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

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…

Spatial Modeling Tools for Cell Biology

National Research Council Canada - National Science Library

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

2006-01-01

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

Kirigami artificial muscles with complex biologically inspired morphologies

International Nuclear Information System (INIS)

Sareh, Sina; Rossiter, Jonathan

2013-01-01

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

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

Biological Inspiration for Agile Autonomous Air Vehicles

Science.gov (United States)

2007-11-01

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

Biologically-Inspired Control Architecture for Musical Performance Robots

Directory of Open Access Journals (Sweden)

Jorge Solis

2014-10-01

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

Biologically inspired water purification through selective transport

International Nuclear Information System (INIS)

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

2013-01-01

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

Biologically inspired collision avoidance system for unmanned vehicles

Science.gov (United States)

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

2009-05-01

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

Biomimetics as a Model for Inspiring Human Innovation

Science.gov (United States)

Bar-Cohen, Yoseph

2006-01-01

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

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.

Artificial heartbeat: design and fabrication of a biologically inspired pump

International Nuclear Information System (INIS)

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

2013-01-01

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

Biological inspiration used for robots motion synthesis.

Science.gov (United States)

Zielińska, Teresa

2009-01-01

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

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...

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

Science.gov (United States)

Wu, Shinq-Jen; Wu, Cheng-Tao

2014-09-18

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

Numerical simulations of odorant detection by biologically inspired sensor arrays

International Nuclear Information System (INIS)

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

2012-01-01

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

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.

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

Science.gov (United States)

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

2013-01-01

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

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

International Nuclear Information System (INIS)

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

2012-01-01

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

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

Directory of Open Access Journals (Sweden)

Edwin Eduardo Millán Rojas

2018-02-01

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

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

Directory of Open Access Journals (Sweden)

Humayun Irshad

2013-01-01

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

Bio-inspired networking

CERN Document Server

Câmara, Daniel

2015-01-01

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

A Comparative Study of Biologically Inspired Walking Gaits through Waypoint Navigation

Directory of Open Access Journals (Sweden)

Umar Asif

2011-01-01

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

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

Science.gov (United States)

Kaluza, Pablo; Urdapilleta, Eugenio

2014-10-01

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

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...

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...

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

DEFF Research Database (Denmark)

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

2017-01-01

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

Biologically-inspired soft exosuit.

Science.gov (United States)

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

2013-06-01

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

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.

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...

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.

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

Science.gov (United States)

Kriegeskorte, Nikolaus

2015-11-24

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

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

Directory of Open Access Journals (Sweden)

Takuma Nemoto

2015-04-01

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

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

Science.gov (United States)

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

2017-09-01

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

Biology-Inspired Autonomous Control

Science.gov (United States)

2011-08-31

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

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.

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.

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...

A bio-inspired spatial patterning circuit.

Science.gov (United States)

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

2014-01-01

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

Guard Cell and Tropomyosin Inspired Chemical Sensor

Directory of Open Access Journals (Sweden)

Jacquelyn K.S. Nagel

2013-10-01

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

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

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

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.

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”.

Synthetic biology, inspired by synthetic chemistry.

Science.gov (United States)

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

2012-07-16

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

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

International Nuclear Information System (INIS)

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

2013-01-01

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

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

Science.gov (United States)

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

2013-12-01

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

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

DEFF Research Database (Denmark)

Afferante, Luciano; Heepe, Lars; Casdorff, Kirstin

2016-01-01

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

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.

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.

An Approach for Calculating Land Valuation by Using Inspire Data Models

Science.gov (United States)

Aydinoglu, A. C.; Bovkir, R.

2017-11-01

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

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.

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.

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.

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.

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

Science.gov (United States)

Maro Kiris, Irem

2018-05-04

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

Progress and Opportunities in Soft Photonics and Biologically Inspired Optics.

Science.gov (United States)

Kolle, Mathias; Lee, Seungwoo

2018-01-01

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

Wireless synapses in bio-inspired neural networks

Science.gov (United States)

Jannson, Tomasz; Forrester, Thomas; Degrood, Kevin

2009-05-01

Wireless (virtual) synapses represent a novel approach to bio-inspired neural networks that follow the infrastructure of the biological brain, except that biological (physical) synapses are replaced by virtual ones based on cellular telephony modeling. Such synapses are of two types: intracluster synapses are based on IR wireless ones, while intercluster synapses are based on RF wireless ones. Such synapses have three unique features, atypical of conventional artificial ones: very high parallelism (close to that of the human brain), very high reconfigurability (easy to kill and to create), and very high plasticity (easy to modify or upgrade). In this paper we analyze the general concept of wireless synapses with special emphasis on RF wireless synapses. Also, biological mammalian (vertebrate) neural models are discussed for comparison, and a novel neural lensing effect is discussed in detail.

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

Science.gov (United States)

Sterritt, Roy; Hinchey, Mike

2006-01-01

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

Biologically inspired EM image alignment and neural reconstruction.

Science.gov (United States)

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

2011-08-15

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

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

Science.gov (United States)

Rañó, Iñaki; Santos, José A

2017-06-05

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

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.

Retina-Inspired Filter.

Science.gov (United States)

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

2018-07-01

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

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

DEFF Research Database (Denmark)

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

2017-01-01

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

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.

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.

Nature as an engineer: one simple concept of a bio-inspired functional artificial muscle.

Science.gov (United States)

Schmitt, S; Haeufle, D F B; Blickhan, R; Günther, M

2012-09-01

The biological muscle is a powerful, flexible and versatile actuator. Its intrinsic characteristics determine the way how movements are generated and controlled. Robotic and prosthetic applications expect to profit from relying on bio-inspired actuators which exhibit natural (muscle-like) characteristics. As of today, when constructing a technical actuator, it is not possible to copy the exact molecular structure of a biological muscle. Alternatively, the question may be put how its characteristics can be realized with known mechanical components. Recently, a mechanical construct for an artificial muscle was proposed, which exhibits hyperbolic force-velocity characteristics. In this paper, we promote the constructing concept which is made by substantiating the mechanical design of biological muscle by a simple model, proving the feasibility of its real-world implementation, and checking their output both for mutual consistency and agreement with biological measurements. In particular, the relations of force, enthalpy rate and mechanical efficiency versus contraction velocity of both the construct's technical implementation and its numerical model were determined in quick-release experiments. All model predictions for these relations and the hardware results are now in good agreement with the biological literature. We conclude that the construct represents a mechanical concept of natural actuation, which is suitable for laying down some useful suggestions when designing bio-inspired actuators.

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

OpenAIRE

Page, T; Thorsteinsson, G

2017-01-01

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

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

Science.gov (United States)

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

2016-10-31

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

Astrophysical constraints on unparticle-inspired models of gravity

International Nuclear Information System (INIS)

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

2009-01-01

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

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

Science.gov (United States)

Nurzaman, Surya G.

2016-01-01

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

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.

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...

Nature as an engineer: one simple concept of a bio-inspired functional artificial muscle

International Nuclear Information System (INIS)

Schmitt, S; Haeufle, D F B; Günther, M; Blickhan, R

2012-01-01

The biological muscle is a powerful, flexible and versatile actuator. Its intrinsic characteristics determine the way how movements are generated and controlled. Robotic and prosthetic applications expect to profit from relying on bio-inspired actuators which exhibit natural (muscle-like) characteristics. As of today, when constructing a technical actuator, it is not possible to copy the exact molecular structure of a biological muscle. Alternatively, the question may be put how its characteristics can be realized with known mechanical components. Recently, a mechanical construct for an artificial muscle was proposed, which exhibits hyperbolic force–velocity characteristics. In this paper, we promote the constructing concept which is made by substantiating the mechanical design of biological muscle by a simple model, proving the feasibility of its real-world implementation, and checking their output both for mutual consistency and agreement with biological measurements. In particular, the relations of force, enthalpy rate and mechanical efficiency versus contraction velocity of both the construct’s technical implementation and its numerical model were determined in quick-release experiments. All model predictions for these relations and the hardware results are now in good agreement with the biological literature. We conclude that the construct represents a mechanical concept of natural actuation, which is suitable for laying down some useful suggestions when designing bio-inspired actuators. (paper)

SABRE: a bio-inspired fault-tolerant electronic architecture

International Nuclear Information System (INIS)

Bremner, P; Samie, M; Dragffy, G; Pipe, A G; Liu, Y; Tempesti, G; Timmis, J; Tyrrell, A M

2013-01-01

As electronic devices become increasingly complex, ensuring their reliable, fault-free operation is becoming correspondingly more challenging. It can be observed that, in spite of their complexity, biological systems are highly reliable and fault tolerant. Hence, we are motivated to take inspiration for biological systems in the design of electronic ones. In SABRE (self-healing cellular architectures for biologically inspired highly reliable electronic systems), we have designed a bio-inspired fault-tolerant hierarchical architecture for this purpose. As in biology, the foundation for the whole system is cellular in nature, with each cell able to detect faults in its operation and trigger intra-cellular or extra-cellular repair as required. At the next level in the hierarchy, arrays of cells are configured and controlled as function units in a transport triggered architecture (TTA), which is able to perform partial-dynamic reconfiguration to rectify problems that cannot be solved at the cellular level. Each TTA is, in turn, part of a larger multi-processor system which employs coarser grain reconfiguration to tolerate faults that cause a processor to fail. In this paper, we describe the details of operation of each layer of the SABRE hierarchy, and how these layers interact to provide a high systemic level of fault tolerance. (paper)

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

Science.gov (United States)

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

1996-06-01

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

Anomalous Diffusion within the Transcriptome as a Bio-Inspired Computing Framework for Resilience

Directory of Open Access Journals (Sweden)

William Seffens

2017-07-01

Full Text Available Much of biology-inspired computer science is based on the Central Dogma, as implemented with genetic algorithms or evolutionary computation. That 60-year-old biological principle based on the genome, transcriptome and proteasome is becoming overshadowed by a new paradigm of complex ordered associations and connections between layers of biological entities, such as interactomes, metabolomics, etc. We define a new hierarchical concept as the “Connectosome”, and propose new venues of computational data structures based on a conceptual framework called “Grand Ensemble” which contains the Central Dogma as a subset. Connectedness and communication within and between living or biology-inspired systems comprise ensembles from which a physical computing system can be conceived. In this framework the delivery of messages is filtered by size and a simple and rapid semantic analysis of their content. This work aims to initiate discussion on the Grand Ensemble in network biology as a representation of a Persistent Turing Machine. This framework adding interaction and persistency to the classic Turing-machine model uses metrics based on resilience that has application to dynamic optimization problem solving in Genetic Programming.

Learning from nature: Nature-inspired algorithms

DEFF Research Database (Denmark)

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

2016-01-01

.), genetic and evolutionary strategies, artificial immune systems etc. Well-known examples of applications include: aircraft wing design, wind turbine design, bionic car, bullet train, optimal decisions related to traffic, appropriate strategies to survive under a well-adapted immune system etc. Based......During last decade, the nature has inspired researchers to develop new algorithms. The largest collection of nature-inspired algorithms is biology-inspired: swarm intelligence (particle swarm optimization, ant colony optimization, cuckoo search, bees' algorithm, bat algorithm, firefly algorithm etc...... on collective social behaviour of organisms, researchers have developed optimization strategies taking into account not only the individuals, but also groups and environment. However, learning from nature, new classes of approaches can be identified, tested and compared against already available algorithms...

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

International Nuclear Information System (INIS)

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

2003-01-01

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

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.

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

International Nuclear Information System (INIS)

Margheri, L; Laschi, C; Mazzolai, B

2012-01-01

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

Bio-inspired algorithms applied to molecular docking simulations.

Science.gov (United States)

Heberlé, G; de Azevedo, W F

2011-01-01

Nature as a source of inspiration has been shown to have a great beneficial impact on the development of new computational methodologies. In this scenario, analyses of the interactions between a protein target and a ligand can be simulated by biologically inspired algorithms (BIAs). These algorithms mimic biological systems to create new paradigms for computation, such as neural networks, evolutionary computing, and swarm intelligence. This review provides a description of the main concepts behind BIAs applied to molecular docking simulations. Special attention is devoted to evolutionary algorithms, guided-directed evolutionary algorithms, and Lamarckian genetic algorithms. Recent applications of these methodologies to protein targets identified in the Mycobacterium tuberculosis genome are described.

Nostalgia-Evoked Inspiration: Mediating Mechanisms and Motivational Implications.

Science.gov (United States)

Stephan, Elena; Sedikides, Constantine; Wildschut, Tim; Cheung, Wing-Yee; Routledge, Clay; Arndt, Jamie

2015-10-01

Six studies examined the nostalgia-inspiration link and its motivational implications. In Study 1, nostalgia proneness was positively associated with inspiration frequency and intensity. In Studies 2 and 3, the recollection of nostalgic (vs. ordinary) experiences increased both general inspiration and specific inspiration to engage in exploratory activities. In Study 4, serial mediational analyses supported a model in which nostalgia increases social connectedness, which subsequently fosters self-esteem, which then boosts inspiration. In Study 5, a rigorous evaluation of this serial mediational model (with a novel nostalgia induction controlling for positive affect) reinforced the idea that nostalgia-elicited social connectedness increases self-esteem, which then heightens inspiration. Study 6 extended the serial mediational model by demonstrating that nostalgia-evoked inspiration predicts goal pursuit (intentions to pursue an important goal). Nostalgia spawns inspiration via social connectedness and attendant self-esteem. In turn, nostalgia-evoked inspiration bolsters motivation. © 2015 by the Society for Personality and Social Psychology, Inc.

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

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

Science.gov (United States)

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

2016-12-17

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

Mapping biological systems to network systems

CERN Document Server

Rathore, Heena

2016-01-01

The book presents the challenges inherent in the paradigm shift of network systems from static to highly dynamic distributed systems – it proposes solutions that the symbiotic nature of biological systems can provide into altering networking systems to adapt to these changes. The author discuss how biological systems – which have the inherent capabilities of evolving, self-organizing, self-repairing and flourishing with time – are inspiring researchers to take opportunities from the biology domain and map them with the problems faced in network domain. The book revolves around the central idea of bio-inspired systems -- it begins by exploring why biology and computer network research are such a natural match. This is followed by presenting a broad overview of biologically inspired research in network systems -- it is classified by the biological field that inspired each topic and by the area of networking in which that topic lies. Each case elucidates how biological concepts have been most successfully ...

Natural and bio-inspired underwater adhesives: Current progress and new perspectives

Science.gov (United States)

Cui, Mengkui; Ren, Susu; Wei, Shicao; Sun, Chengjun; Zhong, Chao

2017-11-01

Many marine organisms harness diverse protein molecules as underwater adhesives to achieve strong and robust interfacial adhesion under dynamic and turbulent environments. Natural underwater adhesion phenomena thus provide inspiration for engineering adhesive materials that can perform in water or high-moisture settings for biomedical and industrial applications. Here we review examples of biological adhesives to show the molecular features of natural adhesives and discuss how such knowledge serves as a heuristic guideline for the rational design of biologically inspired underwater adhesives. In view of future bio-inspired research, we propose several potential opportunities, either in improving upon current L-3, 4-dihydroxyphenylalanine-based and coacervates-enabled adhesives with new features or engineering conceptually new types of adhesives that recapitulate important characteristics of biological adhesives. We underline the importance of viewing natural adhesives as dynamic materials, which owe their outstanding performance to the cellular coordination of protein expression, delivery, deposition, assembly, and curing of corresponding components with spatiotemporal control. We envision that the emerging synthetic biology techniques will provide great opportunities for advancing both fundamental and application aspects of underwater adhesives.

Natural and bio-inspired underwater adhesives: Current progress and new perspectives

Directory of Open Access Journals (Sweden)

Mengkui Cui

2017-11-01

Full Text Available Many marine organisms harness diverse protein molecules as underwater adhesives to achieve strong and robust interfacial adhesion under dynamic and turbulent environments. Natural underwater adhesion phenomena thus provide inspiration for engineering adhesive materials that can perform in water or high-moisture settings for biomedical and industrial applications. Here we review examples of biological adhesives to show the molecular features of natural adhesives and discuss how such knowledge serves as a heuristic guideline for the rational design of biologically inspired underwater adhesives. In view of future bio-inspired research, we propose several potential opportunities, either in improving upon current L-3, 4-dihydroxyphenylalanine-based and coacervates-enabled adhesives with new features or engineering conceptually new types of adhesives that recapitulate important characteristics of biological adhesives. We underline the importance of viewing natural adhesives as dynamic materials, which owe their outstanding performance to the cellular coordination of protein expression, delivery, deposition, assembly, and curing of corresponding components with spatiotemporal control. We envision that the emerging synthetic biology techniques will provide great opportunities for advancing both fundamental and application aspects of underwater adhesives.

A computational model of conditioning inspired by Drosophila olfactory system.

Science.gov (United States)

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

2017-03-01

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

Biology-inspired AMO physics

International Nuclear Information System (INIS)

Mathur, Deepak

2015-01-01

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

Brain Inspired Cognitive Model with Attention for Self-Driving Cars

OpenAIRE

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

2017-01-01

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

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.

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

DEFF Research Database (Denmark)

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

2016-01-01

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

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.

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

Science.gov (United States)

Sasaki, Ken

1987-12-01

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

Biologically inspired technologies using artificial muscles

Science.gov (United States)

Bar-Cohen, Yoseph

2005-01-01

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

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

Science.gov (United States)

Nakajima, Toshiyuki

2015-12-01

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

Bio-Inspired Sustainability Assessment for Building Product Development—Concept and Case Study

Directory of Open Access Journals (Sweden)

Rafael Horn

2018-01-01

Full Text Available Technological advancement culminating in a globalized economy has brought tremendous improvements for mankind in manifold respects but comes at the cost of alienation from nature. Human activities nowadays are unsustainable and cause severe damage especially in terms of global depletion and destabilization of natural systems but also harm its own social resources. In this paper, a sustainability assessment method is developed based on a bio-inspired sustainability framework that has been developed in the project TRR 141-C01 “The biomimetic promise.” It is aims at regaining the advantages of societal embeddedness in its environment through biological inspiration. The method is developed using a structured approach including requirement specification, description of the inventory models on bio-inspiration and sustainability assessment, creation of a bio-inspired sustainability assessment model and its validation. It is defined as an accompanying assessment for decision support, using a six-fold two-dimensional structure of social, economic and environmental functions and burdens. The method is applied and validated in 6 projects of TRR 141 and its applicability is exemplarily shown by the assessment of “Bio-flexi”, a biobased and biodegradable natural fiber reinforced plastic composite for indoor cladding applications. Based on the findings of the application the assessment method itself is proposed to be advanced towards an adaptive structure and a consequent outlook is provided.

eDNA: A Bio-Inspired Reconfigurable Hardware Cell Architecture Supporting Self-organisation and Self-healing

DEFF Research Database (Denmark)

Boesen, Michael Reibel; Madsen, Jan

2009-01-01

This paper presents the concept of a biological inspired reconfigurable hardware cell architecture which supports self-organisation and self-healing. Two fundamental processes in biology, namely fertilization-to-birth and cell self-healing have inspired the development of this cell architecture...... to simulate our self-organisation and self-healing algorithms and the results obtained from this looks promising....

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.

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

Science.gov (United States)

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

2005-01-01

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

Bio-inspired vision

International Nuclear Information System (INIS)

Posch, C

2012-01-01

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

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

Science.gov (United States)

Revell, Christopher; Somveille, Marius

2017-08-29

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

A bio-inspired approach for in situ synthesis of tunable adhesive

International Nuclear Information System (INIS)

Sun, Leming; Yi, Sijia; Wang, Yongzhong; Pan, Kang; Zhong, Qixin; Zhang, Mingjun

2014-01-01

Inspired by the strong adhesive produced by English ivy, this paper proposes an in situ synthesis approach for fabricating tunable nanoparticle enhanced adhesives. Special attention was given to tunable features of the adhesive produced by the biological process. Parameters that may be used to tune properties of the adhesive will be proposed. To illustrate and validate the proposed approach, an experimental platform was presented for fabricating tunable chitosan adhesive enhanced by Au nanoparticles synthesized in situ. This study contributes to a bio-inspired approach for in situ synthesis of tunable nanocomposite adhesives by mimicking the natural biological processes of ivy adhesive synthesis. (paper)

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

Science.gov (United States)

Steinberg, Marc

2011-06-01

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

An Immune-inspired Adaptive Automated Intrusion Response System Model

Directory of Open Access Journals (Sweden)

Ling-xi Peng

2012-09-01

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

Social insects inspire human design

Science.gov (United States)

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

2010-01-01

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

Supersymmetric SO(10) models inspired by deconstruction

International Nuclear Information System (INIS)

Huang Chaoshang; Jiang Jing; Li Tianjun

2004-01-01

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

A bio-inspired electrocommunication system for small underwater robots.

Science.gov (United States)

Wang, Wei; Liu, Jindong; Xie, Guangming; Wen, Li; Zhang, Jianwei

2017-03-29

Weakly electric fishes (Gymnotid and Mormyrid) use an electric field to communicate efficiently (termed electrocommunication) in the turbid waters of confined spaces where other communication modalities fail. Inspired by this biological phenomenon, we design an artificial electrocommunication system for small underwater robots and explore the capabilities of such an underwater robotic communication system. An analytical model for electrocommunication is derived to predict the effect of the key parameters such as electrode distance and emitter current of the system on the communication performance. According to this model, a low-dissipation, and small-sized electrocommunication system is proposed and integrated into a small robotic fish. We characterize the communication performance of the robot in still water, flowing water, water with obstacles and natural water conditions. The results show that underwater robots are able to communicate electrically at a speed of around 1 k baud within about 3 m with a low power consumption (less than 1 W). In addition, we demonstrate that two leader-follower robots successfully achieve motion synchronization through electrocommunication in the three-dimensional underwater space, indicating that this bio-inspired electrocommunication system is a promising setup for the interaction of small underwater robots.

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.…

Novel Approaches for Bio-inspired Mechano-Sensors

DEFF Research Database (Denmark)

Drimus, Alin; Bilberg, Arne

2011-01-01

In this paper, we present novel approaches for building tactile- array sensors for use in robotic grippers inspired from biology. We start by describing the sense of touch for humans and we continue by propos- ing dierent methods to build sensors that mimic this behaviour. For the static tactile...

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

Indian Academy of Sciences (India)

2017-02-28

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

(YIP 10) - Bio-Inspired Interfaces for Hybrid Structures

Science.gov (United States)

2013-07-01

vertebrate bones and teeth, mollusk shells and arthropod exoskeletons [1, 2]. Two interesting examples of such biological systems are gecko’s footpad...range from non-wetting painting and smart adhesives [35-41] to intricate bioinspired designs such as nano- and micro- robotics with climbing abilities...smart adhesion. Advanced Materials, 2008. 20(4): p. 711-716. 42. Wood, R.J., The first takeoff of a biologically inspired at-scale robotic insect

Inspiration and application in the evolution of biomaterials

OpenAIRE

Huebsch, Nathaniel; Mooney, David J.

2009-01-01

Biomaterials, traditionally defined as materials used in medical devices, have been used since antiquity, but recently their degree of sophistication has increased significantly. Biomaterials made today are routinely information rich and incorporate biologically active components derived from nature. In the future, biomaterials will assume an even greater role in medicine and will find use in a wide variety of non-medical applications through biologically inspired design and incorporation of ...

Inspiration and application in the evolution of biomaterials.

Science.gov (United States)

Huebsch, Nathaniel; Mooney, David J

2009-11-26

Biomaterials, traditionally defined as materials used in medical devices, have been used since antiquity, but recently their degree of sophistication has increased significantly. Biomaterials made today are routinely information rich and incorporate biologically active components derived from nature. In the future, biomaterials will assume an even greater role in medicine and will find use in a wide variety of non-medical applications through biologically inspired design and incorporation of dynamic behaviour.

Effect of inspiration on airway dimensions measured in maximal inspiration CT images of subjects without airflow limitation

DEFF Research Database (Denmark)

Petersen, Jens; Wille, Mathilde M.W.; Raket, Lars Lau

2014-01-01

. Automated software was utilized to segment lungs and airways, identify segmental bronchi, and match airway branches in all images of the same subject. Inspiration level was defined as segmented total lung volume (TLV) divided by predicted total lung capacity (pTLC). Mixed-effects models were used to predict......OBJECTIVES: To study the effect of inspiration on airway dimensions measured in voluntary inspiration breath-hold examinations. METHODS: 961 subjects with normal spirometry were selected from the Danish Lung Cancer Screening Trial. Subjects were examined annually for five years with low-dose CT...... • The effect of inspiration is greater in higher-generation (more peripheral) airways • Airways of generation 5 and beyond are as distensible as lung parenchyma • Airway dimensions measured from CT should be adjusted for inspiration level....

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

Science.gov (United States)

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

2003-10-01

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

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.

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.

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

Directory of Open Access Journals (Sweden)

Nurhan Gursel Ozmen

2018-01-01

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

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

Science.gov (United States)

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

2009-07-01

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

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. Copyright © 2010 Elsevier Ltd. All rights reserved.

BioMAV : Bio-inspired intelligence for autonomous flight

NARCIS (Netherlands)

Gerke, P.K.; Langevoort, J.; Lagarde, S.; Bax, L.; Grootswagers, T.; Drenth, R.J.; Slieker, V.; Vuurpijl, L.; Haselager, P.; Sprinkhuizen-Kuyper, I.; Van Otterlo, M.; De Croon, G.C.H.E.

2011-01-01

This paper aims to contribute to research on biologically inspired micro air vehicles in two ways: (i) it explores a novel repertoire of behavioral modules which can be controlled through ?nite state machines (FSM) and (ii) elementary movement detectors (EMD) are combined with a center/surround edge

VI International Workshop on Nature Inspired Cooperative Strategies for Optimization

CERN Document Server

Otero, Fernando; Masegosa, Antonio

2014-01-01

Biological and other natural processes have always been a source of inspiration for computer science and information technology. Many emerging problem solving techniques integrate advanced evolution and cooperation strategies, encompassing a range of spatio-temporal scales for visionary conceptualization of evolutionary computation. This book is a collection of research works presented in the VI International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO) held in Canterbury, UK. Previous editions of NICSO were held in Granada, Spain (2006 & 2010), Acireale, Italy (2007), Tenerife, Spain (2008), and Cluj-Napoca, Romania (2011). NICSO 2013 and this book provides a place where state-of-the-art research, latest ideas and emerging areas of nature inspired cooperative strategies for problem solving are vigorously discussed and exchanged among the scientific community. The breadth and variety of articles in this book report on nature inspired methods and applications such as Swarm In...

Advances in bio-inspired computing for combinatorial optimization problems

CERN Document Server

Pintea, Camelia-Mihaela

2013-01-01

Advances in Bio-inspired Combinatorial Optimization Problems' illustrates several recent bio-inspired efficient algorithms for solving NP-hard problems.Theoretical bio-inspired concepts and models, in particular for agents, ants and virtual robots are described. Large-scale optimization problems, for example: the Generalized Traveling Salesman Problem and the Railway Traveling Salesman Problem, are solved and their results are discussed.Some of the main concepts and models described in this book are: inner rule to guide ant search - a recent model in ant optimization, heterogeneous sensitive a

The scientific study of inspiration in the creative process: Challenges and opportunities

Directory of Open Access Journals (Sweden)

Victoria C. Oleynick

2014-06-01

Full Text Available Inspiration is a motivational state that compels individuals to bring ideas into fruition. Creators have long argued that inspiration is important to the creative process, but until recently, scientists have not investigated this claim. In this article, we review challenges to the study of creative inspiration, as well as solutions to these challenges afforded by theoretical and empirical work on inspiration over the past decade. First, we discuss the problem of definitional ambiguity, which has been addressed through an integrative process of construct conceptualization. Second, we discuss the challenge of how to operationalize inspiration. This challenge has been overcome by the development and validation of the Inspiration Scale, which may be used to assess trait or state inspiration. Third, we address ambiguity regarding how inspiration differs from related concepts (creativity, insight, positive affect by discussing discriminant validity. Next, we discuss the preconception that inspiration is less important than perspiration (effort, and we review empirical evidence that inspiration and effort both play important—but different—roles in the creative process. Finally, with many challenges overcome, we argue that the foundation is now set for a new generation of research focused on neural underpinnings. We discuss potential challenges to and opportunities for the neuroscientific study of inspiration. A better understanding of the biological basis of inspiration will illuminate the process through which creative ideas fire the soul, such that individuals are compelled to transform ideas into products and solutions that may benefit society.

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

Directory of Open Access Journals (Sweden)

Kan Li

2018-04-01

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

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

Science.gov (United States)

Li, Kan; Príncipe, José C

2018-01-01

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

Bio-inspired composites with functionally graded platelets exhibit enhanced stiffness.

Science.gov (United States)

Tapse, Sanjay; S, Anup

2017-11-09

Unidirectional composites inspired from biological materials such as nacre, are composed of stiff platelets arranged in a staggered manner within a soft matrix. Elaborate analyses have been conducted on the aforementioned composites and they are found to have excellent mechanical properties like stiffness, strength and fracture toughness. The superior properties exhibited by these composites have been proved to be the result of its unique structure. An emerging development in the field of composite structures is Functionally Graded Composites(FGC), whose properties vary spatially and possess enhanced thermo-mechanical properties. In this paper, the platelets are functionally graded with its Young's Modulus varying parabolically along the length. Two different models - namely, Tension Shear Chain Model and Minimisation of Complementary Energy Model have been employed to obtain the stiffness of the overall composite analytically. The effect of various parameters that define the composite model such as overlapping length between any two neighbouring platelets, different gradation parameters and platelet aspect ratio on the overall mechanical properties have been studied. Composites with functionally graded platelets are found to possess enhanced stiffness (upto 14% higher) for certain values of these parameters. The obtained solutions have been validated using Finite Element Analysis. Bio-inspired composites with functionally graded platelets can be engineered for structural applications, such as in automobile, aerospace and aircraft industry, where stiffness plays a crucial role. © 2017 IOP Publishing Ltd.

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…

Dark matter in a constrained E6 inspired SUSY model

International Nuclear Information System (INIS)

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

2016-01-01

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

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

Science.gov (United States)

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

2017-02-01

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

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

Science.gov (United States)

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

2016-08-01

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

Bio-inspired passive actuator simulating an abalone shell mechanism for structural control

International Nuclear Information System (INIS)

Yang, Henry T Y; Lin, Chun-Hung; Bridges, Daniel; Randall, Connor J; Hansma, Paul K

2010-01-01

An energy dispersion mechanism called 'sacrificial bonds and hidden length', which is found in some biological systems, such as abalone shells and bones, is the inspiration for new strategies for structural control. Sacrificial bonds and hidden length can substantially increase the stiffness and enhance energy dissipation in the constituent molecules of abalone shells and bone. Having been inspired by the usefulness and effectiveness of such a mechanism, which has evolved over millions of years and countless cycles of evolutions, the authors employ the conceptual underpinnings of this mechanism to develop a bio-inspired passive actuator. This paper presents a fundamental method for optimally designing such bio-inspired passive actuators for structural control. To optimize the bio-inspired passive actuator, a simple method utilizing the force–displacement–velocity (FDV) plots based on LQR control is proposed. A linear regression approach is adopted in this research to find the initial values of the desired parameters for the bio-inspired passive actuator. The illustrative examples, conducted by numerical simulation with experimental validation, suggest that the bio-inspired passive actuator based on sacrificial bonds and hidden length may be comparable in performance to state-of-the-art semi-active actuators

Bio-inspired passive actuator simulating an abalone shell mechanism for structural control

Science.gov (United States)

Yang, Henry T. Y.; Lin, Chun-Hung; Bridges, Daniel; Randall, Connor J.; Hansma, Paul K.

2010-10-01

An energy dispersion mechanism called 'sacrificial bonds and hidden length', which is found in some biological systems, such as abalone shells and bones, is the inspiration for new strategies for structural control. Sacrificial bonds and hidden length can substantially increase the stiffness and enhance energy dissipation in the constituent molecules of abalone shells and bone. Having been inspired by the usefulness and effectiveness of such a mechanism, which has evolved over millions of years and countless cycles of evolutions, the authors employ the conceptual underpinnings of this mechanism to develop a bio-inspired passive actuator. This paper presents a fundamental method for optimally designing such bio-inspired passive actuators for structural control. To optimize the bio-inspired passive actuator, a simple method utilizing the force-displacement-velocity (FDV) plots based on LQR control is proposed. A linear regression approach is adopted in this research to find the initial values of the desired parameters for the bio-inspired passive actuator. The illustrative examples, conducted by numerical simulation with experimental validation, suggest that the bio-inspired passive actuator based on sacrificial bonds and hidden length may be comparable in performance to state-of-the-art semi-active actuators.

Buckling Pneumatic Linear Actuators Inspired by Muscle

OpenAIRE

Yang, Dian; Verma, Mohit Singh; So, Ju-Hee; Mosadegh, Bobak; Keplinger, Christoph; Lee, Benjamin; Khashai, Fatemeh; Lossner, Elton Garret; Suo, Zhigang; Whitesides, George McClelland

2016-01-01

The mechanical features of biological muscles are difficult to reproduce completely in synthetic systems. A new class of soft pneumatic structures (vacuum-actuated muscle-inspired pneumatic structures) is described that combines actuation by negative pressure (vacuum), with cooperative buckling of beams fabricated in a slab of elastomer, to achieve motion and demonstrate many features that are similar to that of mammalian muscle.

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

Science.gov (United States)

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

2017-07-01

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

A bio-inspired glucose controller based on pancreatic β-cell physiology.

Science.gov (United States)

Herrero, Pau; Georgiou, Pantelis; Oliver, Nick; Johnston, Desmond G; Toumazou, Christofer

2012-05-01

Control algorithms for closed-loop insulin delivery in type 1 diabetes have been mainly based on control engineering or artificial intelligence techniques. These, however, are not based on the physiology of the pancreas but seek to implement engineering solutions to biology. Developments in mathematical models of the β-cell physiology of the pancreas have described the glucose-induced insulin release from pancreatic β cells at a molecular level. This has facilitated development of a new class of bio-inspired glucose control algorithms that replicate the functionality of the biological pancreas. However, technologies for sensing glucose levels and delivering insulin use the subcutaneous route, which is nonphysiological and introduces some challenges. In this article, a novel glucose controller is presented as part of a bio-inspired artificial pancreas. A mathematical model of β-cell physiology was used as the core of the proposed controller. In order to deal with delays and lack of accuracy introduced by the subcutaneous route, insulin feedback and a gain scheduling strategy were employed. A United States Food and Drug Administration-accepted type 1 diabetes mellitus virtual population was used to validate the presented controller. Premeal and postmeal mean ± standard deviation blood glucose levels for the adult and adolescent populations were well within the target range set for the controller [(70, 180) mg/dl], with a percent time in range of 92.8 ± 7.3% for the adults and 83.5 ± 14% for the adolescents. This article shows for the first time very good glucose control in a virtual population with type 1 diabetes mellitus using a controller based on a subcellular β-cell model. © 2012 Diabetes Technology Society.

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.

Origami-Inspired Folding of Thick, Rigid Panels

Science.gov (United States)

Trease, Brian P.; Thomson, Mark W.; Sigel, Deborah A.; Walkemeyer, Phillip E.; Zirbel, Shannon; Howell, Larry; Lang, Robert

2014-01-01

To achieve power of 250 kW or greater, a large compression ratio of stowed-to-deployed area is needed. Origami folding patterns were used to inspire the folding of a solar array to achieve synchronous deployment; however, origami models are generally created for near-zero-thickness material. Panel thickness is one of the main challenges of origami-inspired design. Three origami-inspired folding techniques (flasher, square twist, and map fold) were created with rigid panels and hinges. Hinge components are added to the model to enable folding of thick, rigid materials. Origami models are created assuming zero (or near zero) thickness. When a material with finite thickness is used, the panels are required to bend around an increasingly thick fold as they move away from the center of the model. The two approaches for dealing with material thickness are to use membrane hinges to connect the panels, or to add panel hinges, or hinges of the same thickness, at an appropriate width to enable folding.

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.

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

Directory of Open Access Journals (Sweden)

Tashkova Katerina

2011-10-01

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

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

Science.gov (United States)

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

2011-10-11

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

First controlled vertical flight of a biologically inspired microrobot

Energy Technology Data Exchange (ETDEWEB)

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

2011-09-15

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

First controlled vertical flight of a biologically inspired microrobot

International Nuclear Information System (INIS)

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

2011-01-01

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

Flipper-driven terrestrial locomotion of a sea turtle-inspired robot

International Nuclear Information System (INIS)

Mazouchova, Nicole; Umbanhowar, Paul B; Goldman, Daniel I

2013-01-01

To discover principles of flipper-based terrestrial locomotion we study the mechanics of a hatchling sea turtle-inspired robot, FlipperBot (FBot), during quasi-static movement on granular media. FBot implements a symmetric gait using two servo-motor-driven front limbs with flat-plate flippers and either freely rotating or fixed wrist joints. For a range of gaits, FBot moves with a constant step length. However, for gaits with sufficiently shallow flipper penetration or sufficiently large stroke, per step displacement decreases with each successive step resulting in failure (zero forward displacement) within a few steps. For the fixed wrist, failure occurs when FBot interacts with ground disturbed during previous steps, and measurements reveal that flipper generated forces decrease as per step displacement decreases. The biologically inspired free wrist is less prone to failure, but slip-induced failure can still occur if FBot pitches forward and drives its leading edge into the substrate. In the constant step length regime, kinematic and force-based models accurately predict FBot's motion for free and fixed wrist configurations, respectively. When combined with independent force measurements, models and experiments provide insight into how disturbed ground leads to locomotory failure and help explain differences in hatchling sea turtle performance. (paper)

Biology and therapy of inherited retinal degenerative disease: insights from mouse models

Science.gov (United States)

Veleri, Shobi; Lazar, Csilla H.; Chang, Bo; Sieving, Paul A.; Banin, Eyal; Swaroop, Anand

2015-01-01

Retinal neurodegeneration associated with the dysfunction or death of photoreceptors is a major cause of incurable vision loss. Tremendous progress has been made over the last two decades in discovering genes and genetic defects that lead to retinal diseases. The primary focus has now shifted to uncovering disease mechanisms and designing treatment strategies, especially inspired by the successful application of gene therapy in some forms of congenital blindness in humans. Both spontaneous and laboratory-generated mouse mutants have been valuable for providing fundamental insights into normal retinal development and for deciphering disease pathology. Here, we provide a review of mouse models of human retinal degeneration, with a primary focus on diseases affecting photoreceptor function. We also describe models associated with retinal pigment epithelium dysfunction or synaptic abnormalities. Furthermore, we highlight the crucial role of mouse models in elucidating retinal and photoreceptor biology in health and disease, and in the assessment of novel therapeutic modalities, including gene- and stem-cell-based therapies, for retinal degenerative diseases. PMID:25650393

Computational Design of Multi-component Bio-Inspired Bilayer Membranes

Directory of Open Access Journals (Sweden)

Evan Koufos

2014-04-01

Full Text Available Our investigation is motivated by the need to design bilayer membranes with tunable interfacial and mechanical properties for use in a range of applications, such as targeted drug delivery, sensing and imaging. We draw inspiration from biological cell membranes and focus on their principal constituents. In this paper, we present our results on the role of molecular architecture on the interfacial, structural and dynamical properties of bio-inspired membranes. We focus on four lipid architectures with variations in the head group shape and the hydrocarbon tail length. Each lipid species is composed of a hydrophilic head group and two hydrophobic tails. In addition, we study a model of the Cholesterol molecule to understand the interfacial properties of a bilayer membrane composed of rigid, single-tail molecular species. We demonstrate the properties of the bilayer membranes to be determined by the molecular architecture and rigidity of the constituent species. Finally, we demonstrate the formation of a stable mixed bilayer membrane composed of Cholesterol and one of the phospholipid species. Our approach can be adopted to design multi-component bilayer membranes with tunable interfacial and mechanical properties. We use a Molecular Dynamics-based mesoscopic simulation technique called Dissipative Particle Dynamics that resolves the molecular details of the components through soft-sphere coarse-grained models and reproduces the hydrodynamic behavior of the system over extended time scales.

Data specifications for INSPIRE

Science.gov (United States)

Portele, Clemens; Woolf, Andrew; Cox, Simon

2010-05-01

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

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

International Nuclear Information System (INIS)

Zhang, Zhiye; Philen, Michael; Neu, Wayne

2010-01-01

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

Material requirements for bio-inspired sensing systems

Science.gov (United States)

Biggins, Peter; Lloyd, Peter; Salmond, David; Kusterbeck, Anne

2008-10-01

The aim of developing bio-inspired sensing systems is to try and emulate the amazing sensitivity and specificity observed in the natural world. These capabilities have evolved, often for specific tasks, which provide the organism with an advantage in its fight to survive and prosper. Capabilities cover a wide range of sensing functions including vision, temperature, hearing, touch, taste and smell. For some functions, the capabilities of natural systems are still greater than that achieved by traditional engineering solutions; a good example being a dog's sense of smell. Furthermore, attempting to emulate aspects of biological optics, processing and guidance may lead to more simple and effective devices. A bio-inspired sensing system is much more than the sensory mechanism. A system will need to collect samples, especially if pathogens or chemicals are of interest. Other functions could include the provision of power, surfaces and receptors, structure, locomotion and control. In fact it is possible to conceive of a complete bio-inspired system concept which is likely to be radically different from more conventional approaches. This concept will be described and individual component technologies considered.

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

Science.gov (United States)

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

2017-01-01

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

Neuroscience-Inspired Artificial Intelligence.

Science.gov (United States)

Hassabis, Demis; Kumaran, Dharshan; Summerfield, Christopher; Botvinick, Matthew

2017-07-19

The fields of neuroscience and artificial intelligence (AI) have a long and intertwined history. In more recent times, however, communication and collaboration between the two fields has become less commonplace. In this article, we argue that better understanding biological brains could play a vital role in building intelligent machines. We survey historical interactions between the AI and neuroscience fields and emphasize current advances in AI that have been inspired by the study of neural computation in humans and other animals. We conclude by highlighting shared themes that may be key for advancing future research in both fields. Copyright © 2017. Published by Elsevier Inc.

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

Directory of Open Access Journals (Sweden)

Hyun-Ho Choi

2016-03-01

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

A Review of Natural Joint Systems and Numerical Investigation of Bio-Inspired GFRP-to-Steel Joints

Directory of Open Access Journals (Sweden)

Evangelos I. Avgoulas

2016-07-01

Full Text Available There are a great variety of joint types used in nature which can inspire engineering joints. In order to design such biomimetic joints, it is at first important to understand how biological joints work. A comprehensive literature review, considering natural joints from a mechanical point of view, was undertaken. This was used to develop a taxonomy based on the different methods/functions that nature successfully uses to attach dissimilar tissues. One of the key methods that nature uses to join dissimilar materials is a transitional zone of stiffness at the insertion site. This method was used to propose bio-inspired solutions with a transitional zone of stiffness at the joint site for several glass fibre reinforced plastic (GFRP to steel adhesively bonded joint configurations. The transition zone was used to reduce the material stiffness mismatch of the joint parts. A numerical finite element model was used to identify the optimum variation in material stiffness that minimises potential failure of the joint. The best bio-inspired joints showed a 118% increase of joint strength compared to the standard joints.

Accelerating Inspire

CERN Document Server

AUTHOR|(CDS)2266999

2017-01-01

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

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

Science.gov (United States)

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

2017-10-01

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

A bio-inspired design of a hand robotic exoskeleton for rehabilitation

Science.gov (United States)

Ong, Aira Patrice R.; Bugtai, Nilo T.

2018-02-01

This paper presents the methodology for the design of a five-degree of freedom wearable robotic exoskeleton for hand rehabilitation. The design is inspired by the biological structure and mechanism of the human hand. One of the distinct features of the device is the cable-driven actuation, which provides the flexion and extension motion. A prototype of the orthotic device has been developed to prove the model of the system and has been tested in a 3D printed mechanical hand. The result showed that the proposed device was consistent with the requirements of bionics and was able to demonstrate the flexion and extension of the system.

Dipteran wing motor-inspired flapping flight versatility and effectiveness enhancement.

Science.gov (United States)

Harne, R L; Wang, K W

2015-03-06

Insects are a prime source of inspiration towards the development of small-scale, engineered, flapping wing flight systems. To help interpret the possible energy transformation strategies observed in Diptera as inspiration for mechanical flapping flight systems, we revisit the perspective of the dipteran wing motor as a bistable click mechanism and take a new, and more flexible, outlook to the architectural composition previously considered. Using a representative structural model alongside biological insights and cues from nonlinear dynamics, our analyses and experimental results reveal that a flight mechanism able to adjust motor axial support stiffness and compression characteristics may dramatically modulate the amplitude range and type of wing stroke dynamics achievable. This corresponds to significantly more versatile aerodynamic force generation without otherwise changing flapping frequency or driving force amplitude. Whether monostable or bistable, the axial stiffness is key to enhance compressed motor load bearing ability and aerodynamic efficiency, particularly compared with uncompressed linear motors. These findings provide new foundation to guide future development of bioinspired, flapping wing mechanisms for micro air vehicle applications, and may be used to provide insight to the dipteran muscle-to-wing interface. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

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

Science.gov (United States)

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

2014-10-01

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

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

Science.gov (United States)

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

2014-10-23

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

Bioinspiration: applying mechanical design to experimental biology.

Science.gov (United States)

Flammang, Brooke E; Porter, Marianne E

2011-07-01

The production of bioinspired and biomimetic constructs has fostered much collaboration between biologists and engineers, although the extent of biological accuracy employed in the designs produced has not always been a priority. Even the exact definitions of "bioinspired" and "biomimetic" differ among biologists, engineers, and industrial designers, leading to confusion regarding the level of integration and replication of biological principles and physiology. By any name, biologically-inspired mechanical constructs have become an increasingly important research tool in experimental biology, offering the opportunity to focus research by creating model organisms that can be easily manipulated to fill a desired parameter space of structural and functional repertoires. Innovative researchers with both biological and engineering backgrounds have found ways to use bioinspired models to explore the biomechanics of organisms from all kingdoms to answer a variety of different questions. Bringing together these biologists and engineers will hopefully result in an open discourse of techniques and fruitful collaborations for experimental and industrial endeavors.

A bio-inspired memory model for structural health monitoring

International Nuclear Information System (INIS)

Zheng, Wei; Zhu, Yong

2009-01-01

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

A bio-inspired memory model for structural health monitoring

Science.gov (United States)

Zheng, Wei; Zhu, Yong

2009-04-01

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

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

Science.gov (United States)

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

2017-08-01

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

Effect of inspiration on airway dimensions measured in maximal inspiration CT images of subjects without airflow limitation

Energy Technology Data Exchange (ETDEWEB)

Petersen, Jens; Raket, Lars Lau; Nielsen, Mads [University of Copenhagen, Department of Computer Science, Copenhagen (Denmark); Wille, Mathilde M.W.; Dirksen, Asger [University of Copenhagen, Department of Respiratory Medicine, Gentofte Hospital, Hellerup (Denmark); Feragen, Aasa [University of Copenhagen, Department of Computer Science, Copenhagen (Denmark); Max Planck Institute for Intelligent Systems and Max Planck Institute for Developmental Biology, Tuebingen (Germany); Pedersen, Jesper H. [Rigshospitalet, University Hospital of Copenhagen, Department of Cardio-Thoracic Surgery RT, Copenhagen (Denmark); Bruijne, Marleen de [University of Copenhagen, Department of Computer Science, Copenhagen (Denmark); Erasmus MC Rotterdam, Departments of Medical Informatics and Radiology, Rotterdam (Netherlands)

2014-09-15

To study the effect of inspiration on airway dimensions measured in voluntary inspiration breath-hold examinations. 961 subjects with normal spirometry were selected from the Danish Lung Cancer Screening Trial. Subjects were examined annually for five years with low-dose CT. Automated software was utilized to segment lungs and airways, identify segmental bronchi, and match airway branches in all images of the same subject. Inspiration level was defined as segmented total lung volume (TLV) divided by predicted total lung capacity (pTLC). Mixed-effects models were used to predict relative change in lumen diameter (ALD) and wall thickness (AWT) in airways of generation 0 (trachea) to 7 and segmental bronchi (R1-R10 and L1-L10) from relative changes in inspiration level. Relative changes in ALD were related to relative changes in TLV/pTLC, and this distensibility increased with generation (p < 0.001). Relative changes in AWT were inversely related to relative changes in TLV/pTLC in generation 3-7 (p < 0.001). Segmental bronchi were widely dispersed in terms of ALD (5.7 ± 0.7 mm), AWT (0.86 ± 0.07 mm), and distensibility (23.5 ± 7.7 %). Subjects who inspire more deeply prior to imaging have larger ALD and smaller AWT. This effect is more pronounced in higher-generation airways. Therefore, adjustment of inspiration level is necessary to accurately assess airway dimensions. (orig.)

Bio-inspired functional surfaces for advanced applications

DEFF Research Database (Denmark)

Malshe, Ajay; Rajurkar, Kamlakar; Samant, Anoop

2013-01-01

, are being evolved to a higher state of intelligent functionality. These surfaces became more efficient by using combinations of available materials, along with unique physical and chemical strategies. Noteworthy physical strategies include features such as texturing and structure, and chemical strategies...... such as sensing and actuation. These strategies collectively enable functional surfaces to deliver extraordinary adhesion, hydrophobicity, multispectral response, energy scavenging, thermal regulation, antibiofouling, and other advanced functions. Production industries have been intrigued with such biological...... surface strategies in order to learn clever surface architectures and implement those architectures to impart advanced functionalities into manufactured consumer products. This keynote paper delivers a critical review of such inspiring biological surfaces and their nonbiological product analogs, where...

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

Science.gov (United States)

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

2018-04-01

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

Physicists Get INSPIREd: INSPIRE Project and Grid Applications

International Nuclear Information System (INIS)

Klem, Jukka; Iwaszkiewicz, Jan

2011-01-01

INSPIRE is the new high-energy physics scientific information system developed by CERN, DESY, Fermilab and SLAC. INSPIRE combines the curated and trusted contents of SPIRES database with Invenio digital library technology. INSPIRE contains the entire HEP literature with about one million records and in addition to becoming the reference HEP scientific information platform, it aims to provide new kinds of data mining services and metrics to assess the impact of articles and authors. Grid and cloud computing provide new opportunities to offer better services in areas that require large CPU and storage resources including document Optical Character Recognition (OCR) processing, full-text indexing of articles and improved metrics. D4Science-II is a European project that develops and operates an e-Infrastructure supporting Virtual Research Environments (VREs). It develops an enabling technology (gCube) which implements a mechanism for facilitating the interoperation of its e-Infrastructure with other autonomously running data e-Infrastructures. As a result, this creates the core of an e-Infrastructure ecosystem. INSPIRE is one of the e-Infrastructures participating in D4Science-II project. In the context of the D4Science-II project, the INSPIRE e-Infrastructure makes available some of its resources and services to other members of the resulting ecosystem. Moreover, it benefits from the ecosystem via a dedicated Virtual Organization giving access to an array of resources ranging from computing and storage resources of grid infrastructures to data and services.

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

NARCIS (Netherlands)

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

2012-01-01

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

Biology and therapy of inherited retinal degenerative disease: insights from mouse models

Directory of Open Access Journals (Sweden)

Shobi Veleri

2015-02-01

Full Text Available Retinal neurodegeneration associated with the dysfunction or death of photoreceptors is a major cause of incurable vision loss. Tremendous progress has been made over the last two decades in discovering genes and genetic defects that lead to retinal diseases. The primary focus has now shifted to uncovering disease mechanisms and designing treatment strategies, especially inspired by the successful application of gene therapy in some forms of congenital blindness in humans. Both spontaneous and laboratory-generated mouse mutants have been valuable for providing fundamental insights into normal retinal development and for deciphering disease pathology. Here, we provide a review of mouse models of human retinal degeneration, with a primary focus on diseases affecting photoreceptor function. We also describe models associated with retinal pigment epithelium dysfunction or synaptic abnormalities. Furthermore, we highlight the crucial role of mouse models in elucidating retinal and photoreceptor biology in health and disease, and in the assessment of novel therapeutic modalities, including gene- and stem-cell-based therapies, for retinal degenerative diseases.

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

Science.gov (United States)

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

2009-11-01

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

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

Directory of Open Access Journals (Sweden)

Nicolas Pinto

2009-11-01

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

Neuro-Inspired Computing with Stochastic Electronics

KAUST Repository

Naous, Rawan

2016-01-06

The extensive scaling and integration within electronic systems have set the standards for what is addressed to as stochastic electronics. The individual components are increasingly diverting away from their reliable behavior and producing un-deterministic outputs. This stochastic operation highly mimics the biological medium within the brain. Hence, building on the inherent variability, particularly within novel non-volatile memory technologies, paves the way for unconventional neuromorphic designs. Neuro-inspired networks with brain-like structures of neurons and synapses allow for computations and levels of learning for diverse recognition tasks and applications.

Genetic coding and united-hypercomplex systems in the models of algebraic biology.

Science.gov (United States)

Petoukhov, Sergey V

2017-08-01

Structured alphabets of DNA and RNA in their matrix form of representations are connected with Walsh functions and a new type of systems of multidimensional numbers. This type generalizes systems of complex numbers and hypercomplex numbers, which serve as the basis of mathematical natural sciences and many technologies. The new systems of multi-dimensional numbers have interesting mathematical properties and are called in a general case as "systems of united-hypercomplex numbers" (or briefly "U-hypercomplex numbers"). They can be widely used in models of multi-parametrical systems in the field of algebraic biology, artificial life, devices of biological inspired artificial intelligence, etc. In particular, an application of U-hypercomplex numbers reveals hidden properties of genetic alphabets under cyclic permutations in their doublets and triplets. A special attention is devoted to the author's hypothesis about a multi-linguistic in DNA-sequences in a relation with an ensemble of U-numerical sub-alphabets. Genetic multi-linguistic is considered as an important factor to provide noise-immunity properties of the multi-channel genetic coding. Our results attest to the conformity of the algebraic properties of the U-numerical systems with phenomenological properties of the DNA-alphabets and with the complementary device of the double DNA-helix. It seems that in the modeling field of algebraic biology the genetic-informational organization of living bodies can be considered as a set of united-hypercomplex numbers in some association with the famous slogan of Pythagoras "the numbers rule the world". Copyright © 2017 Elsevier B.V. All rights reserved.

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.

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

Science.gov (United States)

McManus, Jeffrey M.; Shaw, Kendrick M.

2010-01-01

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

Smart Nacre-inspired Nanocomposites.

Science.gov (United States)

Peng, Jingsong; Cheng, Qunfeng

2018-03-15

Nacre-inspired nanocomposites with excellent mechanical properties have achieved remarkable attention in the past decades. The high performance of nacre-inspired nanocomposites is a good basis for the further application of smart devices. Recently, some smart nanocomposites inspired by nacre have demonstrated good mechanical properties as well as effective and stable stimuli-responsive functions. In this Concept, we summarize the recent development of smart nacre-inspired nanocomposites, including 1D fibers, 2D films and 3D bulk nanocomposites, in response to temperature, moisture, light, strain, and so on. We show that diverse smart nanocomposites could be designed by combining various conventional fabrication methods of nacre-inspired nanocomposites with responsive building blocks and interface interactions. The nacre-inspired strategy is versatile for different kinds of smart nanocomposites in extensive applications, such as strain sensors, displays, artificial muscles, robotics, and so on, and may act as an effective roadmap for designing smart nanocomposites in the future. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

On the role of emotion in biological and robotic autonomy.

Science.gov (United States)

Ziemke, Tom

2008-02-01

This paper reviews some of the differences between notions of biological and robotic autonomy, and how these differences have been reflected in discussions of embodiment, grounding and other concepts in AI and autonomous robotics. Furthermore, the relations between homeostasis, emotion and embodied cognition are discussed as well as recent proposals to model their interplay in robots, which reflects a commitment to a multi-tiered affectively/emotionally embodied view of mind that takes organismic embodiment more serious than usually done in biologically inspired robotics.

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

Science.gov (United States)

Raman, N; Sudharsan, S

2011-12-01

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

Bio-Inspired Optimization of Sustainable Energy Systems: A Review

Directory of Open Access Journals (Sweden)

Yu-Jun Zheng

2013-01-01

Full Text Available Sustainable energy development always involves complex optimization problems of design, planning, and control, which are often computationally difficult for conventional optimization methods. Fortunately, the continuous advances in artificial intelligence have resulted in an increasing number of heuristic optimization methods for effectively handling those complicated problems. Particularly, algorithms that are inspired by the principles of natural biological evolution and/or collective behavior of social colonies have shown a promising performance and are becoming more and more popular nowadays. In this paper we summarize the recent advances in bio-inspired optimization methods, including artificial neural networks, evolutionary algorithms, swarm intelligence, and their hybridizations, which are applied to the field of sustainable energy development. Literature reviewed in this paper shows the current state of the art and discusses the potential future research trends.

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

Science.gov (United States)

Escalante, George

2017-05-01

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

An autonomous robot inspired by insect neurophysiology pursues moving features in natural environments

Science.gov (United States)

Bagheri, Zahra M.; Cazzolato, Benjamin S.; Grainger, Steven; O'Carroll, David C.; Wiederman, Steven D.

2017-08-01

Objective. Many computer vision and robotic applications require the implementation of robust and efficient target-tracking algorithms on a moving platform. However, deployment of a real-time system is challenging, even with the computational power of modern hardware. Lightweight and low-powered flying insects, such as dragonflies, track prey or conspecifics within cluttered natural environments, illustrating an efficient biological solution to the target-tracking problem. Approach. We used our recent recordings from ‘small target motion detector’ neurons in the dragonfly brain to inspire the development of a closed-loop target detection and tracking algorithm. This model exploits facilitation, a slow build-up of response to targets which move along long, continuous trajectories, as seen in our electrophysiological data. To test performance in real-world conditions, we implemented this model on a robotic platform that uses active pursuit strategies based on insect behaviour. Main results. Our robot performs robustly in closed-loop pursuit of targets, despite a range of challenging conditions used in our experiments; low contrast targets, heavily cluttered environments and the presence of distracters. We show that the facilitation stage boosts responses to targets moving along continuous trajectories, improving contrast sensitivity and detection of small moving targets against textured backgrounds. Moreover, the temporal properties of facilitation play a useful role in handling vibration of the robotic platform. We also show that the adoption of feed-forward models which predict the sensory consequences of self-movement can significantly improve target detection during saccadic movements. Significance. Our results provide insight into the neuronal mechanisms that underlie biological target detection and selection (from a moving platform), as well as highlight the effectiveness of our bio-inspired algorithm in an artificial visual system.

An online model composition tool for system biology models.

Science.gov (United States)

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

2013-09-05

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

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.

Hair flow sensors: from bio-inspiration to bio-mimicking—a review

International Nuclear Information System (INIS)

Tao, Junliang; Yu, Xiong

2012-01-01

A great many living beings, such as aquatics and arthropods, are equipped with highly sensitive flow sensors to help them survive in challenging environments. These sensors are excellent sources of inspiration for developing application-driven artificial flow sensors with high sensitivity and performance. This paper reviews the bio-inspirations on flow sensing in nature and the bio-mimicking efforts to emulate such sensing mechanisms in recent years. The natural flow sensing systems in aquatics and arthropods are reviewed to highlight inspirations at multiple levels such as morphology, sensing mechanism and information processing. Biomimetic hair flow sensors based on different sensing mechanisms and fabrication technologies are also reviewed to capture the recent accomplishments and to point out areas where further progress is necessary. Biomimetic flow sensors are still in their early stages. Further efforts are required to unveil the sensing mechanisms in the natural biological systems and to achieve multi-level bio-mimicking of the natural system to develop their artificial counterparts. (topical review)

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

Science.gov (United States)

Rama, S. Kalyana

2018-06-01

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

Three-Dimensional-Printing of Bio-Inspired Composites

Science.gov (United States)

Xiang Gu, Grace; Su, Isabelle; Sharma, Shruti; Voros, Jamie L.; Qin, Zhao; Buehler, Markus J.

2016-01-01

Optimized for millions of years, natural materials often outperform synthetic materials due to their hierarchical structures and multifunctional abilities. They usually feature a complex architecture that consists of simple building blocks. Indeed, many natural materials such as bone, nacre, hair, and spider silk, have outstanding material properties, making them applicable to engineering applications that may require both mechanical resilience and environmental compatibility. However, such natural materials are very difficult to harvest in bulk, and may be toxic in the way they occur naturally, and therefore, it is critical to use alternative methods to fabricate materials that have material functions similar to material function as their natural counterparts for large-scale applications. Recent progress in additive manufacturing, especially the ability to print multiple materials at upper micrometer resolution, has given researchers an excellent instrument to design and reconstruct natural-inspired materials. The most advanced 3D-printer can now be used to manufacture samples to emulate their geometry and material composition with high fidelity. Its capabilities, in combination with computational modeling, have provided us even more opportunities for designing, optimizing, and testing the function of composite materials, in order to achieve composites of high mechanical resilience and reliability. In this review article, we focus on the advanced material properties of several multifunctional biological materials and discuss how the advanced 3D-printing techniques can be used to mimic their architectures and functions. Lastly, we discuss the limitations of 3D-printing, suggest possible future developments, and discuss applications using bio-inspired materials as a tool in bioengineering and other fields. PMID:26747791

Three-Dimensional-Printing of Bio-Inspired Composites.

Science.gov (United States)

Xiang Gu, Grace; Su, Isabelle; Sharma, Shruti; Voros, Jamie L; Qin, Zhao; Buehler, Markus J

2016-02-01

Optimized for millions of years, natural materials often outperform synthetic materials due to their hierarchical structures and multifunctional abilities. They usually feature a complex architecture that consists of simple building blocks. Indeed, many natural materials such as bone, nacre, hair, and spider silk, have outstanding material properties, making them applicable to engineering applications that may require both mechanical resilience and environmental compatibility. However, such natural materials are very difficult to harvest in bulk, and may be toxic in the way they occur naturally, and therefore, it is critical to use alternative methods to fabricate materials that have material functions similar to material function as their natural counterparts for large-scale applications. Recent progress in additive manufacturing, especially the ability to print multiple materials at upper micrometer resolution, has given researchers an excellent instrument to design and reconstruct natural-inspired materials. The most advanced 3D-printer can now be used to manufacture samples to emulate their geometry and material composition with high fidelity. Its capabilities, in combination with computational modeling, have provided us even more opportunities for designing, optimizing, and testing the function of composite materials, in order to achieve composites of high mechanical resilience and reliability. In this review article, we focus on the advanced material properties of several multifunctional biological materials and discuss how the advanced 3D-printing techniques can be used to mimic their architectures and functions. Lastly, we discuss the limitations of 3D-printing, suggest possible future developments, and discuss applications using bio-inspired materials as a tool in bioengineering and other fields.

Bio-inspired Miniature Suction Cups Actuated by Shape Memory Alloy

Directory of Open Access Journals (Sweden)

Hu Bing-shan

2010-02-01

Full Text Available Wall climbing robots using negative pressure suction always employ air pumps which have great noise and large volume. Two prototypes of bio-inspired miniature suction cup actuated by shape memory alloy (SMA are designed based on studying characteristics of biologic suction apparatuses, and the suction cups in this paper can be used as adhesion mechanisms for miniature wall climbing robots without air pumps. The first prototype with a two-way shape memory effect (TWSME extension TiNi spring imitates the piston structure of the stalked sucker; the second one actuated by a one way SMA actuator with a bias has a basic structure of stiff margin, guiding element, leader and elastic element. Analytical model of the second prototype is founded considering the constitutive model of the SMA actuator, the deflection of the thin elastic plate under compound load and the thermo-dynamic model of the sealed air cavity. Experiments are done to test their suction characteristics, and the analytical model of the second prototype is simulated on Matlab/simulink platform and validated by experiments.

Bio-inspired Miniature Suction Cups Actuated by Shape Memory Alloy

Directory of Open Access Journals (Sweden)

Hu Bing-Shan

2009-09-01

Full Text Available Wall climbing robots using negative pressure suction always employ air pumps which have great noise and large volume. Two prototypes of bio-inspired miniature suction cup actuated by shape memory alloy (SMA are designed based on studying characteristics of biologic suction apparatuses, and the suction cups in this paper can be used as adhesion mechanisms for miniature wall climbing robots without air pumps. The first prototype with a two-way shape memory effect (TWSME extension TiNi spring imitates the piston structure of the stalked sucker; the second one actuated by a one way SMA actuator with a bias has a basic structure of stiff margin, guiding element, leader and elastic element. Analytical model of the second prototype is founded considering the constitutive model of the SMA actuator, the deflection of the thin elastic plate under compound load and the thermo-dynamic model of the sealed air cavity. Experiments are done to test their suction characteristics, and the analytical model of the second prototype is simulated on Matlab/simulink platform and validated by experiments.

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

Integrating systems biology models and biomedical ontologies.

Science.gov (United States)

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

2011-08-11

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

Workshop Introduction: Systems Biology and Biological Models

Science.gov (United States)

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

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

Science.gov (United States)

Baston, Chiara; Ursino, Mauro

2015-01-01

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

A Biologically Inspired Computational Model of Basal Ganglia in Action Selection

Directory of Open Access Journals (Sweden)

Chiara Baston

2015-01-01

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

Research Collaboration Workshop for Women in Mathematical Biology

CERN Document Server

Miller, Laura

2017-01-01

Inspired by the Research Collaboration Workshop for Women in Mathematical Biology, this volume contains research and review articles that cover topics ranging from models of animal movement to the flow of blood cells in the embryonic heart. Hosted by the National Institute for Mathematics and Biological Synthesis (NIMBioS), the workshop brought together women working in biology and mathematics to form four research groups that encouraged multidisciplinary collaboration and lifetime connections in the STEM field. This volume introduces many of the topics from the workshop, including the aerodynamics of spider ballooning; sleep, circadian rhythms, and pain; blood flow regulation in the kidney; and the effects of antimicrobial therapy on gut microbiota and microbiota and Clostridium difficile. Perfect for students and researchers in mathematics and biology, the papers included in this volume offer an introductory glimpse at recent research in mathematical biology. .

Toward synthesizing executable models in biology.

Science.gov (United States)

Fisher, Jasmin; Piterman, Nir; Bodik, Rastislav

2014-01-01

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

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

International Nuclear Information System (INIS)

Gabbiani, F.

1987-01-01

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

3D-printing and mechanics of bio-inspired articulated and multi-material structures.

Science.gov (United States)

Porter, Michael M; Ravikumar, Nakul; Barthelat, Francois; Martini, Roberto

2017-09-01

3D-printing technologies allow researchers to build simplified physical models of complex biological systems to more easily investigate their mechanics. In recent years, a number of 3D-printed structures inspired by the dermal armors of various fishes have been developed to study their multiple mechanical functionalities, including flexible protection, improved hydrodynamics, body support, or tail prehensility. Natural fish armors are generally classified according to their shape, material and structural properties as elasmoid scales, ganoid scales, placoid scales, carapace scutes, or bony plates. Each type of dermal armor forms distinct articulation patterns that facilitate different functional advantages. In this paper, we highlight recent studies that developed 3D-printed structures not only to inform the design and application of some articulated and multi-material structures, but also to explain the mechanics of the natural biological systems they mimic. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

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...

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

CERN Document Server

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

1998-01-01

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

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].

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...

Towards Synthesizing Executable Models in Biology

Directory of Open Access Journals (Sweden)

Jasmin eFisher

2014-12-01

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

Quantum and classical dynamics in biologically inspired systems

International Nuclear Information System (INIS)

Guerreschi, G.

2012-01-01

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

Models for synthetic biology.

Science.gov (United States)

Kaznessis, Yiannis N

2007-11-06

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

Key pillars of data interoperability in Earth Sciences - INSPIRE and beyond

Science.gov (United States)

Tomas, Robert; Lutz, Michael

2013-04-01

The well-known heterogeneity and fragmentation of data models, formats and controlled vocabularies of environmental data limit potential data users from utilising the wealth of environmental information available today across Europe. The main aim of INSPIRE1 is to improve this situation and give users possibility to access, use and correctly interpret environmental data. Over the past years number of INSPIRE technical guidelines (TG) and implementing rules (IR) for interoperability have been developed, involving hundreds of domain experts from across Europe. The data interoperability specifications, which have been developed for all 34 INSPIRE spatial data themes2, are the central component of the TG and IR. Several of these themes are related to the earth sciences, e.g. geology (including hydrogeology, geophysics and geomorphology), mineral and energy resources, soil science, natural hazards, meteorology, oceanography, hydrology and land cover. The following main pillars for data interoperability and harmonisation have been identified during the development of the specifications: Conceptual data models describe the spatial objects and their properties and relationships for the different spatial data themes. To achieve cross-domain harmonization, the data models for all themes are based on a common modelling framework (the INSPIRE Generic Conceptual Model3) and managed in a common UML repository. Harmonised vocabularies (or code lists) are to be used in data exchange in order to overcome interoperability issues caused by heterogeneous free-text and/or multi-lingual content. Since a mapping to a harmonized vocabulary could be difficult, the INSPIRE data models typically allow the provision of more specific terms from local vocabularies in addition to the harmonized terms - utilizing either the extensibility options or additional terminological attributes. Encoding. Currently, specific XML profiles of the Geography Markup Language (GML) are promoted as the standard

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

Science.gov (United States)

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

2014-02-07

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

Inspiration from britain?

DEFF Research Database (Denmark)

Vagnby, Bo

2008-01-01

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

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

Directory of Open Access Journals (Sweden)

Pachelski Wojciech

2017-12-01

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

Human Brain inspired Artificial Intelligence & Developmental Robotics: A Review

Directory of Open Access Journals (Sweden)

Suresh Kumar

2017-06-01

Full Text Available Along with the developments in the field of the robotics, fascinating contributions and developments can be seen in the field of Artificial intelligence (AI. In this paper we will discuss about the developments is the field of artificial intelligence focusing learning algorithms inspired from the field of Biology, particularly large scale brain simulations, and developmental Psychology. We will focus on the emergence of the Developmental robotics and its significance in the field of AI.

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

Science.gov (United States)

Rao, Chen; Liu, Hao

2018-06-08

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

On the Cultivation of Students' Interests in Biology Teaching

Science.gov (United States)

Li, Yan

2011-01-01

This paper introduces the importance of middle school students' interests in learning biology. Considering the psychological characteristics of middle school students, this paper suggests several practical ways for inspiring students' interests in learning biology.

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

Science.gov (United States)

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

2015-08-21

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

Mesoscopic models of biological membranes

DEFF Research Database (Denmark)

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

2006-01-01

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

A Tony Thomas-Inspired Guide to INSPIRE

Energy Technology Data Exchange (ETDEWEB)

O' Connell, Heath B.; /Fermilab

2010-04-01

The SPIRES database was created in the late 1960s to catalogue the high energy physics preprints received by the SLAC Library. In the early 1990s it became the first database on the web and the first website outside of Europe. Although indispensible to the HEP community, its aging software infrastructure is becoming a serious liability. In a joint project involving CERN, DESY, Fermilab and SLAC, a new database, INSPIRE, is being created to replace SPIRES using CERN's modern, open-source Invenio database software. INSPIRE will maintain the content and functionality of SPIRES plus many new features. I describe this evolution from the birth of SPIRES to the current day, noting that the career of Tony Thomas spans this timeline.

A Tony Thomas-Inspired Guide to INSPIRE

International Nuclear Information System (INIS)

O'Connell, Heath B.

2010-01-01

The SPIRES database was created in the late 1960s to catalogue the high energy physics preprints received by the SLAC Library. In the early 1990s it became the first database on the web and the first website outside of Europe. Although indispensible to the HEP community, its aging software infrastructure is becoming a serious liability. In a joint project involving CERN, DESY, Fermilab and SLAC, a new database, INSPIRE, is being created to replace SPIRES using CERN's modern, open-source Invenio database software. INSPIRE will maintain the content and functionality of SPIRES plus many new features. I describe this evolution from the birth of SPIRES to the current day, noting that the career of Tony Thomas spans this timeline.

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

Science.gov (United States)

Manthey, Seth; Brewe, Eric

2013-01-01

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

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.

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....

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

International Nuclear Information System (INIS)

Wang Zhengzhi; Xu Yun; Gu Ping

2012-01-01

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

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...

Piecewise deterministic processes in biological models

CERN Document Server

Rudnicki, Ryszard

2017-01-01

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

Biological transportation networks: Modeling and simulation

KAUST Repository

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

2015-01-01

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

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.

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...

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.

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.

Performance assessment of bio-inspired systems: flow sensing MEMS hairs

International Nuclear Information System (INIS)

Droogendijk, H; Krijnen, G J M; Casas, J; Steinmann, T

2015-01-01

Despite vigorous growth in biomimetic design, the performance of man-made devices relative to their natural templates is still seldom quantified, a procedure which would however significantly increase the rigour of the biomimetic approach. We applied the ubiquitous engineering concept of a figure of merit (FoM) to MEMS flow sensors inspired by cricket filiform hairs. A well known mechanical model of a hair is refined and tailored to this task. Five criteria of varying importance in the biological and engineering fields are computed: responsivity, power transfer, power efficiency, response time and detection threshold. We selected the metrics response time and detection threshold for building the FoM to capture the performance in a single number. Crickets outperform actual MEMS on all criteria for a large range of flow frequencies. Our approach enables us to propose several improvements for MEMS hair-sensor design. (paper)

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

Science.gov (United States)

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

2011-07-01

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

Combining supramolecular chemistry with biology

NARCIS (Netherlands)

Uhlenheuer, D.A.; Petkau - Milroy, K.; Brunsveld, L.

2010-01-01

Supramolecular chemistry has primarily found its inspiration in biological molecules, such as proteins and lipids, and their interactions. Currently the supramolecular assembly of designed compounds can be controlled to great extent. This provides the opportunity to combine these synthetic

Kinds of inspiration in interaction design

DEFF Research Database (Denmark)

Halskov, Kim

2010-01-01

In this paper, we explore the role of sources of inspiration in interaction design. We identify four strategies for relating sources of inspiration to emerging ideas: selection; adaptation; translation; and combination. As our starting point, we argue that sources of inspiration are a form...... of knowledge crucial to creativity. Our research is based on empirical findings arising from the use of Inspiration Card Workshops, which are collaborative design events in which domain and technology insight are combined to create design concepts. In addition to the systematically introduced sources...... of inspiration that form part of the workshop format, a number of spontaneous sources of inspiration emerged during these workshops....

Nature-Inspired Cognitive Evolution to Play MS. Pac-Man

Science.gov (United States)

Tan, Tse Guan; Teo, Jason; Anthony, Patricia

Recent developments in nature-inspired computation have heightened the need for research into the three main areas of scientific, engineering and industrial applications. Some approaches have reported that it is able to solve dynamic problems and very useful for improving the performance of various complex systems. So far however, there has been little discussion about the effectiveness of the application of these models to computer and video games in particular. The focus of this research is to explore the hybridization of nature-inspired computation methods for optimization of neural network-based cognition in video games, in this case the combination of a neural network with an evolutionary algorithm. In essence, a neural network is an attempt to mimic the extremely complex human brain system, which is building an artificial brain that is able to self-learn intelligently. On the other hand, an evolutionary algorithm is to simulate the biological evolutionary processes that evolve potential solutions in order to solve the problems or tasks by applying the genetic operators such as crossover, mutation and selection into the solutions. This paper investigates the abilities of Evolution Strategies (ES) to evolve feed-forward artificial neural network's internal parameters (i.e. weight and bias values) for automatically generating Ms. Pac-man controllers. The main objective of this game is to clear a maze of dots while avoiding the ghosts and to achieve the highest possible score. The experimental results show that an ES-based system can be successfully applied to automatically generate artificial intelligence for a complex, dynamic and highly stochastic video game environment.

Bio-Inspired Design and Kinematic Analysis of Dung Beetle-Like Legs

DEFF Research Database (Denmark)

Aditya, Sai Krishna Venkata; Ignasov, Jevgeni; Filonenko, Konstantin

2017-01-01

The African dung beetle Scarabaeus galenus can use its front legs to walk and manipulate or form a dung ball. The interesting multifunctional legs have not been fully investigated or even used as inspiration for robot leg design. Thus, in this paper, we present the development of real dung beetle......-like front legs based on biological investigation. As a result, each leg consists of three main segments which were built using 3D printing. The segments were combined with in total four active DOFs in order to mimic locomotion and object manipulation of the beetle. Kinematics analysis of the leg was also...... performed to identify its workspace as well as to design its trajectory. To this end, the study contributes not only novel multifunctional robotic legs but also the methodology of the bio-inspired leg design....

Proprioceptive Feedback through a Neuromorphic Muscle Spindle Model

Directory of Open Access Journals (Sweden)

Lorenzo Vannucci

2017-06-01

Full Text Available Connecting biologically inspired neural simulations to physical or simulated embodiments can be useful both in robotics, for the development of a new kind of bio-inspired controllers, and in neuroscience, to test detailed brain models in complete action-perception loops. The aim of this work is to develop a fully spike-based, biologically inspired mechanism for the translation of proprioceptive feedback. The translation is achieved by implementing a computational model of neural activity of type Ia and type II afferent fibers of muscle spindles, the primary source of proprioceptive information, which, in mammals is regulated through fusimotor activation and provides necessary adjustments during voluntary muscle contractions. As such, both static and dynamic γ-motoneurons activities are taken into account in the proposed model. Information from the actual proprioceptive sensors (i.e., motor encoders is then used to simulate the spindle contraction and relaxation, and therefore drive the neural activity. To assess the feasibility of this approach, the model is implemented on the NEST spiking neural network simulator and on the SpiNNaker neuromorphic hardware platform and tested on simulated and physical robotic platforms. The results demonstrate that the model can be used in both simulated and real-time robotic applications to translate encoder values into a biologically plausible neural activity. Thus, this model provides a completely spike-based building block, suitable for neuromorphic platforms, that will enable the development of sensory-motor closed loops which could include neural simulations of areas of the central nervous system or of low-level reflexes.

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.

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.

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.

Dielectric elastomer actuators for octopus inspired suction cups.

Science.gov (United States)

Follador, M; Tramacere, F; Mazzolai, B

2014-09-25

Suction cups are often found in nature as attachment strategy in water. Nevertheless, the application of the artificial counterpart is limited by the dimension of the actuators and their usability in wet conditions. A novel design for the development of a suction cup inspired by octopus suckers is presented. The main focus of this research was on the modelling and characterization of the actuation unit, and a first prototype of the suction cup was realized as a proof of concept. The actuation of the suction cup is based on dielectric elastomer actuators. The presented device works in a wet environment, has an integrated actuation system, and is soft. The dimensions of the artificial suction cups are comparable to proximal octopus suckers, and the attachment mechanism is similar to the biological counterpart. The design approach proposed for the actuator allows the definition of the parameters for its development and for obtaining a desired pressure in water. The fabricated actuator is able to produce up to 6 kPa of pressure in water, reaching the maximum pressure in less than 300 ms.

Dielectric elastomer actuators for octopus inspired suction cups

International Nuclear Information System (INIS)

Follador, M; Tramacere, F; Mazzolai, B

2014-01-01

Suction cups are often found in nature as attachment strategy in water. Nevertheless, the application of the artificial counterpart is limited by the dimension of the actuators and their usability in wet conditions. A novel design for the development of a suction cup inspired by octopus suckers is presented. The main focus of this research was on the modelling and characterization of the actuation unit, and a first prototype of the suction cup was realized as a proof of concept. The actuation of the suction cup is based on dielectric elastomer actuators. The presented device works in a wet environment, has an integrated actuation system, and is soft. The dimensions of the artificial suction cups are comparable to proximal octopus suckers, and the attachment mechanism is similar to the biological counterpart. The design approach proposed for the actuator allows the definition of the parameters for its development and for obtaining a desired pressure in water. The fabricated actuator is able to produce up to 6 kPa of pressure in water, reaching the maximum pressure in less than 300 ms. (paper)

Sensitivity analysis approaches applied to systems biology models.

Science.gov (United States)

Zi, Z

2011-11-01

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

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…

Bio-inspired computation in telecommunications

CERN Document Server

Yang, Xin-She; Ting, TO

2015-01-01

Bio-inspired computation, especially those based on swarm intelligence, has become increasingly popular in the last decade. Bio-Inspired Computation in Telecommunications reviews the latest developments in bio-inspired computation from both theory and application as they relate to telecommunications and image processing, providing a complete resource that analyzes and discusses the latest and future trends in research directions. Written by recognized experts, this is a must-have guide for researchers, telecommunication engineers, computer scientists and PhD students.

Ranked retrieval of Computational Biology models.

Science.gov (United States)

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

2010-08-11

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

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.

Structure–function relationship of skeletal muscle provides inspiration for design of new artificial muscle

International Nuclear Information System (INIS)

Gao, Yingxin; Zhang, Chi

2015-01-01

A variety of actuator technologies have been developed to mimic biological skeletal muscle that generates force in a controlled manner. Force generation process of skeletal muscle involves complicated biophysical and biochemical mechanisms; therefore, it is impossible to replace biological muscle. In biological skeletal muscle tissue, the force generation of a muscle depends not only on the force generation capacity of the muscle fiber, but also on many other important factors, including muscle fiber type, motor unit recruitment, architecture, structure and morphology of skeletal muscle, all of which have significant impact on the force generation of the whole muscle or force transmission from muscle fibers to the tendon. Such factors have often been overlooked, but can be incorporated in artificial muscle design, especially with the discovery of new smart materials and the development of innovative fabrication and manufacturing technologies. A better understanding of the physiology and structure–function relationship of skeletal muscle will therefore benefit the artificial muscle design. In this paper, factors that affect muscle force generation are reviewed. Mathematical models used to model the structure–function relationship of skeletal muscle are reviewed and discussed. We hope the review will provide inspiration for the design of a new generation of artificial muscle by incorporating the structure–function relationship of skeletal muscle into the design of artificial muscle. (topical review)

Structure-function relationship of skeletal muscle provides inspiration for design of new artificial muscle

Science.gov (United States)

Gao, Yingxin; Zhang, Chi

2015-03-01

A variety of actuator technologies have been developed to mimic biological skeletal muscle that generates force in a controlled manner. Force generation process of skeletal muscle involves complicated biophysical and biochemical mechanisms; therefore, it is impossible to replace biological muscle. In biological skeletal muscle tissue, the force generation of a muscle depends not only on the force generation capacity of the muscle fiber, but also on many other important factors, including muscle fiber type, motor unit recruitment, architecture, structure and morphology of skeletal muscle, all of which have significant impact on the force generation of the whole muscle or force transmission from muscle fibers to the tendon. Such factors have often been overlooked, but can be incorporated in artificial muscle design, especially with the discovery of new smart materials and the development of innovative fabrication and manufacturing technologies. A better understanding of the physiology and structure-function relationship of skeletal muscle will therefore benefit the artificial muscle design. In this paper, factors that affect muscle force generation are reviewed. Mathematical models used to model the structure-function relationship of skeletal muscle are reviewed and discussed. We hope the review will provide inspiration for the design of a new generation of artificial muscle by incorporating the structure-function relationship of skeletal muscle into the design of artificial muscle.

Molecular machines with bio-inspired mechanisms.

Science.gov (United States)

Zhang, Liang; Marcos, Vanesa; Leigh, David A

2018-02-26

The widespread use of molecular-level motion in key natural processes suggests that great rewards could come from bridging the gap between the present generation of synthetic molecular machines-which by and large function as switches-and the machines of the macroscopic world, which utilize the synchronized behavior of integrated components to perform more sophisticated tasks than is possible with any individual switch. Should we try to make molecular machines of greater complexity by trying to mimic machines from the macroscopic world or instead apply unfamiliar (and no doubt have to discover or invent currently unknown) mechanisms utilized by biological machines? Here we try to answer that question by exploring some of the advances made to date using bio-inspired machine mechanisms.

INSPIRE 2012 da Istanbul a Firenze

Directory of Open Access Journals (Sweden)

Mauro Salvemini

2012-09-01

Full Text Available DURING THE CONFERENCE HELD IN  ISTANBUL IN  2012 INSPIRE  THE  NEWS  THAT  MOST  IMPRESSED ITALIANS PRESENT,  EVEN THOSE IN THE PUBLIC ADMINISTRATION , WAS THAT THE NEXT  INSPIRE CONFERENCE WILL TAKE PLACE IN  FLORENCEDurante la conferenza INSPIRE 2012 svoltasi ad Istanbul la notizia che ha maggiormente colpito gli italiani presenti, anche quelli della pubblica amministrazione , è stata che la prossima Conferenza INSPIRE si svolgerà a Firenze dal 23 al 27 giugno 2013.

INSPIRE 2012 da Istanbul a Firenze

Directory of Open Access Journals (Sweden)

Mauro Salvemini

2012-09-01

Full Text Available DURING THE CONFERENCE HELD IN  ISTANBUL IN  2012 INSPIRE  THE  NEWS  THAT  MOST  IMPRESSED ITALIANS PRESENT,  EVEN THOSE IN THE PUBLIC ADMINISTRATION , WAS THAT THE NEXT  INSPIRE CONFERENCE WILL TAKE PLACE IN  FLORENCE Durante la conferenza INSPIRE 2012 svoltasi ad Istanbul la notizia che ha maggiormente colpito gli italiani presenti, anche quelli della pubblica amministrazione , è stata che la prossima Conferenza INSPIRE si svolgerà a Firenze dal 23 al 27 giugno 2013.

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

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Blenkinsop, Thomas; Ellis, Jennifer

2017-04-01

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

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.

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

Science.gov (United States)

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

2017-02-17

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

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…

Peristaltic Wave Locomotion and Shape Morphing with a Millipede Inspired System

Science.gov (United States)

Spinello, Davide; Fattahi, Javad S.

2017-08-01

We present the mechanical model of a bio-inspired deformable system, modeled as a Timoshenko beam, which is coupled to a substrate by a system of distributed elements. The locomotion action is inspired by the coordinated motion of coupling elements that mimic the legs of millipedes and centipedes, whose leg-to-ground contact can be described as a peristaltic displacement wave. The multi-legged structure is crucial in providing redundancy and robustness in the interaction with unstructured environments and terrains. A Lagrangian approach is used to derive the governing equations of the system that couple locomotion and shape morphing. Features and limitations of the model are illustrated with numerical simulations.

Nanofluidics in two-dimensional layered materials: inspirations from nature.

Science.gov (United States)

Gao, Jun; Feng, Yaping; Guo, Wei; Jiang, Lei

2017-08-29

With the advance of chemistry, materials science, and nanotechnology, significant progress has been achieved in the design and application of synthetic nanofluidic devices and materials, mimicking the gating, rectifying, and adaptive functions of biological ion channels. Fundamental physics and chemistry behind these novel transport phenomena on the nanoscale have been explored in depth on single-pore platforms. However, toward real-world applications, one major challenge is to extrapolate these single-pore devices into macroscopic materials. Recently, inspired partially by the layered microstructure of nacre, the material design and large-scale integration of artificial nanofluidic devices have stepped into a completely new stage, termed 2D nanofluidics. Unique advantages of the 2D layered materials have been found, such as facile and scalable fabrication, high flux, efficient chemical modification, tunable channel size, etc. These features enable wide applications in, for example, biomimetic ion transport manipulation, molecular sieving, water treatment, and nanofluidic energy conversion and storage. This review highlights the recent progress, current challenges, and future perspectives in this emerging research field of "2D nanofluidics", with emphasis on the thought of bio-inspiration.

Quantum-Inspired Multidirectional Associative Memory With a Self-Convergent Iterative Learning.

Science.gov (United States)

Masuyama, Naoki; Loo, Chu Kiong; Seera, Manjeevan; Kubota, Naoyuki

2018-04-01

Quantum-inspired computing is an emerging research area, which has significantly improved the capabilities of conventional algorithms. In general, quantum-inspired hopfield associative memory (QHAM) has demonstrated quantum information processing in neural structures. This has resulted in an exponential increase in storage capacity while explaining the extensive memory, and it has the potential to illustrate the dynamics of neurons in the human brain when viewed from quantum mechanics perspective although the application of QHAM is limited as an autoassociation. We introduce a quantum-inspired multidirectional associative memory (QMAM) with a one-shot learning model, and QMAM with a self-convergent iterative learning model (IQMAM) based on QHAM in this paper. The self-convergent iterative learning enables the network to progressively develop a resonance state, from inputs to outputs. The simulation experiments demonstrate the advantages of QMAM and IQMAM, especially the stability to recall reliability.

Innovation Inspired by Nature: Capabilities, Potentials and Challenges

Science.gov (United States)

Bar-Cohen, Yoseph

2012-01-01

Through evolution, nature came up with many effective solutions to its challenges and continually improving them. By mimicking, coping and being inspired, humans have been using Nature's solutions to address their own challenges. In recent years, the implementation of nature's capabilities has intensified with our growing understanding of the various biological and nastic mechanisms and processes. Successes include even the making of humanlike robots that perform such lifelike tasks as walking, talking, making eye-contact, interpreting speech and facial expressions, as well as many other humanlike functions. Generally, once humans are able to implement a function then, thru rapid advances in technology, capabilities are developed that can significantly exceed the original source of inspiration in Nature. Examples include flight where there is no species that can fly as high, carry so much mass, has so large dimensions and fly so fast, and operate at as such extreme conditions as our aircraft and other aerospace systems. However, using the capabilities of today's technology, there are many challenges that are not feasible to address in mimicking characteristics of species and plants. In this manuscript, state-of-the-art of biomimetic capabilities, potentials and challenges are reviewed.

Plant-inspired adaptive structures and materials for morphing and actuation: a review.

Science.gov (United States)

Li, Suyi; Wang, K W

2016-12-20

Plants exhibit a variety of reversible motions, from the slow opening of pine cones to the impulsive closing of Venus flytrap leaves. These motions are achieved without muscles and they have inspired a wide spectrum of engineered materials and structures. This review summarizes the recent developments of plant-inspired adaptive structures and materials for morphing and actuation. We begin with a brief overview of the actuation strategies and physiological features associated to these plant movements, showing that different combinations of these strategies and features can lead to motions with different deformation characteristics and response speeds. Then we offer a comprehensive survey of the plant-inspired morphing and actuation systems, including pressurized cellular structures, osmotic actuation, anisotropic hygroscopic materials, and bistable systems for rapid movements. Although these engineered systems are vastly different in terms of their size scales and intended applications, their working principles are all related to the actuation strategies and physiological features in plants. This review is to promote future cross-disciplinary studies between plant biology and engineering, which can foster new solutions for many applications such as morphing airframes, soft robotics and kinetic architectures.

Molecular biology of mycoplasmas: from the minimum cell concept to the artificial cell.

Science.gov (United States)

Cordova, Caio M M; Hoeltgebaum, Daniela L; Machado, Laís D P N; Santos, Larissa Dos

2016-01-01

Mycoplasmas are a large group of bacteria, sorted into different genera in the Mollicutes class, whose main characteristic in common, besides the small genome, is the absence of cell wall. They are considered cellular and molecular biology study models. We present an updated review of the molecular biology of these model microorganisms and the development of replicative vectors for the transformation of mycoplasmas. Synthetic biology studies inspired by these pioneering works became possible and won the attention of the mainstream media. For the first time, an artificial genome was synthesized (a minimal genome produced from consensus sequences obtained from mycoplasmas). For the first time, a functional artificial cell has been constructed by introducing a genome completely synthesized within a cell envelope of a mycoplasma obtained by transformation techniques. Therefore, this article offers an updated insight to the state of the art of these peculiar organisms' molecular biology.

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.

Anti-fouling properties of microstructured surfaces bio-inspired by rice leaves and butterfly wings.

Science.gov (United States)

Bixler, Gregory D; Theiss, Andrew; Bhushan, Bharat; Lee, Stephen C

2014-04-01

Material scientists often look to biology for new engineering solutions to materials science problems. For example, unique surface characteristics of rice leaves and butterfly wings combine the shark skin (antifouling) and lotus leaf (self-cleaning) effects, producing the so-called rice and butterfly wing effect. In this paper, we study antifouling properties of four microstructured surfaces inspired by rice leaves and fabricated with photolithography and hot embossing techniques. Anti-biofouling effectiveness is determined with bioassays using Escherichia coli whilst inorganic fouling with simulated dirt particles. Antifouling data are presented to understand the role of surface geometrical features resistance to fouling. Conceptual modeling provides design guidance when developing novel antifouling surfaces for applications in the medical, marine, and industrial fields. Copyright © 2013 Elsevier Inc. All rights reserved.

Genome-scale biological models for industrial microbial systems.

Science.gov (United States)

Xu, Nan; Ye, Chao; Liu, Liming

2018-04-01

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

Communication analysis for feedback control of civil infrastructure using cochlea-inspired sensing nodes

Science.gov (United States)

Peckens, Courtney A.; Cook, Ireana; Lynch, Jerome P.

2016-04-01

Wireless sensor networks (WSNs) have emerged as a reliable, low-cost alternative to the traditional wired sensing paradigm. While such networks have made significant progress in the field of structural monitoring, significantly less development has occurred for feedback control applications. Previous work in WSNs for feedback control has highlighted many of the challenges of using this technology including latency in the wireless communication channel and computational inundation at the individual sensing nodes. This work seeks to overcome some of those challenges by drawing inspiration from the real-time sensing and control techniques employed by the biological central nervous system and in particular the mammalian cochlea. A novel bio-inspired wireless sensor node was developed that employs analog filtering techniques to perform time-frequency decomposition of a sensor signal, thus encompassing the functionality of the cochlea. The node then utilizes asynchronous sampling of the filtered signal to compress the signal prior to communication. This bio-inspired sensing architecture is extended to a feedback control application in order to overcome the traditional challenges currently faced by wireless control. In doing this, however, the network experiences high bandwidths of low-significance information exchange between nodes, resulting in some lost data. This study considers the impact of this lost data on the control capabilities of the bio-inspired control architecture and finds that it does not significantly impact the effectiveness of control.

Stingray-inspired robot with simply actuated intermediate motion

Science.gov (United States)

Neely, Lincoln; Gaiennie, Jack; Noble, Nick; Erickson, Jonathan C.

2016-04-01

Batoids, or rays, utilize unique forms of locomotion that may offer more efficient techniques of motorized propulsion in various marine environments. We present a novel biomimetic engineering design and assembly of a stingray-inspired robot swimmer. The robots locomotion mimics the Dasyatis americana, or southern stingray, whose distinction among rays is its intermediate motion, characterized by sweeping strokes that propagate between 1/2-1 wavelength of the fin profile in the posterior direction. Though oscillatory ( wavelengths) ray-based robots have been created, this project demonstrates new engineering possibilities in what is, to the best of our knowledge, the first intermediately propelled batoid-based robot. The robots fins were made of silicone rubber, cast in a 3-D printed mold, with wingspan of 42 cm (1/2 - 1/5 scale for males and females, respectively, scale of model organism). Two anteriorly placed servomotors per fin were used, all controlled by one wirelessly enabled Arduino microcontroller. Each servomotor oscillated a flexible rod with cylindrical joint, whose frequency, speed, and front-back phase delay were user-programmed over wireless connection. During free-swimming tests, the fin profile developed about 0.8 wavelength, qualifying for successful mimicry of its biological inspiration. The robot satisfactorily maintained straight-line motion, reaching average peak velocity of 9.4+/-1.0 cm/s (0.27-0.03 body lengths/second) at its optimum flapping frequency of 1.4 Hz. This is in the same order of magnitude of speed normalized to body length achieved by others in two recent batoid-based projects. In summary, our robot performed intermediate stingray locomotion with relatively fewer components, which reveals robust potential for innovation of the simple intermediate batoid-based robot swimmer.

Design and control of a bio-inspired soft wearable robotic device for ankle–foot rehabilitation

International Nuclear Information System (INIS)

Park, Yong-Lae; Chen, Bor-rong; Pérez-Arancibia, Néstor O; Young, Diana; Wood, Robert J; Nagpal, Radhika; Stirling, Leia; Goldfield, Eugene C

2014-01-01

We describe the design and control of a wearable robotic device powered by pneumatic artificial muscle actuators for use in ankle–foot rehabilitation. The design is inspired by the biological musculoskeletal system of the human foot and lower leg, mimicking the morphology and the functionality of the biological muscle–tendon–ligament structure. A key feature of the device is its soft structure that provides active assistance without restricting natural degrees of freedom at the ankle joint. Four pneumatic artificial muscles assist dorsiflexion and plantarflexion as well as inversion and eversion. The prototype is also equipped with various embedded sensors for gait pattern analysis. For the subject tested, the prototype is capable of generating an ankle range of motion of 27° (14° dorsiflexion and 13° plantarflexion). The controllability of the system is experimentally demonstrated using a linear time-invariant (LTI) controller. The controller is found using an identified LTI model of the system, resulting from the interaction of the soft orthotic device with a human leg, and model-based classical control design techniques. The suitability of the proposed control strategy is demonstrated with several angle-reference following experiments. (paper)

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.

Unified Deep Learning Architecture for Modeling Biology Sequence.

Science.gov (United States)

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

2017-10-09

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

Product and technology innovation: what can biomimicry inspire?

Science.gov (United States)

Lurie-Luke, Elena

2014-12-01

Biomimicry (bio- meaning life in Greek, and -mimesis, meaning to copy) is a growing field that seeks to interpolate natural biological mechanisms and structures into a wide range of applications. The rise of interest in biomimicry in recent years has provided a fertile ground for innovation. This review provides an eco-system based analysis of biomimicry inspired technology and product innovation. A multi-disciplinary framework has been developed to accomplish this analysis and the findings focus on the areas that have been most strikingly affected by the application of biomimicry and also highlight the emerging trends and opportunity areas. Copyright © 2014 Elsevier Inc. All rights reserved.

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...

La maturità di INSPIRE

Directory of Open Access Journals (Sweden)

Mauro Salvemini

2010-03-01

Full Text Available INPIRE's maturityThe INSPIRE Conference 2010 took place from 23 to 25 June 2010 in Kraków, Poland. On 22 June pre-conference workshops have been organized. The theme of this year’s edition has been "INSPIRE as a Framework for Cooperation".The INSPIRE Conference has been organised through a series of plenary sessions addressing common policy issues, and parallel sessions focusing in particular on applications and implementations of SDIs, research issues and new and evolvingtechnologies and applications and poster presentations.

Agent-based modelling in synthetic biology.

Science.gov (United States)

Gorochowski, Thomas E

2016-11-30

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

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

International Nuclear Information System (INIS)

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

2013-01-01

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

Nature-inspired optimization algorithms

CERN Document Server

Yang, Xin-She

2014-01-01

Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning

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...

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....

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.

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.

Bio-Inspired Multi-Functional Drug Transport Design Concept and Simulations.

Science.gov (United States)

Pidaparti, Ramana M; Cartin, Charles; Su, Guoguang

2017-04-25

In this study, we developed a microdevice concept for drug/fluidic transport taking an inspiration from supramolecular motor found in biological cells. Specifically, idealized multi-functional design geometry (nozzle/diffuser/nozzle) was developed for (i) fluidic/particle transport; (ii) particle separation; and (iii) droplet generation. Several design simulations were conducted to demonstrate the working principles of the multi-functional device. The design simulations illustrate that the proposed design concept is feasible for multi-functionality. However, further experimentation and optimization studies are needed to fully evaluate the multifunctional device concept for multiple applications.

A biological compression model and its applications.

Science.gov (United States)

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

2011-01-01

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

Color encoding in biologically-inspired convolutional neural networks.

Science.gov (United States)

Rafegas, Ivet; Vanrell, Maria

2018-05-11

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

Systems Biology of the Fluxome

Directory of Open Access Journals (Sweden)

Miguel A. Aon

2015-07-01

Full Text Available The advent of high throughput -omics has made the accumulation of comprehensive data sets possible, consisting of changes in genes, transcripts, proteins and metabolites. Systems biology-inspired computational methods for translating metabolomics data into fluxomics provide a direct functional, dynamic readout of metabolic networks. When combined with appropriate experimental design, these methods deliver insightful knowledge about cellular function under diverse conditions. The use of computational models accounting for detailed kinetics and regulatory mechanisms allow us to unravel the control and regulatory properties of the fluxome under steady and time-dependent behaviors. This approach extends the analysis of complex systems from description to prediction, including control of complex dynamic behavior ranging from biological rhythms to catastrophic lethal arrhythmias. The powerful quantitative metabolomics-fluxomics approach will help our ability to engineer unicellular and multicellular organisms evolve from trial-and-error to a more predictable process, and from cells to organ and organisms.

Norsk inspiration til uddannelse og job

DEFF Research Database (Denmark)

Skovhus, Randi Boelskifte; Thomsen, Rie; Buhl, Rita

2017-01-01

Anmeldelse af bog om det norske fag Utdanningsvalg - inspiration til arbejde med uddannelse og job......Anmeldelse af bog om det norske fag Utdanningsvalg - inspiration til arbejde med uddannelse og job...

Feeling Is Believing: Inspiration Encourages Belief in God.

Science.gov (United States)

Critcher, Clayton R; Lee, Chan Jean

2018-05-01

Even without direct evidence of God's existence, about half of the world's population believes in God. Although previous research has found that people arrive at such beliefs intuitively instead of analytically, relatively little research has aimed to understand what experiences encourage or legitimate theistic belief systems. Using cross-cultural correlational and experimental methods, we investigated whether the experience of inspiration encourages a belief in God. Participants who dispositionally experience more inspiration, were randomly assigned to relive or have an inspirational experience, or reported such experiences to be more inspirational all showed stronger belief in God. These effects were specific to inspiration (instead of adjacent affective experiences) and a belief in God (instead of other empirically unverifiable claims). Being inspired by someone or something (but not inspired to do something) offers a spiritually transcendent experience that elevates belief in God, in part because it makes people feel connected to something beyond themselves.

Cellular potts models multiscale extensions and biological applications

CERN Document Server

Scianna, Marco

2013-01-01

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

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

Science.gov (United States)

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

2010-01-01

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

Unified data model for biological data

International Nuclear Information System (INIS)

Idrees, M.

2014-01-01

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

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

Science.gov (United States)

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

2015-01-01

Probabilistic models have gained widespread acceptance in the systems biology community as a useful way to represent complex biological systems. Such models are developed using existing knowledge of the structure and dynamics of the system, experimental observations, and inferences drawn from statistical analysis of empirical data. A key bottleneck in building such models is that some system variables cannot be measured experimentally. These variables are incorporated into the model as numerical parameters. Determining values of these parameters that justify existing experiments and provide reliable predictions when model simulations are performed is a key research problem. Using an agent-based model of the dynamics of acute inflammation, we demonstrate a novel parameter estimation algorithm by discovering the amount and schedule of doses of bacterial lipopolysaccharide that guarantee a set of observed clinical outcomes with high probability. We synthesized values of twenty-eight unknown parameters such that the parameterized model instantiated with these parameter values satisfies four specifications describing the dynamic behavior of the model. We have developed a new algorithmic technique for discovering parameters in complex stochastic models of biological systems given behavioral specifications written in a formal mathematical logic. Our algorithm uses Bayesian model checking, sequential hypothesis testing, and stochastic optimization to automatically synthesize parameters of probabilistic biological models.

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.

Mobile robots for localizing gas emission sources on landfill sites: is bio-inspiration the way to go?

Science.gov (United States)

Hernandez Bennetts, Victor; Lilienthal, Achim J; Neumann, Patrick P; Trincavelli, Marco

2011-01-01

Roboticists often take inspiration from animals for designing sensors, actuators, or algorithms that control the behavior of robots. Bio-inspiration is motivated with the uncanny ability of animals to solve complex tasks like recognizing and manipulating objects, walking on uneven terrains, or navigating to the source of an odor plume. In particular the task of tracking an odor plume up to its source has nearly exclusively been addressed using biologically inspired algorithms and robots have been developed, for example, to mimic the behavior of moths, dung beetles, or lobsters. In this paper we argue that biomimetic approaches to gas source localization are of limited use, primarily because animals differ fundamentally in their sensing and actuation capabilities from state-of-the-art gas-sensitive mobile robots. To support our claim, we compare actuation and chemical sensing available to mobile robots to the corresponding capabilities of moths. We further characterize airflow and chemosensor measurements obtained with three different robot platforms (two wheeled robots and one flying micro-drone) in four prototypical environments and show that the assumption of a constant and unidirectional airflow, which is the basis of many gas source localization approaches, is usually far from being valid. This analysis should help to identify how underlying principles, which govern the gas source tracking behavior of animals, can be usefully "translated" into gas source localization approaches that fully take into account the capabilities of mobile robots. We also describe the requirements for a reference application, monitoring of gas emissions at landfill sites with mobile robots, and discuss an engineered gas source localization approach based on statistics as an alternative to biologically inspired algorithms.

Mobile Robots for Localizing Gas Emission Sources on Landfill Sites: Is Bio-Inspiration the Way to Go?

Directory of Open Access Journals (Sweden)

Victor eHernandez Bennetts

2012-01-01

Full Text Available Roboticists often take inspiration from animals for designing sensors, actuators or algorithms that control the behaviour of robots. Bio-inspiration is motivated with the uncanny ability of animals to solve complex tasks like recognizing and manipulating objects, walking on uneven terrains, or navigating to the source of an odour plume. In particular the task of tracking an odour plume up to its source has nearly exclusively been addressed using biologically inspired algorithms and robots have been developed, for example, to mimic the behaviour of moths, dungbeetles, or lobsters. In this paper we argue that biomimetic approaches to gas source localization are of limited use, primarily because animals differ fundamentally in their sensing and actuation capabilities from state-of-the-art gas-sensitive mobile robots. To support our claim, we compare actuation and chemical sensing available to mobile robots to the corresponding capabilities of moths. We further characterize airflow and chemosensor measurements obtained with three different robot platforms (two wheeled robots and one flying micro drone in four prototypical environments and show that the assumption of a constant and unidirectional airflow, which is at the basis of many gas source localization approaches, is usually far from being valid. This analysis should help to identify how underlying principles, which govern the gas source tracking behaviour of animals, can be usefully translated into gas source localization approaches that fully take into account the capabilities of mobile robots. We also describe the requirements for a reference application, monitoring of gas emissions at landfill sites with mobile robots, and discuss an engineered gas source localization approach based on statistics as an alternative to biologically-inspired algorithms.

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.

Bio-inspired engineering of cell- and virus-like nanoparticles for drug delivery.

Science.gov (United States)

Parodi, Alessandro; Molinaro, Roberto; Sushnitha, Manuela; Evangelopoulos, Michael; Martinez, Jonathan O; Arrighetti, Noemi; Corbo, Claudia; Tasciotti, Ennio

2017-12-01

The engineering of future generations of nanodelivery systems aims at the creation of multifunctional vectors endowed with improved circulation, enhanced targeting and responsiveness to the biological environment. Moving past purely bio-inert systems, researchers have begun to create nanoparticles capable of proactively interacting with the biology of the body. Nature offers a wide-range of sources of inspiration for the synthesis of more effective drug delivery platforms. Because the nano-bio-interface is the key driver of nanoparticle behavior and function, the modification of nanoparticles' surfaces allows the transfer of biological properties to synthetic carriers by imparting them with a biological identity. Modulation of these surface characteristics governs nanoparticle interactions with the biological barriers they encounter. Building off these observations, we provide here an overview of virus- and cell-derived biomimetic delivery systems that combine the intrinsic hallmarks of biological membranes with the delivery capabilities of synthetic carriers. We describe the features and properties of biomimetic delivery systems, recapitulating the distinctive traits and functions of viruses, exosomes, platelets, red and white blood cells. By mimicking these biological entities, we will learn how to more efficiently interact with the human body and refine our ability to negotiate with the biological barriers that impair the therapeutic efficacy of nanoparticles. Copyright © 2017. Published by Elsevier Ltd.

Network science of biological systems at different scales: A review

Science.gov (United States)

Gosak, Marko; Markovič, Rene; Dolenšek, Jurij; Slak Rupnik, Marjan; Marhl, Marko; Stožer, Andraž; Perc, Matjaž

2018-03-01

Network science is today established as a backbone for description of structure and function of various physical, chemical, biological, technological, and social systems. Here we review recent advances in the study of complex biological systems that were inspired and enabled by methods of network science. First, we present

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.

Biotemplating of Luffa cylindrica sponges to self-supporting hierarchical zeolite macrostructures for bio-inspired structured catalytic reactors

International Nuclear Information System (INIS)

Zampieri, Alessandro; Mabande, Godwin T.P.; Selvam, Thangaraj; Schwieger, Wilhelm; Rudolph, Alexander; Hermann, Ralph; Sieber, Heino; Greil, Peter

2006-01-01

Biomorphic self-supporting MFI-type zeolite frameworks with hierarchical porosity and complex architecture were prepared using a 2-step (in-situ seeding and secondary crystal growth) hydrothermal synthesis in the presence of a biological template (Luffa sponge), employed as a macroscale sacrificial structure builder. The bio-inspired zeolitic replica inherited the complex spongy morphology and the intricate open-porous architecture of the biotemplate. Moreover, it exhibited reasonable mechanical stability in order to study the applicability of the biomorphic catalyst in a technical catalytic process. A bio-inspired catalytic reactor utilising the self-supporting ZSM-5 scaffold in monolithic configuration was developed in order to test the catalytic performance of the material

2D neural hardware versus 3D biological ones

Energy Technology Data Exchange (ETDEWEB)

Beiu, V.

1998-12-31

This paper will present important limitations of hardware neural nets as opposed to biological neural nets (i.e. the real ones). The author starts by discussing neural structures and their biological inspirations, while mentioning the simplifications leading to artificial neural nets. Going further, the focus will be on hardware constraints. The author will present recent results for three different alternatives of implementing neural networks: digital, threshold gate, and analog, while the area and the delay will be related to neurons' fan-in and weights' precision. Based on all of these, it will be shown why hardware implementations cannot cope with their biological inspiration with respect to their power of computation: the mapping onto silicon lacking the third dimension of biological nets. This translates into reduced fan-in, and leads to reduced precision. The main conclusion is that one is faced with the following alternatives: (1) try to cope with the limitations imposed by silicon, by speeding up the computation of the elementary silicon neurons; (2) investigate solutions which would allow one to use the third dimension, e.g. using optical interconnections.

Testing a Firefly-Inspired Synchronization Algorithm in a Complex Wireless Sensor Network.

Science.gov (United States)

Hao, Chuangbo; Song, Ping; Yang, Cheng; Liu, Xiongjun

2017-03-08

Data acquisition is the foundation of soft sensor and data fusion. Distributed data acquisition and its synchronization are the important technologies to ensure the accuracy of soft sensors. As a research topic in bionic science, the firefly-inspired algorithm has attracted widespread attention as a new synchronization method. Aiming at reducing the design difficulty of firefly-inspired synchronization algorithms for Wireless Sensor Networks (WSNs) with complex topologies, this paper presents a firefly-inspired synchronization algorithm based on a multiscale discrete phase model that can optimize the performance tradeoff between the network scalability and synchronization capability in a complex wireless sensor network. The synchronization process can be regarded as a Markov state transition, which ensures the stability of this algorithm. Compared with the Miroll and Steven model and Reachback Firefly Algorithm, the proposed algorithm obtains better stability and performance. Finally, its practicality has been experimentally confirmed using 30 nodes in a real multi-hop topology with low quality links.

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

International Nuclear Information System (INIS)

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

2012-01-01

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

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

Science.gov (United States)

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

2017-01-01

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

Microgravity Fluids for Biology, Workshop

Science.gov (United States)

Griffin, DeVon; Kohl, Fred; Massa, Gioia D.; Motil, Brian; Parsons-Wingerter, Patricia; Quincy, Charles; Sato, Kevin; Singh, Bhim; Smith, Jeffrey D.; Wheeler, Raymond M.

2013-01-01

Microgravity Fluids for Biology represents an intersection of biology and fluid physics that present exciting research challenges to the Space Life and Physical Sciences Division. Solving and managing the transport processes and fluid mechanics in physiological and biological systems and processes are essential for future space exploration and colonization of space by humans. Adequate understanding of the underlying fluid physics and transport mechanisms will provide new, necessary insights and technologies for analyzing and designing biological systems critical to NASAs mission. To enable this mission, the fluid physics discipline needs to work to enhance the understanding of the influence of gravity on the scales and types of fluids (i.e., non-Newtonian) important to biology and life sciences. In turn, biomimetic, bio-inspired and synthetic biology applications based on physiology and biology can enrich the fluid mechanics and transport phenomena capabilities of the microgravity fluid physics community.

An Immune System Inspired Theory for Crime and Violence in Cities

Directory of Open Access Journals (Sweden)

Soumya Banerjee

2017-06-01

Full Text Available Crime is ubiquitous and has been around for millennia. Crime is analogous to a pathogenic infection and police response to it is similar to an immune response. The biological immune system is also engaged in an arms race with pathogens. We propose an immune system inspired theory of crime and violence in human societies, especially in large agglomerations like cities. In this work we suggest that an immune system inspired theory of crime can provide a new perspective on the dynamics of violence in societies. The competitive dynamics between police and criminals has similarities to how the immune system is involved in an arms race with invading pathogens. Cities have properties similar to biological organisms and in this theory the police and military forces would be the immune system that protects against detrimental internal and external forces. Our theory has implications for public policy: ranging from how much financial resource to invest in crime fighting, to optimal policing strategies, pre-placement of police, and number of police to be allocated to different cities. Our work can also be applied to other forms of violence in human societies (like terrorism and violence in other primate societies and eusocial insects. We hope this will be the first step towards a quantitative theory of violence and conflict in human societies. Ultimately we hope that this will help in designing smart and efficient cities that can scale and be sustainable despite population increase.

A survey of bio-inspired compliant legged robot designs

International Nuclear Information System (INIS)

Zhou Xiaodong; Bi Shusheng

2012-01-01

The roles of biological springs in vertebrate animals and their implementations in compliant legged robots offer significant advantages over the rigid legged ones in certain types of scenarios. A large number of robotics institutes have been attempting to work in conjunction with biologists and incorporated these principles into the design of biologically inspired robots. The motivation of this review is to investigate the most published compliant legged robots and categorize them according to the types of compliant elements adopted in their mechanical structures. Based on the typical robots investigated, the trade-off between each category is summarized. In addition, the most significant performances of these robots are compared quantitatively, and multiple available solutions for the future compliant legged robot design are suggested. Finally, the design challenges for compliant legged robots are analysed. This review will provide useful guidance for robotic designers in creating new designs by inheriting the virtues of those successful robots according to the specific tasks. (topical review)

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.

Predictive modelling of complex agronomic and biological systems.

Science.gov (United States)

Keurentjes, Joost J B; Molenaar, Jaap; Zwaan, Bas J

2013-09-01

Biological systems are tremendously complex in their functioning and regulation. Studying the multifaceted behaviour and describing the performance of such complexity has challenged the scientific community for years. The reduction of real-world intricacy into simple descriptive models has therefore convinced many researchers of the usefulness of introducing mathematics into biological sciences. Predictive modelling takes such an approach another step further in that it takes advantage of existing knowledge to project the performance of a system in alternating scenarios. The ever growing amounts of available data generated by assessing biological systems at increasingly higher detail provide unique opportunities for future modelling and experiment design. Here we aim to provide an overview of the progress made in modelling over time and the currently prevalent approaches for iterative modelling cycles in modern biology. We will further argue for the importance of versatility in modelling approaches, including parameter estimation, model reduction and network reconstruction. Finally, we will discuss the difficulties in overcoming the mathematical interpretation of in vivo complexity and address some of the future challenges lying ahead. © 2013 John Wiley & Sons Ltd.

Biological trade and markets.

Science.gov (United States)

Hammerstein, Peter; Noë, Ronald

2016-02-05

Cooperation between organisms can often be understood, like trade between merchants, as a mutually beneficial exchange of services, resources or other 'commodities'. Mutual benefits alone, however, are not sufficient to explain the evolution of trade-based cooperation. First, organisms may reject a particular trade if another partner offers a better deal. Second, while human trade often entails binding contracts, non-human trade requires unwritten 'terms of contract' that 'self-stabilize' trade and prevent cheating even if all traders strive to maximize fitness. Whenever trading partners can be chosen, market-like situations arise in nature that biologists studying cooperation need to account for. The mere possibility of exerting partner choice stabilizes many forms of otherwise cheatable trade, induces competition, facilitates the evolution of specialization and often leads to intricate forms of cooperation. We discuss selected examples to illustrate these general points and review basic conceptual approaches that are important in the theory of biological trade and markets. Comparing these approaches with theory in economics, it turns out that conventional models-often called 'Walrasian' markets-are of limited relevance to biology. In contrast, early approaches to trade and markets, as found in the works of Ricardo and Cournot, contain elements of thought that have inspired useful models in biology. For example, the concept of comparative advantage has biological applications in trade, signalling and ecological competition. We also see convergence between post-Walrasian economics and biological markets. For example, both economists and biologists are studying 'principal-agent' problems with principals offering jobs to agents without being sure that the agents will do a proper job. Finally, we show that mating markets have many peculiarities not shared with conventional economic markets. Ideas from economics are useful for biologists studying cooperation but need

A biomimetic accelerometer inspired by the cricket's clavate hair

NARCIS (Netherlands)

Droogendijk, H.; de Boer, Meint J.; Sanders, Remco G.P.; Krijnen, Gijsbertus J.M.

2014-01-01

Crickets use so-called clavate hairs to sense (gravitational) acceleration to obtain information on their orientation. Inspired by this clavate hair system, a one-axis biomimetic accelerometer has been developed and fabricated using surface micromachining and SU-8 lithography. An analytical model

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...

Superhydrophobic gecko feet with high adhesive forces towards water and their bio-inspired materials

Science.gov (United States)

Liu, Kesong; Du, Jiexing; Wu, Juntao; Jiang, Lei

2012-01-01

Functional integration is an inherent characteristic for multiscale structures of biological materials. In this contribution, we first investigate the liquid-solid adhesive forces between water droplets and superhydrophobic gecko feet using a high-sensitivity micro-electromechanical balance system. It was found, in addition to the well-known solid-solid adhesion, the gecko foot, with a multiscale structure, possesses both superhydrophobic functionality and a high adhesive force towards water. The origin of the high adhesive forces of gecko feet to water could be attributed to the high density nanopillars that contact the water. Inspired by this, polyimide films with gecko-like multiscale structures were constructed by using anodic aluminum oxide templates, exhibiting superhydrophobicity and a strong adhesive force towards water. The static water contact angle is larger than 150° and the adhesive force to water is about 66 μN. The resultant gecko-inspired polyimide film can be used as a ``mechanical hand'' to snatch micro-liter liquids. We expect this work will provide the inspiration to reveal the mechanism of the high-adhesive superhydrophobic of geckos and extend the practical applications of polyimide materials.

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.

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.

Self-assembly of micro- and nano-scale particles using bio-inspired events

International Nuclear Information System (INIS)

McNally, H.; Pingle, M.; Lee, S.W.; Guo, D.; Bergstrom, D.E.; Bashir, R.

2003-01-01

High sensitivity chemical and biological detection techniques and the development of future electronic systems can greatly benefit from self-assembly processes and techniques. We have approached this challenge using biologically inspired events such as the hybridization of single (ss)- to double-stranded (ds) DNA and the strong affinity between the protein avidin and its associated Vitamin, biotin. Using these molecules, micro-scale polystyrene beads and nano-scale gold particles were assembled with high efficiency on gold patterns and the procedures used for these processes were optimized. The DNA and avidin-biotin complex was also used to demonstrate the attachment of micro-scale silicon islands to each other in a fluid. This work also provides insight into the techniques for the self-assembly of heterogeneous materials

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

Science.gov (United States)

Giorgio-Serchi, Francesco; Weymouth, Gabriel

2017-11-01

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

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

Science.gov (United States)

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

2013-12-01

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

Inspiration fra NY-times

DEFF Research Database (Denmark)

Ejersbo, Lisser Rye

2015-01-01

NY-times har en ugentlig klumme med gode råd. For nogle uger siden var ugens inspiration henvendt til lærere/undervisere og drejede sig om, hvordan man skaber taletid til alle uden at have favoritter og overse de mere stille elever.......NY-times har en ugentlig klumme med gode råd. For nogle uger siden var ugens inspiration henvendt til lærere/undervisere og drejede sig om, hvordan man skaber taletid til alle uden at have favoritter og overse de mere stille elever....

Inspiration til undervisning på museer

DEFF Research Database (Denmark)

Hyllested, Trine Elisabeth

2015-01-01

collection and arrangement of knowledge meant to give a general view of, to inspire and to develop teaching at museums in Denmark......collection and arrangement of knowledge meant to give a general view of, to inspire and to develop teaching at museums in Denmark...

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

Science.gov (United States)

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

2013-01-01

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

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

Directory of Open Access Journals (Sweden)

Kohei eNakajima

2013-07-01

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

On gravitational waves in Born-Infeld inspired non-singular cosmologies

Energy Technology Data Exchange (ETDEWEB)

Jiménez, Jose Beltrán [Aix-Marseille Université, Université de Toulon, CNRS, CPT, Marseille (France); Heisenberg, Lavinia [Institute for Theoretical Studies, ETH Zurich, Clausiusstrasse 47, 8092 Zurich (Switzerland); Olmo, Gonzalo J. [Depto. de Física Teórica and IFIC, Universidad de Valencia—CSIC, Calle Dr. Moliner 50, Burjassot 46100, Valencia (Spain); Rubiera-Garcia, Diego, E-mail: jose.beltran@uam.es, E-mail: lavinia.heisenberg@eth-its.ethz.ch, E-mail: gonzalo.olmo@uv.es, E-mail: drgarcia@fc.ul.pt [Instituto de Astrofísica e Ciências do Espaço, Faculdade de Ciências da Universidade de Lisboa, Edifício C8, Campo Grande, P-1749-016 Lisbon (Portugal)

2017-10-01

We study the evolution of gravitational waves for non-singular cosmological solutions within the framework of Born-Infeld inspired gravity theories, with special emphasis on the Eddington-inspired Born-Infeld theory. We review the existence of two types of non-singular cosmologies, namely bouncing and asymptotically Minkowski solutions, from a perspective that makes their features more apparent. We study in detail the propagation of gravitational waves near these non-singular solutions and carefully discuss the origin and severity of the instabilities and strong coupling problems that appear. We also investigate the role of the adiabatic sound speed of the matter sector in the regularisation of the gravitational waves evolution. We extend our analysis to more general Born-Infeld inspired theories where analogous solutions are found. As a general conclusion, we obtain that the bouncing solutions are generally more prone to instabilities, while the asymptotically Minkowski solutions can be rendered stable, making them appealing models for the early universe.

Biologically inspired autonomous structural materials with controlled toughening and healing

Science.gov (United States)

Garcia, Michael E.; Sodano, Henry A.

2010-04-01

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

INSPIRE from the JRC Point of View

Directory of Open Access Journals (Sweden)

Vlado Cetl

2012-12-01

Full Text Available This paper summarises some recent developments in INSPIRE implementation from the JRC (Joint Research Centre point of view. The INSPIRE process started around 11 years ago and today, clear results and benefits can be seen. Spatial data are more accessible and shared more frequently between countries and at the European level. In addition to this, efficient, unified coordination and collaboration between different stakeholders and participants has been achieved, which is another great success. The JRC, as a scientific think-tank of the European Commission, has played a very important role in this process from the very beginning. This role is in line with its mission, which is to provide customer-driven scientific and technical support for the conception, development, implementation and monitoring of European Union (EU policies. The JRC acts as the overall technical coordinator of INSPIRE, but it also carries out the activities necessary to support the coherent implementation of INSPIRE, by helping member states in the implementation process. Experiences drawn from collaboration and negotiation in each country and at the European level will be of great importance in the revision of the INSPIRE Directive, which is envisaged for 2014. Keywords: spatial data infrastructure (SDI; INSPIRE; development; Joint Research Centre (JRC

Nature-inspired computation in engineering

CERN Document Server

2016-01-01

This timely review book summarizes the state-of-the-art developments in nature-inspired optimization algorithms and their applications in engineering. Algorithms and topics include the overview and history of nature-inspired algorithms, discrete firefly algorithm, discrete cuckoo search, plant propagation algorithm, parameter-free bat algorithm, gravitational search, biogeography-based algorithm, differential evolution, particle swarm optimization and others. Applications include vehicle routing, swarming robots, discrete and combinatorial optimization, clustering of wireless sensor networks, cell formation, economic load dispatch, metamodeling, surrogated-assisted cooperative co-evolution, data fitting and reverse engineering as well as other case studies in engineering. This book will be an ideal reference for researchers, lecturers, graduates and engineers who are interested in nature-inspired computation, artificial intelligence and computational intelligence. It can also serve as a reference for relevant...

Speech recognition employing biologically plausible receptive fields

DEFF Research Database (Denmark)

Fereczkowski, Michal; Bothe, Hans-Heinrich

2011-01-01

spectro-temporal receptive fields to auditory spectrogram input, motivated by the auditory pathway of humans, and ii) the adaptation or learning algorithms involved are biologically inspired. This is in contrast to state-of-the-art combinations of Mel-frequency cepstral coefficients and Hidden Markov...

WPMSD: A Malicious Script Detection Method Inspired by the Process of Immunoglobulin Secretion

Directory of Open Access Journals (Sweden)

Hui Zhao

2011-10-01

Full Text Available Inspired by the process of immunoglobulin secretion in biological body, we present a Web Page Malicious Script Detection Method (WPMSD. In this paper, Firstly, the basic definitions of artificial immune items are given. Secondly, according to the spreading range of malicious script, the immunoglobulin number is changed as the detector clone proliferation is stimulated by malicious scripts. Further more, the nonlinear dynamics of antibody number is discussed. Thirdly, we propose a probability approach to trigger alarms to inform that the detected scripts are harmful. Finally, the WPMSD collects the effective immunoglobulin set based on Hidden Markov Model (HMM to update the detector gene library. Compared with the traditional immune based detection methods, such as Negative Selection Algorithm (NSA, Dynamic Colonel Selection (DynamiCS, and Variable size Detector (Vdetector, the false alarm rate of WPMSD has been reduced by 18.09%, 12.6%, and 7.47% respectively.

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

Energy Technology Data Exchange (ETDEWEB)

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

2011-09-15

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

Variable gearing in a biologically inspired pneumatic actuator array

International Nuclear Information System (INIS)

Azizi, Emanuel; Roberts, Thomas J

2013-01-01

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

Variable gearing in a biologically inspired pneumatic actuator array.

Science.gov (United States)

Azizi, Emanuel; Roberts, Thomas J

2013-06-01

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

VARIABLE GEARING IN A BIOLOGICALLY-INSPIRED PNEUMATIC ACTUATOR ARRAY

Science.gov (United States)

Azizi, Emanuel; Roberts, Thomas J.

2013-01-01

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

SEEK: a systems biology data and model management platform.

Science.gov (United States)

Wolstencroft, Katherine; Owen, Stuart; Krebs, Olga; Nguyen, Quyen; Stanford, Natalie J; Golebiewski, Martin; Weidemann, Andreas; Bittkowski, Meik; An, Lihua; Shockley, David; Snoep, Jacky L; Mueller, Wolfgang; Goble, Carole

2015-07-11

Systems biology research typically involves the integration and analysis of heterogeneous data types in order to model and predict biological processes. Researchers therefore require tools and resources to facilitate the sharing and integration of data, and for linking of data to systems biology models. There are a large number of public repositories for storing biological data of a particular type, for example transcriptomics or proteomics, and there are several model repositories. However, this silo-type storage of data and models is not conducive to systems biology investigations. Interdependencies between multiple omics datasets and between datasets and models are essential. Researchers require an environment that will allow the management and sharing of heterogeneous data and models in the context of the experiments which created them. The SEEK is a suite of tools to support the management, sharing and exploration of data and models in systems biology. The SEEK platform provides an access-controlled, web-based environment for scientists to share and exchange data and models for day-to-day collaboration and for public dissemination. A plug-in architecture allows the linking of experiments, their protocols, data, models and results in a configurable system that is available 'off the shelf'. Tools to run model simulations, plot experimental data and assist with data annotation and standardisation combine to produce a collection of resources that support analysis as well as sharing. Underlying semantic web resources additionally extract and serve SEEK metadata in RDF (Resource Description Format). SEEK RDF enables rich semantic queries, both within SEEK and between related resources in the web of Linked Open Data. The SEEK platform has been adopted by many systems biology consortia across Europe. It is a data management environment that has a low barrier of uptake and provides rich resources for collaboration. This paper provides an update on the functions and

Continuum Modeling of Biological Network Formation

KAUST Repository

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

2017-01-01

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

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

Science.gov (United States)

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

2013-07-11

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

Shark skin-inspired designs that improve aerodynamic performance.

Science.gov (United States)

Domel, August G; Saadat, Mehdi; Weaver, James C; Haj-Hariri, Hossein; Bertoldi, Katia; Lauder, George V

2018-02-01

There have been significant efforts recently aimed at improving the aerodynamic performance of aerofoils through the modification of their surfaces. Inspired by the drag-reducing properties of the tooth-like denticles that cover the skin of sharks, we describe here experimental and simulation-based investigations into the aerodynamic effects of novel denticle-inspired designs placed along the suction side of an aerofoil. Through parametric modelling to query a wide range of different designs, we discovered a set of denticle-inspired surface structures that achieve simultaneous drag reduction and lift generation on an aerofoil, resulting in lift-to-drag ratio improvements comparable to the best-reported for traditional low-profile vortex generators and even outperforming these existing designs at low angles of attack with improvements of up to 323%. Such behaviour is enabled by two concurrent mechanisms: (i) a separation bubble in the denticle's wake altering the flow pressure distribution of the aerofoil to enhance suction and (ii) streamwise vortices that replenish momentum loss in the boundary layer due to skin friction. Our findings not only open new avenues for improved aerodynamic design, but also provide new perspective on the role of the complex and potentially multifunctional morphology of shark denticles for increased swimming efficiency. © 2018 The Author(s).

Kids Inspire Kids for STEAM

OpenAIRE

Fenyvesi, Kristof; Houghton, Tony; Diego-Mantecón, José Manuel; Crilly, Elizabeth; Oldknow, Adrian; Lavicza, Zsolt; Blanco, Teresa F.

2017-01-01

Abstract The goal of the Kids Inspiring Kids in STEAM (KIKS) project was to raise students' awareness towards the multi- and transdisciplinary connections between the STEAM subjects (Science, Technology, Engineering, Arts & Mathematics), and make the learning about topics and phenomena from these fields more enjoyable. In order to achieve these goals, KIKS project has popularized the STEAM-concept by projects based on the students inspiring other students-approach and by utilizing new tec...

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

Science.gov (United States)

Gomez-Ramirez, Jaime; Sanz, Ricardo

2013-09-01

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

Denoising of Mechanical Vibration Signals Using Quantum-Inspired Adaptive Wavelet Shrinkage

Directory of Open Access Journals (Sweden)

Yan-long Chen

2014-01-01

Full Text Available The potential application of a quantum-inspired adaptive wavelet shrinkage (QAWS technique to mechanical vibration signals with a focus on noise reduction is studied in this paper. This quantum-inspired shrinkage algorithm combines three elements: an adaptive non-Gaussian statistical model of dual-tree complex wavelet transform (DTCWT coefficients proposed to improve practicability of prior information, the quantum superposition introduced to describe the interscale dependencies of DTCWT coefficients, and the quantum-inspired probability of noise defined to shrink wavelet coefficients in a Bayesian framework. By combining all these elements, this signal processing scheme incorporating the DTCWT with quantum theory can both reduce noise and preserve signal details. A practical vibration signal measured from a power-shift steering transmission is utilized to evaluate the denoising ability of QAWS. Application results demonstrate the effectiveness of the proposed method. Moreover, it achieves better performance than hard and soft thresholding.

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

Science.gov (United States)

Barta, Dániel; Vasúth, Mátyás

2018-06-01

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

The Punishment of Tarpeia and Its Possible Iconographic Inspiration

Directory of Open Access Journals (Sweden)

Lenka Vacinová

2017-10-01

Full Text Available The motif of the Punishment of Tarpeia is surprisingly rare in Roman visual arts. However, the surviving examples show iconographical unity and imply their common primary visual source of inspiration. The article is exploring the possible models considering the less obvious iconographical similarities and resemblances in terms of content found in the Greek art. The cases of the infamous intriguer Dirce and traitor Dolon are discussed, as well as the remarkable resemblances found on some images of the Death of Caeneus. While the latter indicates the inspiration based on free associations and the similar circumstances of death of the both protagonists, Dolon and Dirce seem to influence the creator of the iconographic scheme of the Punishment of Tarpeia in a more straight way.

Research on one Bio-inspired Jumping Locomotion Robot for Search and Rescue

Directory of Open Access Journals (Sweden)

Dunwen Wei

2014-10-01

Full Text Available Jumping locomotion is much more effective than other locomotion means in order to tackle the unstructured and complex environment in research and rescue. Here, a bio-inspired jumping robot with a closed-chain mechanism is proposed to achieve the power amplification during taking-off. Through actuating one variable transmission mechanism to change the transmission ratio, the jumping robot reveals biological characteristics in the phase of posture adjustment when adjusting the height and distance of one jump. The kinematics and dynamics of the simplified jumping mechanism model in one jumping cycle sequence are analysed. A compliant contact model considering nonlinear damping is investigated for jumping performance under different terrain characteristics. The numerical simulation algorithm with regard to solving the dynamical equation is described and simulation results are discussed. Finally, one primary prototype and experiment are described. The experimental results show the distance of jumping in the horizontal direction increases with the increasing gear ratio, while the height of jumping decreases in reverse. The jumping robot can enhance the capability to adapt to unknown cluttered environments, such as those encountered in research and rescue, using this strategy.

Fish-inspired self-powered microelectromechanical flow sensor with biomimetic hydrogel cupula

Science.gov (United States)

Bora, M.; Kottapalli, A. G. P.; Miao, J. M.; Triantafyllou, M. S.

2017-10-01

Flow sensors inspired from lateral line neuromasts of cavefish have been widely investigated over decades to develop artificial sensors. The design and function of these natural sensors have been mimicked using microelectromechanical systems (MEMS) based sensors. However, there is more to the overall function and performance of these natural sensors. Mimicking the morphology and material properties of specialized structures like a cupula would significantly help to improve the existing designs. Toward this goal, the paper reports development of a canal neuromast inspired piezoelectric sensor and investigates the role of a biomimetic cupula in influencing the performance of the sensor. The sensor was developed using microfabrication technology and tested for the detection of the steady-state and oscillatory flows. An artificial cupula was synthesized using a soft hydrogel material and characterized for morphology and mechanical properties. Results show that the artificial cupula had a porous structure and high mechanical strength similar to the biological canal neuromast. Experimental results show the ability of these sensors to measure the steady-state flows accurately, and for oscillatory flows, an increase in the sensor output was detected in the presence of the cupula structure. This is the first time a MEMS based piezoelectric sensor is demonstrated to detect steady-state flows using the principle of vortex-induced vibrations. The bioinspired sensor developed in this work would be investigated further to understand the role of the cupula structure in biological flow sensing mechanisms, thus contributing toward the design of highly sensitive and efficient sensors for various applications such as underwater robotics, microfluidics, and biomedical devices.

INSPIRE: A new scientific information system for HEP

International Nuclear Information System (INIS)

Ivanov, R; Raae, L

2010-01-01

The status of high-energy physics (HEP) information systems has been jointly analyzed by the libraries of CERN, DESY, Fermilab and SLAC. As a result, the four laboratories have started the INSPIRE project - a new platform built by moving the successful SPIRES features and content, curated at DESY, Fermilab and SLAC, into the open-source CDS Invenio digital library software that was developed at CERN. INSPIRE will integrate current acquisition workflows and databases to host the entire body of the HEP literature (about one million records), aiming to become the reference HEP scientific information platform worldwide. It will provide users with fast access to full text journal articles and preprints, but also material such as conference slides and multimedia. INSPIRE will empower scientists with new tools to discover and access the results most relevant to their research, enable novel text- and data-mining applications, and deploy new metrics to assess the impact of articles and authors. In addition, it will introduce the 'Web 2.0' paradigm of user-enriched content in the domain of sciences, with community-based approaches to scientific publishing. INSPIRE represents a natural evolution of scholarly communication built on successful community-based information systems, and it provides a vision for information management in other fields of science. Inspired by the needs of HEP, we hope that the INSPIRE project will be inspiring for other communities.

Ships - inspiring objects in architecture

Science.gov (United States)

Marczak, Elzbieta

2017-10-01

Sea-going vessels have for centuries fascinated people, not only those who happen to work at sea, but first and foremost, those who have never set foot aboard a ship. The environment in which ships operate is reminiscent of freedom and countless adventures, but also of hard and interesting maritime working life. The famous words of Pompey: “Navigare necesseest, vivere non estnecesse” (sailing is necessary, living - is not necessary), which he pronounced on a stormy sea voyage, arouse curiosity and excitement, inviting one to test the truth of this saying personally. It is often the case, however, that sea-faring remains within the realm of dreams, while the fascination with ships demonstrates itself through a transposition of naval features onto land constructions. In such cases, ship-inspired motifs bring alive dreams and yearnings as well as reflect tastes. Tourism is one of the indicators of people’s standard of living and a measure of a society’s civilisation. Maritime tourism has been developing rapidly in recent decades. A sea cruise offers an insight into life at sea. Still, most people derive their knowledge of passenger vessels and their furnishings from the mass media. Passenger vessels, also known as “floating cities,” are described as majestic and grand, while their on-board facilities as luxurious, comfortable, exclusive and inaccessible to common people on land. Freight vessels, on the other hand, are described as enormous objects which dwarf the human being into insignificance. This article presents the results of research intended to answer the following questions: what makes ships a source of inspiration for land architecture? To what extent and by what means do architects draw on ships in their design work? In what places can we find structures inspired by ships? What ships inspire architects? This article presents examples of buildings, whose design was inspired by the architecture and structural details of sea vessels. An analysis of

Biology meets Physics: Reductionism and Multi-scale Modeling of Morphogenesis

DEFF Research Database (Denmark)

Green, Sara; Batterman, Robert

2017-01-01

A common reductionist assumption is that macro-scale behaviors can be described "bottom-up" if only sufficient details about lower-scale processes are available. The view that an "ideal" or "fundamental" physics would be sufficient to explain all macro-scale phenomena has been met with criticism ...... modeling in developmental biology. In such contexts, the relation between models at different scales and from different disciplines is neither reductive nor completely autonomous, but interdependent....... from philosophers of biology. Specifically, scholars have pointed to the impossibility of deducing biological explanations from physical ones, and to the irreducible nature of distinctively biological processes such as gene regulation and evolution. This paper takes a step back in asking whether bottom......-up modeling is feasible even when modeling simple physical systems across scales. By comparing examples of multi-scale modeling in physics and biology, we argue that the “tyranny of scales” problem present a challenge to reductive explanations in both physics and biology. The problem refers to the scale...

Topology Optimization of Lightweight Lattice Structural Composites Inspired by Cuttlefish Bone

Science.gov (United States)

Hu, Zhong; Gadipudi, Varun Kumar; Salem, David R.

2018-03-01

Lattice structural composites are of great interest to various industries where lightweight multifunctionality is important, especially aerospace. However, strong coupling among the composition, microstructure, porous topology, and fabrication of such materials impedes conventional trial-and-error experimental development. In this work, a discontinuous carbon fiber reinforced polymer matrix composite was adopted for structural design. A reliable and robust design approach for developing lightweight multifunctional lattice structural composites was proposed, inspired by biomimetics and based on topology optimization. Three-dimensional periodic lattice blocks were initially designed, inspired by the cuttlefish bone microstructure. The topologies of the three-dimensional periodic blocks were further optimized by computer modeling, and the mechanical properties of the topology optimized lightweight lattice structures were characterized by computer modeling. The lattice structures with optimal performance were identified.

Respectful Modeling: Addressing Uncertainty in Dynamic System Models for Molecular Biology.

Science.gov (United States)

Tsigkinopoulou, Areti; Baker, Syed Murtuza; Breitling, Rainer

2017-06-01

Although there is still some skepticism in the biological community regarding the value and significance of quantitative computational modeling, important steps are continually being taken to enhance its accessibility and predictive power. We view these developments as essential components of an emerging 'respectful modeling' framework which has two key aims: (i) respecting the models themselves and facilitating the reproduction and update of modeling results by other scientists, and (ii) respecting the predictions of the models and rigorously quantifying the confidence associated with the modeling results. This respectful attitude will guide the design of higher-quality models and facilitate the use of models in modern applications such as engineering and manipulating microbial metabolism by synthetic biology. Copyright © 2016 Elsevier Ltd. All rights reserved.

Friction behavior of a microstructured polymer surface inspired by snake skin.

Science.gov (United States)

Baum, Martina J; Heepe, Lars; Gorb, Stanislav N

2014-01-01

The aim of this study was to understand the influence of microstructures found on ventral scales of the biological model, Lampropeltis getula californiae, the California King Snake, on the friction behavior. For this purpose, we compared snake-inspired anisotropic microstructured surfaces to other microstructured surfaces with isotropic and anisotropic geometry. To exclude that the friction measurements were influenced by physico-chemical variations, all friction measurements were performed on the same epoxy polymer. For frictional measurements a microtribometer was used. Original data were processed by fast Fourier transformation (FFT) with a zero frequency related to the average friction and other peaks resulting from periodic stick-slip behavior. The data showed that the specific ventral surface ornamentation of snakes does not only reduce the frictional coefficient and generate anisotropic frictional properties, but also reduces stick-slip vibrations during sliding, which might be an adaptation to reduce wear. Based on this extensive comparative study of different microstructured polymer samples, it was experimentally demonstrated that the friction-induced stick-slip behavior does not solely depend on the frictional coefficient of the contact pair.

Friction behavior of a microstructured polymer surface inspired by snake skin

Directory of Open Access Journals (Sweden)

Martina J. Baum

2014-01-01

Full Text Available The aim of this study was to understand the influence of microstructures found on ventral scales of the biological model, Lampropeltis getula californiae, the California King Snake, on the friction behavior. For this purpose, we compared snake-inspired anisotropic microstructured surfaces to other microstructured surfaces with isotropic and anisotropic geometry. To exclude that the friction measurements were influenced by physico-chemical variations, all friction measurements were performed on the same epoxy polymer. For frictional measurements a microtribometer was used. Original data were processed by fast Fourier transformation (FFT with a zero frequency related to the average friction and other peaks resulting from periodic stick-slip behavior. The data showed that the specific ventral surface ornamentation of snakes does not only reduce the frictional coefficient and generate anisotropic frictional properties, but also reduces stick-slip vibrations during sliding, which might be an adaptation to reduce wear. Based on this extensive comparative study of different microstructured polymer samples, it was experimentally demonstrated that the friction-induced stick-slip behavior does not solely depend on the frictional coefficient of the contact pair.

Inspiration from heart development: Biomimetic development of functional human cardiac organoids.

Science.gov (United States)

Richards, Dylan J; Coyle, Robert C; Tan, Yu; Jia, Jia; Wong, Kerri; Toomer, Katelynn; Menick, Donald R; Mei, Ying

2017-10-01

Recent progress in human organoids has provided 3D tissue systems to model human development, diseases, as well as develop cell delivery systems for regenerative therapies. While direct differentiation of human embryoid bodies holds great promise for cardiac organoid production, intramyocardial cell organization during heart development provides biological foundation to fabricate human cardiac organoids with defined cell types. Inspired by the intramyocardial organization events in coronary vasculogenesis, where a diverse, yet defined, mixture of cardiac cell types self-organizes into functional myocardium in the absence of blood flow, we have developed a defined method to produce scaffold-free human cardiac organoids that structurally and functionally resembled the lumenized vascular network in the developing myocardium, supported hiPSC-CM development and possessed fundamental cardiac tissue-level functions. In particular, this development-driven strategy offers a robust, tunable system to examine the contributions of individual cell types, matrix materials and additional factors for developmental insight, biomimetic matrix composition to advance biomaterial design, tissue/organ-level drug screening, and cell therapy for heart repair. Copyright © 2017 Elsevier Ltd. All rights reserved.

Active Hearing Mechanisms Inspire Adaptive Amplification in an Acoustic Sensor System.

Science.gov (United States)

Guerreiro, Jose; Reid, Andrew; Jackson, Joseph C; Windmill, James F C

2018-06-01

Over many millions of years of evolution, nature has developed some of the most adaptable sensors and sensory systems possible, capable of sensing, conditioning and processing signals in a very power- and size-effective manner. By looking into biological sensors and systems as a source of inspiration, this paper presents the study of a bioinspired concept of signal processing at the sensor level. By exploiting a feedback control mechanism between a front-end acoustic receiver and back-end neuronal based computation, a nonlinear amplification with hysteretic behavior is created. Moreover, the transient response of the front-end acoustic receiver can also be controlled and enhanced. A theoretical model is proposed and the concept is prototyped experimentally through an embedded system setup that can provide dynamic adaptations of a sensory system comprising a MEMS microphone placed in a closed-loop feedback system. It faithfully mimics the mosquito's active hearing response as a function of the input sound intensity. This is an adaptive acoustic sensor system concept that can be exploited by sensor and system designers within acoustics and ultrasonic engineering fields.

Continuous time Boolean modeling for biological signaling: application of Gillespie algorithm.

OpenAIRE

Stoll, Gautier; Viara, Eric; Barillot, Emmanuel; Calzone, Laurence

2012-01-01

Abstract Mathematical modeling is used as a Systems Biology tool to answer biological questions, and more precisely, to validate a network that describes biological observations and predict the effect of perturbations. This article presents an algorithm for modeling biological networks in a discrete framework with continuous time. Background There exist two major types of mathematical modeling approaches: (1) quantitative modeling, representing various chemical species concentrations by real...

DNA-inspired hierarchical polymer design: electrostatics and hydrogen bonding in concert.

Science.gov (United States)

Hemp, Sean T; Long, Timothy E

2012-01-01

Nucleic acids and proteins, two of nature's biopolymers, assemble into complex structures to achieve desired biological functions and inspire the design of synthetic macromolecules containing a wide variety of noncovalent interactions including electrostatics and hydrogen bonding. Researchers have incorporated DNA nucleobases into a wide variety of synthetic monomers/polymers achieving stimuli-responsive materials, supramolecular assemblies, and well-controlled macromolecules. Recently, scientists utilized both electrostatics and complementary hydrogen bonding to orthogonally functionalize a polymer backbone through supramolecular assembly. Diverse macromolecules with noncovalent interactions will create materials with properties necessary for biomedical applications. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Structural biological composites: An overview

Science.gov (United States)

Meyers, Marc A.; Lin, Albert Y. M.; Seki, Yasuaki; Chen, Po-Yu; Kad, Bimal K.; Bodde, Sara

2006-07-01

Biological materials are complex composites that are hierarchically structured and multifunctional. Their mechanical properties are often outstanding, considering the weak constituents from which they are assembled. They are for the most part composed of brittle (often, mineral) and ductile (organic) components. These complex structures, which have risen from millions of years of evolution, are inspiring materials scientists in the design of novel materials. This paper discusses the overall design principles in biological structural composites and illustrates them for five examples; sea spicules, the abalone shell, the conch shell, the toucan and hornbill beaks, and the sheep crab exoskeleton.

Bio-inspired computation in unmanned aerial vehicles

CERN Document Server

Duan, Haibin

2014-01-01

Bio-inspired Computation in Unmanned Aerial Vehicles focuses on the aspects of path planning, formation control, heterogeneous cooperative control and vision-based surveillance and navigation in Unmanned Aerial Vehicles (UAVs) from the perspective of bio-inspired computation. It helps readers to gain a comprehensive understanding of control-related problems in UAVs, presenting the latest advances in bio-inspired computation. By combining bio-inspired computation and UAV control problems, key questions are explored in depth, and each piece is content-rich while remaining accessible. With abundant illustrations of simulation work, this book links theory, algorithms and implementation procedures, demonstrating the simulation results with graphics that are intuitive without sacrificing academic rigor. Further, it pays due attention to both the conceptual framework and the implementation procedures. The book offers a valuable resource for scientists, researchers and graduate students in the field of Control, Aeros...

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

Science.gov (United States)

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

2017-01-01

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

Genome Scale Modeling in Systems Biology: Algorithms and Resources

Science.gov (United States)

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

2014-01-01

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

Designing synthetic biology.

Science.gov (United States)

Agapakis, Christina M

2014-03-21

Synthetic biology is frequently defined as the application of engineering design principles to biology. Such principles are intended to streamline the practice of biological engineering, to shorten the time required to design, build, and test synthetic gene networks. This streamlining of iterative design cycles can facilitate the future construction of biological systems for a range of applications in the production of fuels, foods, materials, and medicines. The promise of these potential applications as well as the emphasis on design has prompted critical reflection on synthetic biology from design theorists and practicing designers from many fields, who can bring valuable perspectives to the discipline. While interdisciplinary connections between biologists and engineers have built synthetic biology via the science and the technology of biology, interdisciplinary collaboration with artists, designers, and social theorists can provide insight on the connections between technology and society. Such collaborations can open up new avenues and new principles for research and design, as well as shed new light on the challenging context-dependence-both biological and social-that face living technologies at many scales. This review is inspired by the session titled "Design and Synthetic Biology: Connecting People and Technology" at Synthetic Biology 6.0 and covers a range of literature on design practice in synthetic biology and beyond. Critical engagement with how design is used to shape the discipline opens up new possibilities for how we might design the future of synthetic biology.

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

Introduction to stochastic models in biology

DEFF Research Database (Denmark)

Ditlevsen, Susanne; Samson, Adeline

2013-01-01

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

Bio-Inspired Extreme Wetting Surfaces for Biomedical Applications

Science.gov (United States)

Shin, Sera; Seo, Jungmok; Han, Heetak; Kang, Subin; Kim, Hyunchul; Lee, Taeyoon

2016-01-01

Biological creatures with unique surface wettability have long served as a source of inspiration for scientists and engineers. More specifically, materials exhibiting extreme wetting properties, such as superhydrophilic and superhydrophobic surfaces, have attracted considerable attention because of their potential use in various applications, such as self-cleaning fabrics, anti-fog windows, anti-corrosive coatings, drag-reduction systems, and efficient water transportation. In particular, the engineering of surface wettability by manipulating chemical properties and structure opens emerging biomedical applications ranging from high-throughput cell culture platforms to biomedical devices. This review describes design and fabrication methods for artificial extreme wetting surfaces. Next, we introduce some of the newer and emerging biomedical applications using extreme wetting surfaces. Current challenges and future prospects of the surfaces for potential biomedical applications are also addressed. PMID:28787916

Bio-inspired heterogeneous composites for broadband vibration mitigation.

Science.gov (United States)

Chen, Yanyu; Wang, Lifeng

2015-12-08

Structural biological materials have developed heterogeneous and hierarchical architectures that are responsible for the outstanding performance to provide protection against environmental threats including static and dynamic loading. Inspired by this observation, this research aims to develop new material and structural concepts for broadband vibration mitigation. The proposed composite materials possess a two-layered heterogeneous architecture where both layers consist of high-volume platelet-shape reinforcements and low-volume matrix, similar to the well-known "brick and mortar" microstructure of biological composites. Using finite element method, we numerically demonstrated that broadband wave attenuation zones can be achieved by tailoring the geometric features of the heterogeneous architecture. We reveal that the resulting broadband attenuation zones are gained by directly superimposing the attenuation zones in each constituent layer. This mechanism is further confirmed by the investigation into the phonon dispersion relation of each layer. Importantly, the broadband wave attenuation capability will be maintained when the mineral platelet orientation is locally manipulated, yet a contrast between the mineral platelet concentrations of the two constituent layers is essential. The findings of this work will provide new opportunities to design heterogeneous composites for broadband vibration mitigation and impact resistance under mechanically challenging environmental conditions.

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

Science.gov (United States)

Bhardwaj, Garima; Webster, Thomas J

2016-01-01

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

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.

Notions of similarity for computational biology models

KAUST Repository

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

2016-01-01

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

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.

Energy-Efficient Train Operation Using Nature-Inspired Algorithms

Directory of Open Access Journals (Sweden)

Kemal Keskin

2017-01-01

Full Text Available A train operation optimization by minimizing its traction energy subject to various constraints is carried out using nature-inspired evolutionary algorithms. The optimization process results in switching points that initiate cruising and coasting phases of the driving. Due to nonlinear optimization formulation of the problem, nature-inspired evolutionary search methods, Genetic Simulated Annealing, Firefly, and Big Bang-Big Crunch algorithms were employed in this study. As a case study a real-like train and test track from a part of Eskisehir light rail network were modeled. Speed limitations, various track alignments, maximum allowable trip time, and changes in train mass were considered, and punctuality was put into objective function as a penalty factor. Results have shown that all three evolutionary methods generated effective and consistent solutions. However, it has also been shown that each one has different accuracy and convergence characteristics.

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.

Constructive biology and approaches to temporal grounding in postreactive robotics

Science.gov (United States)

Nehaniv, Chrystopher L.; Dautenhahn, Kerstin; Loomes, Martin J.

1999-08-01

Constructive Biology means understanding biological mechanisms through building systems that exhibit life-like properties. Applications include learning engineering tricks from biological system, as well as the validation in biological modeling. In particular, biological system in the course of development and experience become temporally grounded. Researchers attempting to transcend mere reactivity have been inspired by the drives, motivations, homeostasis, hormonal control, and emotions of animals. In order to contextualize and modulate behavior, these ideas have been introduced into robotics and synthetic agents, while further flexibility is achieved by introducing learning. Broadening scope of the temporal horizon further requires post-reactive techniques that address not only the action in the now, although such action may perhaps be modulated by drives and affect. Support is needed for expressing and benefitting from pats experiences, predictions of the future, and form interaction histories of the self with the world and with other agents. Mathematical methods provide a new way to support such grounding in the construction of post-reactive systems. Moreover, the communication of such mathematical encoded histories of experience between situated agents opens a route to narrative intelligence, analogous to communication or story telling in societies.

Diversification and enrichment of clinical biomaterials inspired by Darwinian evolution.

Science.gov (United States)

Green, D W; Watson, G S; Watson, J A; Lee, D-J; Lee, J-M; Jung, H-S

2016-09-15

Regenerative medicine and biomaterials design are driven by biomimicry. There is the essential requirement to emulate human cell, tissue, organ and physiological complexity to ensure long-lasting clinical success. Biomimicry projects for biomaterials innovation can be re-invigorated with evolutionary insights and perspectives, since Darwinian evolution is the original dynamic process for biological organisation and complexity. Many existing human inspired regenerative biomaterials (defined as a nature generated, nature derived and nature mimicking structure, produced within a biological system, which can deputise for, or replace human tissues for which it closely matches) are without important elements of biological complexity such as, hierarchy and autonomous actions. It is possible to engineer these essential elements into clinical biomaterials via bioinspired implementation of concepts, processes and mechanisms played out during Darwinian evolution; mechanisms such as, directed, computational, accelerated evolutions and artificial selection contrived in the laboratory. These dynamos for innovation can be used during biomaterials fabrication, but also to choose optimal designs in the regeneration process. Further evolutionary information can help at the design stage; gleaned from the historical evolution of material adaptations compared across phylogenies to changes in their environment and habitats. Taken together, harnessing evolutionary mechanisms and evolutionary pathways, leading to ideal adaptations, will eventually provide a new class of Darwinian and evolutionary biomaterials. This will provide bioengineers with a more diversified and more efficient innovation tool for biomaterial design, synthesis and function than currently achieved with synthetic materials chemistry programmes and rational based materials design approach, which require reasoned logic. It will also inject further creativity, diversity and richness into the biomedical technologies that

A cellular automata based FPGA realization of a new metaheuristic bat-inspired algorithm

Science.gov (United States)

Progias, Pavlos; Amanatiadis, Angelos A.; Spataro, William; Trunfio, Giuseppe A.; Sirakoulis, Georgios Ch.

2016-10-01

Optimization algorithms are often inspired by processes occuring in nature, such as animal behavioral patterns. The main concern with implementing such algorithms in software is the large amounts of processing power they require. In contrast to software code, that can only perform calculations in a serial manner, an implementation in hardware, exploiting the inherent parallelism of single-purpose processors, can prove to be much more efficient both in speed and energy consumption. Furthermore, the use of Cellular Automata (CA) in such an implementation would be efficient both as a model for natural processes, as well as a computational paradigm implemented well on hardware. In this paper, we propose a VHDL implementation of a metaheuristic algorithm inspired by the echolocation behavior of bats. More specifically, the CA model is inspired by the metaheuristic algorithm proposed earlier in the literature, which could be considered at least as efficient than other existing optimization algorithms. The function of the FPGA implementation of our algorithm is explained in full detail and results of our simulations are also demonstrated.

The use of biologically based cancer risk models in radiation epidemiology

International Nuclear Information System (INIS)

Krewski, D.; Zielinski, J.M.; Hazelton, W.D.; Garner, M.J.; Moolgavkar, S.H.

2003-01-01

Biologically based risk projection models for radiation carcinogenesis seek to describe the fundamental biological processes involved in neoplastic transformation of somatic cells into malignant cancer cells. A validated biologically based model, whose parameters have a direct biological interpretation, can also be used to extrapolate cancer risks to different exposure conditions with some confidence. In this article, biologically based models for radiation carcinogenesis, including the two-stage clonal expansion (TSCE) model and its extensions, are reviewed. The biological and mathematical bases for such models are described, and the implications of key model parameters for cancer risk assessment examined. Specific applications of versions of the TSCE model to important epidemiologic datasets are discussed, including the Colorado uranium miners' cohort; a cohort of Chinese tin miners; the lifespan cohort of atomic bomb survivors in Hiroshima and Nagasaki; and a cohort of over 200,000 workers included in the National Dose Registry (NDR) of Canada. (author)

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...

Global existence and asymptotic behavior of a model for biological control of invasive species via supermale introduction

KAUST Repository

Parshad, Rana

2013-01-01

The purpose of this manuscript is to propose a model for the biological control of invasive species, via introduction of phenotypically modified organisms into a target population. We are inspired by the earlier Trojan Y Chromosome model [J.B. Gutierrez, J.L. Teem, J. Theo. Bio., 241(22), 333-341, 2006]. However, in the current work, we remove the assumption of logisticgrowth rate, and do not consider the addition of sex-reversed supermales. Also the constant birth and death coefficients, considered earlier, are replaced by functionally dependent ones. In this case the nonlinearities present serious difficulties since they change sign, and the components of the solution are not a priori bounded, in some Lp-space for p large, to permit theapplication of the well known regularizing effect principle. Thus functional methods to deducethe global existence in time, for the system in question, are not applicable. Our techniques are based on the Lyapunov functional method. We prove global existence of solutions, as well asexistence of a finite dimensional global attractor, that supports states of extinction. Our analytical finding are in accordance with numerical simulations, which we also present. © 2013 International Press.

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

Science.gov (United States)

Engelhardt, Benjamin; Frőhlich, Holger; Kschischo, Maik

2016-02-11

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

Biocellion: accelerating computer simulation of multicellular biological system models.

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

2014-11-01

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

Allothetic and idiothetic sensor fusion in rat-inspired robot localization

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Weitzenfeld, Alfredo; Fellous, Jean-Marc; Barrera, Alejandra; Tejera, Gonzalo

2012-06-01

We describe a spatial cognition model based on the rat's brain neurophysiology as a basis for new robotic navigation architectures. The model integrates allothetic (external visual landmarks) and idiothetic (internal kinesthetic information) cues to train either rat or robot to learn a path enabling it to reach a goal from multiple starting positions. It stands in contrast to most robotic architectures based on SLAM, where a map of the environment is built to provide probabilistic localization information computed from robot odometry and landmark perception. Allothetic cues suffer in general from perceptual ambiguity when trying to distinguish between places with equivalent visual patterns, while idiothetic cues suffer from imprecise motions and limited memory recalls. We experiment with both types of cues in different maze configurations by training rats and robots to find the goal starting from a fixed location, and then testing them to reach the same target from new starting locations. We show that the robot, after having pre-explored a maze, can find a goal with improved efficiency, and is able to (1) learn the correct route to reach the goal, (2) recognize places already visited, and (3) exploit allothetic and idiothetic cues to improve on its performance. We finally contrast our biologically-inspired approach to more traditional robotic approaches and discuss current work in progress.

Efficient network-matrix architecture for general flow transport inspired by natural pinnate leaves.

Science.gov (United States)

Hu, Liguo; Zhou, Han; Zhu, Hanxing; Fan, Tongxiang; Zhang, Di

2014-11-14

Networks embedded in three dimensional matrices are beneficial to deliver physical flows to the matrices. Leaf architectures, pervasive natural network-matrix architectures, endow leaves with high transpiration rates and low water pressure drops, providing inspiration for efficient network-matrix architectures. In this study, the network-matrix model for general flow transport inspired by natural pinnate leaves is investigated analytically. The results indicate that the optimal network structure inspired by natural pinnate leaves can greatly reduce the maximum potential drop and the total potential drop caused by the flow through the network while maximizing the total flow rate through the matrix. These results can be used to design efficient networks in network-matrix architectures for a variety of practical applications, such as tissue engineering, cell culture, photovoltaic devices and heat transfer.

Fusion of nacre, mussel, and lotus leaf: bio-inspired graphene composite paper with multifunctional integration

Science.gov (United States)

Zhong, Da; Yang, Qinglin; Guo, Lin; Dou, Shixue; Liu, Kesong; Jiang, Lei

2013-06-01

Multifunctional integration is an inherent characteristic for biological materials with multiscale structures. Learning from nature is an effective approach for scientists and engineers to construct multifunctional materials. In nature, mollusks (abalone), mussels, and the lotus have evolved different and optimized solutions to survive. Here, bio-inspired multifunctional graphene composite paper was fabricated in situ through the fusion of the different biological solutions from nacre (brick-and-mortar structure), mussel adhesive protein (adhesive property and reducing character), and the lotus leaf (self-cleaning effect). Owing to the special properties (self-polymerization, reduction, and adhesion), dopamine could be simultaneously used as a reducing agent for graphene oxide and as an adhesive, similar to the mortar in nacre, to crosslink the adjacent graphene. The resultant nacre-like graphene paper exhibited stable superhydrophobicity, self-cleaning, anti-corrosion, and remarkable mechanical properties underwater.Multifunctional integration is an inherent characteristic for biological materials with multiscale structures. Learning from nature is an effective approach for scientists and engineers to construct multifunctional materials. In nature, mollusks (abalone), mussels, and the lotus have evolved different and optimized solutions to survive. Here, bio-inspired multifunctional graphene composite paper was fabricated in situ through the fusion of the different biological solutions from nacre (brick-and-mortar structure), mussel adhesive protein (adhesive property and reducing character), and the lotus leaf (self-cleaning effect). Owing to the special properties (self-polymerization, reduction, and adhesion), dopamine could be simultaneously used as a reducing agent for graphene oxide and as an adhesive, similar to the mortar in nacre, to crosslink the adjacent graphene. The resultant nacre-like graphene paper exhibited stable superhydrophobicity, self

How computational models can help unlock biological systems.

Science.gov (United States)

Brodland, G Wayne

2015-12-01

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

Bio-inspired dental fillings

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Deyhle, Hans; Bunk, Oliver; Buser, Stefan; Krastl, Gabriel; Zitzmann, Nicola U.; Ilgenstein, Bernd; Beckmann, Felix; Pfeiffer, Franz; Weiger, Roland; Müller, Bert

2009-08-01

Human teeth are anisotropic composites. Dentin as the core material of the tooth consists of nanometer-sized calcium phosphate crystallites embedded in collagen fiber networks. It shows its anisotropy on the micrometer scale by its well-oriented microtubules. The detailed three-dimensional nanostructure of the hard tissues namely dentin and enamel, however, is not understood, although numerous studies on the anisotropic mechanical properties have been performed and evaluated to explain the tooth function including the enamel-dentin junction acting as effective crack barrier. Small angle X-ray scattering (SAXS) with a spatial resolution in the 10 μm range allows determining the size and orientation of the constituents on the nanometer scale with reasonable precision. So far, only some dental materials, i.e. the fiber reinforced posts exhibit anisotropic properties related to the micrometer-size glass fibers. Dental fillings, composed of nanostructures oriented similar to the natural hard tissues of teeth, however, do not exist at all. The current X-ray-based investigations of extracted human teeth provide evidence for oriented micro- and nanostructures in dentin and enamel. These fundamental quantitative findings result in profound knowledge to develop biologically inspired dental fillings with superior resistance to thermal and mechanical shocks.

A bio-inspired asynchronous skin system for crack detection applications

International Nuclear Information System (INIS)

Sharp, Nathan; Kuntz, Alan; Brubaker, Cole; Amos, Stephanie; Gao, Wei; Gupta, Gautum; Mohite, Aditya; Farrar, Charles; Mascareñas, David

2014-01-01

In many applications of structural health monitoring (SHM) it is imperative or advantageous to have large sensor arrays in order to properly sense the state of health of the structure. Typically these sensor networks are implemented by placing a large number of sensors over a structure and running individual cables from each sensor back to a central measurement station. Data is then collected from each sensor on the network at a constant sampling rate regardless of the current timescales at which events are acting on the structure. These conventional SHM sensor networks have a number of shortfalls. They tend to have a large number of cables that can represent a single point of failure for each sensor as well as add significant weight and installation costs. The constant sampling rate associated with each sensor very quickly leads to large amounts of data that must be analyzed, stored, and possibly transmitted to a remote user. This leads to increased demands on power consumption, bandwidth, and size. It also taxes our current techniques for managing large amounts of data. For the last decade the goal of the SHM community has been to endow structures with the functionality of a biological nervous system. Despite this goal the community has predominantly ignored the biological nervous system as inspiration for building structural nervous systems, choosing instead to focus on experimental mechanics and simulation techniques. In this work we explore the use of a novel, bio-inspired, SHM skin. This skin makes use of distributed computing and asynchronous communication techniques to alleviate the scale of the data management challenge as well as reduce power. The system also periodically sends a ‘heat beat’ signal to provide state-of-health updates. This conductive skin was implemented using conductive ink resistors as well as with graphene-oxide capacitors. (paper)

Moving Bodies beyond the Social/Biological Divide: Toward Theoretical and Transdisciplinary Adventures

Science.gov (United States)

Thorpe, Holly

2014-01-01

In this paper I call for "new forms of thinking and new ways of theorizing" the complex relations between the biological and social in sport and physical culture. I illustrate the inseparability of our biological and social bodies in sport and physical culture via the case of exercise and female reproductive hormones. Inspired by…

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.

Bacteriophage lambda: The path from biology to theranostic agent.

Science.gov (United States)

Catalano, Carlos E

2018-03-13

Viral particles provide an attractive platform for the engineering of semisynthetic therapeutic nanoparticles. They can be modified both genetically and chemically in a defined manner to alter their surface characteristics, for targeting specific cell types, to improve their pharmacokinetic features and to attenuate (or enhance) their antigenicity. These advantages derive from a detailed understanding of virus biology, gleaned from decades of fundamental genetic, biochemical, and structural studies that have provided mechanistic insight into virus assembly pathways. In particular, bacteriophages offer significant advantages as nanoparticle platforms and several have been adapted toward the design and engineering of "designer" nanoparticles for therapeutic and diagnostic (theranostic) applications. The present review focuses on one such virus, bacteriophage lambda; I discuss the biology of lambda, the tools developed to faithfully recapitulate the lambda assembly reactions in vitro and the observations that have led to cooptation of the lambda system for nanoparticle design. This discussion illustrates how a fundamental understanding of virus assembly has allowed the rational design and construction of semisynthetic nanoparticles as potential theranostic agents and illustrates the concept of benchtop to bedside translational research. This article is categorized under: Biology-Inspired Nanomaterials> Protein and Virus-Based Structures Biology-Inspired Nanomaterials> Nucleic Acid-Based Structures. © 2018 Wiley Periodicals, Inc.

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

Science.gov (United States)

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

2017-07-01

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

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.

Practices of Waldorf-Inspired Schools. Research Brief

Science.gov (United States)

Friedlaender, Diane; Beckham, Kyle; Zheng, Xinhua; Darling-Hammond, Linda

2015-01-01

"Growing a Waldorf-Inspired Approach in a Public School District" documents the practices and outcomes of Alice Birney, a Waldorf-Inspired School in Sacramento City Unified School District (SCUSD). This study highlights how such a school addresses students' academic, social, emotional, physical, and creative development. The study also…

The mechanics of soft biological composites.

Energy Technology Data Exchange (ETDEWEB)

Nguyen, Thao D. (Sandia National Laboratories, Livermore, CA); Grazier, John Mark; Boyce, Brad Lee; Jones, Reese E. (Sandia National Laboratories, Livermore, CA)

2007-10-01

Biological tissues are uniquely structured materials with technologically appealing properties. Soft tissues such as skin, are constructed from a composite of strong fibrils and fluid-like matrix components. This was the first coordinated experimental/modeling project at Sandia or in the open literature to consider the mechanics of micromechanically-based anisotropy and viscoelasticity of soft biological tissues. We have exploited and applied Sandia's expertise in experimentation and mechanics modeling to better elucidate the behavior of collagen fibril-reinforced soft tissues. The purpose of this project was to provide a detailed understanding of the deformation of ocular tissues, specifically the highly structured skin-like tissue in the cornea. This discovery improved our knowledge of soft/complex materials testing and modeling. It also provided insight into the way that cornea tissue is bio-engineered such that under physiologically-relevant conditions it has a unique set of properties which enhance functionality. These results also provide insight into how non-physiologic loading conditions, such as corrective surgeries, may push the cornea outside of its natural design window, resulting in unexpected non-linear responses. Furthermore, this project created a clearer understanding of the mechanics of soft tissues that could lead to bio-inspired materials, such as highly supple and impact resistant body armor, and improve our design of human-machine interfaces, such as micro-electrical-mechanical (MEMS) based prosthetics.

Approximate Waveforms for Extreme-Mass-Ratio Inspirals: The Chimera Scheme

International Nuclear Information System (INIS)

Sopuerta, Carlos F; Yunes, Nicolás

2012-01-01

We describe a new kludge scheme to model the dynamics of generic extreme-mass-ratio inspirals (EMRIs; stellar compact objects spiraling into a spinning supermassive black hole) and their gravitational-wave emission. The Chimera scheme is a hybrid method that combines tools from different approximation techniques in General Relativity: (i) A multipolar, post-Minkowskian expansion for the far-zone metric perturbation (the gravitational waveforms) and for the local prescription of the self-force; (ii) a post-Newtonian expansion for the computation of the multipole moments in terms of the trajectories; and (iii) a BH perturbation theory expansion when treating the trajectories as a sequence of self-adjusting Kerr geodesies. The EMRI trajectory is made out of Kerr geodesic fragments joined via the method of osculating elements as dictated by the multipolar post-Minkowskian radiation-reaction prescription. We implemented the proper coordinate mapping between Boyer-Lindquist coordinates, associated with the Kerr geodesies, and harmonic coordinates, associated with the multipolar post-Minkowskian decomposition. The Chimera scheme is thus a combination of approximations that can be used to model generic inspirals of systems with extreme to intermediate mass ratios, and hence, it can provide valuable information for future space-based gravitational-wave observatories, like LISA, and even for advanced ground detectors. The local character in time of our multipolar post-Minkowskian self-force makes this scheme amenable to study the possible appearance of transient resonances in generic inspirals.

Function of dynamic models in systems biology: linking structure to behaviour.

Science.gov (United States)

Knüpfer, Christian; Beckstein, Clemens

2013-10-08

Dynamic models in Systems Biology are used in computational simulation experiments for addressing biological questions. The complexity of the modelled biological systems and the growing number and size of the models calls for computer support for modelling and simulation in Systems Biology. This computer support has to be based on formal representations of relevant knowledge fragments. In this paper we describe different functional aspects of dynamic models. This description is conceptually embedded in our "meaning facets" framework which systematises the interpretation of dynamic models in structural, functional and behavioural facets. Here we focus on how function links the structure and the behaviour of a model. Models play a specific role (teleological function) in the scientific process of finding explanations for dynamic phenomena. In order to fulfil this role a model has to be used in simulation experiments (pragmatical function). A simulation experiment always refers to a specific situation and a state of the model and the modelled system (conditional function). We claim that the function of dynamic models refers to both the simulation experiment executed by software (intrinsic function) and the biological experiment which produces the phenomena under investigation (extrinsic function). We use the presented conceptual framework for the function of dynamic models to review formal accounts for functional aspects of models in Systems Biology, such as checklists, ontologies, and formal languages. Furthermore, we identify missing formal accounts for some of the functional aspects. In order to fill one of these gaps we propose an ontology for the teleological function of models. We have thoroughly analysed the role and use of models in Systems Biology. The resulting conceptual framework for the function of models is an important first step towards a comprehensive formal representation of the functional knowledge involved in the modelling and simulation process

Continuum robot arms inspired by cephalopods

Science.gov (United States)

Walker, Ian D.; Dawson, Darren M.; Flash, Tamar; Grasso, Frank W.; Hanlon, Roger T.; Hochner, Binyamin; Kier, William M.; Pagano, Christopher C.; Rahn, Christopher D.; Zhang, Qiming M.

2005-05-01

In this paper, we describe our recent results in the development of a new class of soft, continuous backbone ("continuum") robot manipulators. Our work is strongly motivated by the dexterous appendages found in cephalopods, particularly the arms and suckers of octopus, and the arms and tentacles of squid. Our ongoing investigation of these animals reveals interesting and unexpected functional aspects of their structure and behavior. The arrangement and dynamic operation of muscles and connective tissue observed in the arms of a variety of octopus species motivate the underlying design approach for our soft manipulators. These artificial manipulators feature biomimetic actuators, including artificial muscles based on both electro-active polymers (EAP) and pneumatic (McKibben) muscles. They feature a "clean" continuous backbone design, redundant degrees of freedom, and exhibit significant compliance that provides novel operational capacities during environmental interaction and object manipulation. The unusual compliance and redundant degrees of freedom provide strong potential for application to delicate tasks in cluttered and/or unstructured environments. Our aim is to endow these compliant robotic mechanisms with the diverse and dexterous grasping behavior observed in octopuses. To this end, we are conducting fundamental research into the manipulation tactics, sensory biology, and neural control of octopuses. This work in turn leads to novel approaches to motion planning and operator interfaces for the robots. The paper describes the above efforts, along with the results of our development of a series of continuum tentacle-like robots, demonstrating the unique abilities of biologically-inspired design.

Business Inspiration: Small Business Leadership in Recovery?

Science.gov (United States)

Rae, David; Price, Liz; Bosworth, Gary; Parkinson, Paul

2012-01-01

Business Inspiration was a short, action-centred leadership and innovation development programme designed for owners and managers of smaller firms to address business survival and repositioning needs arising from the UK's economic downturn. The article examines the design and delivery of Business Inspiration and the impact of the programme on…

Quantitative computational models of molecular self-assembly in systems biology.

Science.gov (United States)

Thomas, Marcus; Schwartz, Russell

2017-05-23

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally.

Setting Parameters for Biological Models With ANIMO

NARCIS (Netherlands)

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

2014-01-01

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

Nature inspires sensors to do more with less.

Science.gov (United States)

Mulvaney, Shawn P; Sheehan, Paul E

2014-10-28

The world is filled with widely varying chemical, physical, and biological stimuli. Over millennia, organisms have refined their senses to cope with these diverse stimuli, becoming virtuosos in differentiating closely related antigens, handling extremes in concentration, resetting the spent sensing mechanisms, and processing the multiple data streams being generated. Nature successfully deals with both repeating and new stimuli, demonstrating great adaptability when confronted with the latter. Interestingly, nature accomplishes these feats using a fairly simple toolbox. The sensors community continues to draw inspiration from nature's example: just look at the antibodies used as biosensor capture agents or the neural networks that process multivariate data streams. Indeed, many successful sensors have been built by simply mimicking natural systems. However, some of the most exciting breakthroughs occur when the community moves beyond mimicking nature and learns to use nature's tools in innovative ways.

Toward computational cumulative biology by combining models of biological datasets.

Science.gov (United States)

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

2014-01-01

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

Natural Inspired Intelligent Visual Computing and Its Application to Viticulture.

Science.gov (United States)

Ang, Li Minn; Seng, Kah Phooi; Ge, Feng Lu

2017-05-23

This paper presents an investigation of natural inspired intelligent computing and its corresponding application towards visual information processing systems for viticulture. The paper has three contributions: (1) a review of visual information processing applications for viticulture; (2) the development of natural inspired computing algorithms based on artificial immune system (AIS) techniques for grape berry detection; and (3) the application of the developed algorithms towards real-world grape berry images captured in natural conditions from vineyards in Australia. The AIS algorithms in (2) were developed based on a nature-inspired clonal selection algorithm (CSA) which is able to detect the arcs in the berry images with precision, based on a fitness model. The arcs detected are then extended to perform the multiple arcs and ring detectors information processing for the berry detection application. The performance of the developed algorithms were compared with traditional image processing algorithms like the circular Hough transform (CHT) and other well-known circle detection methods. The proposed AIS approach gave a Fscore of 0.71 compared with Fscores of 0.28 and 0.30 for the CHT and a parameter-free circle detection technique (RPCD) respectively.

Thermodynamic modeling of transcription: sensitivity analysis differentiates biological mechanism from mathematical model-induced effects.

Science.gov (United States)

Dresch, Jacqueline M; Liu, Xiaozhou; Arnosti, David N; Ay, Ahmet

2010-10-24

Quantitative models of gene expression generate parameter values that can shed light on biological features such as transcription factor activity, cooperativity, and local effects of repressors. An important element in such investigations is sensitivity analysis, which determines how strongly a model's output reacts to variations in parameter values. Parameters of low sensitivity may not be accurately estimated, leading to unwarranted conclusions. Low sensitivity may reflect the nature of the biological data, or it may be a result of the model structure. Here, we focus on the analysis of thermodynamic models, which have been used extensively to analyze gene transcription. Extracted parameter values have been interpreted biologically, but until now little attention has been given to parameter sensitivity in this context. We apply local and global sensitivity analyses to two recent transcriptional models to determine the sensitivity of individual parameters. We show that in one case, values for repressor efficiencies are very sensitive, while values for protein cooperativities are not, and provide insights on why these differential sensitivities stem from both biological effects and the structure of the applied models. In a second case, we demonstrate that parameters that were thought to prove the system's dependence on activator-activator cooperativity are relatively insensitive. We show that there are numerous parameter sets that do not satisfy the relationships proferred as the optimal solutions, indicating that structural differences between the two types of transcriptional enhancers analyzed may not be as simple as altered activator cooperativity. Our results emphasize the need for sensitivity analysis to examine model construction and forms of biological data used for modeling transcriptional processes, in order to determine the significance of estimated parameter values for thermodynamic models. Knowledge of parameter sensitivities can provide the necessary

Computerised modelling for developmental biology : an exploration with case studies

NARCIS (Netherlands)

Bertens, Laura M.F.

2012-01-01

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

Notions of similarity for systems biology models.

Science.gov (United States)

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

2018-01-01

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

METABOLIC MODELLING IN THE DEVELOPMENT OF CELL FACTORIES BY SYNTHETIC BIOLOGY

Directory of Open Access Journals (Sweden)

Paula Jouhten

2012-10-01

Full Text Available Cell factories are commonly microbial organisms utilized for bioconversion of renewable resources to bulk or high value chemicals. Introduction of novel production pathways in chassis strains is the core of the development of cell factories by synthetic biology. Synthetic biology aims to create novel biological functions and systems not found in nature by combining biology with engineering. The workflow of the development of novel cell factories with synthetic biology is ideally linear which will be attainable with the quantitative engineering approach, high-quality predictive models, and libraries of well-characterized parts. Different types of metabolic models, mathematical representations of metabolism and its components, enzymes and metabolites, are useful in particular phases of the synthetic biology workflow. In this minireview, the role of metabolic modelling in synthetic biology will be discussed with a review of current status of compatible methods and models for the in silico design and quantitative evaluation of a cell factory.

Nature as inspiration for leisure education

OpenAIRE

ŠPIRHANZLOVÁ, Andrea

2017-01-01

The thesis deals with the organization of leisure activities where the main tool and inspiration is nature. The theoretical part defines basic concepts of pedagogy of free time and points to the possibility of using nature as an inspiration not only for creating content components of leisure activities, but also as the environment in which the pedagogical - educational process of activities takes place. The practical part contains specific pedagogical - educational activity whose essence is b...

Modeling of nonlinear biological phenomena modeled by S-systems.

Science.gov (United States)

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

2014-03-01

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

Markov Chain-Like Quantum Biological Modeling of Mutations, Aging, and Evolution

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Ivan B. Djordjevic

2015-08-01

Full Text Available Recent evidence suggests that quantum mechanics is relevant in photosynthesis, magnetoreception, enzymatic catalytic reactions, olfactory reception, photoreception, genetics, electron-transfer in proteins, and evolution; to mention few. In our recent paper published in Life, we have derived the operator-sum representation of a biological channel based on codon basekets, and determined the quantum channel model suitable for study of the quantum biological channel capacity. However, this model is essentially memoryless and it is not able to properly model the propagation of mutation errors in time, the process of aging, and evolution of genetic information through generations. To solve for these problems, we propose novel quantum mechanical models to accurately describe the process of creation spontaneous, induced, and adaptive mutations and their propagation in time. Different biological channel models with memory, proposed in this paper, include: (i Markovian classical model, (ii Markovian-like quantum model, and (iii hybrid quantum-classical model. We then apply these models in a study of aging and evolution of quantum biological channel capacity through generations. We also discuss key differences of these models with respect to a multilevel symmetric channel-based Markovian model and a Kimura model-based Markovian process. These models are quite general and applicable to many open problems in biology, not only biological channel capacity, which is the main focus of the paper. We will show that the famous quantum Master equation approach, commonly used to describe different biological processes, is just the first-order approximation of the proposed quantum Markov chain-like model, when the observation interval tends to zero. One of the important implications of this model is that the aging phenotype becomes determined by different underlying transition probabilities in both programmed and random (damage Markov chain-like models of aging, which

Generative models versus underlying symmetries to explain biological pattern.

Science.gov (United States)

Frank, S A

2014-06-01

Mathematical models play an increasingly important role in the interpretation of biological experiments. Studies often present a model that generates the observations, connecting hypothesized process to an observed pattern. Such generative models confirm the plausibility of an explanation and make testable hypotheses for further experiments. However, studies rarely consider the broad family of alternative models that match the same observed pattern. The symmetries that define the broad class of matching models are in fact the only aspects of information truly revealed by observed pattern. Commonly observed patterns derive from simple underlying symmetries. This article illustrates the problem by showing the symmetry associated with the observed rate of increase in fitness in a constant environment. That underlying symmetry reveals how each particular generative model defines a single example within the broad class of matching models. Further progress on the relation between pattern and process requires deeper consideration of the underlying symmetries. © 2014 The Author. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Modified Eddington-inspired-Born-Infeld Gravity with a Trace Term

Energy Technology Data Exchange (ETDEWEB)

Chen, Che-Yu [National Taiwan University, Department of Physics, Taipei (China); LeCosPA, National Taiwan University, Taipei (China); National Taiwan University, Graduate Institute of Astrophysics, Taipei (China); Bouhmadi-Lopez, Mariam [Universidade da Beira Interior, Departamento de Fisica, Covilha (Portugal); Centro de Matematica e Aplicacoes da Universidade da Beira Interior (CMA-UBI), Covilha (Portugal); University of the Basque Country UPV/EHU, Department of Theoretical Physics, P.O. Box 644, Bilbao (Spain); IKERBASQUE, Basque Foundation for Science, Bilbao (Spain); Chen, Pisin [National Taiwan University, Department of Physics, Taipei (China); LeCosPA, National Taiwan University, Taipei (China); National Taiwan University, Graduate Institute of Astrophysics, Taipei (China); Stanford University, SLAC National Accelerator Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Stanford, CA (United States)

2016-01-15

In this paper, a modified Eddington-inspired-Born-Infeld (EiBI) theory with a pure trace term g{sub μν}R being added to the determinantal action is analysed from a cosmological point of view. It corresponds to the most general action constructed from a rank two tensor that contains up to first order terms in curvature. This term can equally be seen as a conformal factor multiplying the metric g{sub μν}. This very interesting type of amendment has not been considered within the Palatini formalism despite the large amount of works on the Born-Infeld-inspired theory of gravity. This model can provide smooth bouncing solutions which were not allowed in the EiBI model for the same EiBI coupling. Most interestingly, for a radiation filled universe there are some regions of the parameter space that can naturally lead to a de Sitter inflationary stage without the need of any exotic matter field. Finally, in this model we discover a new type of cosmic ''quasi-sudden'' singularity, where the cosmic time derivative of the Hubble rate becomes very large but finite at a finite cosmic time. (orig.)

Inspiration and the Texts of the Bible

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Dirk Buchner

1997-12-01

Full Text Available This article seeks to explore what the inspired text of the Old Testament was as it existed for the New Testament authors, particularly for the author of the book of Hebrews. A quick look at the facts makes. it clear that there was, at the time, more than one 'inspired' text, among these were the Septuagint and the Masoretic Text 'to name but two'. The latter eventually gained ascendancy which is why it forms the basis of our translated Old Testament today. Yet we have to ask: what do we make of that other text that was the inspired Bible to the early Church, especially to the writer of the book of Hebrews, who ignored the Masoretic text? This article will take a brief look at some suggestions for a doctrine of inspiration that keeps up with the facts of Scripture. Allied to this, the article is something of a bibliographical study of recent developments in textual research following the discovery of the Dead Sea scrolls.

Biologic Constraints on Modelling Virus Assembly

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Robert L. Garcea

2008-01-01

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

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

cellPACK: a virtual mesoscope to model and visualize structural systems biology.

Science.gov (United States)

Johnson, Graham T; Autin, Ludovic; Al-Alusi, Mostafa; Goodsell, David S; Sanner, Michel F; Olson, Arthur J

2015-01-01

cellPACK assembles computational models of the biological mesoscale, an intermediate scale (10-100 nm) between molecular and cellular biology scales. cellPACK's modular architecture unites existing and novel packing algorithms to generate, visualize and analyze comprehensive three-dimensional models of complex biological environments that integrate data from multiple experimental systems biology and structural biology sources. cellPACK is available as open-source code, with tools for validation of models and with 'recipes' and models for five biological systems: blood plasma, cytoplasm, synaptic vesicles, HIV and a mycoplasma cell. We have applied cellPACK to model distributions of HIV envelope protein to test several hypotheses for consistency with experimental observations. Biologists, educators and outreach specialists can interact with cellPACK models, develop new recipes and perform packing experiments through scripting and graphical user interfaces at http://cellPACK.org/.

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

OpenAIRE

Matthew P. Adams; Catherine J. Collier; Sven Uthicke; Yan X. Ow; Lucas Langlois; Katherine R. O’Brien

2017-01-01

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluat...

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.

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.

Modeling of Biological Intelligence for SCM System Optimization

Science.gov (United States)

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

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms. PMID:22162724

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

International Nuclear Information System (INIS)

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

2014-01-01

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

Firefly Luciferin-Inspired Biocompatible Chemistry for Protein Labeling and In Vivo Imaging.

Science.gov (United States)

Wang, Yuqi; An, Ruibing; Luo, Zhiliang; Ye, Deju

2018-04-17

Biocompatible reactions have emerged as versatile tools to build various molecular imaging probes that hold great promise for the detection of biological processes in vitro and/or in vivo. In this Minireview, we describe the recent advances in the development of a firefly luciferin-inspired biocompatible reaction between cyanobenzothiazole (CBT) and cysteine (Cys), and highlight its versatility to label proteins and build multimodality molecular imaging probes. The review starts from the general introduction of biocompatible reactions, which is followed by briefly describing the development of the firefly luciferin-inspired biocompatible chemistry. We then discuss its applications for the specific protein labeling and for the development of multimodality imaging probes (fluorescence, bioluminescence, MRI, PET, photoacoustic, etc.) that enable high sensitivity and spatial resolution imaging of redox environment, furin and caspase-3/7 activity in living cells and mice. Finally, we offer the conclusions and our perspective on the various and potential applications of this reaction. We hope that this review will contribute to the research of biocompatible reactions for their versatile applications in protein labeling and molecular imaging. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species.

Science.gov (United States)

Adams, Matthew P; Collier, Catherine J; Uthicke, Sven; Ow, Yan X; Langlois, Lucas; O'Brien, Katherine R

2017-01-04

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (T opt ) for maximum photosynthetic rate (P max ). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

Science.gov (United States)

Adams, Matthew P.; Collier, Catherine J.; Uthicke, Sven; Ow, Yan X.; Langlois, Lucas; O'Brien, Katherine R.

2017-01-01

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (Topt) for maximum photosynthetic rate (Pmax). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

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

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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.

Nature-Inspired Design : Strategies for Sustainable Product Development

NARCIS (Netherlands)

De Pauw, I.C.

2015-01-01

Product designers can apply different strategies, methods, and tools for sustainable product development. Nature-Inspired Design Strategies (NIDS) offer designers a distinct class of strategies that use ‘nature’ as a guiding source of knowledge and inspiration for addressing sustainability.

Multi-level and hybrid modelling approaches for systems biology.

Science.gov (United States)

Bardini, R; Politano, G; Benso, A; Di Carlo, S

2017-01-01

During the last decades, high-throughput techniques allowed for the extraction of a huge amount of data from biological systems, unveiling more of their underling complexity. Biological systems encompass a wide range of space and time scales, functioning according to flexible hierarchies of mechanisms making an intertwined and dynamic interplay of regulations. This becomes particularly evident in processes such as ontogenesis, where regulative assets change according to process context and timing, making structural phenotype and architectural complexities emerge from a single cell, through local interactions. The information collected from biological systems are naturally organized according to the functional levels composing the system itself. In systems biology, biological information often comes from overlapping but different scientific domains, each one having its own way of representing phenomena under study. That is, the different parts of the system to be modelled may be described with different formalisms. For a model to have improved accuracy and capability for making a good knowledge base, it is good to comprise different system levels, suitably handling the relative formalisms. Models which are both multi-level and hybrid satisfy both these requirements, making a very useful tool in computational systems biology. This paper reviews some of the main contributions in this field.

Dynamic Modelling for Planar Extensible Continuum Robot Manipulators

Science.gov (United States)

2006-01-01

to the OCTARM continuum ma- nipulator. The OCTARM manipulator is a biologically inspired soft robot manipulator resembling an elephant trunk or an... octopus arm [18]. The OCTARM, shown in Figure 1, is a three-section robot with nine degrees of freedom. Aside from two axis bending with constant...increasing interest in designing �biologically inspired � continuum robots . Some of these designs are mimicking trunks [8], [25], tentacles [17], [21], [24

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.

Systematic integration of experimental data and models in systems biology.