics is of central interest in systems biology. In Boolean models of such networks, the status of each molecule is either "on" or "off" and along with the molecules interact with each other, their individual status changes from "on" to "off" or vice-versa and the system of molecules in the network collectively go through a sequence of changes in state. This sequence of changes is termed a biological process. In this paper, we examine the common perception that events in biomolecular networks occur sequentially, in a cascade-like manner, and ask whether this is likely to be an inherent property. In further investigations of the budding and fission yeast cell-cycle, we identify two generic dynamical rules. A Boolean system that complies with these rules will automatically have a certain robustness. By considering the biological requirements in robustness and designability, we show that those Boolean dynamical systems, compared to an arbitrary dynamical system, statistically present the characteristics of cascadeness and sequentiality, as observed in the budding and fission yeast cell- cycle. These results suggest that cascade-like behavior might be an intrinsic property of biological processes.

  19. Cancer systems biology and modeling: microscopic scale and multiscale approaches.

    Science.gov (United States)

    Masoudi-Nejad, Ali; Bidkhori, Gholamreza; Hosseini Ashtiani, Saman; Najafi, Ali; Bozorgmehr, Joseph H; Wang, Edwin

    2015-02-01

    Cancer has become known as a complex and systematic disease on macroscopic, mesoscopic and microscopic scales. Systems biology employs state-of-the-art computational theories and high-throughput experimental data to model and simulate complex biological procedures such as cancer, which involves genetic and epigenetic, in addition to intracellular and extracellular complex interaction networks. In this paper, different systems biology modeling techniques such as systems of differential equations, stochastic methods, Boolean networks, Petri nets, cellular automata methods and agent-based systems are concisely discussed. We have compared the mentioned formalisms and tried to address the span of applicability they can bear on emerging cancer modeling and simulation approaches. Different scales of cancer modeling, namely, microscopic, mesoscopic and macroscopic scales are explained followed by an illustration of angiogenesis in microscopic scale of the cancer modeling. Then, the modeling of cancer cell proliferation and survival are examined on a microscopic scale and the modeling of multiscale tumor growth is explained along with its advantages.

  20. 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...

  1. Nonlinear Hyperbolic-Parabolic System Modeling Some Biological Phenomena

    Institute of Scientific and Technical Information of China (English)

    WU Shaohua; CHEN Hua

    2011-01-01

    In this paper, we study a nonlinear hyperbolic-parabolic system modeling some biological phenomena. By semigroup theory and Leray-Schauder fixed point argument, the local existence and uniqueness of the weak solutions for this system are proved. For the spatial dimension N = 1, the global existence of the weak solution will be established by the bootstrap argument.

  2. A methodology to annotate systems biology markup language models with the synthetic biology open language.

    Science.gov (United States)

    Roehner, Nicholas; Myers, Chris J

    2014-02-21

    Recently, we have begun to witness the potential of synthetic biology, noted here in the form of bacteria and yeast that have been genetically engineered to produce biofuels, manufacture drug precursors, and even invade tumor cells. The success of these projects, however, has often failed in translation and application to new projects, a problem exacerbated by a lack of engineering standards that combine descriptions of the structure and function of DNA. To address this need, this paper describes a methodology to connect the systems biology markup language (SBML) to the synthetic biology open language (SBOL), existing standards that describe biochemical models and DNA components, respectively. Our methodology involves first annotating SBML model elements such as species and reactions with SBOL DNA components. A graph is then constructed from the model, with vertices corresponding to elements within the model and edges corresponding to the cause-and-effect relationships between these elements. Lastly, the graph is traversed to assemble the annotating DNA components into a composite DNA component, which is used to annotate the model itself and can be referenced by other composite models and DNA components. In this way, our methodology can be used to build up a hierarchical library of models annotated with DNA components. Such a library is a useful input to any future genetic technology mapping algorithm that would automate the process of composing DNA components to satisfy a behavioral specification. Our methodology for SBML-to-SBOL annotation is implemented in the latest version of our genetic design automation (GDA) software tool, iBioSim.

  3. 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...

  4. Effect of the Mn Oxidation State on Single-Molecule-Magnet Properties: Mn(III) vs Mn(IV) in Biologically Inspired DyMn3O4 Cubanes.

    Science.gov (United States)

    Lin, Po-Heng; Tsui, Emily Y; Habib, Fatemah; Murugesu, Muralee; Agapie, Theodor

    2016-06-20

    Inspired by the ferromagnetic coupling in the cubane model CaMn(IV)3O4 of the oxygen-evolving complex of photosystem II, 3d-4f mixed-metal DyMn3O4 clusters were prepared for investigation of the magnetic properties. For comparison, YMn(IV)3O4 and YMn(IV)2Mn(III)O4 clusters were investigated as well and showed ferromagnetic interactions, like the calcium analogue. DyMn(IV)3O4 displays single-molecule-magnet properties, while the one-electron-reduced species (DyMn(IV)2Mn(III)O4) does not, despite the presence of a Mn(III) center with higher spin and single-ion anisotropy.

  5. Noether Symmetries Quantization and Superintegrability of Biological Models

    Directory of Open Access Journals (Sweden)

    Maria Clara Nucci

    2016-12-01

    Full Text Available It is shown that quantization and superintegrability are not concepts that are inherent to classical Physics alone. Indeed, one may quantize and also detect superintegrability of biological models by means of Noether symmetries. We exemplify the method by using a mathematical model that was proposed by Basener and Ross (2005, and that describes the dynamics of growth and sudden decrease in the population of Easter Island.

  6. 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.

  7. 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.

  8. Toward efficient riparian restoration: integrating economic, physical, and biological models.

    Science.gov (United States)

    Watanabe, Michio; Adams, Richard M; Wu, Junjie; Bolte, John P; Cox, Matt M; Johnson, Sherri L; Liss, William J; Boggess, William G; Ebersole, Joseph L

    2005-04-01

    This paper integrates economic, biological, and physical models to explore the efficient combination and spatial allocation of conservation efforts to protect water quality and increase salmonid populations in the Grande Ronde basin, Oregon. We focus on the effects of shade on water temperatures and the subsequent impacts on endangered juvenile salmonid populations. The integrated modeling system consists of a physical model that links riparian conditions and hydrological characteristics to water temperature; a biological model that links water temperature and riparian conditions to salmonid abundance, and an economic model that incorporates both physical and biological models to estimate minimum cost allocations of conservation efforts. Our findings indicate that conservation alternatives such as passive and active riparian restoration, the width of riparian restoration zones, and the types of vegetation used in restoration activities should be selected based on the spatial distribution of riparian characteristics in the basin. The relative effectiveness of passive and active restoration plays an important role in determining the efficient allocations of conservation efforts. The time frame considered in the restoration efforts and the magnitude of desired temperature reductions also affect the efficient combinations of restoration activities. If the objective of conservation efforts is to maximize fish populations, then fishery benefits should be directly targeted. Targeting other criterion such as water temperatures would result in different allocations of conservation efforts, and therefore are not generally efficient.

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. Analyzing Students' Understanding of Models and Modeling Referring to the Disciplines Biology, Chemistry, and Physics

    Science.gov (United States)

    Krell, Moritz; Reinisch, Bianca; Krüger, Dirk

    2015-01-01

    In this study, secondary school students' (N?=?617; grades 7 to 10) understanding of models and modeling was assessed using tasks which explicitly refer to the scientific disciplines of biology, chemistry, and physics and, as a control, to no scientific discipline. The students' responses are interpreted as their biology-, chemistry-, and…

  14. Dynamics of mathematical models in biology bringing mathematics to life

    CERN Document Server

    Zazzu, Valeria; Guarracino, Mario

    2016-01-01

    This volume focuses on contributions from both the mathematics and life science community surrounding the concepts of time and dynamicity of nature, two significant elements which are often overlooked in modeling process to avoid exponential computations. The book is divided into three distinct parts: dynamics of genomes and genetic variation, dynamics of motifs, and dynamics of biological networks. Chapters included in dynamics of genomes and genetic variation analyze the molecular mechanisms and evolutionary processes that shape the structure and function of genomes and those that govern genome dynamics. The dynamics of motifs portion of the volume provides an overview of current methods for motif searching in DNA, RNA and proteins, a key process to discover emergent properties of cells, tissues, and organisms. The part devoted to the dynamics of biological networks covers networks aptly discusses networks in complex biological functions and activities that interpret processes in cells. Moreover, chapters i...

  15. Green Algae as Model Organisms for Biological Fluid Dynamics.

    Science.gov (United States)

    Goldstein, Raymond E

    2015-01-01

    In the past decade the volvocine green algae, spanning from the unicellular Chlamydomonas to multicellular Volvox, have emerged as model organisms for a number of problems in biological fluid dynamics. These include flagellar propulsion, nutrient uptake by swimming organisms, hydrodynamic interactions mediated by walls, collective dynamics and transport within suspensions of microswimmers, the mechanism of phototaxis, and the stochastic dynamics of flagellar synchronization. Green algae are well suited to the study of such problems because of their range of sizes (from 10 μm to several millimetres), their geometric regularity, the ease with which they can be cultured and the availability of many mutants that allow for connections between molecular details and organism-level behavior. This review summarizes these recent developments and highlights promising future directions in the study of biological fluid dynamics, especially in the context of evolutionary biology, that can take advantage of these remarkable organisms.

  16. Programming biological models in Python using PySB.

    Science.gov (United States)

    Lopez, Carlos F; Muhlich, Jeremy L; Bachman, John A; Sorger, Peter K

    2013-01-01

    Mathematical equations are fundamental to modeling biological networks, but as networks get large and revisions frequent, it becomes difficult to manage equations directly or to combine previously developed models. Multiple simultaneous efforts to create graphical standards, rule-based languages, and integrated software workbenches aim to simplify biological modeling but none fully meets the need for transparent, extensible, and reusable models. In this paper we describe PySB, an approach in which models are not only created using programs, they are programs. PySB draws on programmatic modeling concepts from little b and ProMot, the rule-based languages BioNetGen and Kappa and the growing library of Python numerical tools. Central to PySB is a library of macros encoding familiar biochemical actions such as binding, catalysis, and polymerization, making it possible to use a high-level, action-oriented vocabulary to construct detailed models. As Python programs, PySB models leverage tools and practices from the open-source software community, substantially advancing our ability to distribute and manage the work of testing biochemical hypotheses. We illustrate these ideas using new and previously published models of apoptosis.

  17. On linear models and parameter identifiability in experimental biological systems.

    Science.gov (United States)

    Lamberton, Timothy O; Condon, Nicholas D; Stow, Jennifer L; Hamilton, Nicholas A

    2014-10-07

    A key problem in the biological sciences is to be able to reliably estimate model parameters from experimental data. This is the well-known problem of parameter identifiability. Here, methods are developed for biologists and other modelers to design optimal experiments to ensure parameter identifiability at a structural level. The main results of the paper are to provide a general methodology for extracting parameters of linear models from an experimentally measured scalar function - the transfer function - and a framework for the identifiability analysis of complex model structures using linked models. Linked models are composed by letting the output of one model become the input to another model which is then experimentally measured. The linked model framework is shown to be applicable to designing experiments to identify the measured sub-model and recover the input from the unmeasured sub-model, even in cases that the unmeasured sub-model is not identifiable. Applications for a set of common model features are demonstrated, and the results combined in an example application to a real-world experimental system. These applications emphasize the insight into answering "where to measure" and "which experimental scheme" questions provided by both the parameter extraction methodology and the linked model framework. The aim is to demonstrate the tools' usefulness in guiding experimental design to maximize parameter information obtained, based on the model structure.

  18. 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.

  19. Bio-Inspired Concepts: Studies of Biological Response to External Electric Fields for Cellular Manipulation and Diagnostics - Modeling and Experimentation

    Science.gov (United States)

    2005-05-03

    Dielectric Spectroscopy," IEEE trans. On Dielectrics and Electrical Insulation 8, 253 (2001). 8. M. Smoluchowski, "Drei vortrage uber diffusion...Intensity Electric Fields," IEEE Conf. On Dielectrics and Electrical Insulation (Bio- Electrics Workshop), Cancun, Mexico , Oct. 2002 (invited

  20. 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.

  1. 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.

  2. 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

  3. A bio-inspired, computational model suggests velocity gradients of optic flow locally encode ordinal depth at surface borders and globally they encode self-motion.

    Science.gov (United States)

    Raudies, Florian; Ringbauer, Stefan; Neumann, Heiko

    2013-09-01

    Visual navigation requires the estimation of self-motion as well as the segmentation of objects from the background. We suggest a definition of local velocity gradients to compute types of self-motion, segment objects, and compute local properties of optical flow fields, such as divergence, curl, and shear. Such velocity gradients are computed as velocity differences measured locally tangent and normal to the direction of flow. Then these differences are rotated according to the local direction of flow to achieve independence of that direction. We propose a bio-inspired model for the computation of these velocity gradients for video sequences. Simulation results show that local gradients encode ordinal surface depth, assuming self-motion in a rigid scene or object motions in a nonrigid scene. For translational self-motion velocity, gradients can be used to distinguish between static and moving objects. The information about ordinal surface depth and self-motion can help steering control for visual navigation.

  4. 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.

  5. 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.

  6. Bio-inspired variable structural color materials.

    Science.gov (United States)

    Zhao, Yuanjin; Xie, Zhuoying; Gu, Hongcheng; Zhu, Cun; Gu, Zhongze

    2012-04-21

    Natural structural color materials, especially those that can undergo reversible changes, are attracting increasing interest in a wide variety of research fields. Inspired by the natural creatures, many elaborately nanostructured photonic materials with variable structural colors were developed. These materials have found important applications in switches, display devices, sensors, and so on. In this critical review, we will provide up-to-date research concerning the natural and bio-inspired photonic materials with variable structural colors. After introducing the variable structural colors in natural creatures, we will focus on the studies of artificial variable structural color photonic materials, including their bio-inspired designs, fabrications and applications. The prospects for the future development of these fantastic variable structural color materials will also be presented. We believe this review will promote the communications among biology, bionics, chemistry, optical physics, and material science (196 references).

  7. 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.

  8. Inspiration or deflation? Feeling similar or dissimilar to slim and plus-size models affects self-evaluation of restrained eaters.

    Science.gov (United States)

    Papies, Esther K; Nicolaije, Kim A H

    2012-01-01

    The present studies examined the effect of perceiving images of slim and plus-size models on restrained eaters' self-evaluation. While previous research has found that such images can lead to either inspiration or deflation, we argue that these inconsistencies can be explained by differences in perceived similarity with the presented model. The results of two studies (ns=52 and 99) confirmed this and revealed that restrained eaters with high (low) perceived similarity to the model showed more positive (negative) self-evaluations when they viewed a slim model, compared to a plus-size model. In addition, Study 2 showed that inducing in participants a similarities mindset led to more positive self-evaluations after viewing a slim compared to a plus-size model, but only among restrained eaters with a relatively high BMI. These results are discussed in the context of research on social comparison processes and with regard to interventions for protection against the possible detrimental effects of media images.

  9. 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.

  10. 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.

  11. 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.

  12. 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)

  13. Limited Bandwidth Recognition of Collective Behaviors in Bio-Inspired Swarms

    Science.gov (United States)

    2014-05-09

    UAV path planning and applies to some constant-speed, non-holonomic ground robots [5]. Similar to the Couzin model of biological swarms [3] and the...BEHAVIORS IN BIO-INSPIRED SWARMS 5a. CONTRACT NUMBER IN-HOUSE 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 62788F 6. AUTHOR(S) Daniel S. Brown (AFRL... swarming and modes of controlling them are numerous; however, to date swarm researchers have mostly ignored a fundamental problem that impedes

  14. 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.

  15. 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).

  16. 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.

  17. Ferrokinetics: a biologic model for plasma iron exchange in man.

    Science.gov (United States)

    Cook, J D; Marsaglia, G; Eschbach, J W; Funk, D D; Finch, C A

    1970-02-01

    A method is presented for calculating internal iron kinetics. An early reflux associated with extravascular exchange and a late reflux associated with erythropoiesis are described. A biologic model of iron exchange is proposed in which erythron iron turnover is divided into an effective portion (iron fixed in circulating red cells) and wastage iron of erythropoiesis (late reflux). Nonerythroid iron exchange also has a fixed portion (parenchymal uptake) and an early reflux (lymphatic circuit), both of which correlate in amount with the amount of plasma iron. Ferrokinetic measurements in normal subjects and in various pathologic states are presented to validate the model.

  18. 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...

  19. Experimental model of arteriovenous malformation in vitro using biological grafts

    Directory of Open Access Journals (Sweden)

    Sandu Aurelia Mihaela

    2015-06-01

    Full Text Available Introduction: Brain arteriovenous malformations (AVMs represent a serious health problem all around the world. Experimental models help to better understand the pathophysiology of these lesions. Experiment: We performed an experimental model of AVM using biological grafts, arteries and veins harvested from chicken wings at the elbow joint. We used 14 vessels and we performed 20 end-to-end anastomoses to create a nidus with a single feeding artery and a single draining vein. The system was irrigated with colored solution. The experiment was done according with law in force regarding experimental research activity. Conclusions: Experimental models allow us to understand the hemodynamics and predict the outcome of brain AVMs in humans. This experimental model is a useful tool in understanding the hemodynamic properties of brain AVMs. It is very useful in vascular anastomosis training

  20. 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.

  1. 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…

  2. 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)

  3. 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…

  4. Inspire & innovate : Endbericht

    NARCIS (Netherlands)

    Cornelissen, T.; Lugtenaar, M.; Balendonck, J.; Ruckelshausen, A.; Wit, de R.

    2008-01-01

    Met het project Inspire & Innovate helpt de EU Nederlandse en Duitse bedrijven in met name de sectoren Food en Life Sciences op weg. Het project is bedoeld voor MKB-bedrijven in de Euregio Rijn-Waal en de EUREGIO die inhoudelijke en financiële ondersteuning zoeken om hun innovatieplannen door te

  5. 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.

  6. Optimal Control through Biologically-Inspired Pursuit

    Science.gov (United States)

    2004-01-01

    Transactions on Automatic Control 48, 988– 1001. Roumeliotis, S.I. and G.A. Bekey (2002). Distributed multi-robot localization. IEEE Transactions on Robotics and...1999). Distributed covering by ant- robots using evaporating traces. IEEE Transactions on Robotics and Automation 15(5), 918–933.

  7. Biologically Inspired Polymer Micro-Patterned Adhesives

    Science.gov (United States)

    2008-11-01

    contained a volatile, hydrophilic phase.1 Another suggests that the pad secretion from the locust Locusta migratoria is an emulsion of lipidic nano...R.; Stierhof, Y. D.; Gorb, S.; Schwarz, U. Chemical composition of the attachment pad secretion of the locust Locusta migratoria . Insect Biochem

  8. Biological Inspiration for Agile Autonomous Air Vehicles

    Science.gov (United States)

    2007-11-01

    vehicles in confined airspace will quickly exceed the abilities of a remote human operator, substantial autonomy is essential. The political, ethical ...and Kirschner, 1997 provide an in-depth but accessible discussion on the interplay of biochemistry, genetics and embryology in animal evolution

  9. Learning from nature: biologically-inspired sensors

    NARCIS (Netherlands)

    Wicaksono, D.H.B.

    2008-01-01

    New emerging sensing applications demand novel sensors in micro-/nano-scale to enable integration and embedding into higher level structures or systems. Downsizing the structure will usually decrease the sensitivity of the sensors, since the sensitivity is a function of geometrical parameters, e.g.

  10. Project Summary: Biology-Inspired Autonomous Control

    Science.gov (United States)

    2011-02-01

    relative high performance predictability currently associated with automated machines. Anyone who has walked a normally well behaved male dog in the...possibilities as well. Attitude control systems normally include proportional and integral control on sensed attitude, with damping and robustness provided...attacking predators. Some examples include red-wing black bird nest defense [1], meerkat predator mobbing [2], and predator identification in guppy schools

  11. Multi-AUV Hunting Algorithm Based on Bio-inspired Neural Network in Unknown Environments

    Directory of Open Access Journals (Sweden)

    Daqi Zhu

    2015-11-01

    Full Text Available The multi-AUV hunting problem is one of the key issues in multi-robot system research. In order to hunt the target efficiently, a new hunting algorithm based on a bio-inspired neural network has been proposed in this paper. Firstly, the AUV’s working environment can be represented, based on the biological-inspired neural network model. There is one-to-one correspondence between each neuron in the neural network and the position of the grid map in the underwater environment. The activity values of biological neurons then guide the AUV’s sailing path and finally the target is surrounded by AUVs. In addition, a method called negotiation is used to solve the AUV’s allocation of hunting points. The simulation results show that the algorithm used in the paper can provide rapid and highly efficient path planning in the unknown environment with obstacles and non-obstacles.

  12. Biologic

    CERN Document Server

    Kauffman, L H

    2002-01-01

    In this paper we explore the boundary between biology and the study of formal systems (logic). In the end, we arrive at a summary formalism, a chapter in "boundary mathematics" where there are not only containers but also extainers ><, entities open to interaction and distinguishing the space that they are not. The boundary algebra of containers and extainers is to biologic what boolean algebra is to classical logic. We show how this formalism encompasses significant parts of the logic of DNA replication, the Dirac formalism for quantum mechanics, formalisms for protein folding and the basic structure of the Temperley Lieb algebra at the foundations of topological invariants of knots and links.

  13. 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..

  14. 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.

  15. Revision history aware repositories of computational models of biological systems

    Directory of Open Access Journals (Sweden)

    Nickerson David P

    2011-01-01

    Full Text Available Abstract Background Building repositories of computational models of biological systems ensures that published models are available for both education and further research, and can provide a source of smaller, previously verified models to integrate into a larger model. One problem with earlier repositories has been the limitations in facilities to record the revision history of models. Often, these facilities are limited to a linear series of versions which were deposited in the repository. This is problematic for several reasons. Firstly, there are many instances in the history of biological systems modelling where an 'ancestral' model is modified by different groups to create many different models. With a linear series of versions, if the changes made to one model are merged into another model, the merge appears as a single item in the history. This hides useful revision history information, and also makes further merges much more difficult, as there is no record of which changes have or have not already been merged. In addition, a long series of individual changes made outside of the repository are also all merged into a single revision when they are put back into the repository, making it difficult to separate out individual changes. Furthermore, many earlier repositories only retain the revision history of individual files, rather than of a group of files. This is an important limitation to overcome, because some types of models, such as CellML 1.1 models, can be developed as a collection of modules, each in a separate file. The need for revision history is widely recognised for computer software, and a lot of work has gone into developing version control systems and distributed version control systems (DVCSs for tracking the revision history. However, to date, there has been no published research on how DVCSs can be applied to repositories of computational models of biological systems. Results We have extended the Physiome Model

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

    Science.gov (United States)

    Zhu, Zengrong; Huangfu, Danwei

    2013-02-01

    Developmental biology has long benefited from studies of classic model organisms. Recently, human pluripotent stem cells (hPSCs), including human embryonic stem cells and human induced pluripotent stem cells, have emerged as a new model system that offers unique advantages for developmental studies. Here, we discuss how studies of hPSCs can complement classic approaches using model organisms, and how hPSCs can be used to recapitulate aspects of human embryonic development 'in a dish'. We also summarize some of the recently developed genetic tools that greatly facilitate the interrogation of gene function during hPSC differentiation. With the development of high-throughput screening technologies, hPSCs have the potential to revolutionize gene discovery in mammalian development.

  17. Population pharmacokinetic-pharmacodynamic modeling of biological agents: when modeling meets reality.

    Science.gov (United States)

    Mould, Diane R; Frame, Bill

    2010-09-01

    The pharmacokinetics (PK) and pharmacodynamics (PD) of many biological agents (biologics) have inherent complexities requiring specialized approaches to develop reliable, unbiased models. Three cases are covered: preponderance of zero values, nonresponder subpopulations, and adaptive dosing. Engineered biologics exhibit high affinity for target receptors. Biologics can saturate receptors, abolishing free receptor levels for protracted periods. Consequently, the distribution of observations can be heavy at, and near, the boundary. A 2-part model (ie, a truncated δ log-normal distribution) may be appropriate. Mixture models identify subpopulations based on bimodal or multimodal distributions of η values. With biologics, PD may be compromised because of lack of receptors, or the PD may be affected because of other events resulting in erratic excursions. Nonresponders exhibit a random walk-around placebo trajectory, resulting in high residual variability. The distributions of etas are often badly skewed or polymodal. An indescribable mixture model separates subjects who are nonresponders, providing diagnostic pharmacologic information on the drug. Many biologics use PD-based adaptive dosing. During model development, data used for model development include adaptive dosing. For simulation, adaptive dosing must be implemented. Failure to account for dose adjustments results in biased or inflated prediction intervals because subjects in the simulated data undergo inappropriate dose adjustments.

  18. Testing Models: A Key Aspect to Promote Teaching Activities Related to Models and Modelling in Biology Lessons?

    Science.gov (United States)

    Krell, Moritz; Krüger, Dirk

    2016-01-01

    This study investigated biology teachers' (N = 148) understanding of models and modelling (MoMo), their model-related teaching activities and relations between the two. A framework which distinguishes five aspects of MoMo in science ("nature of models," "multiple models," "purpose of models," "testing…

  19. Biomimetics inspired surfaces for drag reduction and oleophobicity/philicity

    Directory of Open Access Journals (Sweden)

    Bharat Bhushan

    2011-02-01

    Full Text Available The emerging field of biomimetics allows one to mimic biology or nature to develop nanomaterials, nanodevices, and processes which provide desirable properties. Hierarchical structures with dimensions of features ranging from the macroscale to the nanoscale are extremely common in nature and possess properties of interest. There are a large number of objects including bacteria, plants, land and aquatic animals, and seashells with properties of commercial interest. Certain plant leaves, such as lotus (Nelumbo nucifera leaves, are known to be superhydrophobic and self-cleaning due to the hierarchical surface roughness and presence of a wax layer. In addition to a self-cleaning effect, these surfaces with a high contact angle and low contact angle hysteresis also exhibit low adhesion and drag reduction for fluid flow. An aquatic animal, such as a shark, is another model from nature for the reduction of drag in fluid flow. The artificial surfaces inspired from the shark skin and lotus leaf have been created, and in this article the influence of structure on drag reduction efficiency is reviewed. Biomimetic-inspired oleophobic surfaces can be used to prevent contamination of the underwater parts of ships by biological and organic contaminants, including oil. The article also reviews the wetting behavior of oil droplets on various superoleophobic surfaces created in the lab.

  20. Biomimetics inspired surfaces for drag reduction and oleophobicity/philicity.

    Science.gov (United States)

    Bhushan, Bharat

    2011-01-01

    The emerging field of biomimetics allows one to mimic biology or nature to develop nanomaterials, nanodevices, and processes which provide desirable properties. Hierarchical structures with dimensions of features ranging from the macroscale to the nanoscale are extremely common in nature and possess properties of interest. There are a large number of objects including bacteria, plants, land and aquatic animals, and seashells with properties of commercial interest. Certain plant leaves, such as lotus (Nelumbo nucifera) leaves, are known to be superhydrophobic and self-cleaning due to the hierarchical surface roughness and presence of a wax layer. In addition to a self-cleaning effect, these surfaces with a high contact angle and low contact angle hysteresis also exhibit low adhesion and drag reduction for fluid flow. An aquatic animal, such as a shark, is another model from nature for the reduction of drag in fluid flow. The artificial surfaces inspired from the shark skin and lotus leaf have been created, and in this article the influence of structure on drag reduction efficiency is reviewed. Biomimetic-inspired oleophobic surfaces can be used to prevent contamination of the underwater parts of ships by biological and organic contaminants, including oil. The article also reviews the wetting behavior of oil droplets on various superoleophobic surfaces created in the lab.

  1. Modeling biological systems with delays in Bio-PEPA

    CERN Document Server

    Caravagna, Giulio; 10.4204/EPTCS.40.7

    2010-01-01

    Delays in biological systems may be used to model events for which the underlying dynamics cannot be precisely observed, or to provide abstraction of some behavior of the system resulting more compact models. In this paper we enrich the stochastic process algebra Bio-PEPA, with the possibility of assigning delays to actions, yielding a new non-Markovian process algebra: Bio-PEPAd. This is a conservative extension meaning that the original syntax of Bio-PEPA is retained and the delay specification which can now be associated with actions may be added to existing Bio-PEPA models. The semantics of the firing of the actions with delays is the delay-as-duration approach, earlier presented in papers on the stochastic simulation of biological systems with delays. These semantics of the algebra are given in the Starting-Terminating style, meaning that the state and the completion of an action are observed as two separate events, as required by delays. Furthermore we outline how to perform stochastic simulation of Bio...

  2. Modeling of biological clogging in unsaturated porous media

    Science.gov (United States)

    Soleimani, Sahar; Van Geel, Paul J.; Isgor, O. Burkan; Mostafa, Mohamed B.

    2009-04-01

    A two-dimensional unsaturated flow and transport model, which includes microbial growth and decay, has been developed to simulate biological clogging in unsaturated soils, specifically biofilters. The bacterial growth and rate of solute reduction due to biodegradation is estimated using the Monod equation. The effect of microbial growth is considered in the proposed conceptual model that relates the relative permeability term for unsaturated flow to the microbial growth. Two applications of the model are presented in this study. Using the model, the clogging mechanism in different soils has been simulated. The results of the model indicate that the time to reach a clogged state is influenced by the hydraulic properties of the soil. Clogging is delayed in soils with higher saturated hydraulic conductivities, and higher porosities. For the relative permeability model proposed, higher van Genuchten n values lead to a delay in clogging. The model was also used to simulate the progressive clogging of a septic bed as the biomat initially forms at the up-gradient end of the distribution pipe, displacing wastewater infiltration and biomat formation further down-gradient over time.

  3. Bridging Mechanistic and Phenomenological Models of Complex Biological Systems

    Science.gov (United States)

    Transtrum, Mark K.; Qiu, Peng

    2016-01-01

    The inherent complexity of biological systems gives rise to complicated mechanistic models with a large number of parameters. On the other hand, the collective behavior of these systems can often be characterized by a relatively small number of phenomenological parameters. We use the Manifold Boundary Approximation Method (MBAM) as a tool for deriving simple phenomenological models from complicated mechanistic models. The resulting models are not black boxes, but remain expressed in terms of the microscopic parameters. In this way, we explicitly connect the macroscopic and microscopic descriptions, characterize the equivalence class of distinct systems exhibiting the same range of collective behavior, and identify the combinations of components that function as tunable control knobs for the behavior. We demonstrate the procedure for adaptation behavior exhibited by the EGFR pathway. From a 48 parameter mechanistic model, the system can be effectively described by a single adaptation parameter τ characterizing the ratio of time scales for the initial response and recovery time of the system which can in turn be expressed as a combination of microscopic reaction rates, Michaelis-Menten constants, and biochemical concentrations. The situation is not unlike modeling in physics in which microscopically complex processes can often be renormalized into simple phenomenological models with only a few effective parameters. The proposed method additionally provides a mechanistic explanation for non-universal features of the behavior. PMID:27187545

  4. Population Dynamics P system (PDP) models: a standardized protocol for describing and applying novel bio-inspired computing tools.

    Science.gov (United States)

    Colomer, Maria Àngels; Margalida, Antoni; Pérez-Jiménez, Mario J

    2013-01-01

    Today, the volume of data and knowledge of processes necessitates more complex models that integrate all available information. This handicap has been solved thanks to the technological advances in both software and hardware. Computational tools available today have allowed developing a new family of models, known as computational models. The description of these models is difficult as they can not be expressed analytically, and it is therefore necessary to create protocols that serve as guidelines for future users. The Population Dynamics P systems models (PDP) are a novel and effective computational tool to model complex problems, are characterized by the ability to work in parallel (simultaneously interrelating different processes), are modular and have a high computational efficiency. However, the difficulty of describing these models therefore requires a protocol to unify the presentation and the steps to follow. We use two case studies to demonstrate the use and implementation of these computational models for population dynamics and ecological process studies, discussing briefly their potential applicability to simulate complex ecosystem dynamics.

  5. A heat transfer model for biological wastewater treatment system

    Science.gov (United States)

    Lin, S. H.

    A heat transfer model for predicting the water temperature of aeration tank in a biological wastewater treatment plant is presented. The heat transfer mechanisms involved in the development of the heat transfer model include heat gains from solar radiation and biochemical reaction and heat losses from evaporation, aeration, wind blowing and conduction through tank walls. Several empirical correlations were adopted and appropriate assumptions made to facilitate the model development. Experiments were conducted in the biological wastewater treatment plant of a chemical fiber company over a year's period. The operational, weather and temperature data were registered. The daily water temperature data were averaged over a month period and compared with the theoretical prediction. Excellent agreement has been obtained between the predicted and measured temperatures, verifying the proposed heat transfer model. Zusammenfassung Es wird ein Wärmeübergangsmodell zur Berechnung der Wassertemperatur im Belüftungstank einer Anlage zur biologischen Abwasserbehandlung vorgestellt. Die in das Modell eingehenden Wärmeübergangsmechanismen umfassen: solare Wärmeeinstrahlung, biochemische Reaktion, Wärmeverluste durch Verdampfung, Belüftung, Windeinfluß und Leitung durch die Behälterwände. Mehrere empirische Beziehungen sowie vertretbare Annahmen tragen zur Modellvereinfachung bei. An der biologischen Abwasser-Kläranlage einer Chemiefaserfirma wurden ein Jahr lang Experimente durchgeführt und dabei Betriebs-, Wetter- und Temperaturdaten aufgezeichnet. Die täglichen Wassertemperaturen, gemittelt über einen Monat, zeigten ausgezeichnete Übereinstimmung mit den theoretischen Vorausberechnungen und bestätigten so die Brauchbarkeit des vorgeschlagenen Wärmeübergangsmodells.

  6. Modeling human risk: Cell & molecular biology in context

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-06-01

    It is anticipated that early in the next century manned missions into outer space will occur, with a mission to Mars scheduled between 2015 and 2020. However, before such missions can be undertaken, a realistic estimation of the potential risks to the flight crews is required. One of the uncertainties remaining in this risk estimation is that posed by the effects of exposure to the radiation environment of outer space. Although the composition of this environment is fairly well understood, the biological effects arising from exposure to it are not. The reasons for this are three-fold: (1) A small but highly significant component of the radiation spectrum in outer space consists of highly charged, high energy (HZE) particles which are not routinely experienced on earth, and for which there are insufficient data on biological effects; (2) Most studies on the biological effects of radiation to date have been high-dose, high dose-rate, whereas in space, with the exception of solar particle events, radiation exposures will be low-dose, low dose-rate; (3) Although it has been established that the virtual absence of gravity in space has a profound effect on human physiology, it is not clear whether these effects will act synergistically with those of radiation exposure. A select panel will evaluate the utilizing experiments and models to accurately predict the risks associated with exposure to HZE particles. Topics of research include cellular and tissue response, health effects associated with radiation damage, model animal systems, and critical markers of Radiation response.

  7. Fluctuating Nonlinear Spring Model of Mechanical Deformation of Biological Particles.

    Directory of Open Access Journals (Sweden)

    Olga Kononova

    2016-01-01

    Full Text Available The mechanical properties of virus capsids correlate with local conformational dynamics in the capsid structure. They also reflect the required stability needed to withstand high internal pressures generated upon genome loading and contribute to the success of important events in viral infectivity, such as capsid maturation, genome uncoating and receptor binding. The mechanical properties of biological nanoparticles are often determined from monitoring their dynamic deformations in Atomic Force Microscopy nanoindentation experiments; but a comprehensive theory describing the full range of observed deformation behaviors has not previously been described. We present a new theory for modeling dynamic deformations of biological nanoparticles, which considers the non-linear Hertzian deformation, resulting from an indenter-particle physical contact, and the bending of curved elements (beams modeling the particle structure. The beams' deformation beyond the critical point triggers a dynamic transition of the particle to the collapsed state. This extreme event is accompanied by a catastrophic force drop as observed in the experimental or simulated force (F-deformation (X spectra. The theory interprets fine features of the spectra, including the nonlinear components of the FX-curves, in terms of the Young's moduli for Hertzian and bending deformations, and the structural damage dependent beams' survival probability, in terms of the maximum strength and the cooperativity parameter. The theory is exemplified by successfully describing the deformation dynamics of natural nanoparticles through comparing theoretical curves with experimental force-deformation spectra for several virus particles. This approach provides a comprehensive description of the dynamic structural transitions in biological and artificial nanoparticles, which is essential for their optimal use in nanotechnology and nanomedicine applications.

  8. Bone regeneration strategy inspired by the study of calcification behavior in deer antler.

    Science.gov (United States)

    Shi, Haishan; Yu, Tao; Li, Zhaoyang; Lu, William; Zhang, Ming; Ye, Jiandong

    2015-12-01

    Bone regeneration has attracted much attention from various researchers and inspired numerous strategies for bone formation. In this study, rapid calcification of deer antlers was studied to unravel bone biology by investigating mineral composition, morphology and microstructure. Calcification model was hypothesized and preliminarily established by in vitro experiments. In our model, mineral deposition and phase conversions in the gel matrix were mimicked. Results revealed that mineral metabolism including deposition and phase conversion plays key roles in calcification in vivo, which inspired the bone regeneration strategy with three main components, i.e. enhanced mineral nucleation, mineral ions sources and crystals habits. Rapid mineral metabolism of implant apatite biomaterials was supposed as the critical aspect of bone regeneration. This study will provide a relatively ideal model for peer bone regeneration studies.

  9. Separable Watermarking Technique Using the Biological Color Model

    Directory of Open Access Journals (Sweden)

    David Nino

    2009-01-01

    Full Text Available Problem statement: The issue of having robust and fragile watermarking is still main focus for various researchers worldwide. Performance of a watermarking technique depends on how complex as well as how feasible to implement. These issues are tested using various kinds of attacks including geometry and transformation. Watermarking techniques in color images are more challenging than gray images in terms of complexity and information handling. In this study, we focused on implementation of watermarking technique in color images using the biological model. Approach: We proposed a novel method for watermarking using spatial and the Discrete Cosine Transform (DCT domains. The proposed method deled with colored images in the biological color model, the Hue, Saturation and Intensity (HSI. Technique was implemented and used against various colored images including the standard ones such as pepper image. The experiments were done using various attacks such as cropping, transformation and geometry. Results: The method robustness showed high accuracy in retrieval data and technique is fragile against geometric attacks. Conclusion: Watermark security was increased by using the Hadamard transform matrix. The watermarks used were meaningful and of varying sizes and details.

  10. Introduction to mathematical biology modeling, analysis, and simulations

    CERN Document Server

    Chou, Ching Shan

    2016-01-01

    This book is based on a one semester course that the authors have been teaching for several years, and includes two sets of case studies. The first includes chemostat models, predator-prey interaction, competition among species, the spread of infectious diseases, and oscillations arising from bifurcations. In developing these topics, readers will also be introduced to the basic theory of ordinary differential equations, and how to work with MATLAB without having any prior programming experience. The second set of case studies were adapted from recent and current research papers to the level of the students. Topics have been selected based on public health interest. This includes the risk of atherosclerosis associated with high cholesterol levels, cancer and immune interactions, cancer therapy, and tuberculosis. Readers will experience how mathematical models and their numerical simulations can provide explanations that guide biological and biomedical research. Considered to be the undergraduate companion to t...

  11. Modeling of biological doses and mechanical effects on bone transduction

    CERN Document Server

    Rieger, Romain; Jennane, Rachid; 10.1016/j.jtbi.2011.01.003

    2012-01-01

    Shear stress, hormones like parathyroid and mineral elements like calcium mediate the amplitude of stimulus signal which affects the rate of bone remodeling. The current study investigates the theoretical effects of different metabolic doses in stimulus signal level on bone. The model was built considering the osteocyte as the sensing center mediated by coupled mechanical shear stress and some biological factors. The proposed enhanced model was developed based on previously published works dealing with different aspects of bone transduction. It describes the effects of physiological doses variations of Calcium, Parathyroid Hormone, Nitric Oxide and Prostaglandin E2 on the stimulus level sensed by osteocytes in response to applied shear stress generated by interstitial fluid flow. We retained the metabolic factors (Parathyroid Hormone, Nitric Oxide, and Prostaglandin E2) as parameters of bone cell mechanosensitivity because stimulation/inhibition of induced pathways stimulates osteogenic response in vivo. We t...

  12. Fluctuating Nonlinear Spring Model of Mechanical Deformation of Biological Particles

    CERN Document Server

    Kononova, Olga; Marx, Kenneth A; Wuite, Gijs J L; Roos, Wouter H; Barsegov, Valeri

    2015-01-01

    We present a new theory for modeling forced indentation spectral lineshapes of biological particles, which considers non-linear Hertzian deformation due to an indenter-particle physical contact and bending deformations of curved beams modeling the particle structure. The bending of beams beyond the critical point triggers the particle dynamic transition to the collapsed state, an extreme event leading to the catastrophic force drop as observed in the force (F)-deformation (X) spectra. The theory interprets fine features of the spectra: the slope of the FX curves and the position of force-peak signal, in terms of mechanical characteristics --- the Young's moduli for Hertzian and bending deformations E_H and E_b, and the probability distribution of the maximum strength with the strength of the strongest beam F_b^* and the beams' failure rate m. The theory is applied to successfully characterize the $FX$ curves for spherical virus particles --- CCMV, TrV, and AdV.

  13. A bio-inspired image coder with temporal scalability

    CERN Document Server

    Masmoudi, Khaled; Kornprobst, Pierre

    2011-01-01

    We present a novel bio-inspired and dynamic coding scheme for static images. Our coder aims at reproducing the main steps of the visual stimulus processing in the mammalians retina taking into account its time behavior. The main novelty of this work is to show how to exploit the time behavior of the retina cells to ensure, in a simple way, scalability and bit allocation. To do so, our main source of inspiration will be the biologically plausible retina model called Virtual Retina. Following a similar structure, our model has two stages. The first stage is an image transform which is performed by the outer layers in the retina. Here it is modelled by filtering the image with a bank of difference of Gaussians with time-delays. The second stage is a time-dependent analog-to-digital conversion which is performed by the inner layers in the retina. Thanks to its conception, our coder enables scalability and bit allocation across time. Also, compared to the JPEG standards, our decoded images do not show annoying art...

  14. Quasi – biological model of radiogenic cancer morbidity

    Directory of Open Access Journals (Sweden)

    A. T. Gubin

    2015-01-01

    Full Text Available The methods: Linear differential equations were used to formalize contemporary assumptions of self –sustaining tissue cell kinetics under the impact of adverse factors, on the formation and repairing of cell “pre-cancer” defects, on inheritance and retaining such defects in daughter cells which results in malignant neoplasms, on age-dependent impairment of human body’s function to eliminate such cells.The results: The model reproduces the well-known regularities of radiogenic cancer morbidity increase depending on instantaneous radiation exposure age and on attained age: the relative reduction at increased radiation age which the model attributes to age decrease of stem cells, relative reduction at increased time after radiation induced by “sorting out” of cells with “pre-cancer” defects, absolute increase with age proportional to natural cause mortality rate.The relevance of the developed quasi-biological model is displayed via comparison to the ICRP model for radiogenic increase of solid carcinomas’ morbidity after single radiation exposure. The latter model had been developed after Japanese cohort observations. For both genders high goodness-of-fit was achieved between the models at values of Gompertz’ law factor which had been defined for men and women in this cohort via selecting the value of the only free parameter indicating age-dependent exponential retardation of stem cells’ division.The conclusion: The proposed model suggests that the estimation of radiogenic risk inter-population transfer can be done on the basis of the data on age-dependent mortality intensity increase from all natural causes. The model also creates the premises for inter-species transfer of risk following the well-known parameters of cell populations’ kinetics in animal’s organs and tissues and Gompertz’s law parameters. This model is applicable also for analyses of age-dependent changes of background cancer morbidity. 

  15. Biophysically inspired model for functionalized nanocarrier adhesion to cell surface: roles of protein expression and mechanical factors

    Science.gov (United States)

    Ramakrishnan, N.; Tourdot, Richard W.; Eckmann, David M.; Ayyaswamy, Portonovo S.; Muzykantov, Vladimir R.; Radhakrishnan, Ravi

    2016-06-01

    In order to achieve selective targeting of affinity-ligand coated nanoparticles to the target tissue, it is essential to understand the key mechanisms that govern their capture by the target cell. Next-generation pharmacokinetic (PK) models that systematically account for proteomic and mechanical factors can accelerate the design, validation and translation of targeted nanocarriers (NCs) in the clinic. Towards this objective, we have developed a computational model to delineate the roles played by target protein expression and mechanical factors of the target cell membrane in determining the avidity of functionalized NCs to live cells. Model results show quantitative agreement with in vivo experiments when specific and non-specific contributions to NC binding are taken into account. The specific contributions are accounted for through extensive simulations of multivalent receptor-ligand interactions, membrane mechanics and entropic factors such as membrane undulations and receptor translation. The computed NC avidity is strongly dependent on ligand density, receptor expression, bending mechanics of the target cell membrane, as well as entropic factors associated with the membrane and the receptor motion. Our computational model can predict the in vivo targeting levels of the intracellular adhesion molecule-1 (ICAM1)-coated NCs targeted to the lung, heart, kidney, liver and spleen of mouse, when the contributions due to endothelial capture are accounted for. The effect of other cells (such as monocytes, etc.) do not improve the model predictions at steady state. We demonstrate the predictive utility of our model by predicting partitioning coefficients of functionalized NCs in mice and human tissues and report the statistical accuracy of our model predictions under different scenarios.

  16. Modelling biological behaviours with the unified modelling language: an immunological case study and critique.

    Science.gov (United States)

    Read, Mark; Andrews, Paul S; Timmis, Jon; Kumar, Vipin

    2014-10-01

    We present a framework to assist the diagrammatic modelling of complex biological systems using the unified modelling language (UML). The framework comprises three levels of modelling, ranging in scope from the dynamics of individual model entities to system-level emergent properties. By way of an immunological case study of the mouse disease experimental autoimmune encephalomyelitis, we show how the framework can be used to produce models that capture and communicate the biological system, detailing how biological entities, interactions and behaviours lead to higher-level emergent properties observed in the real world. We demonstrate how the UML can be successfully applied within our framework, and provide a critique of UML's ability to capture concepts fundamental to immunology and biology more generally. We show how specialized, well-explained diagrams with less formal semantics can be used where no suitable UML formalism exists. We highlight UML's lack of expressive ability concerning cyclic feedbacks in cellular networks, and the compounding concurrency arising from huge numbers of stochastic, interacting agents. To compensate for this, we propose several additional relationships for expressing these concepts in UML's activity diagram. We also demonstrate the ambiguous nature of class diagrams when applied to complex biology, and question their utility in modelling such dynamic systems. Models created through our framework are non-executable, and expressly free of simulation implementation concerns. They are a valuable complement and precursor to simulation specifications and implementations, focusing purely on thoroughly exploring the biology, recording hypotheses and assumptions, and serve as a communication medium detailing exactly how a simulation relates to the real biology.

  17. Inspiring a generation

    CERN Multimedia

    2012-01-01

    The motto of the 2012 Olympic and Paralympic Games is ‘Inspire a generation’ so it was particularly pleasing to see science, the LHC and Higgs bosons featuring so strongly in the opening ceremony of the Paralympics last week.   It’s a sign of just how far our field has come that such a high-profile event featured particle physics so strongly, and we can certainly add our support to that motto. If the legacy of London 2012 is a generation inspired by science as well as sport, then the games will have more than fulfilled their mission. Particle physics has truly inspiring stories to tell, going well beyond Higgs and the LHC, and the entire community has played its part in bringing the excitement of frontier research in particle physics to a wide audience. Nevertheless, we cannot rest on our laurels: maintaining the kind of enthusiasm for science we witnessed at the Paralympic opening ceremony will require constant vigilance, and creative thinking about ways to rea...

  18. A micromechanics-inspired constitutive model for shape-memory alloys that accounts for initiation and saturation of phase transformation

    Science.gov (United States)

    Kelly, Alex; Stebner, Aaron P.; Bhattacharya, Kaushik

    2016-12-01

    A constitutive model to describe macroscopic elastic and transformation behaviors of polycrystalline shape-memory alloys is formulated using an internal variable thermodynamic framework. In a departure from prior phenomenological models, the proposed model treats initiation, growth kinetics, and saturation of transformation distinctly, consistent with physics revealed by recent multi-scale experiments and theoretical studies. Specifically, the proposed approach captures the macroscopic manifestations of three micromechanial facts, even though microstructures are not explicitly modeled: (1) Individual grains with favorable orientations and stresses for transformation are the first to nucleate martensite, and the local nucleation strain is relatively large. (2) Then, transformation interfaces propagate according to growth kinetics to traverse networks of grains, while previously formed martensite may reorient. (3) Ultimately, transformation saturates prior to 100% completion as some unfavorably-oriented grains do not transform; thus the total transformation strain of a polycrystal is modest relative to the initial, local nucleation strain. The proposed formulation also accounts for tension-compression asymmetry, processing anisotropy, and the distinction between stress-induced and temperature-induced transformations. Consequently, the model describes thermoelastic responses of shape-memory alloys subject to complex, multi-axial thermo-mechanical loadings. These abilities are demonstrated through detailed comparisons of simulations with experiments.

  19. Models for integrated pest control and their biological implications.

    Science.gov (United States)

    Tang, Sanyi; Cheke, Robert A

    2008-09-01

    Successful integrated pest management (IPM) control programmes depend on many factors which include host-parasitoid ratios, starting densities, timings of parasitoid releases, dosages and timings of insecticide applications and levels of host-feeding and parasitism. Mathematical models can help us to clarify and predict the effects of such factors on the stability of host-parasitoid systems, which we illustrate here by extending the classical continuous and discrete host-parasitoid models to include an IPM control programme. The results indicate that one of three control methods can maintain the host level below the economic threshold (ET) in relation to different ET levels, initial densities of host and parasitoid populations and host-parasitoid ratios. The effects of host intrinsic growth rate and parasitoid searching efficiency on host mean outbreak period can be calculated numerically from the models presented. The instantaneous pest killing rate of an insecticide application is also estimated from the models. The results imply that the modelling methods described can help in the design of appropriate control strategies and assist management decision-making. The results also indicate that a high initial density of parasitoids (such as in inundative releases) and high parasitoid inter-generational survival rates will lead to more frequent host outbreaks and, therefore, greater economic damage. The biological implications of this counter intuitive result are discussed.

  20. A Color-Opponency Based Biological Model for Color Constancy

    Directory of Open Access Journals (Sweden)

    Yongjie Li

    2011-05-01

    Full Text Available Color constancy is the ability of the human visual system to adaptively correct color-biased scenes under different illuminants. Most of the existing color constancy models are nonphysiologically plausible. Among the limited biological models, the great majority is Retinex and its variations, and only two or three models directly simulate the feature of color-opponency, but only of the very earliest stages of visual pathway, i.e., the single-opponent mechanisms involved at the levels of retinal ganglion cells and lateral geniculate nucleus (LGN neurons. Considering the extensive physiological evidences supporting that both the single-opponent cells in retina and LGN and the double-opponent neurons in primary visual cortex (V1 are the building blocks for color constancy, in this study we construct a color-opponency based color constancy model by simulating the opponent fashions of both the single-opponent and double-opponent cells in a forward manner. As for the spatial structure of the receptive fields (RF, both the classical RF (CRF center and the nonclassical RF (nCRF surround are taken into account for all the cells. The proposed model was tested on several typical image databases commonly used for performance evaluation of color constancy methods, and exciting results were achieved.

  1. Analysis of a growth model inspired by Gompertz and Korf laws, and an analogous birth-death process.

    Science.gov (United States)

    Di Crescenzo, Antonio; Spina, Serena

    2016-12-01

    We propose a new deterministic growth model which captures certain features of both the Gompertz and Korf laws. We investigate its main properties, with special attention to the correction factor, the relative growth rate, the inflection point, the maximum specific growth rate, the lag time and the threshold crossing problem. Some data analytic examples and their performance are also considered. Furthermore, we study a stochastic counterpart of the proposed model, that is a linear time-inhomogeneous birth-death process whose mean behaves as the deterministic one. We obtain the transition probabilities, the moments and the population ultimate extinction probability for this process. We finally treat the special case of a simple birth process, which better mimics the proposed growth model.

  2. Building Blocks Propagation in Quantum-Inspired Genetic Algorithm

    OpenAIRE

    Nowotniak, Robert; Kucharski, Jacek

    2010-01-01

    This paper presents an analysis of building blocks propagation in Quantum-Inspired Genetic Algorithm, which belongs to a new class of metaheuristics drawing their inspiration from both biological evolution and unitary evolution of quantum systems. The expected number of quantum chromosomes matching a schema has been analyzed and a random variable corresponding to this issue has been introduced. The results have been compared with Simple Genetic Algorithm. Also, it has been presented how selec...

  3. Structurally tuned iridescent surfaces inspired by nature

    Energy Technology Data Exchange (ETDEWEB)

    Deparis, Olivier; Rassart, Marie; Vandenbem, Cedric; Welch, Victoria; Vigneron, Jean Pol [Laboratoire de Physique du Solide, University of Namur, 61 rue de Bruxelles, 5000 Namur (Belgium); Lucas, Stephane [Laboratoire d' Analyses par Reactions Nucleaires, University of Namur, 61 rue de Bruxelles, 5000 Namur (Belgium)], E-mail: olivier.deparis@fundp.ac.be

    2008-01-15

    Iridescent surfaces exhibit vivid colours which change with the angle of incidence or viewing due to optical wave interference in the multilayer structure present at the wavelength scale underneath the surface. In nature, one can find examples of iridescent Coleoptera for which the hue changes either greatly or slightly with the angle. Because these species typically make these structures from a single biological material (usually chitin) and air or water as the low refractive index component, they have evolved by adjusting the layer thicknesses in order to display quite different iridescent aspects. Taking inspiration from this proven strategy, we have designed and fabricated periodic TiO{sub 2}/SiO{sub 2} multilayer films in order to demonstrate the concept of structurally tuned iridescent surfaces. Titanium or silicon oxide layers were deposited on a glass substrate using dc reactive or RF magnetron sputtering techniques, respectively. Two structures were designed for which the period and the TiO{sub 2}/SiO{sub 2} layer thickness ratio were varied in such a way that the films displayed radically different iridescent aspects: a reddish-to-greenish changing hue and a stable bluish hue. The fabricated samples were characterized through specular reflectance/transmittance measurements. Modelling of transmittance spectra using standard multilayer film theory confirmed the high quality of the twelve-period Bragg reflectors. The chromaticity coordinates, which were calculated from measured reflectance spectra taken at different angles, were in accordance with theoretical predictions.

  4. First steps in computational systems biology: A practical session in metabolic modeling and simulation.

    Science.gov (United States)

    Reyes-Palomares, Armando; Sánchez-Jiménez, Francisca; Medina, Miguel Ángel

    2009-05-01

    A comprehensive understanding of biological functions requires new systemic perspectives, such as those provided by systems biology. Systems biology approaches are hypothesis-driven and involve iterative rounds of model building, prediction, experimentation, model refinement, and development. Developments in computer science are allowing for ever faster numerical simulations of mathematical models. Mathematical modeling plays an essential role in new systems biology approaches. As a complex, integrated system, metabolism is a suitable topic of study for systems biology approaches. However, up until recently, this topic has not been properly covered in biochemistry courses. This communication reports the development and implementation of a practical lesson plan on metabolic modeling and simulation.

  5. Numerical simulation of humidification and heating during inspiration in nose models with three different located septal perforations.

    Science.gov (United States)

    Lindemann, Jörg; Reichert, Michael; Kröger, Ralf; Schuler, Patrick; Hoffmann, Thomas; Sommer, Fabian

    2016-07-01

    Nasal septum perforations (SP) are characterized by nasal obstruction, bleeding and crusting. The disturbed heating and humidification of the inhaled air are important factors, which cause these symptoms due to a disturbed airflow. Numerical simulations offer a great potential to avoid these limitations and to provide valid data. The aim of the study was to simulate the humidification and heating of the inhaled air in digital nose models with three different SPs and without SP. Four realistic bilateral nose models based on a multi-slice CT scan were created. The SP were located anterior caudal, anterior cranial and posterior caudal. One model was without SP. A numerical simulation was performed. Boundary conditions were based on previous in vivo measurements. Heating and humidification of the inhaled air were displayed, analyzed in each model and compared to each other. Anterior caudal SPs cause a disturbed decrease of temperature and humidity of the inhaled air. The reduced temperature and humidity values can still be shown in the posterior nose. The anterior cranial and the posterior caudal perforation have only a minor influence on heating and humidification. A reduced humidification and heating of the air can be shown by numerical simulations due to SP depending on their localization. The anterior caudal SP representing a typical localization after previous surgery has the biggest influence on heating and humidification. The results explain the typical symptoms such as crusting by drying-out the nasal mucosa. The size and the localization of the SP are essential for the symptoms.

  6. Distinct failure modes in bio-inspired 3D-printed staggered composites under non-aligned loadings

    Science.gov (United States)

    Slesarenko, Viacheslav; Kazarinov, Nikita; Rudykh, Stephan

    2017-03-01

    The superior mechanical properties of biological materials originate in their complex hierarchical microstructures, combining stiff and soft constituents at different length scales. In this work, we employ a three-dimensional multi-materials printing to fabricate the bio-inspired staggered composites, and study their mechanical properties and failure mechanisms. We observe that bio-inspired staggered composites with inclined stiff tablets are able to undergo two different failure modes, depending on the inclination angle. We find that such artificial structure demonstrates high toughness only under loading applied at relatively small angle to the tablets stacking direction, while for higher angles the composites fail catastrophically. This aspect of the failure behavior was captured experimentally as well as by means of the finite element analysis. We show that even a relatively simple failure model with a strain energy limiter, can be utilized to qualitatively distinguish these two different modes of failure, occurring in the artificial bio-inspired composites.

  7. Bio-inspired approaches to sensing for defence and security applications.

    Science.gov (United States)

    Biggins, Peter D E; Kusterbeck, Anne; Hiltz, John A

    2008-05-01

    Interdisciplinary research in biotechnology and related scientific areas has increased tremendously over the past decade. This rapid pace, in conjunction with advances in microfabricated systems, computer hardware, bioengineering and the availability of low-powered miniature components, has now made it feasible to design bio-inspired materials, sensors and systems with tremendous potential for defence and security applications. To realize the full potential of biotechnology and bio-inspiration, there is a need to define specific requirements to meet the challenges of the changing world and its threats. One approach to assisting the defence and security communities in defining their requirements is through the use of a conceptual model. The distributed or intelligent autonomous sensing (DIAS) system is one such model. The DIAS model is not necessarily aimed at a single component, for instance a sensor, but can include a system, or even a system of systems in the same way that a single organism, a multi-cellular organism or group of organisms is configured. This paper provides an overview of the challenges to and opportunities for bio-inspired sensors and systems together with examples of how they are being implemented. Examples focus on both learning new things from biological organisms that have application to the defence and security forces and adapting known discoveries in biology and biochemistry for practical use by these communities.

  8. Regulatory Impact Analysis Practice in New Zealand in the Light of Models of Evaluation Use – Inspiration for the Polish Government

    Directory of Open Access Journals (Sweden)

    Tomasz Kupiec

    2015-06-01

    Full Text Available Purpose: The paper describes the functioning of the RIA system in New Zealand using the analogy of RIA and the evaluation of public interventions. Presented solutions can provide nspiration for the Polish government in the process of improving the quality and extent of the use of RIA. Methodology: The analysis is based on a review of government documents and literature, as well as individual interviews and correspondence with representatives of the government of NZ. Conclusions: The RIA system in NZ is not error-free and its shortcomings include inter alia the lack of solutions with respect to ex-post analysis and insufficiently rigorous methodological approach. At the same time, a number of solutions can be regarded as good practice, e.g.: regular external quality reviews of RIS, obligation to supplement each RIS with ‘quality assessment’ and a ‘disclosure statement’ outlining their credibility and utility. Practical implications: The presented strengths of the RIA system in NZ may serve as an inspiration for modifying the RIA system in Poland. Originality: The RIA system is presented through the prism of the model of evaluation use, which is a related tool of collecting information about non-regulatory interventions.

  9. A new numerical approach to solve Thomas-Fermi model of an atom using bio-inspired heuristics integrated with sequential quadratic programming.

    Science.gov (United States)

    Raja, Muhammad Asif Zahoor; Zameer, Aneela; Khan, Aziz Ullah; Wazwaz, Abdul Majid

    2016-01-01

    In this study, a novel bio-inspired computing approach is developed to analyze the dynamics of nonlinear singular Thomas-Fermi equation (TFE) arising in potential and charge density models of an atom by exploiting the strength of finite difference scheme (FDS) for discretization and optimization through genetic algorithms (GAs) hybrid with sequential quadratic programming. The FDS procedures are used to transform the TFE differential equations into a system of nonlinear equations. A fitness function is constructed based on the residual error of constituent equations in the mean square sense and is formulated as the minimization problem. Optimization of parameters for the system is carried out with GAs, used as a tool for viable global search integrated with SQP algorithm for rapid refinement of the results. The design scheme is applied to solve TFE for five different scenarios by taking various step sizes and different input intervals. Comparison of the proposed results with the state of the art numerical and analytical solutions reveals that the worth of our scheme in terms of accuracy and convergence. The reliability and effectiveness of the proposed scheme are validated through consistently getting optimal values of statistical performance indices calculated for a sufficiently large number of independent runs to establish its significance.

  10. Switchable bio-inspired adhesives

    Science.gov (United States)

    Kroner, Elmar

    2015-03-01

    Geckos have astonishing climbing abilities. They can adhere to almost any surface and can run on walls and even stick to ceilings. The extraordinary adhesion performance is caused by a combination of a complex surface pattern on their toes and the biomechanics of its movement. These biological dry adhesives have been intensely investigated during recent years because of the unique combination of adhesive properties. They provide high adhesion, allow for easy detachment, can be removed residue-free, and have self-cleaning properties. Many aspects have been successfully mimicked, leading to artificial, bio-inspired, patterned dry adhesives, and were addressed and in some aspects they even outperform the adhesion capabilities of geckos. However, designing artificial patterned adhesion systems with switchable adhesion remains a big challenge; the gecko's adhesion system is based on a complex hierarchical surface structure and on advanced biomechanics, which are both difficult to mimic. In this paper, two approaches are presented to achieve switchable adhesion. The first approach is based on a patterned polydimethylsiloxane (PDMS) polymer, where adhesion can be switched on and off by applying a low and a high compressive preload. The switch in adhesion is caused by a reversible mechanical instability of the adhesive silicone structures. The second approach is based on a composite material consisting of a Nickel- Titanium (NiTi) shape memory alloy and a patterned adhesive PDMS layer. The NiTi alloy is trained to change its surface topography as a function of temperature, which results in a change of the contact area and of alignment of the adhesive pattern towards a substrate, leading to switchable adhesion. These examples show that the unique properties of bio-inspired adhesives can be greatly improved by new concepts such as mechanical instability or by the use of active materials which react to external stimuli.

  11. A cortically-inspired model for inverse kinematics computation of a humanoid finger with mechanically coupled joints.

    Science.gov (United States)

    Gentili, Rodolphe J; Oh, Hyuk; Kregling, Alissa V; Reggia, James A

    2016-05-19

    The human hand's versatility allows for robust and flexible grasping. To obtain such efficiency, many robotic hands include human biomechanical features such as fingers having their two last joints mechanically coupled. Although such coupling enables human-like grasping, controlling the inverse kinematics of such mechanical systems is challenging. Here we propose a cortical model for fine motor control of a humanoid finger, having its two last joints coupled, that learns the inverse kinematics of the effector. This neural model functionally mimics the population vector coding as well as sensorimotor prediction processes of the brain's motor/premotor and parietal regions, respectively. After learning, this neural architecture could both overtly (actual execution) and covertly (mental execution or motor imagery) perform accurate, robust and flexible finger movements while reproducing the main human finger kinematic states. This work contributes to developing neuro-mimetic controllers for dexterous humanoid robotic/prosthetic upper-extremities, and has the potential to promote human-robot interactions.

  12. A physically inspired model of Dip d792 and d1519 of the Kepler light curve seen at KIC8462852

    CERN Document Server

    Heindl, Eduard

    2016-01-01

    The star KIC 8462852 shows a very unusual and hard to comprehend light curve. The dip d7922 absorbs 16% of the starlight. The light curve is unusually smooth but the very steep edges make it hard to find a simple natural explanation by covering due to comets or other well-known planetary objects. We describe a mathematical approximation to the light curve, which is motivated by a physically meaningful event of a large stellar beam which generates an orbiting cloud. The data might fit to the science fiction idea of star lifting, a mining technology that could extract star matter. We extend the model to d1519 and d1568 using multiple beams and get an encouraging result that fits essential parts of the dips but misses other parts of the measured flux. We recommend further exploration of this concept with refined models.

  13. Magnetic breakdown phenomenon in quasi-two-dimensional organic conductors: A quantum model inspired by a realistic band structure

    Science.gov (United States)

    Kim, Ju H.; Han, S. Y.; Brooks, J. S.

    1999-08-01

    We investigate the phenomenon of magnetic breakdown in quasi-two-dimensional organic conductors such as α-(ET)2KHg(SCN)4 and κ-(ET)2Cu(NCS)2 by constructing a tight-binding model based on a realistic band structure which is derived from the crystallographic data. We solve the model numerically to compute the magnetic field dependence of the magnetization and show that the present model accounts naturally for the experimentally observed magnetization oscillation frequencies that are forbidden in the semiclassical picture. The computed values of the fundamental and magnetic breakdown frequencies with no adjustable parameters are close to the experimentally measured values. For completeness, we carry out the computation for both canonical (fixed number of particles) and grand canonical (fixed chemical potential) ensembles, and show that the forbidden frequencies appear in both cases. Hence, the appearance of anomalous frequencies in the de Haas-van Alphen effect has a quantum-mechanical origin and arises from the interplay of electronic states from two partially occupied bands near the Fermi energy as a function of magnetic field. We also compute the temperature dependence of the magnetization and apply ad hoc the Lifshitz-Kosevich analysis to the amplitudes of the Fourier components at moderately high temperatures. This yields effective mass values for α-(ET)2KHg(SCN)4 in good agreement with experimental values.

  14. Micrasterias as a Model System in Plant Cell Biology

    Science.gov (United States)

    Lütz-Meindl, Ursula

    2016-01-01

    The unicellular freshwater alga Micrasterias denticulata is an exceptional organism due to its complex star-shaped, highly symmetric morphology and has thus attracted the interest of researchers for many decades. As a member of the Streptophyta, Micrasterias is not only genetically closely related to higher land plants but shares common features with them in many physiological and cell biological aspects. These facts, together with its considerable cell size of about 200 μm, its modest cultivation conditions and the uncomplicated accessibility particularly to any microscopic techniques, make Micrasterias a very well suited cell biological plant model system. The review focuses particularly on cell wall formation and composition, dictyosomal structure and function, cytoskeleton control of growth and morphogenesis as well as on ionic regulation and signal transduction. It has been also shown in the recent years that Micrasterias is a highly sensitive indicator for environmental stress impact such as heavy metals, high salinity, oxidative stress or starvation. Stress induced organelle degradation, autophagy, adaption and detoxification mechanisms have moved in the center of interest and have been investigated with modern microscopic techniques such as 3-D- and analytical electron microscopy as well as with biochemical, physiological and molecular approaches. This review is intended to summarize and discuss the most important results obtained in Micrasterias in the last 20 years and to compare the results to similar processes in higher plant cells. PMID:27462330

  15. Models to Study NK Cell Biology and Possible Clinical Application.

    Science.gov (United States)

    Zamora, Anthony E; Grossenbacher, Steven K; Aguilar, Ethan G; Murphy, William J

    2015-08-03

    Natural killer (NK) cells are large granular lymphocytes of the innate immune system, responsible for direct targeting and killing of both virally infected and transformed cells. NK cells rapidly recognize and respond to abnormal cells in the absence of prior sensitization due to their wide array of germline-encoded inhibitory and activating receptors, which differs from the receptor diversity found in B and T lymphocytes that is due to the use of recombination-activation gene (RAG) enzymes. Although NK cells have traditionally been described as natural killers that provide a first line of defense prior to the induction of adaptive immunity, a more complex view of NK cells is beginning to emerge, indicating they may also function in various immunoregulatory roles and have the capacity to shape adaptive immune responses. With the growing appreciation for the diverse functions of NK cells, and recent technological advancements that allow for a more in-depth understanding of NK cell biology, we can now begin to explore new ways to manipulate NK cells to increase their clinical utility. In this overview unit, we introduce the reader to various aspects of NK cell biology by reviewing topics ranging from NK cell diversity and function, mouse models, and the roles of NK cells in health and disease, to potential clinical applications. © 2015 by John Wiley & Sons, Inc.

  16. Micrasterias as a model system in plant cell biology

    Directory of Open Access Journals (Sweden)

    Ursula Luetz-Meindl

    2016-07-01

    Full Text Available The unicellular freshwater alga Micrasterias denticulata is an exceptional organism due to its extraordinary star-shaped, highly symmetric morphology and has thus attracted the interest of researchers for many decades. As a member of the Streptophyta, Micrasterias is not only genetically closely related to higher land plants but shares common features with them in many physiological and cell biological aspects. These facts, together with its considerable cell size of about 200 µm, its modest cultivation conditions and the uncomplicated accessibility particularly to any microscopic techniques, make Micrasterias a very well suited cell biological plant model system. The review focuses particularly on cell wall formation and composition, dictyosomal structure and function, cytoskeleton control of growth and morphogenesis as well as on ionic regulation and signal transduction. It has been also shown in the recent years that Micrasterias is a highly sensitive indicator for environmental stress impact such as heavy metals, high salinity, oxidative stress or starvation. Stress induced organelle degradation, autophagy, adaption and detoxification mechanisms have moved in the center of interest and have been investigated with modern microscopic techniques such as 3-D- and analytical electron microscopy as well as with biochemical, physiological and molecular approaches. This review is intended to summarize and discuss the most important results obtained in Micrasterias in the last 20 years and to compare the results to similar processes in higher plant cells.

  17. Biological materials: a materials science approach.

    Science.gov (United States)

    Meyers, Marc A; Chen, Po-Yu; Lopez, Maria I; Seki, Yasuaki; Lin, Albert Y M

    2011-07-01

    The approach used by Materials Science and Engineering is revealing new aspects in the structure and properties of biological materials. The integration of advanced characterization, mechanical testing, and modeling methods can rationalize heretofore unexplained aspects of these structures. As an illustration of the power of this methodology, we apply it to biomineralized shells, avian beaks and feathers, and fish scales. We also present a few selected bioinspired applications: Velcro, an Al2O3-PMMA composite inspired by the abalone shell, and synthetic attachment devices inspired by gecko.

  18. First Steps in Computational Systems Biology: A Practical Session in Metabolic Modeling and Simulation

    Science.gov (United States)

    Reyes-Palomares, Armando; Sanchez-Jimenez, Francisca; Medina, Miguel Angel

    2009-01-01

    A comprehensive understanding of biological functions requires new systemic perspectives, such as those provided by systems biology. Systems biology approaches are hypothesis-driven and involve iterative rounds of model building, prediction, experimentation, model refinement, and development. Developments in computer science are allowing for ever…

  19. A biologically plausible embodied model of action discovery

    Directory of Open Access Journals (Sweden)

    Rufino eBolado-Gomez

    2013-03-01

    Full Text Available During development, animals can spontaneously discover action-outcomepairings enabling subsequent achievement of their goals. We present abiologically plausible embodied model addressing key aspects of thisprocess. The biomimetic model core comprises the basal ganglia and itsloops through cortex and thalamus. We incorporate reinforcementlearning with phasic dopamine supplying a sensory prediction error,signalling 'surprising' outcomes. Phasic dopamine is used in acorticostriatal learning rule which is consistent with recent data. Wealso hypothesised that objects associated with surprising outcomesacquire 'novelty salience' contingent on the predicability of theoutcome. To test this idea we used a simple model of predictiongoverning the dynamics of novelty salience and phasic dopamine. Thetask of the virtual robotic agent mimicked an in vivo counterpart(Gancarz et al., 2011 and involved interaction with a target objectwhich caused a light flash, or a control object which did not.Learning took place according to two schedules. In one, the phasicoutcome was delivered after interaction with the target in anunpredictable way which emulated the in vivo protocol. Without noveltysalience, the model was unable to account for the experimental data.In the other schedule, the phasic outcome was reliably delivered andthe agent showed a rapid increase in the number of interactions withthe target which then decreased over subsequent sessions. We arguethis is precisely the kind of change in behaviour required torepeatedly present representations of context, action and outcome, toneural networks responsible for learning action-outcome contingency.The model also showed corticostriatal plasticity consistent withlearning a new action in basal ganglia. We conclude that actionlearning is underpinned by a complex interplay of plasticity andstimulus salience, and that our model contains many of the elementsfor biological action discovery to take place.

  20. Using a Truss-Inspired Model with the Uniform Strength Optimization Theory to Predict Spongy Bone Geometry in Proximal Femur

    Directory of Open Access Journals (Sweden)

    Hamed Pishdast

    2009-01-01

    Full Text Available This paper presents a new naïve approach for simulating bone remodeling process. It is based on the uniform strength theory of optimization and employs a truss-like model for bone. The truss was subjected to external loads including 5 point loads simulating the hip joint contact forces and 3 muscular forces at the attachment sites of the muscles to the bone and the rest are reactions of ligaments. The strain in the links was calculated and the links with high strains were identified. The initial truss is modified by introducing new links wherever the strain exceeds a prescribed or critical value. The critical value was assumed to be equal to an average of the absolute value of strains in the initial model. Each link which undergoes a high strain is replaced by several new links by adding new nodes around it using Delaunay method. Introducing the new links to the truss, which is conducted according to a weighted arithmetic mean formula, will strengthen the structure and reduce the strain within the respective zone. This procedure was repeated for several times. Convergence was achieved when there were no critical links remaining. This method was used to study the 2D shape of proximal femur in the frontal plane and provided results which are in a fairly good agreement with CT image of the human proximal femur.