biologically inspired visual: Topics by Science.gov

Sample records for biologically inspired visual

Endogenous Biologically Inspired Art of Complex Systems.

PubMed

Ji, Haru; Wakefield, Graham

2016-01-01

Since 2007, Graham Wakefield and Haru Ji have looked to nature for inspiration as they have created a series of "artificial natures," or interactive visualizations of biologically inspired complex systems that can evoke nature-like aesthetic experiences within mixed-reality art installations. This article describes how they have applied visualization, sonification, and interaction design in their work with artificial ecosystems and organisms using specific examples from their exhibited installations.
Feature extraction inspired by V1 in visual cortex

NASA Astrophysics Data System (ADS)

Lv, Chao; Xu, Yuelei; Zhang, Xulei; Ma, Shiping; Li, Shuai; Xin, Peng; Zhu, Mingning; Ma, Hongqiang

2018-04-01

Target feature extraction plays an important role in pattern recognition. It is the most complicated activity in the brain mechanism of biological vision. Inspired by high properties of primary visual cortex (V1) in extracting dynamic and static features, a visual perception model was raised. Firstly, 28 spatial-temporal filters with different orientations, half-squaring operation and divisive normalization were adopted to obtain the responses of V1 simple cells; then, an adjustable parameter was added to the output weight so that the response of complex cells was got. Experimental results indicate that the proposed V1 model can perceive motion information well. Besides, it has a good edge detection capability. The model inspired by V1 has good performance in feature extraction and effectively combines brain-inspired intelligence with computer vision.
Deep Neural Networks: A New Framework for Modeling Biological Vision and Brain Information Processing.

PubMed

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

PubMed

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

2014-09-01

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

PubMed

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.
Biologically Inspired Strategies, Algorithms and Hardware for Visual Guidance of Autonomous Helicopters

DTIC Science & Technology

2011-05-02

Dacke, J. Reinhard and M.V. Srinivasan (2010) The moment before touchdown: Landing manoeuvres of the honeybee Apis mellifera . Journal of Experimental...moment before touchdown: Landing manoeuvres of the honeybee Apis mellifera . Journal of Experimental Biology 213, 262-270. M.V. Srinivasan (2010
Fast neuromimetic object recognition using FPGA outperforms GPU implementations.

PubMed

Orchard, Garrick; Martin, Jacob G; Vogelstein, R Jacob; Etienne-Cummings, Ralph

2013-08-01

Recognition of objects in still images has traditionally been regarded as a difficult computational problem. Although modern automated methods for visual object recognition have achieved steadily increasing recognition accuracy, even the most advanced computational vision approaches are unable to obtain performance equal to that of humans. This has led to the creation of many biologically inspired models of visual object recognition, among them the hierarchical model and X (HMAX) model. HMAX is traditionally known to achieve high accuracy in visual object recognition tasks at the expense of significant computational complexity. Increasing complexity, in turn, increases computation time, reducing the number of images that can be processed per unit time. In this paper we describe how the computationally intensive and biologically inspired HMAX model for visual object recognition can be modified for implementation on a commercial field-programmable aate Array, specifically the Xilinx Virtex 6 ML605 evaluation board with XC6VLX240T FPGA. We show that with minor modifications to the traditional HMAX model we can perform recognition on images of size 128 × 128 pixels at a rate of 190 images per second with a less than 1% loss in recognition accuracy in both binary and multiclass visual object recognition tasks.
Visual Cortex Inspired CNN Model for Feature Construction in Text Analysis

PubMed Central

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

2016-01-01

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

PubMed

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

2016-01-01

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

PubMed

Gatys, Leon A; Ecker, Alexander S; Bethge, Matthias

2017-10-01

Although the study of biological vision and computer vision attempt to understand powerful visual information processing from different angles, they have a long history of informing each other. Recent advances in texture synthesis that were motivated by visual neuroscience have led to a substantial advance in image synthesis and manipulation in computer vision using convolutional neural networks (CNNs). Here, we review these recent advances and discuss how they can in turn inspire new research in visual perception and computational neuroscience. Copyright © 2017. Published by Elsevier Ltd.
a Novel Ship Detection Method for Large-Scale Optical Satellite Images Based on Visual Lbp Feature and Visual Attention Model

NASA Astrophysics Data System (ADS)

Haigang, Sui; Zhina, Song

2016-06-01

Reliably ship detection in optical satellite images has a wide application in both military and civil fields. However, this problem is very difficult in complex backgrounds, such as waves, clouds, and small islands. Aiming at these issues, this paper explores an automatic and robust model for ship detection in large-scale optical satellite images, which relies on detecting statistical signatures of ship targets, in terms of biologically-inspired visual features. This model first selects salient candidate regions across large-scale images by using a mechanism based on biologically-inspired visual features, combined with visual attention model with local binary pattern (CVLBP). Different from traditional studies, the proposed algorithm is high-speed and helpful to focus on the suspected ship areas avoiding the separation step of land and sea. Largearea images are cut into small image chips and analyzed in two complementary ways: Sparse saliency using visual attention model and detail signatures using LBP features, thus accordant with sparseness of ship distribution on images. Then these features are employed to classify each chip as containing ship targets or not, using a support vector machine (SVM). After getting the suspicious areas, there are still some false alarms such as microwaves and small ribbon clouds, thus simple shape and texture analysis are adopted to distinguish between ships and nonships in suspicious areas. Experimental results show the proposed method is insensitive to waves, clouds, illumination and ship size.
Honeybees as a model for the study of visually guided flight, navigation, and biologically inspired robotics.

PubMed

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

PubMed

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

2016-10-01

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

PubMed

Porod, Wolfgang; Werblin, Frank; Chua, Leon O; Roska, Tamas; Rodriguez-Vazquez, Angel; Roska, Botond; Fay, Patrick; Bernstein, Gary H; Huang, Yih-Fang; Csurgay, Arpad I

2004-05-01

Nanotechnology opens new ways to utilize recent discoveries in biological image processing by translating the underlying functional concepts into the design of CNN (cellular neural/nonlinear network)-based systems incorporating nanoelectronic devices. There is a natural intersection joining studies of retinal processing, spatio-temporal nonlinear dynamics embodied in CNN, and the possibility of miniaturizing the technology through nanotechnology. This intersection serves as the springboard for our multidisciplinary project. Biological feature and motion detectors map directly into the spatio-temporal dynamics of CNN for target recognition, image stabilization, and tracking. The neural interactions underlying color processing will drive the development of nanoscale multispectral sensor arrays for image fusion. Implementing such nanoscale sensors on a CNN platform will allow the implementation of device feedback control, a hallmark of biological sensory systems. These biologically inspired CNN subroutines are incorporated into the new world of analog-and-logic algorithms and software, containing also many other active-wave computing mechanisms, including nature-inspired (physics and chemistry) as well as PDE-based sophisticated spatio-temporal algorithms. Our goal is to design and develop several miniature prototype devices for target detection, navigation, tracking, and robotics. This paper presents an example illustrating the synergies emerging from the convergence of nanotechnology, biotechnology, and information and cognitive science.
Zebrafish response to a robotic replica in three dimensions

PubMed Central

Ruberto, Tommaso; Mwaffo, Violet; Singh, Sukhgewanpreet; Neri, Daniele

2016-01-01

As zebrafish emerge as a species of choice for the investigation of biological processes, a number of experimental protocols are being developed to study their social behaviour. While live stimuli may elicit varying response in focal subjects owing to idiosyncrasies, tiredness and circadian rhythms, video stimuli suffer from the absence of physical input and rely only on two-dimensional projections. Robotics has been recently proposed as an alternative approach to generate physical, customizable, effective and consistent stimuli for behavioural phenotyping. Here, we contribute to this field of investigation through a novel four-degree-of-freedom robotics-based platform to manoeuvre a biologically inspired three-dimensionally printed replica. The platform enables three-dimensional motions as well as body oscillations to mimic zebrafish locomotion. In a series of experiments, we demonstrate the differential role of the visual stimuli associated with the biologically inspired replica and its three-dimensional motion. Three-dimensional tracking and information-theoretic tools are complemented to quantify the interaction between zebrafish and the robotic stimulus. Live subjects displayed a robust attraction towards the moving replica, and such attraction was lost when controlling for its visual appearance or motion. This effort is expected to aid zebrafish behavioural phenotyping, by offering a novel approach to generate physical stimuli moving in three dimensions. PMID:27853566
Objects Classification by Learning-Based Visual Saliency Model and Convolutional Neural Network.

PubMed

Li, Na; Zhao, Xinbo; Yang, Yongjia; Zou, Xiaochun

2016-01-01

Humans can easily classify different kinds of objects whereas it is quite difficult for computers. As a hot and difficult problem, objects classification has been receiving extensive interests with broad prospects. Inspired by neuroscience, deep learning concept is proposed. Convolutional neural network (CNN) as one of the methods of deep learning can be used to solve classification problem. But most of deep learning methods, including CNN, all ignore the human visual information processing mechanism when a person is classifying objects. Therefore, in this paper, inspiring the completed processing that humans classify different kinds of objects, we bring forth a new classification method which combines visual attention model and CNN. Firstly, we use the visual attention model to simulate the processing of human visual selection mechanism. Secondly, we use CNN to simulate the processing of how humans select features and extract the local features of those selected areas. Finally, not only does our classification method depend on those local features, but also it adds the human semantic features to classify objects. Our classification method has apparently advantages in biology. Experimental results demonstrated that our method made the efficiency of classification improve significantly.
Enhanced HMAX model with feedforward feature learning for multiclass categorization.

PubMed

Li, Yinlin; Wu, Wei; Zhang, Bo; Li, Fengfu

2015-01-01

In recent years, the interdisciplinary research between neuroscience and computer vision has promoted the development in both fields. Many biologically inspired visual models are proposed, and among them, the Hierarchical Max-pooling model (HMAX) is a feedforward model mimicking the structures and functions of V1 to posterior inferotemporal (PIT) layer of the primate visual cortex, which could generate a series of position- and scale- invariant features. However, it could be improved with attention modulation and memory processing, which are two important properties of the primate visual cortex. Thus, in this paper, based on recent biological research on the primate visual cortex, we still mimic the first 100-150 ms of visual cognition to enhance the HMAX model, which mainly focuses on the unsupervised feedforward feature learning process. The main modifications are as follows: (1) To mimic the attention modulation mechanism of V1 layer, a bottom-up saliency map is computed in the S1 layer of the HMAX model, which can support the initial feature extraction for memory processing; (2) To mimic the learning, clustering and short-term memory to long-term memory conversion abilities of V2 and IT, an unsupervised iterative clustering method is used to learn clusters with multiscale middle level patches, which are taken as long-term memory; (3) Inspired by the multiple feature encoding mode of the primate visual cortex, information including color, orientation, and spatial position are encoded in different layers of the HMAX model progressively. By adding a softmax layer at the top of the model, multiclass categorization experiments can be conducted, and the results on Caltech101 show that the enhanced model with a smaller memory size exhibits higher accuracy than the original HMAX model, and could also achieve better accuracy than other unsupervised feature learning methods in multiclass categorization task.
Advanced biologically plausible algorithms for low-level image processing

NASA Astrophysics Data System (ADS)

Gusakova, Valentina I.; Podladchikova, Lubov N.; Shaposhnikov, Dmitry G.; Markin, Sergey N.; Golovan, Alexander V.; Lee, Seong-Whan

1999-08-01

At present, in computer vision, the approach based on modeling the biological vision mechanisms is extensively developed. However, up to now, real world image processing has no effective solution in frameworks of both biologically inspired and conventional approaches. Evidently, new algorithms and system architectures based on advanced biological motivation should be developed for solution of computational problems related to this visual task. Basic problems that should be solved for creation of effective artificial visual system to process real world imags are a search for new algorithms of low-level image processing that, in a great extent, determine system performance. In the present paper, the result of psychophysical experiments and several advanced biologically motivated algorithms for low-level processing are presented. These algorithms are based on local space-variant filter, context encoding visual information presented in the center of input window, and automatic detection of perceptually important image fragments. The core of latter algorithm are using local feature conjunctions such as noncolinear oriented segment and composite feature map formation. Developed algorithms were integrated into foveal active vision model, the MARR. It is supposed that proposed algorithms may significantly improve model performance while real world image processing during memorizing, search, and recognition.
Methods and Apparatus for Autonomous Robotic Control

NASA Technical Reports Server (NTRS)

Gorshechnikov, Anatoly (Inventor); Livitz, Gennady (Inventor); Versace, Massimiliano (Inventor); Palma, Jesse (Inventor)

2017-01-01

Sensory processing of visual, auditory, and other sensor information (e.g., visual imagery, LIDAR, RADAR) is conventionally based on "stovepiped," or isolated processing, with little interactions between modules. Biological systems, on the other hand, fuse multi-sensory information to identify nearby objects of interest more quickly, more efficiently, and with higher signal-to-noise ratios. Similarly, examples of the OpenSense technology disclosed herein use neurally inspired processing to identify and locate objects in a robot's environment. This enables the robot to navigate its environment more quickly and with lower computational and power requirements.
Visual control of navigation in insects and its relevance for robotics.

PubMed

Srinivasan, Mandyam V

2011-08-01

Flying insects display remarkable agility, despite their diminutive eyes and brains. This review describes our growing understanding of how these creatures use visual information to stabilize flight, avoid collisions with objects, regulate flight speed, detect and intercept other flying insects such as mates or prey, navigate to a distant food source, and orchestrate flawless landings. It also outlines the ways in which these insights are now being used to develop novel, biologically inspired strategies for the guidance of autonomous, airborne vehicles. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2003-10-01

In view of the growing complexity of computational tasks and their design, we propose that certain interactive systems may be better designed by utilizing computational strategies based on the study of the human brain. Compared with current engineering paradigms, brain theory offers the promise of improved self-organization and adaptation to the current environment, freeing the programmer from having to address those issues in a procedural manner when designing and implementing large-scale complex systems. To advance this hypothesis, we discus a multi-agent surveillance system where 12 agent CPUs each with its own camera, compete and cooperate to monitor a large room. To cope with the overload of image data streaming from 12 cameras, we take inspiration from the primate"s visual system, which allows the animal to operate a real-time selection of the few most conspicuous locations in visual input. This is accomplished by having each camera agent utilize the bottom-up, saliency-based visual attention algorithm of Itti and Koch (Vision Research 2000;40(10-12):1489-1506) to scan the scene for objects of interest. Real time operation is achieved using a distributed version that runs on a 16-CPU Beowulf cluster composed of the agent computers. The algorithm guides cameras to track and monitor salient objects based on maps of color, orientation, intensity, and motion. To spread camera view points or create cooperation in monitoring highly salient targets, camera agents bias each other by increasing or decreasing the weight of different feature vectors in other cameras, using mechanisms similar to excitation and suppression that have been documented in electrophysiology, psychophysics and imaging studies of low-level visual processing. In addition, if cameras need to compete for computing resources, allocation of computational time is weighed based upon the history of each camera. A camera agent that has a history of seeing more salient targets is more likely to obtain 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.
Extending human perception of electromagnetic radiation to the UV region through biologically inspired photochromic fuzzy logic (BIPFUL) systems.

PubMed

Gentili, Pier Luigi; Rightler, Amanda L; Heron, B Mark; Gabbutt, Christopher D

2016-01-25

Photochromic fuzzy logic systems have been designed that extend human visual perception into the UV region. The systems are founded on a detailed knowledge of the activation wavelengths and quantum yields of a series of thermally reversible photochromic compounds. By appropriate matching of the photochromic behaviour unique colour signatures are generated in response differing UV activation frequencies.
Complexity Level Analysis Revisited: What Can 30 Years of Hindsight Tell Us about How the Brain Might Represent Visual Information?

PubMed Central

Tsotsos, John K.

2017-01-01

Much has been written about how the biological brain might represent and process visual information, and how this might inspire and inform machine vision systems. Indeed, tremendous progress has been made, and especially during the last decade in the latter area. However, a key question seems too often, if not mostly, be ignored. This question is simply: do proposed solutions scale with the reality of the brain's resources? This scaling question applies equally to brain and to machine solutions. A number of papers have examined the inherent computational difficulty of visual information processing using theoretical and empirical methods. The main goal of this activity had three components: to understand the deep nature of the computational problem of visual information processing; to discover how well the computational difficulty of vision matches to the fixed resources of biological seeing systems; and, to abstract from the matching exercise the key principles that lead to the observed characteristics of biological visual performance. This set of components was termed complexity level analysis in Tsotsos (1987) and was proposed as an important complement to Marr's three levels of analysis. This paper revisits that work with the advantage that decades of hindsight can provide. PMID:28848458
Complexity Level Analysis Revisited: What Can 30 Years of Hindsight Tell Us about How the Brain Might Represent Visual Information?

PubMed

Tsotsos, John K

2017-01-01

Much has been written about how the biological brain might represent and process visual information, and how this might inspire and inform machine vision systems. Indeed, tremendous progress has been made, and especially during the last decade in the latter area. However, a key question seems too often, if not mostly, be ignored. This question is simply: do proposed solutions scale with the reality of the brain's resources? This scaling question applies equally to brain and to machine solutions. A number of papers have examined the inherent computational difficulty of visual information processing using theoretical and empirical methods. The main goal of this activity had three components: to understand the deep nature of the computational problem of visual information processing; to discover how well the computational difficulty of vision matches to the fixed resources of biological seeing systems; and, to abstract from the matching exercise the key principles that lead to the observed characteristics of biological visual performance. This set of components was termed complexity level analysis in Tsotsos (1987) and was proposed as an important complement to Marr's three levels of analysis. This paper revisits that work with the advantage that decades of hindsight can provide.
Visual learning in drosophila: application on a roving robot and comparisons

NASA Astrophysics Data System (ADS)

Arena, P.; De Fiore, S.; Patané, L.; Termini, P. S.; Strauss, R.

2011-05-01

Visual learning is an important aspect of fly life. Flies are able to extract visual cues from objects, like colors, vertical and horizontal distributedness, and others, that can be used for learning to associate a meaning to specific features (i.e. a reward or a punishment). Interesting biological experiments show trained stationary flying flies avoiding flying towards specific visual objects, appearing on the surrounding environment. Wild-type flies effectively learn to avoid those objects but this is not the case for the learning mutant rutabaga defective in the cyclic AMP dependent pathway for plasticity. A bio-inspired architecture has been proposed to model the fly behavior and experiments on roving robots were performed. Statistical comparisons have been considered and mutant-like effect on the model has been also investigated.
Creative design inspired by biological knowledge: Technologies and methods

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

PubMed Central

Brinkworth, Russell S. A.; O'Carroll, David C.

2009-01-01

The extraction of accurate self-motion information from the visual world is a difficult problem that has been solved very efficiently by biological organisms utilizing non-linear processing. Previous bio-inspired models for motion detection based on a correlation mechanism have been dogged by issues that arise from their sensitivity to undesired properties of the image, such as contrast, which vary widely between images. Here we present a model with multiple levels of non-linear dynamic adaptive components based directly on the known or suspected responses of neurons within the visual motion pathway of the fly brain. By testing the model under realistic high-dynamic range conditions we show that the addition of these elements makes the motion detection model robust across a large variety of images, velocities and accelerations. Furthermore the performance of the entire system is more than the incremental improvements offered by the individual components, indicating beneficial non-linear interactions between processing stages. The algorithms underlying the model can be implemented in either digital or analog hardware, including neuromorphic analog VLSI, but defy an analytical solution due to their dynamic non-linear operation. The successful application of this algorithm has applications in the development of miniature autonomous systems in defense and civilian roles, including robotics, miniature unmanned aerial vehicles and collision avoidance sensors. PMID:19893631
Neuro-inspired smart image sensor: analog Hmax implementation

NASA Astrophysics Data System (ADS)

Paindavoine, Michel; Dubois, Jérôme; Musa, Purnawarman

2015-03-01

Neuro-Inspired Vision approach, based on models from biology, allows to reduce the computational complexity. One of these models - The Hmax model - shows that the recognition of an object in the visual cortex mobilizes V1, V2 and V4 areas. From the computational point of view, V1 corresponds to the area of the directional filters (for example Sobel filters, Gabor filters or wavelet filters). This information is then processed in the area V2 in order to obtain local maxima. This new information is then sent to an artificial neural network. This neural processing module corresponds to area V4 of the visual cortex and is intended to categorize objects present in the scene. In order to realize autonomous vision systems (consumption of a few milliwatts) with such treatments inside, we studied and realized in 0.35μm CMOS technology prototypes of two image sensors in order to achieve the V1 and V2 processing of Hmax model.
Biological basis for space-variant sensor design I: parameters of monkey and human spatial vision

NASA Astrophysics Data System (ADS)

Rojer, Alan S.; Schwartz, Eric L.

1991-02-01

Biological sensor design has long provided inspiration for sensor design in machine vision. However relatively little attention has been paid to the actual design parameters provided by biological systems as opposed to the general nature of biological vision architectures. In the present paper we will provide a review of current knowledge of primate spatial vision design parameters and will present recent experimental and modeling work from our lab which demonstrates that a numerical conformal mapping which is a refinement of our previous complex logarithmic model provides the best current summary of this feature of the primate visual system. In this paper we will review recent work from our laboratory which has characterized some of the spatial architectures of the primate visual system. In particular we will review experimental and modeling studies which indicate that: . The global spatial architecture of primate visual cortex is well summarized by a numerical conformal mapping whose simplest analytic approximation is the complex logarithm function . The columnar sub-structure of primate visual cortex can be well summarized by a model based on a band-pass filtered white noise. We will also refer to ongoing work in our lab which demonstrates that: . The joint columnar/map structure of primate visual cortex can be modeled and summarized in terms of a new algorithm the ''''proto-column'''' algorithm. This work provides a reference-point for current engineering approaches to novel architectures for
Spectrally queued feature selection for robotic visual odometery

NASA Astrophysics Data System (ADS)

Pirozzo, David M.; Frederick, Philip A.; Hunt, Shawn; Theisen, Bernard; Del Rose, Mike

2011-01-01

Over the last two decades, research in Unmanned Vehicles (UV) has rapidly progressed and become more influenced by the field of biological sciences. Researchers have been investigating mechanical aspects of varying species to improve UV air and ground intrinsic mobility, they have been exploring the computational aspects of the brain for the development of pattern recognition and decision algorithms and they have been exploring perception capabilities of numerous animals and insects. This paper describes a 3 month exploratory applied research effort performed at the US ARMY Research, Development and Engineering Command's (RDECOM) Tank Automotive Research, Development and Engineering Center (TARDEC) in the area of biologically inspired spectrally augmented feature selection for robotic visual odometry. The motivation for this applied research was to develop a feasibility analysis on multi-spectrally queued feature selection, with improved temporal stability, for the purposes of visual odometry. The intended application is future semi-autonomous Unmanned Ground Vehicle (UGV) control as the richness of data sets required to enable human like behavior in these systems has yet to be defined.
Learning invariance from natural images inspired by observations in the primary visual cortex.

PubMed

Teichmann, Michael; Wiltschut, Jan; Hamker, Fred

2012-05-01

The human visual system has the remarkable ability to largely recognize objects invariant of their position, rotation, and scale. A good interpretation of neurobiological findings involves a computational model that simulates signal processing of the visual cortex. In part, this is likely achieved step by step from early to late areas of visual perception. While several algorithms have been proposed for learning feature detectors, only few studies at hand cover the issue of biologically plausible learning of such invariance. In this study, a set of Hebbian learning rules based on calcium dynamics and homeostatic regulations of single neurons is proposed. Their performance is verified within a simple model of the primary visual cortex to learn so-called complex cells, based on a sequence of static images. As a result, the learned complex-cell responses are largely invariant to phase and position.
MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers

PubMed Central

Allot, Alexis; Chennen, Kirsley; Nevers, Yannis; Poidevin, Laetitia; Kress, Arnaud; Ripp, Raymond; Thompson, Julie Dawn; Poch, Olivier

2017-01-01

Background The constant and massive increase of biological data offers unprecedented opportunities to decipher the function and evolution of genes and their roles in human diseases. However, the multiplicity of sources and flow of data mean that efficient access to useful information and knowledge production has become a major challenge. This challenge can be addressed by taking inspiration from Web 2.0 and particularly social networks, which are at the forefront of big data exploration and human-data interaction. Objective MyGeneFriends is a Web platform inspired by social networks, devoted to genetic disease analysis, and organized around three types of proactive agents: genes, humans, and genetic diseases. The aim of this study was to improve exploration and exploitation of biological, postgenomic era big data. Methods MyGeneFriends leverages conventions popularized by top social networks (Facebook, LinkedIn, etc), such as networks of friends, profile pages, friendship recommendations, affinity scores, news feeds, content recommendation, and data visualization. Results MyGeneFriends provides simple and intuitive interactions with data through evaluation and visualization of connections (friendships) between genes, humans, and diseases. The platform suggests new friends and publications and allows agents to follow the activity of their friends. It dynamically personalizes information depending on the user’s specific interests and provides an efficient way to share information with collaborators. Furthermore, the user’s behavior itself generates new information that constitutes an added value integrated in the network, which can be used to discover new connections between biological agents. Conclusions We have developed MyGeneFriends, a Web platform leveraging conventions from popular social networks to redefine the relationship between humans and biological big data and improve human processing of biomedical data. MyGeneFriends is available at lbgi.fr/mygenefriends. PMID:28623182
2016 Summer Series - Vytas SunSpiral - SUPERBall: A Biologically Inspired Robot for Planetary Exploration

NASA Image and Video Library

2016-06-14

Nature is a major source of inspiration for robotics and aerospace engineering, giving rise to biologically inspired structures. Tensegrity robots mimic a structure similar to muscles and bones to produce a robust three-dimensional skeletal structure that is able to adapt. Vytas SunSpiral will present his work on biologically inspired robotics for advancing NASA space exploration missions.
Holarchical Systems and Emotional Holons : Biologically-Inspired System Designs for Control of Autonomous Aerial Vehicles

NASA Technical Reports Server (NTRS)

Ippolito, Corey; Plice, Laura; Pisanich, Greg

2003-01-01

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

NASA Technical Reports Server (NTRS)

Hinchey, Michael G.; Sterritt, Roy

2006-01-01

Greater understanding of biology in modem times has enabled significant breakthroughs in improving healthcare, quality of life, and eliminating many diseases and congenital illnesses. Simultaneously there is a move towards emulating nature and copying many of the wonders uncovered in biology, resulting in "biologically inspired" systems. Significant results have been reported in a wide range of areas, with systems inspired by nature enabling exploration, communication, and advances that were never dreamed possible just a few years ago. We warn, that as in many other fields of endeavor, we should be inspired by nature and biology, not engage in mimicry. We describe some results of biological inspiration that augur promise in terms of improving the safety and security of systems, and in developing self-managing systems, that we hope will ultimately lead to self-governing systems.
Robotics-inspired biology.

PubMed

Gravish, Nick; Lauder, George V

2018-03-29

For centuries, designers and engineers have looked to biology for inspiration. Biologically inspired robots are just one example of the application of knowledge of the natural world to engineering problems. However, recent work by biologists and interdisciplinary teams have flipped this approach, using robots and physical models to set the course for experiments on biological systems and to generate new hypotheses for biological research. We call this approach robotics-inspired biology; it involves performing experiments on robotic systems aimed at the discovery of new biological phenomena or generation of new hypotheses about how organisms function that can then be tested on living organisms. This new and exciting direction has emerged from the extensive use of physical models by biologists and is already making significant advances in the areas of biomechanics, locomotion, neuromechanics and sensorimotor control. Here, we provide an introduction and overview of robotics-inspired biology, describe two case studies and suggest several directions for the future of this exciting new research area. © 2018. Published by The Company of Biologists Ltd.
Art in Science Competition invites artworks to the annual exhibition on ISMB 2018 in Chicago.

PubMed

Welch, Lonnie; Gaeta, Bruno; Kovats, Diane E; Frenkel Morgenstern, Milana

2018-01-01

The International Society of Computational Biology and Bioinformatics (ISCB) brings together scientists from a wide range of disciplines, including biology, medicine, computer science, mathematics and statistics. Practitioners in these fields are constantly dealing with information in visual form: from microscope images and photographs of gels to scatter plots, network graphs and phylogenetic trees, structural formulae and protein models to flow diagrams, visual aids for problem-solving are omnipresent. The ISCB Art in Science Competition 2017 at the ISCB/ECCB 2017 conference in Prague offered a way to show the beauty of science in art form. Past artworks in this annual exhibition at ISMB combined outstanding beauty and aesthetics with deep insight that perfectly validated the exhibit's approach or went beyond the problem's solution. Others were surprising and inspiring through the transition from science to art, opening eyes and minds to reflect on the work being undertaken.
Event-Based Computation of Motion Flow on a Neuromorphic Analog Neural Platform

PubMed Central

Giulioni, Massimiliano; Lagorce, Xavier; Galluppi, Francesco; Benosman, Ryad B.

2016-01-01

Estimating the speed and direction of moving objects is a crucial component of agents behaving in a dynamic world. Biological organisms perform this task by means of the neural connections originating from their retinal ganglion cells. In artificial systems the optic flow is usually extracted by comparing activity of two or more frames captured with a vision sensor. Designing artificial motion flow detectors which are as fast, robust, and efficient as the ones found in biological systems is however a challenging task. Inspired by the architecture proposed by Barlow and Levick in 1965 to explain the spiking activity of the direction-selective ganglion cells in the rabbit's retina, we introduce an architecture for robust optical flow extraction with an analog neuromorphic multi-chip system. The task is performed by a feed-forward network of analog integrate-and-fire neurons whose inputs are provided by contrast-sensitive photoreceptors. Computation is supported by the precise time of spike emission, and the extraction of the optical flow is based on time lag in the activation of nearby retinal neurons. Mimicking ganglion cells our neuromorphic detectors encode the amplitude and the direction of the apparent visual motion in their output spiking pattern. Hereby we describe the architectural aspects, discuss its latency, scalability, and robustness properties and demonstrate that a network of mismatched delicate analog elements can reliably extract the optical flow from a simple visual scene. This work shows how precise time of spike emission used as a computational basis, biological inspiration, and neuromorphic systems can be used together for solving specific tasks. PMID:26909015
Event-Based Computation of Motion Flow on a Neuromorphic Analog Neural Platform.

PubMed

Giulioni, Massimiliano; Lagorce, Xavier; Galluppi, Francesco; Benosman, Ryad B

2016-01-01

Estimating the speed and direction of moving objects is a crucial component of agents behaving in a dynamic world. Biological organisms perform this task by means of the neural connections originating from their retinal ganglion cells. In artificial systems the optic flow is usually extracted by comparing activity of two or more frames captured with a vision sensor. Designing artificial motion flow detectors which are as fast, robust, and efficient as the ones found in biological systems is however a challenging task. Inspired by the architecture proposed by Barlow and Levick in 1965 to explain the spiking activity of the direction-selective ganglion cells in the rabbit's retina, we introduce an architecture for robust optical flow extraction with an analog neuromorphic multi-chip system. The task is performed by a feed-forward network of analog integrate-and-fire neurons whose inputs are provided by contrast-sensitive photoreceptors. Computation is supported by the precise time of spike emission, and the extraction of the optical flow is based on time lag in the activation of nearby retinal neurons. Mimicking ganglion cells our neuromorphic detectors encode the amplitude and the direction of the apparent visual motion in their output spiking pattern. Hereby we describe the architectural aspects, discuss its latency, scalability, and robustness properties and demonstrate that a network of mismatched delicate analog elements can reliably extract the optical flow from a simple visual scene. This work shows how precise time of spike emission used as a computational basis, biological inspiration, and neuromorphic systems can be used together for solving specific tasks.
An Active System for Visually-Guided Reaching in 3D across Binocular Fixations

PubMed Central

2014-01-01

Based on the importance of relative disparity between objects for accurate hand-eye coordination, this paper presents a biological approach inspired by the cortical neural architecture. So, the motor information is coded in egocentric coordinates obtained from the allocentric representation of the space (in terms of disparity) generated from the egocentric representation of the visual information (image coordinates). In that way, the different aspects of the visuomotor coordination are integrated: an active vision system, composed of two vergent cameras; a module for the 2D binocular disparity estimation based on a local estimation of phase differences performed through a bank of Gabor filters; and a robotic actuator to perform the corresponding tasks (visually-guided reaching). The approach's performance is evaluated through experiments on both simulated and real data. PMID:24672295

Learning and disrupting invariance in visual recognition with a temporal association rule

PubMed Central

Isik, Leyla; Leibo, Joel Z.; Poggio, Tomaso

2012-01-01

Learning by temporal association rules such as Foldiak's trace rule is an attractive hypothesis that explains the development of invariance in visual recognition. Consistent with these rules, several recent experiments have shown that invariance can be broken at both the psychophysical and single cell levels. We show (1) that temporal association learning provides appropriate invariance in models of object recognition inspired by the visual cortex, (2) that we can replicate the “invariance disruption” experiments using these models with a temporal association learning rule to develop and maintain invariance, and (3) that despite dramatic single cell effects, a population of cells is very robust to these disruptions. We argue that these models account for the stability of perceptual invariance despite the underlying plasticity of the system, the variability of the visual world and expected noise in the biological mechanisms. PMID:22754523
Benchmarking Spike-Based Visual Recognition: A Dataset and Evaluation

PubMed Central

Liu, Qian; Pineda-García, Garibaldi; Stromatias, Evangelos; Serrano-Gotarredona, Teresa; Furber, Steve B.

2016-01-01

Today, increasing attention is being paid to research into spike-based neural computation both to gain a better understanding of the brain and to explore biologically-inspired computation. Within this field, the primate visual pathway and its hierarchical organization have been extensively studied. Spiking Neural Networks (SNNs), inspired by the understanding of observed biological structure and function, have been successfully applied to visual recognition and classification tasks. In addition, implementations on neuromorphic hardware have enabled large-scale networks to run in (or even faster than) real time, making spike-based neural vision processing accessible on mobile robots. Neuromorphic sensors such as silicon retinas are able to feed such mobile systems with real-time visual stimuli. A new set of vision benchmarks for spike-based neural processing are now needed to measure progress quantitatively within this rapidly advancing field. We propose that a large dataset of spike-based visual stimuli is needed to provide meaningful comparisons between different systems, and a corresponding evaluation methodology is also required to measure the performance of SNN models and their hardware implementations. In this paper we first propose an initial NE (Neuromorphic Engineering) dataset based on standard computer vision benchmarksand that uses digits from the MNIST database. This dataset is compatible with the state of current research on spike-based image recognition. The corresponding spike trains are produced using a range of techniques: rate-based Poisson spike generation, rank order encoding, and recorded output from a silicon retina with both flashing and oscillating input stimuli. In addition, a complementary evaluation methodology is presented to assess both model-level and hardware-level performance. Finally, we demonstrate the use of the dataset and the evaluation methodology using two SNN models to validate the performance of the models and their hardware implementations. With this dataset we hope to (1) promote meaningful comparison between algorithms in the field of neural computation, (2) allow comparison with conventional image recognition methods, (3) provide an assessment of the state of the art in spike-based visual recognition, and (4) help researchers identify future directions and advance the field. PMID:27853419
Benchmarking Spike-Based Visual Recognition: A Dataset and Evaluation.

PubMed

Liu, Qian; Pineda-García, Garibaldi; Stromatias, Evangelos; Serrano-Gotarredona, Teresa; Furber, Steve B

2016-01-01

Today, increasing attention is being paid to research into spike-based neural computation both to gain a better understanding of the brain and to explore biologically-inspired computation. Within this field, the primate visual pathway and its hierarchical organization have been extensively studied. Spiking Neural Networks (SNNs), inspired by the understanding of observed biological structure and function, have been successfully applied to visual recognition and classification tasks. In addition, implementations on neuromorphic hardware have enabled large-scale networks to run in (or even faster than) real time, making spike-based neural vision processing accessible on mobile robots. Neuromorphic sensors such as silicon retinas are able to feed such mobile systems with real-time visual stimuli. A new set of vision benchmarks for spike-based neural processing are now needed to measure progress quantitatively within this rapidly advancing field. We propose that a large dataset of spike-based visual stimuli is needed to provide meaningful comparisons between different systems, and a corresponding evaluation methodology is also required to measure the performance of SNN models and their hardware implementations. In this paper we first propose an initial NE (Neuromorphic Engineering) dataset based on standard computer vision benchmarksand that uses digits from the MNIST database. This dataset is compatible with the state of current research on spike-based image recognition. The corresponding spike trains are produced using a range of techniques: rate-based Poisson spike generation, rank order encoding, and recorded output from a silicon retina with both flashing and oscillating input stimuli. In addition, a complementary evaluation methodology is presented to assess both model-level and hardware-level performance. Finally, we demonstrate the use of the dataset and the evaluation methodology using two SNN models to validate the performance of the models and their hardware implementations. With this dataset we hope to (1) promote meaningful comparison between algorithms in the field of neural computation, (2) allow comparison with conventional image recognition methods, (3) provide an assessment of the state of the art in spike-based visual recognition, and (4) help researchers identify future directions and advance the field.
Biologically-Inspired Anisotropic Flexible Wing for Optimal Flapping Flight

DTIC Science & Technology

2013-07-01

AFRL-OSR-VA-TR-2013-0400 Biologically-Inspired, Anisotropic Flexible Wing for Optimal Flapping Flight Luis Bernal, Wei Shyy...Final Report Contract Number: FA9550-07-1-0547 Biologically-Inspired, Anisotropic Flexible Wing for Optimal Flapping Flight University of...minimize power consumption; 2. The interactions of unsteady aerodynamic loading with flexible structures; 3. Flexible , light-weight, multifunctional
Ant- and Ant-Colony-Inspired ALife Visual Art.

PubMed

Greenfield, Gary; Machado, Penousal

2015-01-01

Ant- and ant-colony-inspired ALife art is characterized by the artistic exploration of the emerging collective behavior of computational agents, developed using ants as a metaphor. We present a chronology that documents the emergence and history of such visual art, contextualize ant- and ant-colony-inspired art within generative art practices, and consider how it relates to other ALife art. We survey many of the algorithms that artists have used in this genre, address some of their aims, and explore the relationships between ant- and ant-colony-inspired art and research on ant and ant colony behavior.
Integration of bio-inspired, control-based visual and olfactory data for the detection of an elusive target

NASA Astrophysics Data System (ADS)

Duong, Tuan A.; Duong, Nghi; Le, Duong

2017-01-01

In this paper, we present an integration technique using a bio-inspired, control-based visual and olfactory receptor system to search for elusive targets in practical environments where the targets cannot be seen obviously by either sensory data. Bio-inspired Visual System is based on a modeling of extended visual pathway which consists of saccadic eye movements and visual pathway (vertebrate retina, lateral geniculate nucleus and visual cortex) to enable powerful target detections of noisy, partial, incomplete visual data. Olfactory receptor algorithm, namely spatial invariant independent component analysis, that was developed based on data of old factory receptor-electronic nose (enose) of Caltech, is adopted to enable the odorant target detection in an unknown environment. The integration of two systems is a vital approach and sets up a cornerstone for effective and low-cost of miniaturized UAVs or fly robots for future DOD and NASA missions, as well as for security systems in Internet of Things environments.
A cascade model of information processing and encoding for retinal prosthesis.

PubMed

Pei, Zhi-Jun; Gao, Guan-Xin; Hao, Bo; Qiao, Qing-Li; Ai, Hui-Jian

2016-04-01

Retinal prosthesis offers a potential treatment for individuals suffering from photoreceptor degeneration diseases. Establishing biological retinal models and simulating how the biological retina convert incoming light signal into spike trains that can be properly decoded by the brain is a key issue. Some retinal models have been presented, ranking from structural models inspired by the layered architecture to functional models originated from a set of specific physiological phenomena. However, Most of these focus on stimulus image compression, edge detection and reconstruction, but do not generate spike trains corresponding to visual image. In this study, based on state-of-the-art retinal physiological mechanism, including effective visual information extraction, static nonlinear rectification of biological systems and neurons Poisson coding, a cascade model of the retina including the out plexiform layer for information processing and the inner plexiform layer for information encoding was brought forward, which integrates both anatomic connections and functional computations of retina. Using MATLAB software, spike trains corresponding to stimulus image were numerically computed by four steps: linear spatiotemporal filtering, static nonlinear rectification, radial sampling and then Poisson spike generation. The simulated results suggested that such a cascade model could recreate visual information processing and encoding functionalities of the retina, which is helpful in developing artificial retina for the retinally blind.
Biologically Inspired Technology Using Electroactive Polymers (EAP)

NASA Technical Reports Server (NTRS)

Bar-Cohen, Yoseph

2006-01-01

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

PubMed

Pfeifer, Rolf; Lungarella, Max; Iida, Fumiya

2007-11-16

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

PubMed

Allot, Alexis; Chennen, Kirsley; Nevers, Yannis; Poidevin, Laetitia; Kress, Arnaud; Ripp, Raymond; Thompson, Julie Dawn; Poch, Olivier; Lecompte, Odile

2017-06-16

The constant and massive increase of biological data offers unprecedented opportunities to decipher the function and evolution of genes and their roles in human diseases. However, the multiplicity of sources and flow of data mean that efficient access to useful information and knowledge production has become a major challenge. This challenge can be addressed by taking inspiration from Web 2.0 and particularly social networks, which are at the forefront of big data exploration and human-data interaction. MyGeneFriends is a Web platform inspired by social networks, devoted to genetic disease analysis, and organized around three types of proactive agents: genes, humans, and genetic diseases. The aim of this study was to improve exploration and exploitation of biological, postgenomic era big data. MyGeneFriends leverages conventions popularized by top social networks (Facebook, LinkedIn, etc), such as networks of friends, profile pages, friendship recommendations, affinity scores, news feeds, content recommendation, and data visualization. MyGeneFriends provides simple and intuitive interactions with data through evaluation and visualization of connections (friendships) between genes, humans, and diseases. The platform suggests new friends and publications and allows agents to follow the activity of their friends. It dynamically personalizes information depending on the user's specific interests and provides an efficient way to share information with collaborators. Furthermore, the user's behavior itself generates new information that constitutes an added value integrated in the network, which can be used to discover new connections between biological agents. We have developed MyGeneFriends, a Web platform leveraging conventions from popular social networks to redefine the relationship between humans and biological big data and improve human processing of biomedical data. MyGeneFriends is available at lbgi.fr/mygenefriends. ©Alexis Allot, Kirsley Chennen, Yannis Nevers, Laetitia Poidevin, Arnaud Kress, Raymond Ripp, Julie Dawn Thompson, Olivier Poch, Odile Lecompte. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 16.06.2017.
Applications of biological pores in nanomedicine, sensing, and nanoelectronics

PubMed Central

Majd, Sheereen; Yusko, Erik C; Billeh, Yazan N; Macrae, Michael X; Yang, Jerry; Mayer, Michael

2011-01-01

Biological protein pores and pore-forming peptides can generate a pathway for the flux of ions and other charged or polar molecules across cellular membranes. In nature, these nanopores have diverse and essential functions that range from maintaining cell homeostasis and participating in cell signaling to activating or killing cells. The combination of the nanoscale dimensions and sophisticated – often regulated – functionality of these biological pores make them particularly attractive for the growing field of nanobiotechnology. Applications range from single-molecule sensing to drug delivery and targeted killing of malignant cells. Potential future applications may include the use of nanopores for single strand DNA sequencing and for generating bio-inspired, and possibly, biocompatible visual detection systems and batteries. This article reviews the current state of applications of pore-forming peptides and proteins in nanomedicine, sensing, and nanoelectronics. PMID:20561776
Large-scale functional models of visual cortex for remote sensing

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

Brumby, Steven P; Kenyon, Garrett; Rasmussen, Craig E

Neuroscience has revealed many properties of neurons and of the functional organization of visual cortex that are believed to be essential to human vision, but are missing in standard artificial neural networks. Equally important may be the sheer scale of visual cortex requiring {approx}1 petaflop of computation. In a year, the retina delivers {approx}1 petapixel to the brain, leading to massively large opportunities for learning at many levels of the cortical system. We describe work at Los Alamos National Laboratory (LANL) to develop large-scale functional models of visual cortex on LANL's Roadrunner petaflop supercomputer. An initial run of a simplemore » region VI code achieved 1.144 petaflops during trials at the IBM facility in Poughkeepsie, NY (June 2008). Here, we present criteria for assessing when a set of learned local representations is 'complete' along with general criteria for assessing computer vision models based on their projected scaling behavior. Finally, we extend one class of biologically-inspired learning models to problems of remote sensing imagery.« less
Bioinspired Functional Surfaces for Technological Applications

NASA Astrophysics Data System (ADS)

Sharma, Vipul; Kumar, Suneel; Reddy, Kumbam Lingeshwar; Bahuguna, Ashish; Krishnan, Venkata

2016-08-01

Biological matters have been in continuous encounter with extreme environmental conditions leading to their evolution over millions of years. The fittest have survived through continuous evolution, an ongoing process. Biological surfaces are the important active interfaces between biological matters and the environment, and have been evolving over time to a higher state of intelligent functionality. Bioinspired surfaces with special functionalities have grabbed attention in materials research in the recent times. The microstructures and mechanisms behind these functional biological surfaces with interesting properties have inspired scientists to create artificial materials and surfaces which possess the properties equivalent to their counterparts. In this review, we have described the interplay between unique multiscale (micro- and nano-scale) structures of biological surfaces with intrinsic material properties which have inspired researchers to achieve the desired wettability and functionalities. Inspired by naturally occurring surfaces, researchers have designed and fabricated novel interfacial materials with versatile functionalities and wettability, such as superantiwetting surfaces (superhydrophobic and superoleophobic), omniphobic, switching wettability and water collecting surfaces. These strategies collectively enable functional surfaces to be utilized in different applications such as fog harvesting, surface-enhanced Raman spectroscopy (SERS), catalysis, sensing and biological applications. This paper delivers a critical review of such inspiring biological surfaces and artificial bioinspired surfaces utilized in different applications, where material science and engineering have merged by taking inspiration from the natural systems.
Discoveries from a Reggio-Inspired Classroom: Meeting Developmental Needs through the Visual Arts

ERIC Educational Resources Information Center

Griebling, Susan

2011-01-01

Educators from Reggio Emilia encourage educators to see children as competent and strong. They persuade educators to acknowledge the children's use of the visual arts as a "language," especially during project work. Inspired by the philosophy from Reggio Emilia, the author initiated a 10-week ethnographic study of young children in a…
Biologically inspired toys using artificial muscles

NASA Technical Reports Server (NTRS)

Bar-Cohen, Y.

2001-01-01

Recent developments in electroactive polymers, so-called artificial muscles, could one day be used to make bionics possible. Meanwhile, as this technology evolves novel mechanisms are expected to emerge that are biologically inspired.
Biologically inspired LED lens from cuticular nanostructures of firefly lantern

PubMed Central

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

2012-01-01

Cuticular nanostructures found in insects effectively manage light for light polarization, structural color, or optical index matching within an ultrathin natural scale. These nanostructures are mainly dedicated to manage incoming light and recently inspired many imaging and display applications. A bioluminescent organ, such as a firefly lantern, helps to out-couple light from the body in a highly efficient fashion for delivering strong optical signals in sexual communication. However, the cuticular nanostructures, except the light-producing reactions, have not been well investigated for physical principles and engineering biomimetics. Here we report a unique observation of high-transmission nanostructures on a firefly lantern and its biological inspiration for highly efficient LED illumination. Both numerical and experimental results clearly reveal high transmission through the nanostructures inspired from the lantern cuticle. The nanostructures on an LED lens surface were fabricated by using a large-area nanotemplating and reconfigurable nanomolding with heat-induced shear thinning. The biologically inspired LED lens, distinct from a smooth surface lens, substantially increases light transmission over visible ranges, comparable to conventional antireflection coating. This biological inspiration can offer new opportunities for increasing the light extraction efficiency of high-power LED packages. PMID:23112185
Directed area search using socio-biological vision algorithms and cognitive Bayesian reasoning

NASA Astrophysics Data System (ADS)

Medasani, S.; Owechko, Y.; Allen, D.; Lu, T. C.; Khosla, D.

2010-04-01

Volitional search systems that assist the analyst by searching for specific targets or objects such as vehicles, factories, airports, etc in wide area overhead imagery need to overcome multiple problems present in current manual and automatic approaches. These problems include finding targets hidden in terabytes of information, relatively few pixels on targets, long intervals between interesting regions, time consuming analysis requiring many analysts, no a priori representative examples or templates of interest, detecting multiple classes of objects, and the need for very high detection rates and very low false alarm rates. This paper describes a conceptual analyst-centric framework that utilizes existing technology modules to search and locate occurrences of targets of interest (e.g., buildings, mobile targets of military significance, factories, nuclear plants, etc.), from video imagery of large areas. Our framework takes simple queries from the analyst and finds the queried targets with relatively minimum interaction from the analyst. It uses a hybrid approach that combines biologically inspired bottom up attention, socio-biologically inspired object recognition for volitionally recognizing targets, and hierarchical Bayesian networks for modeling and representing the domain knowledge. This approach has the benefits of high accuracy, low false alarm rate and can handle both low-level visual information and high-level domain knowledge in a single framework. Such a system would be of immense help for search and rescue efforts, intelligence gathering, change detection systems, and other surveillance systems.
Competitive repetition suppression (CoRe) clustering: a biologically inspired learning model with application to robust clustering.

PubMed

Bacciu, Davide; Starita, Antonina

2008-11-01

Determining a compact neural coding for a set of input stimuli is an issue that encompasses several biological memory mechanisms as well as various artificial neural network models. In particular, establishing the optimal network structure is still an open problem when dealing with unsupervised learning models. In this paper, we introduce a novel learning algorithm, named competitive repetition-suppression (CoRe) learning, inspired by a cortical memory mechanism called repetition suppression (RS). We show how such a mechanism is used, at various levels of the cerebral cortex, to generate compact neural representations of the visual stimuli. From the general CoRe learning model, we derive a clustering algorithm, named CoRe clustering, that can automatically estimate the unknown cluster number from the data without using a priori information concerning the input distribution. We illustrate how CoRe clustering, besides its biological plausibility, posses strong theoretical properties in terms of robustness to noise and outliers, and we provide an error function describing CoRe learning dynamics. Such a description is used to analyze CoRe relationships with the state-of-the art clustering models and to highlight CoRe similitude with rival penalized competitive learning (RPCL), showing how CoRe extends such a model by strengthening the rival penalization estimation by means of loss functions from robust statistics.
Applications of biological pores in nanomedicine, sensing, and nanoelectronics.

PubMed

Majd, Sheereen; Yusko, Erik C; Billeh, Yazan N; Macrae, Michael X; Yang, Jerry; Mayer, Michael

2010-08-01

Biological protein pores and pore-forming peptides can generate a pathway for the flux of ions and other charged or polar molecules across cellular membranes. In nature, these nanopores have diverse and essential functions that range from maintaining cell homeostasis and participating in cell signaling to activating or killing cells. The combination of the nanoscale dimensions and sophisticated - often regulated - functionality of these biological pores make them particularly attractive for the growing field of nanobiotechnology. Applications range from single-molecule sensing to drug delivery and targeted killing of malignant cells. Potential future applications may include the use of nanopores for single strand DNA sequencing and for generating bio-inspired, and possibly, biocompatible visual detection systems and batteries. This article reviews the current state of applications of pore-forming peptides and proteins in nanomedicine, sensing, and nanoelectronics. Copyright © 2010 Elsevier Ltd. All rights reserved.
Hyperspectral image visualization based on a human visual model

NASA Astrophysics Data System (ADS)

Zhang, Hongqin; Peng, Honghong; Fairchild, Mark D.; Montag, Ethan D.

2008-02-01

Hyperspectral image data can provide very fine spectral resolution with more than 200 bands, yet presents challenges for visualization techniques for displaying such rich information on a tristimulus monitor. This study developed a visualization technique by taking advantage of both the consistent natural appearance of a true color image and the feature separation of a PCA image based on a biologically inspired visual attention model. The key part is to extract the informative regions in the scene. The model takes into account human contrast sensitivity functions and generates a topographic saliency map for both images. This is accomplished using a set of linear "center-surround" operations simulating visual receptive fields as the difference between fine and coarse scales. A difference map between the saliency map of the true color image and that of the PCA image is derived and used as a mask on the true color image to select a small number of interesting locations where the PCA image has more salient features than available in the visible bands. The resulting representations preserve hue for vegetation, water, road etc., while the selected attentional locations may be analyzed by more advanced algorithms.

Biologically Inspired Micro-Flight Research

NASA Technical Reports Server (NTRS)

Raney, David L.; Waszak, Martin R.

2003-01-01

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

NASA Astrophysics Data System (ADS)

Gellis, B. S.; McElroy, B. J.

2016-12-01

PATTERNS across Wyoming is a science and art project that promotes new and innovative approaches to STEM education and outreach, helping to re-contextualize how educators think about creative knowledge, and how to reach diverse audiences through informal education. The convergence of art, science and STEM outreach efforts is vital to increasing the presence of art in geosciences, developing multidisciplinary student research opportunities, expanding creative STEM thinking, and generating creative approaches of visualizing scientific data. A major goal of this project is to train art students to think critically about the value of scientific and artistic inquiry. PATTERNS across Wyoming makes science tangible to Wyoming citizens through K-14 art classrooms, and promotes novel maker-based art explorations centered around Wyoming's geosciences. The first PATTERNS across Wyoming scientific learning module (SIM) is a fish-tank sized flume that recreates natural patterns in sand as a result of fluid flow and sediment transport. It will help promotes the understanding of river systems found across Wyoming (e.g. Green, Yellowstone, Snake). This SIM, and the student artwork inspired by it, will help to visualize environmental-water changes in the central Rocky Mountains and will provide the essential inspiration and tools for Wyoming art students to design biological-driven creative explorations. Each art class will receive different fluvial system conditions, allowing for greater understanding of river system interactions. Artwork will return to the University of Wyoming for a STE{A}M Exhibition inspired by Wyoming's varying fluvial systems. It is our hope that new generations of science and art critical thinkers will not only explore questions of `why' and `how' scientific phenomena occur, but also `how' to better predict, conserve and study invaluable artifacts, and visualize conditions which allow for better control of scientific outcomes and public understanding.
Allothetic and idiothetic sensor fusion in rat-inspired robot localization

NASA Astrophysics Data System (ADS)

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.
Biologically-Inspired Concepts for Self-Management of Complexity

NASA Technical Reports Server (NTRS)

Sterritt, Roy; Hinchey, G.

2006-01-01

Inherent complexity in large-scale applications may be impossible to eliminate or even ameliorate despite a number of promising advances. In such cases, the complexity must be tolerated and managed. Such management may be beyond the abilities of humans, or require such overhead as to make management by humans unrealistic. A number of initiatives inspired by concepts in biology have arisen for self-management of complex systems. We present some ideas and techniques we have been experimenting with, inspired by lesser-known concepts in biology that show promise in protecting complex systems and represent a step towards self-management of complexity.
Whole-field visual motion drives swimming in larval zebrafish via a stochastic process

PubMed Central

Portugues, Ruben; Haesemeyer, Martin; Blum, Mirella L.; Engert, Florian

2015-01-01

ABSTRACT Caudo-rostral whole-field visual motion elicits forward locomotion in many organisms, including larval zebrafish. Here, we investigate the dependence on the latency to initiate this forward swimming as a function of the speed of the visual motion. We show that latency is highly dependent on speed for slow speeds (<10 mm s−1) and then plateaus for higher values. Typical latencies are >1.5 s, which is much longer than neuronal transduction processes. What mechanisms underlie these long latencies? We propose two alternative, biologically inspired models that could account for this latency to initiate swimming: an integrate and fire model, which is history dependent, and a stochastic Poisson model, which has no history dependence. We use these models to predict the behavior of larvae when presented with whole-field motion of varying speed and find that the stochastic process shows better agreement with the experimental data. Finally, we discuss possible neuronal implementations of these models. PMID:25792753
Whole-field visual motion drives swimming in larval zebrafish via a stochastic process.

PubMed

Portugues, Ruben; Haesemeyer, Martin; Blum, Mirella L; Engert, Florian

2015-05-01

Caudo-rostral whole-field visual motion elicits forward locomotion in many organisms, including larval zebrafish. Here, we investigate the dependence on the latency to initiate this forward swimming as a function of the speed of the visual motion. We show that latency is highly dependent on speed for slow speeds (<10 mm s(-1)) and then plateaus for higher values. Typical latencies are >1.5 s, which is much longer than neuronal transduction processes. What mechanisms underlie these long latencies? We propose two alternative, biologically inspired models that could account for this latency to initiate swimming: an integrate and fire model, which is history dependent, and a stochastic Poisson model, which has no history dependence. We use these models to predict the behavior of larvae when presented with whole-field motion of varying speed and find that the stochastic process shows better agreement with the experimental data. Finally, we discuss possible neuronal implementations of these models. © 2015. Published by The Company of Biologists Ltd.
Natural Inspired Intelligent Visual Computing and Its Application to Viticulture.

PubMed

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.
Object Segmentation from Motion Discontinuities and Temporal Occlusions–A Biologically Inspired Model

PubMed Central

Beck, Cornelia; Ognibeni, Thilo; Neumann, Heiko

2008-01-01

Background Optic flow is an important cue for object detection. Humans are able to perceive objects in a scene using only kinetic boundaries, and can perform the task even when other shape cues are not provided. These kinetic boundaries are characterized by the presence of motion discontinuities in a local neighbourhood. In addition, temporal occlusions appear along the boundaries as the object in front covers the background and the objects that are spatially behind it. Methodology/Principal Findings From a technical point of view, the detection of motion boundaries for segmentation based on optic flow is a difficult task. This is due to the problem that flow detected along such boundaries is generally not reliable. We propose a model derived from mechanisms found in visual areas V1, MT, and MSTl of human and primate cortex that achieves robust detection along motion boundaries. It includes two separate mechanisms for both the detection of motion discontinuities and of occlusion regions based on how neurons respond to spatial and temporal contrast, respectively. The mechanisms are embedded in a biologically inspired architecture that integrates information of different model components of the visual processing due to feedback connections. In particular, mutual interactions between the detection of motion discontinuities and temporal occlusions allow a considerable improvement of the kinetic boundary detection. Conclusions/Significance A new model is proposed that uses optic flow cues to detect motion discontinuities and object occlusion. We suggest that by combining these results for motion discontinuities and object occlusion, object segmentation within the model can be improved. This idea could also be applied in other models for object segmentation. In addition, we discuss how this model is related to neurophysiological findings. The model was successfully tested both with artificial and real sequences including self and object motion. PMID:19043613
Near-Infrared Trigged Stimulus-Responsive Photonic Crystals with Hierarchical Structures.

PubMed

Lu, Tao; Pan, Hui; Ma, Jun; Li, Yao; Zhu, Shenmin; Zhang, Di

2017-10-04

Stimuli-responsive photonic crystals (PCs) trigged by light would provide a novel intuitive and quantitative method for noninvasive detection. Inspired by the flame-detecting aptitude of fire beetles and the hierarchical photonic structures of butterfly wings, we herein developed near-infrared stimuli-responsive PCs through coupling photothermal Fe 3 O 4 nanoparticles with thermoresponsive poly(N-isopropylacrylamide) (PNIPAM), with hierarchical photonic structured butterfly wing scales as the template. The nanoparticles within 10 s transferred near-infrared radiation into heat that triggered the phase transition of PNIPAM; this almost immediately posed an anticipated effect on the PNIPAM refractive index and resulted in a composite spectrum change of ∼26 nm, leading to the direct visual readout. It is noteworthy that the whole process is durable and stable mainly owing to the chemical bonding formed between PNIPAM and the biotemplate. We envision that this biologically inspired approach could be utilized in a broad range of applications and would have a great impact on various monitoring processes and medical sensing.
Biologically Inspired Model for Inference of 3D Shape from Texture

PubMed Central

Gomez, Olman; Neumann, Heiko

2016-01-01

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

PubMed

Butail, Sachit; Polverino, Giovanni; Phamduy, Paul; Del Sette, Fausto; Porfiri, Maurizio

2014-12-15

In animal studies, robots have been recently used as a valid tool for testing a wide spectrum of hypotheses. These robots often exploit visual or auditory cues to modulate animal behavior. The propensity of zebrafish, a model organism in biological studies, toward fish with similar color patterns and shape has been leveraged to design biologically inspired robots that successfully attract zebrafish in preference tests. With an aim of extending the application of such robots to field studies, here, we investigate the response of zebrafish to multiple robotic fish swimming at different speeds and in varying arrangements. A soft real-time multi-target tracking and control system remotely steers the robots in circular trajectories during the experimental trials. Our findings indicate a complex behavioral response of zebrafish to biologically inspired robots. More robots produce a significant change in salient measures of stress, with a fast robot swimming alone causing more freezing and erratic activity than two robots swimming slowly together. In addition, fish spend more time in the proximity of a robot when they swim far apart than when the robots swim close to each other. Increase in the number of robots also significantly alters the degree of alignment of fish motion with a robot. Results from this study are expected to advance our understanding of robot perception by live animals and aid in hypothesis-driven studies in unconstrained free-swimming environments. Copyright © 2014 Elsevier B.V. All rights reserved.
A deep (learning) dive into visual search behaviour of breast radiologists

NASA Astrophysics Data System (ADS)

Mall, Suneeta; Brennan, Patrick C.; Mello-Thoms, Claudia

2018-03-01

Visual search, the process of detecting and identifying objects using the eye movements (saccades) and the foveal vision, has been studied for identification of root causes of errors in the interpretation of mammography. The aim of this study is to model visual search behaviour of radiologists and their interpretation of mammograms using deep machine learning approaches. Our model is based on a deep convolutional neural network, a biologically-inspired multilayer perceptron that simulates the visual cortex, and is reinforced with transfer learning techniques. Eye tracking data obtained from 8 radiologists (of varying experience levels in reading mammograms) reviewing 120 two-view digital mammography cases (59 cancers) have been used to train the model, which was pre-trained with the ImageNet dataset for transfer learning. Areas of the mammogram that received direct (foveally fixated), indirect (peripherally fixated) or no (never fixated) visual attention were extracted from radiologists' visual search maps (obtained by a head mounted eye tracking device). These areas, along with the radiologists' assessment (including confidence of the assessment) of suspected malignancy were used to model: 1) Radiologists' decision; 2) Radiologists' confidence on such decision; and 3) The attentional level (i.e. foveal, peripheral or none) obtained by an area of the mammogram. Our results indicate high accuracy and low misclassification in modelling such behaviours.
Hierarchical biointerfaces assembled by leukocyte-inspired particles for specifically recognizing cancer cells.

PubMed

Meng, Jingxin; Liu, Hongliang; Liu, Xueli; Yang, Gao; Zhang, Pengchao; Wang, Shutao; Jiang, Lei

2014-09-24

By mimicking certain biochemical and physical attributes of biological cells, bio-inspired particles have attracted great attention for potential biomedical applications based on cell-like biological functions. Inspired by leukocytes, hierarchical biointerfaces are designed and prepared based on specific molecules-modified leukocyte-inspired particles. These biointerfaces can efficiently recognize cancer cells from whole blood samples through the synergistic effect of molecular recognition and topographical interaction. Compared to flat, mono-micro or nano-biointerfaces, these micro/nano hierarchical biointerfaces are better able to promote specific recognition interactions, resulting in an enhanced cell-capture efficiency. It is anticipated that this study may provide promising guidance to develop new bio-inspired hierarchical biointerfaces for biomedical applications. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Controlled inspiration depth reduces variance in breath-holding-induced BOLD signal.

PubMed

Thomason, Moriah E; Glover, Gary H

2008-01-01

Recent studies have shown that blood oxygen level dependent (BOLD) response amplitude during short periods of breath holding (BH) measured by functional magnetic resonance imaging (fMRI) can be an effective metric for intersubject calibration procedures. However, inconsistency in the depth of inspiration during the BH scan may account for a portion of BOLD variation observed in such scans, and it is likely to reduce the effectiveness of the calibration measurement. While modulation of BOLD signal has been correlated with end-tidal CO2 and other measures of breathing, fluctuations in performance of BH have not been studied in the context of their impact on BOLD signal. Here, we studied the degree to which inspiration depth corresponds to BOLD signal change and tested the effectiveness of a method designed to control inspiration level through visual cues during the BH task paradigm. We observed reliable differences in BOLD signal amplitude corresponding to the depth of inspiration. It was determined that variance in BOLD signal response to BH could be significantly reduced when subjects were given visual feedback during task inspiration periods. The implications of these findings for routine BH studies of BOLD-derived neurovascular response are discussed.
Four types of ensemble coding in data visualizations.

PubMed

Szafir, Danielle Albers; Haroz, Steve; Gleicher, Michael; Franconeri, Steven

2016-01-01

Ensemble coding supports rapid extraction of visual statistics about distributed visual information. Researchers typically study this ability with the goal of drawing conclusions about how such coding extracts information from natural scenes. Here we argue that a second domain can serve as another strong inspiration for understanding ensemble coding: graphs, maps, and other visual presentations of data. Data visualizations allow observers to leverage their ability to perform visual ensemble statistics on distributions of spatial or featural visual information to estimate actual statistics on data. We survey the types of visual statistical tasks that occur within data visualizations across everyday examples, such as scatterplots, and more specialized images, such as weather maps or depictions of patterns in text. We divide these tasks into four categories: identification of sets of values, summarization across those values, segmentation of collections, and estimation of structure. We point to unanswered questions for each category and give examples of such cross-pollination in the current literature. Increased collaboration between the data visualization and perceptual psychology research communities can inspire new solutions to challenges in visualization while simultaneously exposing unsolved problems in perception research.
Biomimetics as a Model for Inspiring Human Innovation

NASA Technical Reports Server (NTRS)

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

NASA Astrophysics Data System (ADS)

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.
A physarum-inspired prize-collecting steiner tree approach to identify subnetworks for drug repositioning.

PubMed

Sun, Yahui; Hameed, Pathima Nusrath; Verspoor, Karin; Halgamuge, Saman

2016-12-05

Drug repositioning can reduce the time, costs and risks of drug development by identifying new therapeutic effects for known drugs. It is challenging to reposition drugs as pharmacological data is large and complex. Subnetwork identification has already been used to simplify the visualization and interpretation of biological data, but it has not been applied to drug repositioning so far. In this paper, we fill this gap by proposing a new Physarum-inspired Prize-Collecting Steiner Tree algorithm to identify subnetworks for drug repositioning. Drug Similarity Networks (DSN) are generated using the chemical, therapeutic, protein, and phenotype features of drugs. In DSNs, vertex prizes and edge costs represent the similarities and dissimilarities between drugs respectively, and terminals represent drugs in the cardiovascular class, as defined in the Anatomical Therapeutic Chemical classification system. A new Physarum-inspired Prize-Collecting Steiner Tree algorithm is proposed in this paper to identify subnetworks. We apply both the proposed algorithm and the widely-used GW algorithm to identify subnetworks in our 18 generated DSNs. In these DSNs, our proposed algorithm identifies subnetworks with an average Rand Index of 81.1%, while the GW algorithm can only identify subnetworks with an average Rand Index of 64.1%. We select 9 subnetworks with high Rand Index to find drug repositioning opportunities. 10 frequently occurring drugs in these subnetworks are identified as candidates to be repositioned for cardiovascular diseases. We find evidence to support previous discoveries that nitroglycerin, theophylline and acarbose may be able to be repositioned for cardiovascular diseases. Moreover, we identify seven previously unknown drug candidates that also may interact with the biological cardiovascular system. These discoveries show our proposed Prize-Collecting Steiner Tree approach as a promising strategy for drug repositioning.
Geometric Bioinspired Networks for Recognition of 2-D and 3-D Low-Level Structures and Transformations.

PubMed

Bayro-Corrochano, Eduardo; Vazquez-Santacruz, Eduardo; Moya-Sanchez, Eduardo; Castillo-Munis, Efrain

2016-10-01

This paper presents the design of radial basis function geometric bioinspired networks and their applications. Until now, the design of neural networks has been inspired by the biological models of neural networks but mostly using vector calculus and linear algebra. However, these designs have never shown the role of geometric computing. The question is how biological neural networks handle complex geometric representations involving Lie group operations like rotations. Even though the actual artificial neural networks are biologically inspired, they are just models which cannot reproduce a plausible biological process. Until now researchers have not shown how, using these models, one can incorporate them into the processing of geometric computing. Here, for the first time in the artificial neural networks domain, we address this issue by designing a kind of geometric RBF using the geometric algebra framework. As a result, using our artificial networks, we show how geometric computing can be carried out by the artificial neural networks. Such geometric neural networks have a great potential in robot vision. This is the most important aspect of this contribution to propose artificial geometric neural networks for challenging tasks in perception and action. In our experimental analysis, we show the applicability of our geometric designs, and present interesting experiments using 2-D data of real images and 3-D screw axis data. In general, our models should be used to process different types of inputs, such as visual cues, touch (texture, elasticity, temperature), taste, and sound. One important task of a perception-action system is to fuse a variety of cues coming from the environment and relate them via a sensor-motor manifold with motor modules to carry out diverse reasoned actions.
An insect-inspired model for visual binding II: functional analysis and visual attention.

PubMed

Northcutt, Brandon D; Higgins, Charles M

2017-04-01

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

A Project-Based Biologically-Inspired Robotics Module

ERIC Educational Resources Information Center

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

NASA Astrophysics Data System (ADS)

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.
What can neuromorphic event-driven precise timing add to spike-based pattern recognition?

PubMed

Akolkar, Himanshu; Meyer, Cedric; Clady, Zavier; Marre, Olivier; Bartolozzi, Chiara; Panzeri, Stefano; Benosman, Ryad

2015-03-01

This letter introduces a study to precisely measure what an increase in spike timing precision can add to spike-driven pattern recognition algorithms. The concept of generating spikes from images by converting gray levels into spike timings is currently at the basis of almost every spike-based modeling of biological visual systems. The use of images naturally leads to generating incorrect artificial and redundant spike timings and, more important, also contradicts biological findings indicating that visual processing is massively parallel, asynchronous with high temporal resolution. A new concept for acquiring visual information through pixel-individual asynchronous level-crossing sampling has been proposed in a recent generation of asynchronous neuromorphic visual sensors. Unlike conventional cameras, these sensors acquire data not at fixed points in time for the entire array but at fixed amplitude changes of their input, resulting optimally sparse in space and time-pixel individually and precisely timed only if new, (previously unknown) information is available (event based). This letter uses the high temporal resolution spiking output of neuromorphic event-based visual sensors to show that lowering time precision degrades performance on several recognition tasks specifically when reaching the conventional range of machine vision acquisition frequencies (30-60 Hz). The use of information theory to characterize separability between classes for each temporal resolution shows that high temporal acquisition provides up to 70% more information that conventional spikes generated from frame-based acquisition as used in standard artificial vision, thus drastically increasing the separability between classes of objects. Experiments on real data show that the amount of information loss is correlated with temporal precision. Our information-theoretic study highlights the potentials of neuromorphic asynchronous visual sensors for both practical applications and theoretical investigations. Moreover, it suggests that representing visual information as a precise sequence of spike times as reported in the retina offers considerable advantages for neuro-inspired visual computations.
From Visual Exploration to Storytelling and Back Again.

PubMed

Gratzl, S; Lex, A; Gehlenborg, N; Cosgrove, N; Streit, M

2016-06-01

The primary goal of visual data exploration tools is to enable the discovery of new insights. To justify and reproduce insights, the discovery process needs to be documented and communicated. A common approach to documenting and presenting findings is to capture visualizations as images or videos. Images, however, are insufficient for telling the story of a visual discovery, as they lack full provenance information and context. Videos are difficult to produce and edit, particularly due to the non-linear nature of the exploratory process. Most importantly, however, neither approach provides the opportunity to return to any point in the exploration in order to review the state of the visualization in detail or to conduct additional analyses. In this paper we present CLUE (Capture, Label, Understand, Explain), a model that tightly integrates data exploration and presentation of discoveries. Based on provenance data captured during the exploration process, users can extract key steps, add annotations, and author "Vistories", visual stories based on the history of the exploration. These Vistories can be shared for others to view, but also to retrace and extend the original analysis. We discuss how the CLUE approach can be integrated into visualization tools and provide a prototype implementation. Finally, we demonstrate the general applicability of the model in two usage scenarios: a Gapminder-inspired visualization to explore public health data and an example from molecular biology that illustrates how Vistories could be used in scientific journals. (see Figure 1 for visual abstract).
Behavior Selection of Mobile Robot Based on Integration of Multimodal Information

NASA Astrophysics Data System (ADS)

Chen, Bin; Kaneko, Masahide

Recently, biologically inspired robots have been developed to acquire the capacity for directing visual attention to salient stimulus generated from the audiovisual environment. On purpose to realize this behavior, a general method is to calculate saliency maps to represent how much the external information attracts the robot's visual attention, where the audiovisual information and robot's motion status should be involved. In this paper, we represent a visual attention model where three modalities, that is, audio information, visual information and robot's motor status are considered, while the previous researches have not considered all of them. Firstly, we introduce a 2-D density map, on which the value denotes how much the robot pays attention to each spatial location. Then we model the attention density using a Bayesian network where the robot's motion statuses are involved. Secondly, the information from both of audio and visual modalities is integrated with the attention density map in integrate-fire neurons. The robot can direct its attention to the locations where the integrate-fire neurons are fired. Finally, the visual attention model is applied to make the robot select the visual information from the environment, and react to the content selected. Experimental results show that it is possible for robots to acquire the visual information related to their behaviors by using the attention model considering motion statuses. The robot can select its behaviors to adapt to the dynamic environment as well as to switch to another task according to the recognition results of visual attention.
From Visual Exploration to Storytelling and Back Again

PubMed Central

Gratzl, S.; Lex, A.; Gehlenborg, N.; Cosgrove, N.; Streit, M.

2016-01-01

The primary goal of visual data exploration tools is to enable the discovery of new insights. To justify and reproduce insights, the discovery process needs to be documented and communicated. A common approach to documenting and presenting findings is to capture visualizations as images or videos. Images, however, are insufficient for telling the story of a visual discovery, as they lack full provenance information and context. Videos are difficult to produce and edit, particularly due to the non-linear nature of the exploratory process. Most importantly, however, neither approach provides the opportunity to return to any point in the exploration in order to review the state of the visualization in detail or to conduct additional analyses. In this paper we present CLUE (Capture, Label, Understand, Explain), a model that tightly integrates data exploration and presentation of discoveries. Based on provenance data captured during the exploration process, users can extract key steps, add annotations, and author “Vistories”, visual stories based on the history of the exploration. These Vistories can be shared for others to view, but also to retrace and extend the original analysis. We discuss how the CLUE approach can be integrated into visualization tools and provide a prototype implementation. Finally, we demonstrate the general applicability of the model in two usage scenarios: a Gapminder-inspired visualization to explore public health data and an example from molecular biology that illustrates how Vistories could be used in scientific journals. (see Figure 1 for visual abstract) PMID:27942091
From Here to Autonomicity: Self-Managing Agents and the Biological Metaphors that Inspire Them

NASA Technical Reports Server (NTRS)

Sterritt, Roy; Hinchey, Mike

2005-01-01

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

NASA Astrophysics Data System (ADS)

Wan, Qianwen; Panetta, Karen; Agaian, Sos

2017-05-01

Autonomous facial recognition system is widely used in real-life applications, such as homeland border security, law enforcement identification and authentication, and video-based surveillance analysis. Issues like low image quality, non-uniform illumination as well as variations in poses and facial expressions can impair the performance of recognition systems. To address the non-uniform illumination challenge, we present a novel robust autonomous facial recognition system inspired by the human visual system based, so called, logarithmical image visualization technique. In this paper, the proposed method, for the first time, utilizes the logarithmical image visualization technique coupled with the local binary pattern to perform discriminative feature extraction for facial recognition system. The Yale database, the Yale-B database and the ATT database are used for computer simulation accuracy and efficiency testing. The extensive computer simulation demonstrates the method's efficiency, accuracy, and robustness of illumination invariance for facial recognition.
Biologically-inspired hexapod robot design and simulation

NASA Technical Reports Server (NTRS)

Espenschied, Kenneth S.; Quinn, Roger D.

1994-01-01

The design and construction of a biologically-inspired hexapod robot is presented. A previously developed simulation is modified to include models of the DC drive motors, the motor driver circuits and their transmissions. The application of this simulation to the design and development of the robot is discussed. The mechanisms thought to be responsible for the leg coordination of the walking stick insect were previously applied to control the straight-line locomotion of a robot. We generalized these rules for a robot walking on a plane. This biologically-inspired control strategy is used to control the robot in simulation. Numerical results show that the general body motion and performance of the simulated robot is similar to that of the robot based on our preliminary experimental results.
Biologically inspired intelligent robots

NASA Astrophysics Data System (ADS)

Bar-Cohen, Yoseph; Breazeal, Cynthia

2003-07-01

Humans throughout history have always sought to mimic the appearance, mobility, functionality, intelligent operation, and thinking process of biological creatures. This field of biologically inspired technology, having the moniker biomimetics, has evolved from making static copies of human and animals in the form of statues to the emergence of robots that operate with realistic behavior. Imagine a person walking towards you where suddenly you notice something weird about him--he is not real but rather he is a robot. Your reaction would probably be "I can't believe it but this robot looks very real" just as you would react to an artificial flower that is a good imitation. You may even proceed and touch the robot to check if your assessment is correct but, as oppose to the flower case, the robot may be programmed to respond physical and verbally. This science fiction scenario could become a reality as the current trend continues in developing biologically inspired technologies. Technology evolution led to such fields as artificial muscles, artificial intelligence, and artificial vision as well as biomimetic capabilities in materials science, mechanics, electronics, computing science, information technology and many others. This paper will review the state of the art and challenges to biologically-inspired technologies and the role that EAP is expected to play as the technology evolves.
Occupational therapy intervention to inspire self-efficacy in a patient with spinal ataxia and visual disturbance

PubMed Central

Tohyama, Satsuki; Usuki, Fusako

2015-01-01

We report a case of a patient with severe ataxia and visual disturbance due to vitamin E deficiency, whose self-efficacy was inspired by intervention with an appropriate occupational therapy activity. Before the handloom intervention, her severe neurological deficits decreased her activities of daily living (ADL) ability, which made her feel pessimistic and depressed. The use of a handloom, however, inspired her sense of accomplishment because she could perform the weft movement by using her residual physical function, thereby relieving her pessimistic attitude. This perception of capability motivated her to participate in further rehabilitation. Finally, her eager practice enhanced her ADL ability and quality of life (QOL). The result suggests that it is important to provide an appropriate occupational therapy activity that can inspire self-efficacy in patients with chronic refractory neurological disorders because the perception of capability can enhance the motivation to improve performance in general activities, ADL ability and QOL. PMID:25666249
Occupational therapy intervention to inspire self-efficacy in a patient with spinal ataxia and visual disturbance.

PubMed

Tohyama, Satsuki; Usuki, Fusako

2015-02-09

We report a case of a patient with severe ataxia and visual disturbance due to vitamin E deficiency, whose self-efficacy was inspired by intervention with an appropriate occupational therapy activity. Before the handloom intervention, her severe neurological deficits decreased her activities of daily living (ADL) ability, which made her feel pessimistic and depressed. The use of a handloom, however, inspired her sense of accomplishment because she could perform the weft movement by using her residual physical function, thereby relieving her pessimistic attitude. This perception of capability motivated her to participate in further rehabilitation. Finally, her eager practice enhanced her ADL ability and quality of life (QOL). The result suggests that it is important to provide an appropriate occupational therapy activity that can inspire self-efficacy in patients with chronic refractory neurological disorders because the perception of capability can enhance the motivation to improve performance in general activities, ADL ability and QOL. 2015 BMJ Publishing Group Ltd.
Additive manufacturing of biologically-inspired materials.

PubMed

Studart, André R

2016-01-21

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

PubMed Central

Raudies, Florian; Neumann, Heiko

2012-01-01

The analysis of motion crowds is concerned with the detection of potential hazards for individuals of the crowd. Existing methods analyze the statistics of pixel motion to classify non-dangerous or dangerous behavior, to detect outlier motions, or to estimate the mean throughput of people for an image region. We suggest a biologically inspired model for the analysis of motion crowds that extracts motion features indicative for potential dangers in crowd behavior. Our model consists of stages for motion detection, integration, and pattern detection that model functions of the primate primary visual cortex area (V1), the middle temporal area (MT), and the medial superior temporal area (MST), respectively. This model allows for the processing of motion transparency, the appearance of multiple motions in the same visual region, in addition to processing opaque motion. We suggest that motion transparency helps to identify “danger zones” in motion crowds. For instance, motion transparency occurs in small exit passages during evacuation. However, motion transparency occurs also for non-dangerous crowd behavior when people move in opposite directions organized into separate lanes. Our analysis suggests: The combination of motion transparency and a slow motion speed can be used for labeling of candidate regions that contain dangerous behavior. In addition, locally detected decelerations or negative speed gradients of motions are a precursor of danger in crowd behavior as are globally detected motion patterns that show a contraction toward a single point. In sum, motion transparency, image speeds, motion patterns, and speed gradients extracted from visual motion in videos are important features to describe the behavioral state of a motion crowd. PMID:23300930
Polarization-difference imaging: a biologically inspired technique for observation through scattering media

NASA Astrophysics Data System (ADS)

Rowe, M. P.; Pugh, E. N., Jr.; Tyo, J. S.; Engheta, N.

1995-03-01

Many animals have visual systems that exploit the polarization of light, and some of these systems are thought to compute difference signals in parallel from arrays of photoreceptors optimally tuned to orthogonal polarizations. We hypothesize that such polarization-difference systems can improve the visibility of objects in scattering media by serving as common-mode rejection amplifiers that reduce the effects of background scattering and amplify the signal from targets whose polarization-difference magnitude is distinct from the background. We present experimental results obtained with a target in a highly scattering medium, demonstrating that a manmade polarization-difference system can render readily visible surface features invisible to conventional imaging.
Event-driven visual attention for the humanoid robot iCub

PubMed Central

Rea, Francesco; Metta, Giorgio; Bartolozzi, Chiara

2013-01-01

Fast reaction to sudden and potentially interesting stimuli is a crucial feature for safe and reliable interaction with the environment. Here we present a biologically inspired attention system developed for the humanoid robot iCub. It is based on input from unconventional event-driven vision sensors and an efficient computational method. The resulting system shows low-latency and fast determination of the location of the focus of attention. The performance is benchmarked against an instance of the state of the art in robotics artificial attention system used in robotics. Results show that the proposed system is two orders of magnitude faster that the benchmark in selecting a new stimulus to attend. PMID:24379753
Ranging through Gabor logons-a consistent, hierarchical approach.

PubMed

Chang, C; Chatterjee, S

1993-01-01

In this work, the correspondence problem in stereo vision is handled by matching two sets of dense feature vectors. Inspired by biological evidence, these feature vectors are generated by a correlation between a bank of Gabor sensors and the intensity image. The sensors consist of two-dimensional Gabor filters at various scales (spatial frequencies) and orientations, which bear close resemblance to the receptive field profiles of simple V1 cells in visual cortex. A hierarchical, stochastic relaxation method is then used to obtain the dense stereo disparities. Unlike traditional hierarchical methods for stereo, feature based hierarchical processing yields consistent disparities. To avoid false matchings due to static occlusion, a dual matching, based on the imaging geometry, is used.
Adhesion design maps for bio-inspired attachment systems.

PubMed

Spolenak, Ralph; Gorb, Stanislav; Arzt, Eduard

2005-01-01

Fibrous surface structures can improve the adhesion of objects to other surfaces. Animals, such as flies and geckos, take advantage of this principle by developing "hairy" contact structures which ensure controlled and repeatable adhesion and detachment. Mathematical models for fiber adhesion predict pronounced dependencies of contact performance on the geometry and the elastic properties of the fibers. In this paper the limits of such contacts imposed by fiber strength, fiber condensation, compliance, and ideal contact strength are modeled for spherical contact tips. Based on this, we introduce the concept of "adhesion design maps" which visualize the predicted mechanical behavior. The maps are useful for understanding biological systems and for guiding experimentation to achieve optimum artificial contacts.
Orientation selectivity in a multi-gated organic electrochemical transistor

NASA Astrophysics Data System (ADS)

Gkoupidenis, Paschalis; Koutsouras, Dimitrios A.; Lonjaret, Thomas; Fairfield, Jessamyn A.; Malliaras, George G.

2016-06-01

Neuromorphic devices offer promising computational paradigms that transcend the limitations of conventional technologies. A prominent example, inspired by the workings of the brain, is spatiotemporal information processing. Here we demonstrate orientation selectivity, a spatiotemporal processing function of the visual cortex, using a poly(3,4ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) organic electrochemical transistor with multiple gates. Spatially distributed inputs on a gate electrode array are found to correlate with the output of the transistor, leading to the ability to discriminate between different stimuli orientations. The demonstration of spatiotemporal processing in an organic electronic device paves the way for neuromorphic devices with new form factors and a facile interface with biology.
Flexible wings in flapping flight

NASA Astrophysics Data System (ADS)

Moret, Lionel; Thiria, Benjamin; Zhang, Jun

2007-11-01

We study the effect of passive pitching and flexible deflection of wings on the forward flapping flight. The wings are flapped vertically in water and are allowed to move freely horizontally. The forward speed is chosen by the flapping wing itself by balance of drag and thrust. We show, that by allowing the wing to passively pitch or by adding a flexible extension at its trailing edge, the forward speed is significantly increased. Detailed measurements of wing deflection and passive pitching, together with flow visualization, are used to explain our observations. The advantage of having a wing with finite rigidity/flexibility is discussed as we compare the current results with our biological inspirations such as birds and fish.

Designing Networks that are Capable of Self-Healing and Adapting

DTIC Science & Technology

2017-04-01

from statistical mechanics, combinatorics, boolean networks, and numerical simulations, and inspired by design principles from biological networks, we... principles for self-healing networks, and applications, and construct an all-possible-paths model for network adaptation. 2015-11-16 UNIT CONVERSION...combinatorics, boolean networks, and numerical simulations, and inspired by design principles from biological networks, we will undertake the fol
Biologically inspired dynamic material systems.

PubMed

Studart, André R

2015-03-09

Numerous examples of material systems that dynamically interact with and adapt to the surrounding environment are found in nature, from hair-based mechanoreceptors in animals to self-shaping seed dispersal units in plants to remodeling bone in vertebrates. Inspired by such fascinating biological structures, a wide range of synthetic material systems have been created to replicate the design concepts of dynamic natural architectures. Examples of biological structures and their man-made counterparts are herein revisited to illustrate how dynamic and adaptive responses emerge from the intimate microscale combination of building blocks with intrinsic nanoscale properties. By using top-down photolithographic methods and bottom-up assembly approaches, biologically inspired dynamic material systems have been created 1) to sense liquid flow with hair-inspired microelectromechanical systems, 2) to autonomously change shape by utilizing plantlike heterogeneous architectures, 3) to homeostatically influence the surrounding environment through self-regulating adaptive surfaces, and 4) to spatially concentrate chemical species by using synthetic microcompartments. The ever-increasing complexity and remarkable functionalities of such synthetic systems offer an encouraging perspective to the rich set of dynamic and adaptive properties that can potentially be implemented in future man-made material systems. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Bioinspired Infrared Sensing Materials and Systems.

PubMed

Shen, Qingchen; Luo, Zhen; Ma, Shuai; Tao, Peng; Song, Chengyi; Wu, Jianbo; Shang, Wen; Deng, Tao

2018-05-11

Bioinspired engineering offers a promising alternative approach in accelerating the development of many man-made systems. Next-generation infrared (IR) sensing systems can also benefit from such nature-inspired approach. The inherent compact and uncooled operation of biological IR sensing systems provides ample inspiration for the engineering of portable and high-performance artificial IR sensing systems. This review overviews the current understanding of the biological IR sensing systems, most of which are thermal-based IR sensors that rely on either bolometer-like or photomechanic sensing mechanism. The existing efforts inspired by the biological IR sensing systems and possible future bioinspired approaches in the development of new IR sensing systems are also discussed in the review. Besides these biological IR sensing systems, other biological systems that do not have IR sensing capabilities but can help advance the development of engineered IR sensing systems are also discussed, and the related engineering efforts are overviewed as well. Further efforts in understanding the biological IR sensing systems, the learning from the integration of multifunction in biological systems, and the reduction of barriers to maximize the multidiscipline collaborations are needed to move this research field forward. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Biomimetic MEMS sensor array for navigation and water detection

NASA Astrophysics Data System (ADS)

Futterknecht, Oliver; Macqueen, Mark O.; Karman, Salmah; Diah, S. Zaleha M.; Gebeshuber, Ille C.

2013-05-01

The focus of this study is biomimetic concept development for a MEMS sensor array for navigation and water detection. The MEMS sensor array is inspired by abstractions of the respective biological functions: polarized skylight-based navigation sensors in honeybees (Apis mellifera) and the ability of African elephants (Loxodonta africana) to detect water. The focus lies on how to navigate to and how to detect water sources in desert-like or remote areas. The goal is to develop a sensor that can provide both, navigation clues and help in detecting nearby water sources. We basically use the information provided by the natural polarization pattern produced by the sunbeams scattered within the atmosphere combined with the capability of the honeybee's compound eye to extrapolate the navigation information. The detection device uses light beam reactive MEMS, which are capable to detect the skylight polarization based on the Rayleigh sky model. For water detection we present various possible approaches to realize the sensor. In the first approach, polarization is used: moisture saturated areas near ground have a small but distinctively different effect on scattering and polarizing light than less moist ones. Modified skylight polarization sensors (Karman, Diah and Gebeshuber, 2012) are used to visualize this small change in scattering. The second approach is inspired by the ability of elephants to detect infrasound produced by underground water reservoirs, and shall be used to determine the location of underground rivers and visualize their exact routes.
A high-throughput screening approach to discovering good forms of biologically inspired visual representation.

PubMed

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

PubMed Central

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

2009-01-01

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. PMID:19956750
Bio-inspired synthesis and biological evaluation of a colchicine-related compound library.

PubMed

Nicolaou, K C; Valiulin, Roman A; Pokorski, Jonathan K; Chang, Vicki; Chen, Jason S

2012-06-01

A bio-inspired investigation of the reactions of substrates of type 1 with VOF(3) and PIFA [phenyliodine(III) bis(trifluoroacetate)] led to a collection of colchicine-like compounds 2-5 and related systems. Biological evaluation revealed that some of the synthesized products had significant cytotoxic properties against the colon cancer cell line HT-29. Copyright © 2012 Elsevier Ltd. All rights reserved.
On-chip visual perception of motion: a bio-inspired connectionist model on FPGA.

PubMed

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.
Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences

PubMed Central

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns. PMID:26147887
Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences.

PubMed

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.
Metal-coordination: Using one of nature’s tricks to control soft material mechanics

PubMed Central

Holten-Andersen, Niels; Jaishankar, Aditya; Harrington, Matthew; Fullenkamp, Dominic E.; DiMarco, Genevieve; He, Lihong; McKinley, Gareth H.; Messersmith, Phillip B.; Lee, Ka Yee C.

2015-01-01

Growing evidence supports a critical role of dynamic metal-coordination crosslinking in soft biological material properties such as self-healing and underwater adhesion1. Using bio-inspired metal-coordinating polymers, initial efforts to mimic these properties have shown promise2. Here we demonstrate how bio-inspired aqueous polymer network mechanics can be easily controlled via metal-coordination crosslink dynamics; metal ion-based crosslink stability control allows aqueous polymer network relaxation times to be finely tuned over several orders of magnitude. In addition to further biological material insights, our demonstration of this compositional scaling mechanism should provide inspiration for new polymer material property-control designs. PMID:26413297
Bio-inspired algorithms applied to molecular docking simulations.

PubMed

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.
BIOCOMPUTATION: some history and prospects.

PubMed

Cull, Paul

2013-06-01

At first glance, biology and computer science are diametrically opposed sciences. Biology deals with carbon based life forms shaped by evolution and natural selection. Computer Science deals with electronic machines designed by engineers and guided by mathematical algorithms. In this brief paper, we review biologically inspired computing. We discuss several models of computation which have arisen from various biological studies. We show what these have in common, and conjecture how biology can still suggest answers and models for the next generation of computing problems. We discuss computation and argue that these biologically inspired models do not extend the theoretical limits on computation. We suggest that, in practice, biological models may give more succinct representations of various problems, and we mention a few cases in which biological models have proved useful. We also discuss the reciprocal impact of computer science on biology and cite a few significant contributions to biological science. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Bionic Manufacturing: Towards Cyborg Cells and Sentient Microbots.

PubMed

Srivastava, Sarvesh Kumar; Yadav, Vikramaditya G

2018-05-01

Bio-inspired engineering applies biological design principles towards developing engineering solutions but is not practical as a manufacturing paradigm. We advocate 'bionic manufacturing', a synergistic fusion of biotic and abiotic components, to transition away from bio-inspiration toward bio-augmentation to address current limitations in bio-inspired manufacturing. Copyright © 2017 Elsevier Ltd. All rights reserved.
Molecular and Cellular Biology Animations: Development and Impact on Student Learning

PubMed Central

2005-01-01

Educators often struggle when teaching cellular and molecular processes because typically they have only two-dimensional tools to teach something that plays out in four dimensions. Learning research has demonstrated that visualizing processes in three dimensions aids learning, and animations are effective visualization tools for novice learners and aid with long-term memory retention. The World Wide Web Instructional Committee at North Dakota State University has used these research results as an inspiration to develop a suite of high-quality animations of molecular and cellular processes. Currently, these animations represent transcription, translation, bacterial gene expression, messenger RNA (mRNA) processing, mRNA splicing, protein transport into an organelle, the electron transport chain, and the use of a biological gradient to drive adenosine triphosphate synthesis. These animations are integrated with an educational module that consists of First Look and Advanced Look components that feature captioned stills from the animation representing the key steps in the processes at varying levels of complexity. These animation-based educational modules are available via the World Wide Web at http://vcell.ndsu.edu/animations. An in-class research experiment demonstrated that student retention of content material was significantly better when students received a lecture coupled with the animations and then used the animation as an individual study activity. PMID:15917875
Target recognition and scene interpretation in image/video understanding systems based on network-symbolic models

NASA Astrophysics Data System (ADS)

Kuvich, Gary

2004-08-01

Vision is only a part of a system that converts visual information into knowledge structures. These structures drive the vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, which is an interpretation of visual information in terms of these knowledge models. These mechanisms provide a reliable recognition if the object is occluded or cannot be recognized as a whole. It is hard to split the entire system apart, and reliable solutions to the target recognition problems are possible only within the solution of a more generic Image Understanding Problem. Brain reduces informational and computational complexities, using implicit symbolic coding of features, hierarchical compression, and selective processing of visual information. Biologically inspired Network-Symbolic representation, where both systematic structural/logical methods and neural/statistical methods are parts of a single mechanism, is the most feasible for such models. It converts visual information into relational Network-Symbolic structures, avoiding artificial precise computations of 3-dimensional models. Network-Symbolic Transformations derive abstract structures, which allows for invariant recognition of an object as exemplar of a class. Active vision helps creating consistent models. Attention, separation of figure from ground and perceptual grouping are special kinds of network-symbolic transformations. Such Image/Video Understanding Systems will be reliably recognizing targets.
Inspiration and application in the evolution of biomaterials.

PubMed

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.
SABRE: a bio-inspired fault-tolerant electronic architecture.

PubMed

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

2013-03-01

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.
Smart unattended sensor networks with scene understanding capabilities

NASA Astrophysics Data System (ADS)

Kuvich, Gary

2006-05-01

Unattended sensor systems are new technologies that are supposed to provide enhanced situation awareness to military and law enforcement agencies. A network of such sensors cannot be very effective in field conditions only if it can transmit visual information to human operators or alert them on motion. In the real field conditions, events may happen in many nodes of a network simultaneously. But the real number of control personnel is always limited, and attention of human operators can be simply attracted to particular network nodes, while more dangerous threat may be unnoticed at the same time in the other nodes. Sensor networks would be more effective if equipped with a system that is similar to human vision in its abilities to understand visual information. Human vision uses for that a rough but wide peripheral system that tracks motions and regions of interests, narrow but precise foveal vision that analyzes and recognizes objects in the center of selected region of interest, and visual intelligence that provides scene and object contexts and resolves ambiguity and uncertainty in the visual information. Biologically-inspired Network-Symbolic models convert image information into an 'understandable' Network-Symbolic format, which is similar to relational knowledge models. The equivalent of interaction between peripheral and foveal systems in the network-symbolic system is achieved via interaction between Visual and Object Buffers and the top-level knowledge system.
Pulse-coupled neural network implementation in FPGA

NASA Astrophysics Data System (ADS)

Waldemark, Joakim T. A.; Lindblad, Thomas; Lindsey, Clark S.; Waldemark, Karina E.; Oberg, Johnny; Millberg, Mikael

1998-03-01

Pulse Coupled Neural Networks (PCNN) are biologically inspired neural networks, mainly based on studies of the visual cortex of small mammals. The PCNN is very well suited as a pre- processor for image processing, particularly in connection with object isolation, edge detection and segmentation. Several implementations of PCNN on von Neumann computers, as well as on special parallel processing hardware devices (e.g. SIMD), exist. However, these implementations are not as flexible as required for many applications. Here we present an implementation in Field Programmable Gate Arrays (FPGA) together with a performance analysis. The FPGA hardware implementation may be considered a platform for further, extended implementations and easily expanded into various applications. The latter may include advanced on-line image analysis with close to real-time performance.

Influence of neural adaptation on dynamics and equilibrium state of neural activities in a ring neural network

NASA Astrophysics Data System (ADS)

Takiyama, Ken

2017-12-01

How neural adaptation affects neural information processing (i.e. the dynamics and equilibrium state of neural activities) is a central question in computational neuroscience. In my previous works, I analytically clarified the dynamics and equilibrium state of neural activities in a ring-type neural network model that is widely used to model the visual cortex, motor cortex, and several other brain regions. The neural dynamics and the equilibrium state in the neural network model corresponded to a Bayesian computation and statistically optimal multiple information integration, respectively, under a biologically inspired condition. These results were revealed in an analytically tractable manner; however, adaptation effects were not considered. Here, I analytically reveal how the dynamics and equilibrium state of neural activities in a ring neural network are influenced by spike-frequency adaptation (SFA). SFA is an adaptation that causes gradual inhibition of neural activity when a sustained stimulus is applied, and the strength of this inhibition depends on neural activities. I reveal that SFA plays three roles: (1) SFA amplifies the influence of external input in neural dynamics; (2) SFA allows the history of the external input to affect neural dynamics; and (3) the equilibrium state corresponds to the statistically optimal multiple information integration independent of the existence of SFA. In addition, the equilibrium state in a ring neural network model corresponds to the statistically optimal integration of multiple information sources under biologically inspired conditions, independent of the existence of SFA.
Biomimetics - using nature as an inspiring model for innovation

NASA Technical Reports Server (NTRS)

Bar-Cohen, Yoseph

2006-01-01

In this presentation, various aspects of the field of biomimetics will be reviewed, examples of inspiring biological models and practical applications will be described, and challenges and potential direction of the field will be discussed.
Natural product-inspired cascade synthesis yields modulators of centrosome integrity.

PubMed

Dückert, Heiko; Pries, Verena; Khedkar, Vivek; Menninger, Sascha; Bruss, Hanna; Bird, Alexander W; Maliga, Zoltan; Brockmeyer, Andreas; Janning, Petra; Hyman, Anthony; Grimme, Stefan; Schürmann, Markus; Preut, Hans; Hübel, Katja; Ziegler, Slava; Kumar, Kamal; Waldmann, Herbert

2011-12-25

In biology-oriented synthesis, the scaffolds of biologically relevant compound classes inspire the synthesis of focused compound collections enriched in bioactivity. This criterion is, in particular, met by the scaffolds of natural products selected in evolution. The synthesis of natural product-inspired compound collections calls for efficient reaction sequences that preferably combine multiple individual transformations in one operation. Here we report the development of a one-pot, twelve-step cascade reaction sequence that includes nine different reactions and two opposing kinds of organocatalysis. The cascade sequence proceeds within 10-30 min and transforms readily available substrates into complex indoloquinolizines that resemble the core tetracyclic scaffold of numerous polycyclic indole alkaloids. Biological investigation of a corresponding focused compound collection revealed modulators of centrosome integrity, termed centrocountins, which caused fragmented and supernumerary centrosomes, chromosome congression defects, multipolar mitotic spindles, acentrosomal spindle poles and multipolar cell division by targeting the centrosome-associated proteins nucleophosmin and Crm1.
Is Self-organization a Rational Expectation?

NASA Astrophysics Data System (ADS)

Luediger, Heinz

Over decades and under varying names the study of biology-inspired algorithms applied to non-living systems has been the subject of a small and somewhat exotic research community. Only the recent coincidence of a growing inability to master the design, development and operation of increasingly intertwined systems and processes, and an accelerated trend towards a naïve if not romanticizing view of nature in the sciences, has led to the adoption of biology-inspired algorithmic research by a wider range of sciences. Adaptive systems, as we apparently observe in nature, are meanwhile viewed as a promising way out of the complexity trap and, propelled by a long list of ‘self’ catchwords, complexity research has become an influential stream in the science community. This paper presents four provocative theses that cast doubt on the strategic potential of complexity research and the viability of large scale deployment of biology-inspired algorithms in an expectation driven world.
Neural networks for data compression and invariant image recognition

NASA Technical Reports Server (NTRS)

Gardner, Sheldon

1989-01-01

An approach to invariant image recognition (I2R), based upon a model of biological vision in the mammalian visual system (MVS), is described. The complete I2R model incorporates several biologically inspired features: exponential mapping of retinal images, Gabor spatial filtering, and a neural network associative memory. In the I2R model, exponentially mapped retinal images are filtered by a hierarchical set of Gabor spatial filters (GSF) which provide compression of the information contained within a pixel-based image. A neural network associative memory (AM) is used to process the GSF coded images. We describe a 1-D shape function method for coding of scale and rotationally invariant shape information. This method reduces image shape information to a periodic waveform suitable for coding as an input vector to a neural network AM. The shape function method is suitable for near term applications on conventional computing architectures equipped with VLSI FFT chips to provide a rapid image search capability.
A Model for the Detection of Moving Targets in Visual Clutter Inspired by Insect Physiology

DTIC Science & Technology

2008-07-01

paper: SDW PS DCO. References 1. Wagner H (1986) Flight performance and visual control of flight of the free- flying housefly (Musca domestica L) 3...differences in the chasing behaviour of houseflies (musca). Biol Cybern 32: 239–241. 3. Land MF (1997) Visual acuity in insects. Annu Rev Entomol 42: 147
A Reggio-Inspired Music Atelier: Opening the Door between Visual Arts and Music

ERIC Educational Resources Information Center

Hanna, Wendell

2014-01-01

The Reggio Emilia approach is based on the idea that every child has at least, "one hundred languages" available for expressing perspectives of the world, and one of those languages is music. While all of the arts (visual, music, dance, drama) are considered equally important in Reggio schools, the visual arts have been particularly…
Carpe Diem: Seizing the Common Core with Visual Thinking Strategies in the Visual Arts Classroom

ERIC Educational Resources Information Center

Franco, Mary; Unrath, Kathleen

2014-01-01

This article demonstrates how Visual Thinking Strategies (VTS) art discussions and subsequent, inspired artmaking can help reach the goals of the Common Core State Standards for English Language Arts & Literacy in History/Social Studies, Science, & Technical Subjects (CCSS-ELA). The authors describe how this was achieved in a remedial…
Mixing enhancement by biologically inspired convection in a micro-chamber using alternating current galvanotactic control of the Tetrahymena pyriformis

NASA Astrophysics Data System (ADS)

Kim, Jihoon; Jang, Yonghee; Byun, Doyoung; Hyung Kim, Dal; Jun Kim, Min

2013-09-01

Recently, there has been increasing interest in the swimming behavior of microorganisms and biologically inspired micro-robots. In this study, we investigated biologically induced convection flow with living microorganism using galvanotaxis. We fabricated and evaluated our micro-mixer with motile cells. For the cell based active micro-mixers, two miscible fluids were used to measure the mixing index. Under alternating current (AC) electric fields with varying frequency, a group of motile Tetrahymena pyriformis cells generated reciprocal motion with circulating flows around their pathline, enhancing the mixing ratio.
Overview of the HFM-181 Symposium Programme, Medical Technology Repurposed to Enhance Human Performance

DTIC Science & Technology

2009-10-01

BIO -INSPIRED HUMAN PERFORMANCE ENHANCEMENT 3.1 Biological performance currently outside of the bounds of the human species HPE opportunities may...strategies to preferentially burn fat in weight reduction (85). 3.2 Bio -inspired opportunities for human performance There are many interesting...solutions to assist human performance Nonmedical applications of bio -inspired engineering and computing technologies are a recognized priority in
A neural network model of ventriloquism effect and aftereffect.

PubMed

Magosso, Elisa; Cuppini, Cristiano; Ursino, Mauro

2012-01-01

Presenting simultaneous but spatially discrepant visual and auditory stimuli induces a perceptual translocation of the sound towards the visual input, the ventriloquism effect. General explanation is that vision tends to dominate over audition because of its higher spatial reliability. The underlying neural mechanisms remain unclear. We address this question via a biologically inspired neural network. The model contains two layers of unimodal visual and auditory neurons, with visual neurons having higher spatial resolution than auditory ones. Neurons within each layer communicate via lateral intra-layer synapses; neurons across layers are connected via inter-layer connections. The network accounts for the ventriloquism effect, ascribing it to a positive feedback between the visual and auditory neurons, triggered by residual auditory activity at the position of the visual stimulus. Main results are: i) the less localized stimulus is strongly biased toward the most localized stimulus and not vice versa; ii) amount of the ventriloquism effect changes with visual-auditory spatial disparity; iii) ventriloquism is a robust behavior of the network with respect to parameter value changes. Moreover, the model implements Hebbian rules for potentiation and depression of lateral synapses, to explain ventriloquism aftereffect (that is, the enduring sound shift after exposure to spatially disparate audio-visual stimuli). By adaptively changing the weights of lateral synapses during cross-modal stimulation, the model produces post-adaptive shifts of auditory localization that agree with in-vivo observations. The model demonstrates that two unimodal layers reciprocally interconnected may explain ventriloquism effect and aftereffect, even without the presence of any convergent multimodal area. The proposed study may provide advancement in understanding neural architecture and mechanisms at the basis of visual-auditory integration in the spatial realm.
Rainbow peacock spiders inspire miniature super-iridescent optics.

PubMed

Hsiung, Bor-Kai; Siddique, Radwanul Hasan; Stavenga, Doekele G; Otto, Jürgen C; Allen, Michael C; Liu, Ying; Lu, Yong-Feng; Deheyn, Dimitri D; Shawkey, Matthew D; Blackledge, Todd A

2017-12-22

Colour produced by wavelength-dependent light scattering is a key component of visual communication in nature and acts particularly strongly in visual signalling by structurally-coloured animals during courtship. Two miniature peacock spiders (Maratus robinsoni and M. chrysomelas) court females using tiny structured scales (~ 40 × 10 μm 2 ) that reflect the full visual spectrum. Using TEM and optical modelling, we show that the spiders' scales have 2D nanogratings on microscale 3D convex surfaces with at least twice the resolving power of a conventional 2D diffraction grating of the same period. Whereas the long optical path lengths required for light-dispersive components to resolve individual wavelengths constrain current spectrometers to bulky sizes, our nano-3D printed prototypes demonstrate that the design principle of the peacock spiders' scales could inspire novel, miniature light-dispersive components.
On the Cultivation of Students' Interests in Biology Teaching

ERIC Educational Resources Information Center

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.
The "Biologically-Inspired Computing" Column

NASA Technical Reports Server (NTRS)

Hinchey, Mike

2007-01-01

Self-managing systems, whether viewed from the perspective of Autonomic Computing, or from that of another initiative, offers a holistic vision for the development and evolution of biologically-inspired computer-based systems. It aims to bring new levels of automation and dependability to systems, while simultaneously hiding their complexity and reducing costs. A case can certainly be made that all computer-based systems should exhibit autonomic properties [6], and we envisage greater interest in, and uptake of, autonomic principles in future system development.
Motion-seeded object-based attention for dynamic visual imagery

NASA Astrophysics Data System (ADS)

Huber, David J.; Khosla, Deepak; Kim, Kyungnam

2017-05-01

This paper† describes a novel system that finds and segments "objects of interest" from dynamic imagery (video) that (1) processes each frame using an advanced motion algorithm that pulls out regions that exhibit anomalous motion, and (2) extracts the boundary of each object of interest using a biologically-inspired segmentation algorithm based on feature contours. The system uses a series of modular, parallel algorithms, which allows many complicated operations to be carried out by the system in a very short time, and can be used as a front-end to a larger system that includes object recognition and scene understanding modules. Using this method, we show 90% accuracy with fewer than 0.1 false positives per frame of video, which represents a significant improvement over detection using a baseline attention algorithm.
Inspiring Integration in College Students Reading Multiple Biology Texts

ERIC Educational Resources Information Center

Firetto, Carla

2013-01-01

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

NASA Astrophysics Data System (ADS)

Loh, Kenneth J.; Azhari, Faezeh

2012-07-01

The highly optimized performance of nature's creations and biological assemblies has inspired the development of their bio-inspired artificial counterparts that can potentially outperform conventional systems. In particular, the skin of humans, animals, and insects exhibits unique functionalities and properties and has subsequently led to active research in developing skin-inspired sensors. This paper presents a summary of selected work related to skin-inspired tactile, distributed strain, and artificial hair cell flow sensors, with a particular focus on technologies enabled by recent advancements in the nanotechnology domain. The purpose is not to present a comprehensive review on this broad subject matter but rather to use selected work to outline the diversity of current research activities.
Visual Inspirations: The Pedagogical and Cultural Significance of Creative Posters in the Art Classroom

ERIC Educational Resources Information Center

Hasio, Cindy

2015-01-01

Creative posters in the classroom can inspire students to become engaged and motivated in learning art. Within the classroom, there are many places to put posters so that students can read them (especially when they get bored in the classroom) - on the cabinets, near the chalkboard, on the teacher's desk and any spare space on the wall. There is…
Deformation behavior of dragonfly-inspired nodus structured wing in gliding flight through experimental visualization approach.

PubMed

Zhang, Sheng; Sunami, Yuta; Hashimoto, Hiromu

2018-04-10

Dragonfly has excellent flight performance and maneuverability due to the complex vein structure of wing. In this research, nodus as an important structural element of the dragonfly wing is investigated through an experimental visualization approach. Three vein structures were fabricated as, open-nodus structure, closed-nodus structure (with a flex-limiter) and rigid wing. The samples were conducted in a wind tunnel with a high speed camera to visualize the deformation of wing structure in order to study the function of nodus structured wing in gliding flight. According to the experimental results, nodus has a great influence on the flexibility of the wing structure. Moreover, the closed-nodus wing (with a flex-limiter) enables the vein structure to be flexible without losing the strength and rigidity of the joint. These findings enhance the knowledge of insect-inspired nodus structured wing and facilitate the application of Micro Air Vehicle (MAV) in gliding flight.
Biomimetic cellular metals-using hierarchical structuring for energy absorption.

PubMed

Bührig-Polaczek, A; Fleck, C; Speck, T; Schüler, P; Fischer, S F; Caliaro, M; Thielen, M

2016-07-19

Fruit walls as well as nut and seed shells typically perform a multitude of functions. One of the biologically most important functions consists in the direct or indirect protection of the seeds from mechanical damage or other negative environmental influences. This qualifies such biological structures as role models for the development of new materials and components that protect commodities and/or persons from damage caused for example by impacts due to rough handling or crashes. We were able to show how the mechanical properties of metal foam based components can be improved by altering their structure on various hierarchical levels inspired by features and principles important for the impact and/or puncture resistance of the biological role models, rather than by tuning the properties of the bulk material. For this various investigation methods have been established which combine mechanical testing with different imaging methods, as well as with in situ and ex situ mechanical testing methods. Different structural hierarchies especially important for the mechanical deformation and failure behaviour of the biological role models, pomelo fruit (Citrus maxima) and Macadamia integrifolia, were identified. They were abstracted and transferred into corresponding structural principles and thus hierarchically structured bio-inspired metal foams have been designed. A production route for metal based bio-inspired structures by investment casting was successfully established. This allows the production of complex and reliable structures, by implementing and combining different hierarchical structural elements found in the biological concept generators, such as strut design and integration of fibres, as well as by minimising casting defects. To evaluate the structural effects, similar investigation methods and mechanical tests were applied to both the biological role models and the metallic foams. As a result an even deeper quantitative understanding of the form-structure-function relationship of the biological concept generators as well as the bio-inspired metal foams was achieved, on deeper hierarchical levels and overarching different levels.

Noise-invariant Neurons in the Avian Auditory Cortex: Hearing the Song in Noise

PubMed Central

Moore, R. Channing; Lee, Tyler; Theunissen, Frédéric E.

2013-01-01

Given the extraordinary ability of humans and animals to recognize communication signals over a background of noise, describing noise invariant neural responses is critical not only to pinpoint the brain regions that are mediating our robust perceptions but also to understand the neural computations that are performing these tasks and the underlying circuitry. Although invariant neural responses, such as rotation-invariant face cells, are well described in the visual system, high-level auditory neurons that can represent the same behaviorally relevant signal in a range of listening conditions have yet to be discovered. Here we found neurons in a secondary area of the avian auditory cortex that exhibit noise-invariant responses in the sense that they responded with similar spike patterns to song stimuli presented in silence and over a background of naturalistic noise. By characterizing the neurons' tuning in terms of their responses to modulations in the temporal and spectral envelope of the sound, we then show that noise invariance is partly achieved by selectively responding to long sounds with sharp spectral structure. Finally, to demonstrate that such computations could explain noise invariance, we designed a biologically inspired noise-filtering algorithm that can be used to separate song or speech from noise. This novel noise-filtering method performs as well as other state-of-the-art de-noising algorithms and could be used in clinical or consumer oriented applications. Our biologically inspired model also shows how high-level noise-invariant responses could be created from neural responses typically found in primary auditory cortex. PMID:23505354
Noise-invariant neurons in the avian auditory cortex: hearing the song in noise.

PubMed

Moore, R Channing; Lee, Tyler; Theunissen, Frédéric E

2013-01-01

Given the extraordinary ability of humans and animals to recognize communication signals over a background of noise, describing noise invariant neural responses is critical not only to pinpoint the brain regions that are mediating our robust perceptions but also to understand the neural computations that are performing these tasks and the underlying circuitry. Although invariant neural responses, such as rotation-invariant face cells, are well described in the visual system, high-level auditory neurons that can represent the same behaviorally relevant signal in a range of listening conditions have yet to be discovered. Here we found neurons in a secondary area of the avian auditory cortex that exhibit noise-invariant responses in the sense that they responded with similar spike patterns to song stimuli presented in silence and over a background of naturalistic noise. By characterizing the neurons' tuning in terms of their responses to modulations in the temporal and spectral envelope of the sound, we then show that noise invariance is partly achieved by selectively responding to long sounds with sharp spectral structure. Finally, to demonstrate that such computations could explain noise invariance, we designed a biologically inspired noise-filtering algorithm that can be used to separate song or speech from noise. This novel noise-filtering method performs as well as other state-of-the-art de-noising algorithms and could be used in clinical or consumer oriented applications. Our biologically inspired model also shows how high-level noise-invariant responses could be created from neural responses typically found in primary auditory cortex.
Knowing Bodies: A Visual and Poetic Inquiry into the Professoriate

ERIC Educational Resources Information Center

Blaikie, Fiona

2009-01-01

Through arts-informed research (Cole & Knowles, 2007) I explore visual identity and scholarship. I conversed with and photographed Lisette, Edward, Kris, Todd, William and Theresa, asking "How are your clothing choices determined by your work as a scholar?" The photographs and transcripts inspired drawings, paintings and poetry. The…
Nature as an engineer: one simple concept of a bio-inspired functional artificial muscle.

PubMed

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.
Retina-Inspired Filter.

PubMed

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

NASA Astrophysics Data System (ADS)

Marco, S.; Gutierrez-Gálvez, A.

2009-05-01

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

NASA Astrophysics Data System (ADS)

Al-Milli, S.; Shaukat, A.; Spiteri, C.; Gao, Y.

2014-04-01

The main objective of the FASTER remote sensing system is the detection of rocks on planetary surfaces by employing models that can efficiently characterise rocks in terms of semantic descriptions. The proposed technique abates some of the algorithmic limitations of existing methods with no training requirements, lower computational complexity and greater robustness towards visual tracking applications over long-distance planetary terrains. Visual saliency models inspired from biological systems help to identify important regions (such as rocks) in the visual scene. Surface rocks are therefore completely described in terms of their local or global conspicuity pop-out characteristics. These local and global pop-out cues are (but not limited to); colour, depth, orientation, curvature, size, luminance intensity, shape, topology etc. The currently applied methods follow a purely bottom-up strategy of visual attention for selection of conspicuous regions in the visual scene without any topdown control. Furthermore the choice of models used (tested and evaluated) are relatively fast among the state-of-the-art and have very low computational load. Quantitative evaluation of these state-ofthe- art models was carried out using benchmark datasets including the Surrey Space Centre Lab Testbed, Pangu generated images, RAL Space SEEKER and CNES Mars Yard datasets. The analysis indicates that models based on visually salient information in the frequency domain (SRA, SDSR, PQFT) are the best performing ones for detecting rocks in an extra-terrestrial setting. In particular the SRA model seems to be the most optimum of the lot especially that it requires the least computational time while keeping errors competitively low. The salient objects extracted using these models can then be merged with the Digital Elevation Models (DEMs) generated from the same navigation cameras in order to be fused to the navigation map thus giving a clear indication of the rock locations.
Naturally selecting solutions: the use of genetic algorithms in bioinformatics.

PubMed

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

2013-01-01

For decades, computer scientists have looked to nature for biologically inspired solutions to computational problems; ranging from robotic control to scheduling optimization. Paradoxically, as we move deeper into the post-genomics era, the reverse is occurring, as biologists and bioinformaticians look to computational techniques, to solve a variety of biological problems. One of the most common biologically inspired techniques are genetic algorithms (GAs), which take the Darwinian concept of natural selection as the driving force behind systems for solving real world problems, including those in the bioinformatics domain. Herein, we provide an overview of genetic algorithms and survey some of the most recent applications of this approach to bioinformatics based problems.
Biological materials: a materials science approach.

PubMed

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.
Applications of CFD and visualization techniques

NASA Technical Reports Server (NTRS)

Saunders, James H.; Brown, Susan T.; Crisafulli, Jeffrey J.; Southern, Leslie A.

1992-01-01

In this paper, three applications are presented to illustrate current techniques for flow calculation and visualization. The first two applications use a commercial computational fluid dynamics (CFD) code, FLUENT, performed on a Cray Y-MP. The results are animated with the aid of data visualization software, apE. The third application simulates a particulate deposition pattern using techniques inspired by developments in nonlinear dynamical systems. These computations were performed on personal computers.
Making Pictures as a Method of Teaching Art History

ERIC Educational Resources Information Center

Martikainen, Jari

2017-01-01

Inspired by the affective and sensory turns in the paradigm of art history, this article discusses making pictures as a method of teaching art history in Finnish Upper Secondary Vocational Education and Training (Qualification in Visual Expression, Study Programmes in Visual and Media Arts and Photography). A total of 25 students majoring in…
Visual-Spatial Art and Design Literacy as a Prelude to Aesthetic Growth

ERIC Educational Resources Information Center

Lerner, Fern

2018-01-01

In bridging ideas from the forum of visual-spatial learning with those of art and design learning, inspiration is taken from Piaget who explained that the evolution of spatial cognition occurs through perception, as well as through thought and imagination. Insights are embraced from interdisciplinary educational theorists, intertwining and…
Painting in Tongues: Faith-Based Languages of Formalist Art

ERIC Educational Resources Information Center

Moore, Kevin Z.

2007-01-01

Cephalopods have a visual language that may be considered artful; they flash color-forms on their hides to communicate intents and emotions. Formalist inspired artists and their critic-expositors describe abstract pattern-painting as though it were a visual language equal to that of the cephalopod. In this article, the author argues that although…
A Model of the Superior Colliculus Predicts Fixation Locations during Scene Viewing and Visual Search.

PubMed

Adeli, Hossein; Vitu, Françoise; Zelinsky, Gregory J

2017-02-08

Modern computational models of attention predict fixations using saliency maps and target maps, which prioritize locations for fixation based on feature contrast and target goals, respectively. But whereas many such models are biologically plausible, none have looked to the oculomotor system for design constraints or parameter specification. Conversely, although most models of saccade programming are tightly coupled to underlying neurophysiology, none have been tested using real-world stimuli and tasks. We combined the strengths of these two approaches in MASC, a model of attention in the superior colliculus (SC) that captures known neurophysiological constraints on saccade programming. We show that MASC predicted the fixation locations of humans freely viewing naturalistic scenes and performing exemplar and categorical search tasks, a breadth achieved by no other existing model. Moreover, it did this as well or better than its more specialized state-of-the-art competitors. MASC's predictive success stems from its inclusion of high-level but core principles of SC organization: an over-representation of foveal information, size-invariant population codes, cascaded population averaging over distorted visual and motor maps, and competition between motor point images for saccade programming, all of which cause further modulation of priority (attention) after projection of saliency and target maps to the SC. Only by incorporating these organizing brain principles into our models can we fully understand the transformation of complex visual information into the saccade programs underlying movements of overt attention. With MASC, a theoretical footing now exists to generate and test computationally explicit predictions of behavioral and neural responses in visually complex real-world contexts. SIGNIFICANCE STATEMENT The superior colliculus (SC) performs a visual-to-motor transformation vital to overt attention, but existing SC models cannot predict saccades to visually complex real-world stimuli. We introduce a brain-inspired SC model that outperforms state-of-the-art image-based competitors in predicting the sequences of fixations made by humans performing a range of everyday tasks (scene viewing and exemplar and categorical search), making clear the value of looking to the brain for model design. This work is significant in that it will drive new research by making computationally explicit predictions of SC neural population activity in response to naturalistic stimuli and tasks. It will also serve as a blueprint for the construction of other brain-inspired models, helping to usher in the next generation of truly intelligent autonomous systems. Copyright © 2017 the authors 0270-6474/17/371453-15$15.00/0.
A biologically inspired neural model for visual and proprioceptive integration including sensory training.

PubMed

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 simulation.
Controlling free flight of a robotic fly using an onboard vision sensor inspired by insect ocelli

PubMed Central

Fuller, Sawyer B.; Karpelson, Michael; Censi, Andrea; Ma, Kevin Y.; Wood, Robert J.

2014-01-01

Scaling a flying robot down to the size of a fly or bee requires advances in manufacturing, sensing and control, and will provide insights into mechanisms used by their biological counterparts. Controlled flight at this scale has previously required external cameras to provide the feedback to regulate the continuous corrective manoeuvres necessary to keep the unstable robot from tumbling. One stabilization mechanism used by flying insects may be to sense the horizon or Sun using the ocelli, a set of three light sensors distinct from the compound eyes. Here, we present an ocelli-inspired visual sensor and use it to stabilize a fly-sized robot. We propose a feedback controller that applies torque in proportion to the angular velocity of the source of light estimated by the ocelli. We demonstrate theoretically and empirically that this is sufficient to stabilize the robot's upright orientation. This constitutes the first known use of onboard sensors at this scale. Dipteran flies use halteres to provide gyroscopic velocity feedback, but it is unknown how other insects such as honeybees stabilize flight without these sensory organs. Our results, using a vehicle of similar size and dynamics to the honeybee, suggest how the ocelli could serve this role. PMID:24942846
Visually guided gait modifications for stepping over an obstacle: a bio-inspired approach.

PubMed

Silva, Pedro; Matos, Vitor; Santos, Cristina P

2014-02-01

There is an increasing interest in conceiving robotic systems that are able to move and act in an unstructured and not predefined environment, for which autonomy and adaptability are crucial features. In nature, animals are autonomous biological systems, which often serve as bio-inspiration models, not only for their physical and mechanical properties, but also their control structures that enable adaptability and autonomy-for which learning is (at least) partially responsible. This work proposes a system which seeks to enable a quadruped robot to online learn to detect and to avoid stumbling on an obstacle in its path. The detection relies in a forward internal model that estimates the robot's perceptive information by exploring the locomotion repetitive nature. The system adapts the locomotion in order to place the robot optimally before attempting to step over the obstacle, avoiding any stumbling. Locomotion adaptation is achieved by changing control parameters of a central pattern generator (CPG)-based locomotion controller. The mechanism learns the necessary alterations to the stride length in order to adapt the locomotion by changing the required CPG parameter. Both learning tasks occur online and together define a sensorimotor map, which enables the robot to learn to step over the obstacle in its path. Simulation results show the feasibility of the proposed approach.
A model of proto-object based saliency

PubMed Central

Russell, Alexander F.; Mihalaş, Stefan; von der Heydt, Rudiger; Niebur, Ernst; Etienne-Cummings, Ralph

2013-01-01

Organisms use the process of selective attention to optimally allocate their computational resources to the instantaneously most relevant subsets of a visual scene, ensuring that they can parse the scene in real time. Many models of bottom-up attentional selection assume that elementary image features, like intensity, color and orientation, attract attention. Gestalt psychologists, how-ever, argue that humans perceive whole objects before they analyze individual features. This is supported by recent psychophysical studies that show that objects predict eye-fixations better than features. In this report we present a neurally inspired algorithm of object based, bottom-up attention. The model rivals the performance of state of the art non-biologically plausible feature based algorithms (and outperforms biologically plausible feature based algorithms) in its ability to predict perceptual saliency (eye fixations and subjective interest points) in natural scenes. The model achieves this by computing saliency as a function of proto-objects that establish the perceptual organization of the scene. All computational mechanisms of the algorithm have direct neural correlates, and our results provide evidence for the interface theory of attention. PMID:24184601
Comparison between Frame-Constrained Fix-Pixel-Value and Frame-Free Spiking-Dynamic-Pixel ConvNets for Visual Processing

PubMed Central

Farabet, Clément; Paz, Rafael; Pérez-Carrasco, Jose; Zamarreño-Ramos, Carlos; Linares-Barranco, Alejandro; LeCun, Yann; Culurciello, Eugenio; Serrano-Gotarredona, Teresa; Linares-Barranco, Bernabe

2012-01-01

Most scene segmentation and categorization architectures for the extraction of features in images and patches make exhaustive use of 2D convolution operations for template matching, template search, and denoising. Convolutional Neural Networks (ConvNets) are one example of such architectures that can implement general-purpose bio-inspired vision systems. In standard digital computers 2D convolutions are usually expensive in terms of resource consumption and impose severe limitations for efficient real-time applications. Nevertheless, neuro-cortex inspired solutions, like dedicated Frame-Based or Frame-Free Spiking ConvNet Convolution Processors, are advancing real-time visual processing. These two approaches share the neural inspiration, but each of them solves the problem in different ways. Frame-Based ConvNets process frame by frame video information in a very robust and fast way that requires to use and share the available hardware resources (such as: multipliers, adders). Hardware resources are fixed- and time-multiplexed by fetching data in and out. Thus memory bandwidth and size is important for good performance. On the other hand, spike-based convolution processors are a frame-free alternative that is able to perform convolution of a spike-based source of visual information with very low latency, which makes ideal for very high-speed applications. However, hardware resources need to be available all the time and cannot be time-multiplexed. Thus, hardware should be modular, reconfigurable, and expansible. Hardware implementations in both VLSI custom integrated circuits (digital and analog) and FPGA have been already used to demonstrate the performance of these systems. In this paper we present a comparison study of these two neuro-inspired solutions. A brief description of both systems is presented and also discussions about their differences, pros and cons. PMID:22518097
Comparison between Frame-Constrained Fix-Pixel-Value and Frame-Free Spiking-Dynamic-Pixel ConvNets for Visual Processing.

PubMed

Farabet, Clément; Paz, Rafael; Pérez-Carrasco, Jose; Zamarreño-Ramos, Carlos; Linares-Barranco, Alejandro; Lecun, Yann; Culurciello, Eugenio; Serrano-Gotarredona, Teresa; Linares-Barranco, Bernabe

2012-01-01

Most scene segmentation and categorization architectures for the extraction of features in images and patches make exhaustive use of 2D convolution operations for template matching, template search, and denoising. Convolutional Neural Networks (ConvNets) are one example of such architectures that can implement general-purpose bio-inspired vision systems. In standard digital computers 2D convolutions are usually expensive in terms of resource consumption and impose severe limitations for efficient real-time applications. Nevertheless, neuro-cortex inspired solutions, like dedicated Frame-Based or Frame-Free Spiking ConvNet Convolution Processors, are advancing real-time visual processing. These two approaches share the neural inspiration, but each of them solves the problem in different ways. Frame-Based ConvNets process frame by frame video information in a very robust and fast way that requires to use and share the available hardware resources (such as: multipliers, adders). Hardware resources are fixed- and time-multiplexed by fetching data in and out. Thus memory bandwidth and size is important for good performance. On the other hand, spike-based convolution processors are a frame-free alternative that is able to perform convolution of a spike-based source of visual information with very low latency, which makes ideal for very high-speed applications. However, hardware resources need to be available all the time and cannot be time-multiplexed. Thus, hardware should be modular, reconfigurable, and expansible. Hardware implementations in both VLSI custom integrated circuits (digital and analog) and FPGA have been already used to demonstrate the performance of these systems. In this paper we present a comparison study of these two neuro-inspired solutions. A brief description of both systems is presented and also discussions about their differences, pros and cons.

Thrust performance of unsteady propulsors using a novel measurement system, and corresponding wake patterns

PubMed Central

Clark, Richard P.; Smits, Alexander J.

2009-01-01

An apparatus is described for the measurement of unsteady thrust and propulsive efficiency produced by biologically inspired oscillating hydrodynamic propulsors. Force measurement is achieved using a strain-gauge-based force transducer, augmented with a lever to amplify or attenuate the applied force and control the measurement sensitivity and natural frequency of vibration. The lever can be used to tune the system to a specific application and it is shown that, using the lever, the stiffness can be made to increase more rapidly than the measurement sensitivity decreases. Efficiency is computed from measurements of the time-averaged power imparted to the fluid. The apparatus is applied to two different propulsors, demonstrating the versatility of the system; wake visualizations are examined, which provide insight into the physical mechanisms of efficient propulsion. PMID:19946574
Characterization of selected elementary motion detector cells to image primitives.

PubMed

Benson, Leslie A; Barrett, Steven F; Wright, Cameron H G

2008-01-01

Developing a visual sensing system, complete with motion processing hardware and software would have many applications to current technology. It could be mounted on many autonomous vehicles to provide information about the navigational environment, as well as obstacle avoidance features. Incorporating the motion processing capabilities into the sensor requires a new approach to the algorithm implementation. This research, and that of many others, have turned to nature for inspiration. Elementary motion detector (EMD) cells are involved in a biological preprocessing network to provide information to the motion processing lobes of the house degrees y Musca domestica. This paper describes the response of the photoreceptor inputs to the EMDs. The inputs to the EMD components are tested as they are stimulated with varying image primitives. This is the first of many steps in characterizing the EMD response to image primitives.
Intrinsic dimensionality predicts the saliency of natural dynamic scenes.

PubMed

Vig, Eleonora; Dorr, Michael; Martinetz, Thomas; Barth, Erhardt

2012-06-01

Since visual attention-based computer vision applications have gained popularity, ever more complex, biologically inspired models seem to be needed to predict salient locations (or interest points) in naturalistic scenes. In this paper, we explore how far one can go in predicting eye movements by using only basic signal processing, such as image representations derived from efficient coding principles, and machine learning. To this end, we gradually increase the complexity of a model from simple single-scale saliency maps computed on grayscale videos to spatiotemporal multiscale and multispectral representations. Using a large collection of eye movements on high-resolution videos, supervised learning techniques fine-tune the free parameters whose addition is inevitable with increasing complexity. The proposed model, although very simple, demonstrates significant improvement in predicting salient locations in naturalistic videos over four selected baseline models and two distinct data labeling scenarios.
Biologically inspired computation and learning in Sensorimotor Systems

NASA Astrophysics Data System (ADS)

Lee, Daniel D.; Seung, H. S.

2001-11-01

Networking systems presently lack the ability to intelligently process the rich multimedia content of the data traffic they carry. Endowing artificial systems with the ability to adapt to changing conditions requires algorithms that can rapidly learn from examples. We demonstrate the application of such learning algorithms on an inexpensive quadruped robot constructed to perform simple sensorimotor tasks. The robot learns to track a particular object by discovering the salient visual and auditory cues unique to that object. The system uses a convolutional neural network that automatically combines color, luminance, motion, and auditory information. The weights of the networks are adjusted using feedback from a teacher to reflect the reliability of the various input channels in the surrounding environment. Additionally, the robot is able to compensate for its own motion by adapting the parameters of a vestibular ocular reflex system.
Drawing inspiration from biological optical systems

NASA Astrophysics Data System (ADS)

Wolpert, H. D.

2009-08-01

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

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

Berlyand, Leonid

2017-01-24

The completed research project concerns the development of novel computational techniques for modeling nonlinear multiscale physical and biological phenomena. Specifically, it addresses the theoretical development and applications of the homogenization theory (coarse graining) approach to calculation of the effective properties of highly heterogenous biological and bio-inspired materials with many spatial scales and nonlinear behavior. This theory studies properties of strongly heterogeneous media in problems arising in materials science, geoscience, biology, etc. Modeling of such media raises fundamental mathematical questions, primarily in partial differential equations (PDEs) and calculus of variations, the subject of the PI’s research. The focus of completed researchmore » was on mathematical models of biological and bio-inspired materials with the common theme of multiscale analysis and coarse grain computational techniques. Biological and bio-inspired materials offer the unique ability to create environmentally clean functional materials used for energy conversion and storage. These materials are intrinsically complex, with hierarchical organization occurring on many nested length and time scales. The potential to rationally design and tailor the properties of these materials for broad energy applications has been hampered by the lack of computational techniques, which are able to bridge from the molecular to the macroscopic scale. The project addressed the challenge of computational treatments of such complex materials by the development of a synergistic approach that combines innovative multiscale modeling/analysis techniques with high performance computing.« less
The 'Biologically-Inspired Computing' Column

NASA Technical Reports Server (NTRS)

Hinchey, Mike

2006-01-01

The field of Biology changed dramatically in 1953, with the determination by Francis Crick and James Dewey Watson of the double helix structure of DNA. This discovery changed Biology for ever, allowing the sequencing of the human genome, and the emergence of a "new Biology" focused on DNA, genes, proteins, data, and search. Computational Biology and Bioinformatics heavily rely on computing to facilitate research into life and development. Simultaneously, an understanding of the biology of living organisms indicates a parallel with computing systems: molecules in living cells interact, grow, and transform according to the "program" dictated by DNA. Moreover, paradigms of Computing are emerging based on modelling and developing computer-based systems exploiting ideas that are observed in nature. This includes building into computer systems self-management and self-governance mechanisms that are inspired by the human body's autonomic nervous system, modelling evolutionary systems analogous to colonies of ants or other insects, and developing highly-efficient and highly-complex distributed systems from large numbers of (often quite simple) largely homogeneous components to reflect the behaviour of flocks of birds, swarms of bees, herds of animals, or schools of fish. This new field of "Biologically-Inspired Computing", often known in other incarnations by other names, such as: Autonomic Computing, Pervasive Computing, Organic Computing, Biomimetics, and Artificial Life, amongst others, is poised at the intersection of Computer Science, Engineering, Mathematics, and the Life Sciences. Successes have been reported in the fields of drug discovery, data communications, computer animation, control and command, exploration systems for space, undersea, and harsh environments, to name but a few, and augur much promise for future progress.
Training mechanical engineering students to utilize biological inspiration during product development.

PubMed

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.
Design with the World in Mind

ERIC Educational Resources Information Center

Kabbeko, Erica

2008-01-01

Good design brings the excitement of the Olympic Games into the visual realm of public media. Inspired by the design involved in the making of the Olympic Games, the author developed a lesson called Fashion Forward. Fashion Forward, which is taught to ninth and tenth graders, is based on the enduring idea that visual images are power communication…
Delayed Match Retrieval: A Novel Anticipation-Based Visual Working Memory Paradigm

ERIC Educational Resources Information Center

Kaldy, Zsuzsa; Guillory, Sylvia B.; Blaser, Erik

2016-01-01

We tested 8- and 10-month-old infants' visual working memory (VWM) for object-location bindings--"what is where"--with a novel paradigm, Delayed Match Retrieval, that measured infants' anticipatory gaze responses (using a Tobii T120 eye tracker). In an inversion of Delayed-Match-to-Sample tasks and with inspiration from the game…
On a biologically inspired topology optimization method

NASA Astrophysics Data System (ADS)

Kobayashi, Marcelo H.

2010-03-01

This work concerns the development of a biologically inspired methodology for the study of topology optimization in engineering and natural systems. The methodology is based on L systems and its turtle interpretation for the genotype-phenotype modeling of the topology development. The topology is analyzed using the finite element method, and optimized using an evolutionary algorithm with the genetic encoding of the L system and its turtle interpretation, as well as, body shape and physical characteristics. The test cases considered in this work clearly show the suitability of the proposed method for the study of engineering and natural complex systems.
Planar maneuvering control of underwater snake robots using virtual holonomic constraints.

PubMed

Kohl, Anna M; Kelasidi, Eleni; Mohammadi, Alireza; Maggiore, Manfredi; Pettersen, Kristin Y

2016-11-24

This paper investigates the problem of planar maneuvering control for bio-inspired underwater snake robots that are exposed to unknown ocean currents. The control objective is to make a neutrally buoyant snake robot which is subject to hydrodynamic forces and ocean currents converge to a desired planar path and traverse the path with a desired velocity. The proposed feedback control strategy enforces virtual constraints which encode biologically inspired gaits on the snake robot configuration. The virtual constraints, parametrized by states of dynamic compensators, are used to regulate the orientation and forward speed of the snake robot. A two-state ocean current observer based on relative velocity sensors is proposed. It enables the robot to follow the path in the presence of unknown constant ocean currents. The efficacy of the proposed control algorithm for several biologically inspired gaits is verified both in simulations for different path geometries and in experiments.
Network science of biological systems at different scales: A review

NASA Astrophysics Data System (ADS)

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
Engaging Non-Science Majors in Biology, One Disease at a Time

ERIC Educational Resources Information Center

Garcia, Rebecca; Rahman, Alvina; Klein, Janette Gomos

2015-01-01

We designed a human biology course that interests nonmajors while improving science literacy through student engagement, using a constructivist-inspired, topic-centered approach. This way of learning highlights common diseases that provide a basis to incorporate specific biological concepts. The topic-centered approach triggers interest and…
Research Update: Programmable tandem repeat proteins inspired by squid ring teeth

NASA Astrophysics Data System (ADS)

Pena-Francesch, Abdon; Domeradzka, Natalia E.; Jung, Huihun; Barbu, Benjamin; Vural, Mert; Kikuchi, Yusuke; Allen, Benjamin D.; Demirel, Melik C.

2018-01-01

Cephalopods have evolved many interesting features that can serve as inspiration. Repetitive squid ring teeth (SRT) proteins from cephalopods exhibit properties such as strength, self-healing, and biocompatibility. These proteins have been engineered to design novel adhesives, self-healing textiles, and the assembly of 2d-layered materials. Compared to conventional polymers, repetitive proteins are easy to modify and can assemble in various morphologies and molecular architectures. This research update discusses the molecular biology and materials science of polypeptides inspired by SRT proteins, their properties, and perspectives for future applications.
The inorganic side of chemical biology.

PubMed

Lippard, Stephen J

2006-10-01

Bioinorganic chemistry remains a vibrant discipline at the interface of chemistry and the biological sciences. Metal ions function in numerous metalloenzymes, are incorporated into pharmaceuticals and imaging agents, and inspire the synthesis of catalysts used to achieve many chemical transformations.
Learning to attend: modeling the shaping of selectivity in infero-temporal cortex in a categorization task.

PubMed

Szabo, Miruna; Deco, Gustavo; Fusi, Stefano; Del Giudice, Paolo; Mattia, Maurizio; Stetter, Martin

2006-05-01

Recent experiments on behaving monkeys have shown that learning a visual categorization task makes the neurons in infero-temporal cortex (ITC) more selective to the task-relevant features of the stimuli (Sigala and Logothetis in Nature 415 318-320, 2002). We hypothesize that such a selectivity modulation emerges from the interaction between ITC and other cortical area, presumably the prefrontal cortex (PFC), where the previously learned stimulus categories are encoded. We propose a biologically inspired model of excitatory and inhibitory spiking neurons with plastic synapses, modified according to a reward based Hebbian learning rule, to explain the experimental results and test the validity of our hypothesis. We assume that the ITC neurons, receiving feature selective inputs, form stronger connections with the category specific neurons to which they are consistently associated in rewarded trials. After learning, the top-down influence of PFC neurons enhances the selectivity of the ITC neurons encoding the behaviorally relevant features of the stimuli, as observed in the experiments. We conclude that the perceptual representation in visual areas like ITC can be strongly affected by the interaction with other areas which are devoted to higher cognitive functions.
Conceptual Elements: A Detailed Framework to Support and Assess Student Learning of Biology Core Concepts

ERIC Educational Resources Information Center

Cary, Tawnya; Branchaw, Janet

2017-01-01

The "Vision and Change in Undergraduate Biology Education: Call to Action" report has inspired and supported a nationwide movement to restructure undergraduate biology curricula to address overarching disciplinary concepts and competencies. The report outlines the concepts and competencies generally but does not provide a detailed…
Developmentally-inspired shrink-wrap polymers for mechanical induction of tissue differentiation.

PubMed

Hashmi, Basma; Zarzar, Lauren D; Mammoto, Tadanori; Mammoto, Akiko; Jiang, Amanda; Aizenberg, Joanna; Ingber, Donald E

2014-05-28

A biologically inspired thermoresponsive polymer has been developed that mechanically induces tooth differentiation in vitro and in vivo by promoting mesenchymal cell compaction as seen in each pore of the scaffold. This normally occurs during the physiological mesenchymal condensation response that triggers tooth formation in the embryo. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Bio-inspired passive actuator simulating an abalone shell mechanism for structural control

NASA Astrophysics Data System (ADS)

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.

Biologically Inspired SNN for Robot Control.

PubMed

Nichols, Eric; McDaid, Liam J; Siddique, Nazmul

2013-02-01

This paper proposes a spiking-neural-network-based robot controller inspired by the control structures of biological systems. Information is routed through the network using facilitating dynamic synapses with short-term plasticity. Learning occurs through long-term synaptic plasticity which is implemented using the temporal difference learning rule to enable the robot to learn to associate the correct movement with the appropriate input conditions. The network self-organizes to provide memories of environments that the robot encounters. A Pioneer robot simulator with laser and sonar proximity sensors is used to verify the performance of the network with a wall-following task, and the results are presented.
Biologically inspired robots elicit a robust fear response in zebrafish

NASA Astrophysics Data System (ADS)

Ladu, Fabrizio; Bartolini, Tiziana; Panitz, Sarah G.; Butail, Sachit; Macrı, Simone; Porfiri, Maurizio

2015-03-01

We investigate the behavioral response of zebrafish to three fear-evoking stimuli. In a binary choice test, zebrafish are exposed to a live allopatric predator, a biologically-inspired robot, and a computer-animated image of the live predator. A target tracking algorithm is developed to score zebrafish behavior. Unlike computer-animated images, the robotic and live predator elicit a robust avoidance response. Importantly, the robotic stimulus elicits more consistent inter-individual responses than the live predator. Results from this effort are expected to aid in hypothesis-driven studies on zebrafish fear response, by offering a valuable approach to maximize data-throughput and minimize animal subjects.
Nanoelectronic programmable synapses based on phase change materials for brain-inspired computing.

PubMed

Kuzum, Duygu; Jeyasingh, Rakesh G D; Lee, Byoungil; Wong, H-S Philip

2012-05-09

Brain-inspired computing is an emerging field, which aims to extend the capabilities of information technology beyond digital logic. A compact nanoscale device, emulating biological synapses, is needed as the building block for brain-like computational systems. Here, we report a new nanoscale electronic synapse based on technologically mature phase change materials employed in optical data storage and nonvolatile memory applications. We utilize continuous resistance transitions in phase change materials to mimic the analog nature of biological synapses, enabling the implementation of a synaptic learning rule. We demonstrate different forms of spike-timing-dependent plasticity using the same nanoscale synapse with picojoule level energy consumption.
Advances in biologically inspired on/near sensor processing

NASA Astrophysics Data System (ADS)

McCarley, Paul L.

1999-07-01

As electro-optic sensors increase in size and frame rate, the data transfer and digital processing resource requirements also increase. In many missions, the spatial area of interest is but a small fraction of the available field of view. Choosing the right region of interest, however, is a challenge and still requires an enormous amount of downstream digital processing resources. In order to filter this ever-increasing amount of data, we look at how nature solves the problem. The Advanced Guidance Division of the Munitions Directorate, Air Force Research Laboratory at Elgin AFB, Florida, has been pursuing research in the are of advanced sensor and image processing concepts based on biologically inspired sensory information processing. A summary of two 'neuromorphic' processing efforts will be presented along with a seeker system concept utilizing this innovative technology. The Neuroseek program is developing a 256 X 256 2-color dual band IRFPA coupled to an optimized silicon CMOS read-out and processing integrated circuit that provides simultaneous full-frame imaging in MWIR/LWIR wavebands along with built-in biologically inspired sensor image processing functions. Concepts and requirements for future such efforts will also be discussed.
Bio-Inspired Self-Cleaning Surfaces

NASA Astrophysics Data System (ADS)

Liu, Kesong; Jiang, Lei

2012-08-01

Self-cleaning surfaces have drawn a lot of interest for both fundamental research and practical applications. This review focuses on the recent progress in mechanism, preparation, and application of self-cleaning surfaces. To date, self-cleaning has been demonstrated by the following four conceptual approaches: (a) TiO2-based superhydrophilic self-cleaning, (b) lotus effect self-cleaning (superhydrophobicity with a small sliding angle), (c) gecko setae-inspired self-cleaning, and (d) underwater organisms-inspired antifouling self-cleaning. Although a number of self-cleaning products have been commercialized, the remaining challenges and future outlook of self-cleaning surfaces are also briefly addressed. Through evolution, nature, which has long been a source of inspiration for scientists and engineers, has arrived at what is optimal. We hope this review will stimulate interdisciplinary collaboration among material science, chemistry, biology, physics, nanoscience, engineering, etc., which is essential for the rational design and reproducible construction of bio-inspired multifunctional self-cleaning surfaces in practical applications.
The E(thi)co-Political Aesthetics of Designer Water: The Need for a Strategic Visual Pedagogy

ERIC Educational Resources Information Center

Jagodzinski, Jan

2007-01-01

This essay attempts to affectively politicize the visual art educator to the global condition of water in the larger context of designer capitalism. The ethical concerns of "designer water" are raised within the broader agenda of ecosophy as inspired by Giles Deleuze and by the last great essay by Felix Guattari. The essay takes an aesthetic line…
Multisensory architectures for action-oriented perception

NASA Astrophysics Data System (ADS)

Alba, L.; Arena, P.; De Fiore, S.; Listán, J.; Patané, L.; Salem, A.; Scordino, G.; Webb, B.

2007-05-01

In order to solve the navigation problem of a mobile robot in an unstructured environment a versatile sensory system and efficient locomotion control algorithms are necessary. In this paper an innovative sensory system for action-oriented perception applied to a legged robot is presented. An important problem we address is how to utilize a large variety and number of sensors, while having systems that can operate in real time. Our solution is to use sensory systems that incorporate analog and parallel processing, inspired by biological systems, to reduce the required data exchange with the motor control layer. In particular, as concerns the visual system, we use the Eye-RIS v1.1 board made by Anafocus, which is based on a fully parallel mixed-signal array sensor-processor chip. The hearing sensor is inspired by the cricket hearing system and allows efficient localization of a specific sound source with a very simple analog circuit. Our robot utilizes additional sensors for touch, posture, load, distance, and heading, and thus requires customized and parallel processing for concurrent acquisition. Therefore a Field Programmable Gate Array (FPGA) based hardware was used to manage the multi-sensory acquisition and processing. This choice was made because FPGAs permit the implementation of customized digital logic blocks that can operate in parallel allowing the sensors to be driven simultaneously. With this approach the multi-sensory architecture proposed can achieve real time capabilities.
Neuro-Inspired Spike-Based Motion: From Dynamic Vision Sensor to Robot Motor Open-Loop Control through Spike-VITE

PubMed Central

Perez-Peña, Fernando; Morgado-Estevez, Arturo; Linares-Barranco, Alejandro; Jimenez-Fernandez, Angel; Gomez-Rodriguez, Francisco; Jimenez-Moreno, Gabriel; Lopez-Coronado, Juan

2013-01-01

In this paper we present a complete spike-based architecture: from a Dynamic Vision Sensor (retina) to a stereo head robotic platform. The aim of this research is to reproduce intended movements performed by humans taking into account as many features as possible from the biological point of view. This paper fills the gap between current spike silicon sensors and robotic actuators by applying a spike processing strategy to the data flows in real time. The architecture is divided into layers: the retina, visual information processing, the trajectory generator layer which uses a neuroinspired algorithm (SVITE) that can be replicated into as many times as DoF the robot has; and finally the actuation layer to supply the spikes to the robot (using PFM). All the layers do their tasks in a spike-processing mode, and they communicate each other through the neuro-inspired AER protocol. The open-loop controller is implemented on FPGA using AER interfaces developed by RTC Lab. Experimental results reveal the viability of this spike-based controller. Two main advantages are: low hardware resources (2% of a Xilinx Spartan 6) and power requirements (3.4 W) to control a robot with a high number of DoF (up to 100 for a Xilinx Spartan 6). It also evidences the suitable use of AER as a communication protocol between processing and actuation. PMID:24264330
Neuro-inspired spike-based motion: from dynamic vision sensor to robot motor open-loop control through spike-VITE.

PubMed

Perez-Peña, Fernando; Morgado-Estevez, Arturo; Linares-Barranco, Alejandro; Jimenez-Fernandez, Angel; Gomez-Rodriguez, Francisco; Jimenez-Moreno, Gabriel; Lopez-Coronado, Juan

2013-11-20

In this paper we present a complete spike-based architecture: from a Dynamic Vision Sensor (retina) to a stereo head robotic platform. The aim of this research is to reproduce intended movements performed by humans taking into account as many features as possible from the biological point of view. This paper fills the gap between current spike silicon sensors and robotic actuators by applying a spike processing strategy to the data flows in real time. The architecture is divided into layers: the retina, visual information processing, the trajectory generator layer which uses a neuroinspired algorithm (SVITE) that can be replicated into as many times as DoF the robot has; and finally the actuation layer to supply the spikes to the robot (using PFM). All the layers do their tasks in a spike-processing mode, and they communicate each other through the neuro-inspired AER protocol. The open-loop controller is implemented on FPGA using AER interfaces developed by RTC Lab. Experimental results reveal the viability of this spike-based controller. Two main advantages are: low hardware resources (2% of a Xilinx Spartan 6) and power requirements (3.4 W) to control a robot with a high number of DoF (up to 100 for a Xilinx Spartan 6). It also evidences the suitable use of AER as a communication protocol between processing and actuation.
Space Vision: Making Astronomy Accessible to Visually Impaired Students

NASA Astrophysics Data System (ADS)

Ries, J. G.; Baguio, M. R.; Jurgens, T. D.; Pruett, K. M.

2004-05-01

Astronomy, with good reason, is thought of as a visual science. Spectacular images of deep space objects or other worlds of our solar system inspire public interest in Astronomy. People encounter news about the universe during their daily life. Developing concepts about celestial objects presents an extra challenge of abstraction for people with visual impairments. The Texas Space Grant Consortium with educators at the Texas School for the Blind and Visually Impaired have developed a 2 day workshop to be held in April 2004 to help students with visual impairments understand these concepts. Hands-on activities and experiments will emphasize non-visual senses. For example, students will learn about: - Constellations as historical ways of finding one's way across the sky. - The size and structure of the Solar System by building a scale model on a running track. They will also: - Plan a planetary exploration mission. - Explore wave phenomenon using heat and sound waves. In preparation for the workshop we worked with teens involved in the countywide 4-H Teens Leading with Character (TLC) program to create the tactile materials necessary for the activities. The teens attended solar system education training so they would have the skills necessary to make the tactile displays to be used during the workshop. The results and evaluation of the workshop will be presented at the meeting. Touch the Universe: A NASA Braille Book of Astronomy inspired this workshop, and it is supported by HST Grant HST-ED-90255.01-A.
Moving Bodies beyond the Social/Biological Divide: Toward Theoretical and Transdisciplinary Adventures

ERIC Educational Resources Information Center

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…
A new parallel DNA algorithm to solve the task scheduling problem based on inspired computational model.

PubMed

Wang, Zhaocai; Ji, Zuwen; Wang, Xiaoming; Wu, Tunhua; Huang, Wei

2017-12-01

As a promising approach to solve the computationally intractable problem, the method based on DNA computing is an emerging research area including mathematics, computer science and molecular biology. The task scheduling problem, as a well-known NP-complete problem, arranges n jobs to m individuals and finds the minimum execution time of last finished individual. In this paper, we use a biologically inspired computational model and describe a new parallel algorithm to solve the task scheduling problem by basic DNA molecular operations. In turn, we skillfully design flexible length DNA strands to represent elements of the allocation matrix, take appropriate biological experiment operations and get solutions of the task scheduling problem in proper length range with less than O(n 2 ) time complexity. Copyright © 2017. Published by Elsevier B.V.
Implementation of Multi-Agent Object Attention System Based on Biologically Inspired Attractor Selection

NASA Astrophysics Data System (ADS)

Hashimoto, Ryoji; Matsumura, Tomoya; Nozato, Yoshihiro; Watanabe, Kenji; Onoye, Takao

A multi-agent object attention system is proposed, which is based on biologically inspired attractor selection model. Object attention is facilitated by using a video sequence and a depth map obtained through a compound-eye image sensor TOMBO. Robustness of the multi-agent system over environmental changes is enhanced by utilizing the biological model of adaptive response by attractor selection. To implement the proposed system, an efficient VLSI architecture is employed with reducing enormous computational costs and memory accesses required for depth map processing and multi-agent attractor selection process. According to the FPGA implementation result of the proposed object attention system, which is accomplished by using 7,063 slices, 640×512 pixel input images can be processed in real-time with three agents at a rate of 9fps in 48MHz operation.
Biologically-Inspired Deceptive Behavior for a Robot

DTIC Science & Technology

2012-01-01

by sending false signals either intentionally or unintentionally, are essential for animals’ survival. For example, camouflage and mimicry are well...detection by both predators and their prey. While camouflage or mimicry are examples of unknowingly deceiving, a deceptive behavior can include...face this situation, where it is important to discourage an adversary from discovering a protected site, so the application of these bio -inspired
Social insects inspire human design

PubMed Central

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
Bio-inspired display of polarization information using selected visual cues

NASA Astrophysics Data System (ADS)

Yemelyanov, Konstantin M.; Lin, Shih-Schon; Luis, William Q.; Pugh, Edward N., Jr.; Engheta, Nader

2003-12-01

For imaging systems the polarization of electromagnetic waves carries much potentially useful information about such features of the world as the surface shape, material contents, local curvature of objects, as well as about the relative locations of the source, object and imaging system. The imaging system of the human eye however, is "polarization-blind", and cannot utilize the polarization of light without the aid of an artificial, polarization-sensitive instrument. Therefore, polarization information captured by a man-made polarimetric imaging system must be displayed to a human observer in the form of visual cues that are naturally processed by the human visual system, while essentially preserving the other important non-polarization information (such as spectral and intensity information) in an image. In other words, some forms of sensory substitution are needed for representing polarization "signals" without affecting other visual information such as color and brightness. We are investigating several bio-inspired representational methodologies for mapping polarization information into visual cues readily perceived by the human visual system, and determining which mappings are most suitable for specific applications such as object detection, navigation, sensing, scene classifications, and surface deformation. The visual cues and strategies we are exploring are the use of coherently moving dots superimposed on image to represent various range of polarization signals, overlaying textures with spatial and/or temporal signatures to segregate regions of image with differing polarization, modulating luminance and/or color contrast of scenes in terms of certain aspects of polarization values, and fusing polarization images into intensity-only images. In this talk, we will present samples of our findings in this area.
Cooperative Lander-Surface/Aerial Microflyer Missions for Mars Exploration

NASA Technical Reports Server (NTRS)

Thakoor, Sarita; Lay, Norman; Hine, Butler; Zornetzer, Steven

2004-01-01

Concepts are being investigated for exploratory missions to Mars based on Bioinspired Engineering of Exploration Systems (BEES), which is a guiding principle of this effort to develop biomorphic explorers. The novelty lies in the use of a robust telecom architecture for mission data return, utilizing multiple local relays (including the lander itself as a local relay and the explorers in the dual role of a local relay) to enable ranges 10 to 1,000 km and downlink of color imagery. As illustrated in Figure 1, multiple microflyers that can be both surface or aerially launched are envisioned in shepherding, metamorphic, and imaging roles. These microflyers imbibe key bio-inspired principles in their flight control, navigation, and visual search operations. Honey-bee inspired algorithms utilizing visual cues to perform autonomous navigation operations such as terrain following will be utilized. The instrument suite will consist of a panoramic imager and polarization imager specifically optimized to detect ice and water. For microflyers, particularly at small sizes, bio-inspired solutions appear to offer better alternate solutions than conventional engineered approaches. This investigation addresses a wide range of interrelated issues, including desired scientific data, sizes, rates, and communication ranges that can be accomplished in alternative mission scenarios. The mission illustrated in Figure 1 offers the most robust telecom architecture and the longest range for exploration with two landers being available as main local relays in addition to an ephemeral aerial probe local relay. The shepherding or metamorphic plane are in their dual role as local relays and image data collection/storage nodes. Appropriate placement of the landing site for the scout lander with respect to the main mission lander can allow coverage of extremely large ranges and enable exhaustive survey of the area of interest. In particular, this mission could help with the path planning and risk mitigation in the traverse of the long-distance surface explorer/rover. The basic requirements of design and operation of BEES to implement the scenarios are discussed. Terrestrial applications of such concepts include distributed aerial/surface measurements of meteorological events, i.e., storm watch, seismic monitoring, reconnaissance, biological chemical sensing, search and rescue, surveillance, autonomous security/ protection agents, and/or delivery and lateral distribution of agents (sensors, surface/subsurface crawlers, clean-up agents). Figure 2 illustrates an Earth demonstration that is in development, and its implementation will illustrate the value of these biomorphic mission concepts.
Biologically Inspired Visual Model With Preliminary Cognition and Active Attention Adjustment.

PubMed

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 methods.
Soft network composite materials with deterministic and bio-inspired designs

PubMed Central

Jang, Kyung-In; Chung, Ha Uk; Xu, Sheng; Lee, Chi Hwan; Luan, Haiwen; Jeong, Jaewoong; Cheng, Huanyu; Kim, Gwang-Tae; Han, Sang Youn; Lee, Jung Woo; Kim, Jeonghyun; Cho, Moongee; Miao, Fuxing; Yang, Yiyuan; Jung, Han Na; Flavin, Matthew; Liu, Howard; Kong, Gil Woo; Yu, Ki Jun; Rhee, Sang Il; Chung, Jeahoon; Kim, Byunggik; Kwak, Jean Won; Yun, Myoung Hee; Kim, Jin Young; Song, Young Min; Paik, Ungyu; Zhang, Yihui; Huang, Yonggang; Rogers, John A.

2015-01-01

Hard and soft structural composites found in biology provide inspiration for the design of advanced synthetic materials. Many examples of bio-inspired hard materials can be found in the literature; far less attention has been devoted to soft systems. Here we introduce deterministic routes to low-modulus thin film materials with stress/strain responses that can be tailored precisely to match the non-linear properties of biological tissues, with application opportunities that range from soft biomedical devices to constructs for tissue engineering. The approach combines a low-modulus matrix with an open, stretchable network as a structural reinforcement that can yield classes of composites with a wide range of desired mechanical responses, including anisotropic, spatially heterogeneous, hierarchical and self-similar designs. Demonstrative application examples in thin, skin-mounted electrophysiological sensors with mechanics precisely matched to the human epidermis and in soft, hydrogel-based vehicles for triggered drug release suggest their broad potential uses in biomedical devices. PMID:25782446
Actions, Observations, and Decision-Making: Biologically Inspired Strategies for Autonomous Aerial Vehicles

NASA Technical Reports Server (NTRS)

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.

A biologically plausible computational model for auditory object recognition.

PubMed

Larson, Eric; Billimoria, Cyrus P; Sen, Kamal

2009-01-01

Object recognition is a task of fundamental importance for sensory systems. Although this problem has been intensively investigated in the visual system, relatively little is known about the recognition of complex auditory objects. Recent work has shown that spike trains from individual sensory neurons can be used to discriminate between and recognize stimuli. Multiple groups have developed spike similarity or dissimilarity metrics to quantify the differences between spike trains. Using a nearest-neighbor approach the spike similarity metrics can be used to classify the stimuli into groups used to evoke the spike trains. The nearest prototype spike train to the tested spike train can then be used to identify the stimulus. However, how biological circuits might perform such computations remains unclear. Elucidating this question would facilitate the experimental search for such circuits in biological systems, as well as the design of artificial circuits that can perform such computations. Here we present a biologically plausible model for discrimination inspired by a spike distance metric using a network of integrate-and-fire model neurons coupled to a decision network. We then apply this model to the birdsong system in the context of song discrimination and recognition. We show that the model circuit is effective at recognizing individual songs, based on experimental input data from field L, the avian primary auditory cortex analog. We also compare the performance and robustness of this model to two alternative models of song discrimination: a model based on coincidence detection and a model based on firing rate.
Filter feeding mechanics of Hypophthalmichthys molitrix regarding porous gill rakers

NASA Astrophysics Data System (ADS)

Palumbo, David; Bulusu, Kartik V.; Cohen, Karly; Hernandez, Particia; Leftwich, Megan C.; Plesniak, Michael W.

2017-11-01

The silver carp (Hypophthalmichthys molitrix) is a filter-feeding fish known to feed upon algal-growth in lakes, rivers, and aquacultures. The filter-feeding process centers on sponge-like membranes located in the carp's pharynx supported by fused gill rakers (GRs), which can efficiently strain suspended food particles as small as 4 µm without clogging. Guided by the anatomy of the silver carp, scanning electron microscope (SEM) images of GRs, and video of the silver carp feeding, we have hypothesized that the filtration mechanism involves a pump-based biological function to capture food particles within the GRs. Dye visualization experiments were performed on a silver carp cadaver head, an excised GR sample, and on a scaled GR in vitro model - the Artificial Gill Raker (AGR). Measurements are performed for the AGR using laser Doppler velocimetry (LDV) and penetration pressure monitoring with a biologically-inspired pumping mechanism. The role of mucus in the retention and capture of food particles has also been explored through rheological measurements, and further experimentation is planned. Our motivation stems from the potential to develop bioinspired industrial-scale filtration technologies ranging from wastewater treatment to filtration in the food industry. supported by GW Center for Biomimetics and Bioinspired Engineering.
Novel locomotion via biological inspiration

NASA Astrophysics Data System (ADS)

Quinn, Roger D.; Boxerbaum, Alexander; Palmer, Luther; Chiel, Hillel; Diller, Eric; Hunt, Alexander; Bachmann, Richard

2011-05-01

Animal behavioral, physiological and neurobiological studies are providing a wealth of inspirational data for robot design and control. Several very different biologically inspired mobile robots will be reviewed. A robot called DIGbot is being developed that moves independent of the direction of gravity using Distributed Inward Gripping (DIG) as a rapid and robust attachment mechanism observed in climbing animals. DIGbot is an 18 degree of freedom hexapod with onboard power and control systems. Passive compliance in its feet, which is inspired by the flexible tarsus of the cockroach, increases the robustness of the adhesion strategy and enables DIGbot to execute large steps and stationary turns while walking on mesh screens. A Whegs™ robot, inspired by insect locomotion principles, is being developed that can be rapidly reconfigured between tracks and wheel-legs and carry GeoSystems Zipper Mast. The mechanisms that cause it to passively change its gait on irregular terrain have been integrated into its hubs for a compact and modular design. The robot is designed to move smoothly on moderately rugged terrain using its tracks and run on irregular terrain and stairs using its wheel-legs. We are also developing soft bodied robots that use peristalsis, the same method of locomotion earthworms use. We present a technique of using a braided mesh exterior to produce fluid waves of motion along the body of the robot that increase the robot's speed relative to previous designs. The concept is highly scalable, for endoscopes to water, oil or gas line inspection.
Illustrative visualization of 3D city models

NASA Astrophysics Data System (ADS)

Doellner, Juergen; Buchholz, Henrik; Nienhaus, Marc; Kirsch, Florian

2005-03-01

This paper presents an illustrative visualization technique that provides expressive representations of large-scale 3D city models, inspired by the tradition of artistic and cartographic visualizations typically found in bird"s-eye view and panoramic maps. We define a collection of city model components and a real-time multi-pass rendering algorithm that achieves comprehensible, abstract 3D city model depictions based on edge enhancement, color-based and shadow-based depth cues, and procedural facade texturing. Illustrative visualization provides an effective visual interface to urban spatial information and associated thematic information complementing visual interfaces based on the Virtual Reality paradigm, offering a huge potential for graphics design. Primary application areas include city and landscape planning, cartoon worlds in computer games, and tourist information systems.
Bio-inspired engineering of cell- and virus-like nanoparticles for drug delivery.

PubMed

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

Somayaji, Anil B.; Amai, Wendy A.; Walther, Eleanor A.

This reports describes the successful extension of artificial immune systems from the domain of computer security to the domain of real time control systems for robotic vehicles. A biologically-inspired computer immune system was added to the control system of two different mobile robots. As an additional layer in a multi-layered approach, the immune system is complementary to traditional error detection and error handling techniques. This can be thought of as biologically-inspired defense in depth. We demonstrated an immune system can be added with very little application developer effort, resulting in little to no performance impact. The methods described here aremore » extensible to any system that processes a sequence of data through a software interface.« less
Biologically inspired emotion recognition from speech

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

DTIC Science & Technology

2008-02-01

shunting subsystem). Visual input from the lateral geniculate enters the visual buffer via the black arrow at the bottom. Processing subsystems used... lateral geniculate nucleus of the thalamus (LGNd), the superior colliculus of the midbrain, and cortical regions V1 through V4. Beyond early vision...resonance imaging FOA: focus of attention IMPER: IMagery and PERception model IS: information shunting system LGNd: dorsal lateral geniculate nucleus
Imaging Inelastic Fracture Processes in Biomimetic Nanocomposites and Nacre by Laser Speckle for Better Toughness.

PubMed

Verho, Tuukka; Karppinen, Pasi; Gröschel, André H; Ikkala, Olli

2018-01-01

Mollusk nacre is a prototypical biological inorganic-organic composite that combines high toughness, stiffness, and strength by its brick-and-mortar microstructure, which has inspired several synthetic mimics. Its remarkable fracture toughness relies on inelastic deformations at the process zone at the crack tip that dissolve stress concentrations and stop cracks. The micrometer-scale structure allows resolving the size and shape of the process zone to understand the fracture processes. However, for better scalability, nacre-mimetic nanocomposites with aligned inorganic or graphene nanosheets are extensively pursued, to avoid the packing problems of mesoscale sheets like in nacre or slow in situ biomineralization. This calls for novel methods to explore the process zone of biomimetic nanocomposites. Here the fracture of nacre and nacre-inspired clay/polymer nanocomposite is explored using laser speckle imaging that reveals the process zone even in absence of changes in optical scattering. To demonstrate the diagnostic value, compared to nacre, the nacre-inspired nanocomposite develops a process zone more abruptly with macroscopic crack deflection shown by a flattened process zone. In situ scanning electron microscopy suggests similar toughening mechanisms in nanocomposite and nacre. These new insights guide the design of nacre-inspired nanocomposites toward better mechanical properties to reach the level of synergy of their biological model.
Bio-Inspired Metal-Coordination Dynamics: A Unique Tool for Engineering Soft Matter Mechanics

NASA Astrophysics Data System (ADS)

Holten-Andersen, Niels

Growing evidence supports a critical role of metal-coordination in soft biological material properties such as self-healing, underwater adhesion and autonomous wound plugging. Using bio-inspired metal-binding polymers, initial efforts to mimic these properties with metal-coordination crosslinked polymer materials have shown promise. In addition, with polymer network mechanics strongly coupled to coordinate crosslink dynamics material properties can be easily tuned from visco-elastic fluids to solids. Given their exploitation in desirable material applications in Nature, bio-inspired metal-coordinate complex crosslinking provides an opportunity to further advance synthetic polymer materials design. Early lessons from this pursuit are presented.
Biomimetic Sniffing Improves the Detection Performance of a 3D Printed Nose of a Dog and a Commercial Trace Vapor Detector

NASA Astrophysics Data System (ADS)

Staymates, Matthew E.; Maccrehan, William A.; Staymates, Jessica L.; Kunz, Roderick R.; Mendum, Thomas; Ong, Ta-Hsuan; Geurtsen, Geoffrey; Gillen, Greg J.; Craven, Brent A.

2016-12-01

Unlike current chemical trace detection technology, dogs actively sniff to acquire an odor sample. Flow visualization experiments with an anatomically-similar 3D printed dog’s nose revealed the external aerodynamics during canine sniffing, where ventral-laterally expired air jets entrain odorant-laden air toward the nose, thereby extending the “aerodynamic reach” for inspiration of otherwise inaccessible odors. Chemical sampling and detection experiments quantified two modes of operation with the artificial nose-active sniffing and continuous inspiration-and demonstrated an increase in odorant detection by a factor of up to 18 for active sniffing. A 16-fold improvement in detection was demonstrated with a commercially-available explosives detector by applying this bio-inspired design principle and making the device “sniff” like a dog. These lessons learned from the dog may benefit the next-generation of vapor samplers for explosives, narcotics, pathogens, or even cancer, and could inform future bio-inspired designs for optimized sampling of odor plumes.
Biomimetic Sniffing Improves the Detection Performance of a 3D Printed Nose of a Dog and a Commercial Trace Vapor Detector

PubMed Central

Staymates, Matthew E.; MacCrehan, William A.; Staymates, Jessica L.; Kunz, Roderick R.; Mendum, Thomas; Ong, Ta-Hsuan; Geurtsen, Geoffrey; Gillen, Greg J.; Craven, Brent A.

2016-01-01

Unlike current chemical trace detection technology, dogs actively sniff to acquire an odor sample. Flow visualization experiments with an anatomically-similar 3D printed dog’s nose revealed the external aerodynamics during canine sniffing, where ventral-laterally expired air jets entrain odorant-laden air toward the nose, thereby extending the “aerodynamic reach” for inspiration of otherwise inaccessible odors. Chemical sampling and detection experiments quantified two modes of operation with the artificial nose-active sniffing and continuous inspiration-and demonstrated an increase in odorant detection by a factor of up to 18 for active sniffing. A 16-fold improvement in detection was demonstrated with a commercially-available explosives detector by applying this bio-inspired design principle and making the device “sniff” like a dog. These lessons learned from the dog may benefit the next-generation of vapor samplers for explosives, narcotics, pathogens, or even cancer, and could inform future bio-inspired designs for optimized sampling of odor plumes. PMID:27906156
Adaptation of sensor morphology: an integrative view of perception from biologically inspired robotics perspective

PubMed Central

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
DNA codes for nanoscience.

PubMed

Samorì, Bruno; Zuccheri, Giampaolo

2005-02-11

The nanometer scale is a special place where all sciences meet and develop a particularly strong interdisciplinarity. While biology is a source of inspiration for nanoscientists, chemistry has a central role in turning inspirations and methods from biological systems to nanotechnological use. DNA is the biological molecule by which nanoscience and nanotechnology is mostly fascinated. Nature uses DNA not only as a repository of the genetic information, but also as a controller of the expression of the genes it contains. Thus, there are codes embedded in the DNA sequence that serve to control recognition processes on the atomic scale, such as the base pairing, and others that control processes taking place on the nanoscale. From the chemical point of view, DNA is the supramolecular building block with the highest informational content. Nanoscience has therefore the opportunity of using DNA molecules to increase the level of complexity and efficiency in self-assembling and self-directing processes.
Kirigami artificial muscles with complex biologically inspired morphologies

NASA Astrophysics Data System (ADS)

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.
Pushing the lipid envelope: using bio-inspired nanocomposites to understand and exploit lipid membrane limitations

NASA Astrophysics Data System (ADS)

Montano, Gabriel

Lipids serve as the organizing matrix material for biological membranes, the site of interaction of cells with the external environment. . As such, lipids play a critical role in structure/function relationships of an extraordinary number of critical biological processes. In this talk, we will look at bio-inspired membrane assemblies to better understand the roles of lipids in biological systems as well as attempt to generate materials that can mimic and potentially advance upon biological membrane processes. First, we will investigate the response of lipids to adverse conditions. In particular, I will present data that demonstrates the response of lipids to harsh conditions and how such responses can be exploited to generate nanocomposite rearrangements. I will also show the effect of adding the endotoxin lipopolysaccharide (LPS) to lipid bilayer assemblies and describe implications on our understanding of LPS organization in biological systems as well as describe induced lipid modifications that can be exploited to organize membrane composites with precise, two-dimensional geometric control. Lastly, I will describe the use of amphiphilic block copolymers to create membrane nanocomposites capable of mimicking biological systems. In particular, I will describe the use of our polymer-based membranes in creating artificial photosynthetic assemblies that rival biological systems in function in a more flexible, dynamic matrix.
The essence of student visual-spatial literacy and higher order thinking skills in undergraduate biology.

PubMed

Milner-Bolotin, Marina; Nashon, Samson Madera

2012-02-01

Science, engineering and mathematics-related disciplines have relied heavily on a researcher's ability to visualize phenomena under study and being able to link and superimpose various abstract and concrete representations including visual, spatial, and temporal. The spatial representations are especially important in all branches of biology (in developmental biology time becomes an important dimension), where 3D and often 4D representations are crucial for understanding the phenomena. By the time biology students get to undergraduate education, they are supposed to have acquired visual-spatial thinking skills, yet it has been documented that very few undergraduates and a small percentage of graduate students have had a chance to develop these skills to a sufficient degree. The current paper discusses the literature that highlights the essence of visual-spatial thinking and the development of visual-spatial literacy, considers the application of the visual-spatial thinking to biology education, and proposes how modern technology can help to promote visual-spatial literacy and higher order thinking among undergraduate students of biology.
Diversity of Students' Beliefs about Biological Evolution

ERIC Educational Resources Information Center

Clores, Michael A.; Limjap, Auxencia A.

2006-01-01

The purpose of this study was to determine the beliefs about biological evolution held by college freshman students in one Catholic university in the Philippines. After 4 weeks of constructivist-inspired instruction, interviews and journal entries revealed that the students have diverse beliefs about the theory of evolution. They posited…
Inspired Biological Engineering: Detection and Production of Polarized Light by Animals

DTIC Science & Technology

2009-05-26

polarizers in some mantis shrimps, where the animals’ cuticles combine dichroic polarizers based on the cuticular carotenoid, astaxanthin , with a... astaxanthin in animals - the first demonstration of a pigment-based polarizer intended for signaling in any biological system. We are preparing a paper for
An insect-inspired model for visual binding I: learning objects and their characteristics.

PubMed

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

2017-04-01

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

The role of pattern recognition in creative problem solving: a case study in search of new mathematics for biology.

PubMed

Hong, Felix T

2013-09-01

Rosen classified sciences into two categories: formalizable and unformalizable. Whereas formalizable sciences expressed in terms of mathematical theories were highly valued by Rutherford, Hutchins pointed out that unformalizable parts of soft sciences are of genuine interest and importance. Attempts to build mathematical theories for biology in the past century was met with modest and sporadic successes, and only in simple systems. In this article, a qualitative model of humans' high creativity is presented as a starting point to consider whether the gap between soft and hard sciences is bridgeable. Simonton's chance-configuration theory, which mimics the process of evolution, was modified and improved. By treating problem solving as a process of pattern recognition, the known dichotomy of visual thinking vs. verbal thinking can be recast in terms of analog pattern recognition (non-algorithmic process) and digital pattern recognition (algorithmic process), respectively. Additional concepts commonly encountered in computer science, operations research and artificial intelligence were also invoked: heuristic searching, parallel and sequential processing. The refurbished chance-configuration model is now capable of explaining several long-standing puzzles in human cognition: a) why novel discoveries often came without prior warning, b) why some creators had no ideas about the source of inspiration even after the fact, c) why some creators were consistently luckier than others, and, last but not least, d) why it was so difficult to explain what intuition, inspiration, insight, hunch, serendipity, etc. are all about. The predictive power of the present model was tested by means of resolving Zeno's paradox of Achilles and the Tortoise after one deliberately invoked visual thinking. Additional evidence of its predictive power must await future large-scale field studies. The analysis was further generalized to constructions of scientific theories in general. This approach is in line with Campbell's evolutionary epistemology. Instead of treating science as immutable Natural Laws, which already existed and which were just waiting to be discovered, scientific theories are regarded as humans' mental constructs, which must be invented to reconcile with observed natural phenomena. In this way, the pursuit of science is shifted from diligent and systematic (or random) searching for existing Natural Laws to firing up humans' imagination to comprehend Nature's behavioral pattern. The insights gained in understanding human creativity indicated that new mathematics that is capable of handling effectively parallel processing and human subjectivity is sorely needed. The past classification of formalizability vs. non-formalizability was made in reference to contemporary mathematics. Rosen's conclusion did not preclude future inventions of new biology-friendly mathematics. Copyright © 2013 Elsevier Ltd. All rights reserved.
Photosystem Inspired Peptide Hybrid Catalysts

DTIC Science & Technology

2017-06-07

greenhouse gas , CO2 also can be an abundant C1 feedstock. Inspired by biological enzyme system, especially dehydrogenase catalyzing CO2 reduction...utilizing a potentiostat and converted to the RHE reference scale. Typically, before the electrolysis, the catholyte was saturated with CO2 gas for at...least 15 min to satisfy the saturation of pH. When the passed charge runs to 5 C, the electrolysis was stopped. Then, gas products were sampled using a
Diverted organic synthesis (DOS): accessing a new, natural product inspired, neurotrophically active scaffold through an intramolecular Pauson-Khand reaction.

PubMed

Mehta, Goverdhan; Samineni, Ramesh; Srihari, Pabbaraja; Reddy, R Gajendra; Chakravarty, Sumana

2012-09-14

Drawing inspiration from the impressive neurotrophic activity exhibited by the natural product paecilomycine A, we have designed a new natural product-like scaffold employing an intramolecular Pauson-Khand reaction. Several compounds based on the new designer scaffold exhibited promising neurotrophic activity and are worthy of further biological evaluation. Our findings also highlight the importance of a DOS strategy in creating useful therapeutical leads.
Sundew-Inspired Adhesive Hydrogels Combined with Adipose-Derived Stem Cells for Wound Healing

PubMed Central

Sun, Leming; Huang, Yujian; Bian, Zehua; Petrosino, Jennifer; Fan, Zhen; Wang, Yongzhong; Park, Ki Ho; Yue, Tao; Schmidt, Michael; Galster, Scott; Ma, Jianjie; Zhu, Hua; Zhang, Mingjun

2016-01-01

The potential to harness the unique physical, chemical, and biological properties of the sundew (Drosera) plant’s adhesive hydrogels has long intrigued researchers searching for novel wound-healing applications. However, the ability to collect sufficient quantities of the sundew plant’s adhesive hydrogels is problematic and has eclipsed their therapeutic promise. Inspired by these natural hydrogels, we asked if sundew-inspired adhesive hydrogels could overcome the drawbacks associated with natural sundew hydrogels and be used in combination with stem-cell-based therapy to enhance wound-healing therapeutics. Using a bioinspired approach, we synthesized adhesive hydrogels comprised of sodium alginate, gum arabic, and calcium ions to mimic the properties of the natural sundew-derived adhesive hydrogels. We then characterized and showed that these sundew-inspired hydrogels promote wound healing through their superior adhesive strength, nanostructure, and resistance to shearing when compared to other hydrogels in vitro. In vivo, sundew-inspired hydrogels promoted a “suturing” effect to wound sites, which was demonstrated by enhanced wound closure following topical application of the hydrogels. In combination with mouse adipose-derived stem cells (ADSCs) and compared to other therapeutic biomaterials, the sundew-inspired hydrogels demonstrated superior wound-healing capabilities. Collectively, our studies show that sundew-inspired hydrogels contain ideal properties that promote wound healing and suggest that sundew-inspired-ADSCs combination therapy is an efficacious approach for treating wounds without eliciting noticeable toxicity or inflammation. PMID:26731614
Sundew-Inspired Adhesive Hydrogels Combined with Adipose-Derived Stem Cells for Wound Healing.

PubMed

Sun, Leming; Huang, Yujian; Bian, Zehua; Petrosino, Jennifer; Fan, Zhen; Wang, Yongzhong; Park, Ki Ho; Yue, Tao; Schmidt, Michael; Galster, Scott; Ma, Jianjie; Zhu, Hua; Zhang, Mingjun

2016-01-27

The potential to harness the unique physical, chemical, and biological properties of the sundew (Drosera) plant's adhesive hydrogels has long intrigued researchers searching for novel wound-healing applications. However, the ability to collect sufficient quantities of the sundew plant's adhesive hydrogels is problematic and has eclipsed their therapeutic promise. Inspired by these natural hydrogels, we asked if sundew-inspired adhesive hydrogels could overcome the drawbacks associated with natural sundew hydrogels and be used in combination with stem-cell-based therapy to enhance wound-healing therapeutics. Using a bioinspired approach, we synthesized adhesive hydrogels comprised of sodium alginate, gum arabic, and calcium ions to mimic the properties of the natural sundew-derived adhesive hydrogels. We then characterized and showed that these sundew-inspired hydrogels promote wound healing through their superior adhesive strength, nanostructure, and resistance to shearing when compared to other hydrogels in vitro. In vivo, sundew-inspired hydrogels promoted a "suturing" effect to wound sites, which was demonstrated by enhanced wound closure following topical application of the hydrogels. In combination with mouse adipose-derived stem cells (ADSCs) and compared to other therapeutic biomaterials, the sundew-inspired hydrogels demonstrated superior wound-healing capabilities. Collectively, our studies show that sundew-inspired hydrogels contain ideal properties that promote wound healing and suggest that sundew-inspired-ADSCs combination therapy is an efficacious approach for treating wounds without eliciting noticeable toxicity or inflammation.
Visualized and precise design of artificial small RNAs for regulating T7 RNA polymerase and enhancing recombinant protein folding in Escherichia coli.

PubMed

Zhao, Yujia; Fan, Jingjing; Li, Jinlin; Li, Jun; Zhou, Xiaohong; Li, Chun

2016-12-01

Small non-coding RNAs (sRNAs) have received much attention in recent years due to their unique biological properties, which can efficiently and specifically tune target gene expressions in bacteria. Inspired by natural sRNAs, recent works have proposed the use of artificial sRNAs (asRNAs) as genetic tools to regulate desired gene that has been applied in several fields, such as metabolic engineering and bacterial physiology studies. However, the rational design of asRNAs is still a challenge. In this study, we proposed structure and length as two criteria to implement rational visualized and precise design of asRNAs. T7 expression system was one of the most useful recombinant protein expression systems. However, it was deeply limited by the formation of inclusion body. To settle this problem, we designed a series of asRNAs to inhibit the T7 RNA polymerase (Gene1) expression to balance the rate between transcription and folding of recombinant protein. Based on the heterologous expression of Aspergillus oryzae Li-3 glucuronidase in E. coli , the asRNA-antigene1-17bp can effectively decrease the inclusion body and increase the enzyme activity by 169.9%.
The painful muse: migrainous artistic archetypes from visual cortex.

PubMed

Aguggia, Marco; Grassi, Enrico

2014-05-01

Neurological diseases which constituted traditionally obstacles to artistic creation can, in the case of migraine, be transformed by the artists into a source of inspiration and artistic production. These phenomena represent a chapter of a broader embryonic neurobiology of painting.
A Compact VLSI System for Bio-Inspired Visual Motion Estimation.

PubMed

Shi, Cong; Luo, Gang

2018-04-01

This paper proposes a bio-inspired visual motion estimation algorithm based on motion energy, along with its compact very-large-scale integration (VLSI) architecture using low-cost embedded systems. The algorithm mimics motion perception functions of retina, V1, and MT neurons in a primate visual system. It involves operations of ternary edge extraction, spatiotemporal filtering, motion energy extraction, and velocity integration. Moreover, we propose the concept of confidence map to indicate the reliability of estimation results on each probing location. Our algorithm involves only additions and multiplications during runtime, which is suitable for low-cost hardware implementation. The proposed VLSI architecture employs multiple (frame, pixel, and operation) levels of pipeline and massively parallel processing arrays to boost the system performance. The array unit circuits are optimized to minimize hardware resource consumption. We have prototyped the proposed architecture on a low-cost field-programmable gate array platform (Zynq 7020) running at 53-MHz clock frequency. It achieved 30-frame/s real-time performance for velocity estimation on 160 × 120 probing locations. A comprehensive evaluation experiment showed that the estimated velocity by our prototype has relatively small errors (average endpoint error < 0.5 pixel and angular error < 10°) for most motion cases.
Developing an active artificial hair cell using nonlinear feedback control

NASA Astrophysics Data System (ADS)

Joyce, Bryan S.; Tarazaga, Pablo A.

2015-09-01

The hair cells in the mammalian cochlea convert sound-induced vibrations into electrical signals. These cells have inspired a variety of artificial hair cells (AHCs) to serve as biologically inspired sound, fluid flow, and acceleration sensors and could one day replace damaged hair cells in humans. Most of these AHCs rely on passive transduction of stimulus while it is known that the biological cochlea employs active processes to amplify sound-induced vibrations and improve sound detection. In this work, an active AHC mimics the active, nonlinear behavior of the cochlea. The AHC consists of a piezoelectric bimorph beam subjected to a base excitation. A feedback control law is used to reduce the linear damping of the beam and introduce a cubic damping term which gives the AHC the desired nonlinear behavior. Model and experimental results show the AHC amplifies the response due to small base accelerations, has a higher frequency sensitivity than the passive system, and exhibits a compressive nonlinearity like that of the mammalian cochlea. This bio-inspired accelerometer could lead to new sensors with lower thresholds of detection, improved frequency sensitivities, and wider dynamic ranges.
Expanded experimental parameter space of semiflexible polymer assemblies through programmable nanomaterials

NASA Astrophysics Data System (ADS)

Smith, David; Schuldt, Carsten; Lorenz, Jessica; Tschirner, Teresa; Moebius-Winkler, Maximilian; Kaes, Josef; Glaser, Martin; Haendler, Tina; Schnauss, Joerg

2015-03-01

Biologically evolved materials are often used as inspiration in the development of new materials as well as examinations into the underlying physical principles governing their behavior. For instance, the biopolymer constituents of the highly dynamic cellular cytoskeleton such as actin have inspired a deep understanding of soft polymer-based materials. However, the molecular toolbox provided by biological systems has been evolutionarily optimized to carry out the necessary functions of cells, and the inability modify basic properties such as biopolymer stiffness hinders a meticulous examination of parameter space. Using actin as inspiration, we circumvent these limitations using model systems assembled from programmable materials such as DNA. Nanorods with comparable, but controllable dimensions and mechanical properties as actin can be constructed from small sets of specially designed DNA strands. In entangled gels, these allow us to systematically determine the dependence of network mechanical properties on parameters such as persistence length and crosslink strength. At higher concentrations in the presence of local attractive forces, we see a transition to highly-ordered bundled and ``aster'' phases similar to those previously characterized in systems of actin or microtubules.
How chemistry supports cell biology: the chemical toolbox at your service.

PubMed

Wijdeven, Ruud H; Neefjes, Jacques; Ovaa, Huib

2014-12-01

Chemical biology is a young and rapidly developing scientific field. In this field, chemistry is inspired by biology to create various tools to monitor and modulate biochemical and cell biological processes. Chemical contributions such as small-molecule inhibitors and activity-based probes (ABPs) can provide new and unique insights into previously unexplored cellular processes. This review provides an overview of recent breakthroughs in chemical biology that are likely to have a significant impact on cell biology. We also discuss the application of several chemical tools in cell biology research. Copyright © 2014 Elsevier Ltd. All rights reserved.
Dew inspired breathing-based detection of genetic point mutation visualized by naked eye

PubMed Central

Xie, Liping; Wang, Tongzhou; Huang, Tianqi; Hou, Wei; Huang, Guoliang; Du, Yanan

2014-01-01

A novel label-free method based on breathing-induced vapor condensation was developed for detection of genetic point mutation. The dew-inspired detection was realized by integration of target-induced DNA ligation with rolling circle amplification (RCA). The vapor condensation induced by breathing transduced the RCA-amplified variances in DNA contents into visible contrast. The image could be recorded by a cell phone for further or even remote analysis. This green assay offers a naked-eye-reading method potentially applied for point-of-care liver cancer diagnosis in resource-limited regions. PMID:25199907
Dew inspired breathing-based detection of genetic point mutation visualized by naked eye

NASA Astrophysics Data System (ADS)

Xie, Liping; Wang, Tongzhou; Huang, Tianqi; Hou, Wei; Huang, Guoliang; Du, Yanan

2014-09-01

A novel label-free method based on breathing-induced vapor condensation was developed for detection of genetic point mutation. The dew-inspired detection was realized by integration of target-induced DNA ligation with rolling circle amplification (RCA). The vapor condensation induced by breathing transduced the RCA-amplified variances in DNA contents into visible contrast. The image could be recorded by a cell phone for further or even remote analysis. This green assay offers a naked-eye-reading method potentially applied for point-of-care liver cancer diagnosis in resource-limited regions.
Dew inspired breathing-based detection of genetic point mutation visualized by naked eye.

PubMed

Xie, Liping; Wang, Tongzhou; Huang, Tianqi; Hou, Wei; Huang, Guoliang; Du, Yanan

2014-09-09

A novel label-free method based on breathing-induced vapor condensation was developed for detection of genetic point mutation. The dew-inspired detection was realized by integration of target-induced DNA ligation with rolling circle amplification (RCA). The vapor condensation induced by breathing transduced the RCA-amplified variances in DNA contents into visible contrast. The image could be recorded by a cell phone for further or even remote analysis. This green assay offers a naked-eye-reading method potentially applied for point-of-care liver cancer diagnosis in resource-limited regions.
Bacteriophage lambda: The path from biology to theranostic agent.

PubMed

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.
Development of the Biological Experimental Design Concept Inventory (BEDCI)

ERIC Educational Resources Information Center

Deane, Thomas; Nomme, Kathy; Jeffery, Erica; Pollock, Carol; Birol, Gulnur

2014-01-01

Interest in student conception of experimentation inspired the development of a fully validated 14-question inventory on experimental design in biology (BEDCI) by following established best practices in concept inventory (CI) design. This CI can be used to diagnose specific examples of non-expert-like thinking in students and to evaluate the…
Target position uncertainty during visually guided deep-inspiration breath-hold radiotherapy in locally advanced lung cancer.

PubMed

Scherman Rydhög, Jonas; Riisgaard de Blanck, Steen; Josipovic, Mirjana; Irming Jølck, Rasmus; Larsen, Klaus Richter; Clementsen, Paul; Lars Andersen, Thomas; Poulsen, Per Rugaard; Fredberg Persson, Gitte; Munck Af Rosenschold, Per

2017-04-01

The purpose of this study was to estimate the uncertainty in voluntary deep-inspiration breath-hold (DIBH) radiotherapy for locally advanced non-small cell lung cancer (NSCLC) patients. Perpendicular fluoroscopic movies were acquired in free breathing (FB) and DIBH during a course of visually guided DIBH radiotherapy of nine patients with NSCLC. Patients had liquid markers injected in mediastinal lymph nodes and primary tumours. Excursion, systematic- and random errors, and inter-breath-hold position uncertainty were investigated using an image based tracking algorithm. A mean reduction of 2-6mm in marker excursion in DIBH versus FB was seen in the anterior-posterior (AP), left-right (LR) and cranio-caudal (CC) directions. Lymph node motion during DIBH originated from cardiac motion. The systematic- (standard deviation (SD) of all the mean marker positions) and random errors (root-mean-square of the intra-BH SD) during DIBH were 0.5 and 0.3mm (AP), 0.5 and 0.3mm (LR), 0.8 and 0.4mm (CC), respectively. The mean inter-breath-hold shifts were -0.3mm (AP), -0.2mm (LR), and -0.2mm (CC). Intra- and inter-breath-hold uncertainty of tumours and lymph nodes were small in visually guided breath-hold radiotherapy of NSCLC. Target motion could be substantially reduced, but not eliminated, using visually guided DIBH. Copyright © 2017 Elsevier B.V. All rights reserved.
The interplay of biology and technology

PubMed Central

Fields, Stanley

2001-01-01

Technologies for biological research arise in multiple ways—through serendipity, through inspired insights, and through incremental advances—and they are tightly coupled to progress in engineering. Underlying the complex dynamics of technology and biology are the different motivations of those who work in the two realms. Consideration of how methodologies emerge has implications for the planning of interdisciplinary centers and the training of the next generation of scientists. PMID:11517346
Sociology through Photography

ERIC Educational Resources Information Center

Hyde, Katherine

2015-01-01

This chapter describes how photography can inspire and cultivate sociological mindfulness. One set of assignments uses self-portraiture to highlight the complexity of visual representations of social identity. Another uses photography to guide sociological inquiry. Both sets of assignments draw on the Literacy Through Photography methodology,…
Seeing Cells: Teaching the Visual/Verbal Rhetoric of Biology

ERIC Educational Resources Information Center

Dinolfo, John; Heifferon, Barbara; Temesvari, Lesly A.

2007-01-01

This pilot study obtained baseline information on verbal and visual rhetorics to teach microscopy techniques to college biology majors. We presented cell images to students in cell biology and biology writing classes and then asked them to identify textual, verbal, and visual cues that support microscopy learning. Survey responses suggest that…

Ventral-stream-like shape representation: from pixel intensity values to trainable object-selective COSFIRE models

PubMed Central

Azzopardi, George; Petkov, Nicolai

2014-01-01

The remarkable abilities of the primate visual system have inspired the construction of computational models of some visual neurons. We propose a trainable hierarchical object recognition model, which we call S-COSFIRE (S stands for Shape and COSFIRE stands for Combination Of Shifted FIlter REsponses) and use it to localize and recognize objects of interests embedded in complex scenes. It is inspired by the visual processing in the ventral stream (V1/V2 → V4 → TEO). Recognition and localization of objects embedded in complex scenes is important for many computer vision applications. Most existing methods require prior segmentation of the objects from the background which on its turn requires recognition. An S-COSFIRE filter is automatically configured to be selective for an arrangement of contour-based features that belong to a prototype shape specified by an example. The configuration comprises selecting relevant vertex detectors and determining certain blur and shift parameters. The response is computed as the weighted geometric mean of the blurred and shifted responses of the selected vertex detectors. S-COSFIRE filters share similar properties with some neurons in inferotemporal cortex, which provided inspiration for this work. We demonstrate the effectiveness of S-COSFIRE filters in two applications: letter and keyword spotting in handwritten manuscripts and object spotting in complex scenes for the computer vision system of a domestic robot. S-COSFIRE filters are effective to recognize and localize (deformable) objects in images of complex scenes without requiring prior segmentation. They are versatile trainable shape detectors, conceptually simple and easy to implement. The presented hierarchical shape representation contributes to a better understanding of the brain and to more robust computer vision algorithms. PMID:25126068
Multiscale wavelet representations for mammographic feature analysis

NASA Astrophysics Data System (ADS)

Laine, Andrew F.; Song, Shuwu

1992-12-01

This paper introduces a novel approach for accomplishing mammographic feature analysis through multiresolution representations. We show that efficient (nonredundant) representations may be identified from digital mammography and used to enhance specific mammographic features within a continuum of scale space. The multiresolution decomposition of wavelet transforms provides a natural hierarchy in which to embed an interactive paradigm for accomplishing scale space feature analysis. Choosing wavelets (or analyzing functions) that are simultaneously localized in both space and frequency, results in a powerful methodology for image analysis. Multiresolution and orientation selectivity, known biological mechanisms in primate vision, are ingrained in wavelet representations and inspire the techniques presented in this paper. Our approach includes local analysis of complete multiscale representations. Mammograms are reconstructed from wavelet coefficients, enhanced by linear, exponential and constant weight functions localized in scale space. By improving the visualization of breast pathology we can improve the changes of early detection of breast cancers (improve quality) while requiring less time to evaluate mammograms for most patients (lower costs).
Autonomous Visual Navigation of an Indoor Environment Using a Parsimonious, Insect Inspired Familiarity Algorithm

PubMed Central

Brayfield, Brad P.

2016-01-01

The navigation of bees and ants from hive to food and back has captivated people for more than a century. Recently, the Navigation by Scene Familiarity Hypothesis (NSFH) has been proposed as a parsimonious approach that is congruent with the limited neural elements of these insects’ brains. In the NSFH approach, an agent completes an initial training excursion, storing images along the way. To retrace the path, the agent scans the area and compares the current scenes to those previously experienced. By turning and moving to minimize the pixel-by-pixel differences between encountered and stored scenes, the agent is guided along the path without having memorized the sequence. An important premise of the NSFH is that the visual information of the environment is adequate to guide navigation without aliasing. Here we demonstrate that an image landscape of an indoor setting possesses ample navigational information. We produced a visual landscape of our laboratory and part of the adjoining corridor consisting of 2816 panoramic snapshots arranged in a grid at 12.7-cm centers. We show that pixel-by-pixel comparisons of these images yield robust translational and rotational visual information. We also produced a simple algorithm that tracks previously experienced routes within our lab based on an insect-inspired scene familiarity approach and demonstrate that adequate visual information exists for an agent to retrace complex training routes, including those where the path’s end is not visible from its origin. We used this landscape to systematically test the interplay of sensor morphology, angles of inspection, and similarity threshold with the recapitulation performance of the agent. Finally, we compared the relative information content and chance of aliasing within our visually rich laboratory landscape to scenes acquired from indoor corridors with more repetitive scenery. PMID:27119720
Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition

PubMed Central

Cadieu, Charles F.; Hong, Ha; Yamins, Daniel L. K.; Pinto, Nicolas; Ardila, Diego; Solomon, Ethan A.; Majaj, Najib J.; DiCarlo, James J.

2014-01-01

The primate visual system achieves remarkable visual object recognition performance even in brief presentations, and under changes to object exemplar, geometric transformations, and background variation (a.k.a. core visual object recognition). This remarkable performance is mediated by the representation formed in inferior temporal (IT) cortex. In parallel, recent advances in machine learning have led to ever higher performing models of object recognition using artificial deep neural networks (DNNs). It remains unclear, however, whether the representational performance of DNNs rivals that of the brain. To accurately produce such a comparison, a major difficulty has been a unifying metric that accounts for experimental limitations, such as the amount of noise, the number of neural recording sites, and the number of trials, and computational limitations, such as the complexity of the decoding classifier and the number of classifier training examples. In this work, we perform a direct comparison that corrects for these experimental limitations and computational considerations. As part of our methodology, we propose an extension of “kernel analysis” that measures the generalization accuracy as a function of representational complexity. Our evaluations show that, unlike previous bio-inspired models, the latest DNNs rival the representational performance of IT cortex on this visual object recognition task. Furthermore, we show that models that perform well on measures of representational performance also perform well on measures of representational similarity to IT, and on measures of predicting individual IT multi-unit responses. Whether these DNNs rely on computational mechanisms similar to the primate visual system is yet to be determined, but, unlike all previous bio-inspired models, that possibility cannot be ruled out merely on representational performance grounds. PMID:25521294
Irrational Numbers Can "In-Spiral" You

ERIC Educational Resources Information Center

Lewis, Leslie D.

2007-01-01

This article describes the instructional process of helping students visualize irrational numbers. Students learn to create a spiral, called "the wheel of Theodorus," which demonstrates irrational and rational lengths. Examples of student work help the reader appreciate the delightful possibilities of this project. (Contains 4 figures.)
Cooperative Mission Concepts Using Biomorphic Explorers

NASA Technical Reports Server (NTRS)

Thakoor, S.; Miralles, C.; Martin, T.; Kahn, R.; Zurek, R.

2000-01-01

Inspired by the immense variety of naturally curious explorers (insects, animals, and birds), their wellintegrated biological sensor-processor suites, efficiently packaged in compact but highly dexterous forms, and their complex, intriguing, cooperative behavior, this paper focuses on "Biomorphic Explorers", their defination/classification, their designs, and presents planetary exploration scenarios based on the designs. Judicious blend of bio-inspired concepts and recent advances in micro-air vehicles, microsensors, microinstruments, MEMS, and microprocessors clearly suggests that the time of small, dedicated, low cost explorers that capture some of the key features of biological systems has arrived. Just as even small insects like ants, termites, honey bees etc working cooperatively in colonies can achieve big tasks, the biomorphic explorers hold the potential for obtaining science in-accessible by current large singular exploration platforms.
Object Persistence Enhances Spatial Navigation: A Case Study in Smartphone Vision Science.

PubMed

Liverence, Brandon M; Scholl, Brian J

2015-07-01

Violations of spatiotemporal continuity disrupt performance in many tasks involving attention and working memory, but experiments on this topic have been limited to the study of moment-by-moment on-line perception, typically assessed by passive monitoring tasks. We tested whether persisting object representations also serve as underlying units of longer-term memory and active spatial navigation, using a novel paradigm inspired by the visual interfaces common to many smartphones. Participants used key presses to navigate through simple visual environments consisting of grids of icons (depicting real-world objects), only one of which was visible at a time through a static virtual window. Participants found target icons faster when navigation involved persistence cues (via sliding animations) than when persistence was disrupted (e.g., via temporally matched fading animations), with all transitions inspired by smartphone interfaces. Moreover, this difference occurred even after explicit memorization of the relevant information, which demonstrates that object persistence enhances spatial navigation in an automatic and irresistible fashion. © The Author(s) 2015.
Engaging Patients With Advance Directives Using an Information Visualization Approach.

PubMed

Woollen, Janet; Bakken, Suzanne

2016-01-01

Despite the benefits of advance directives (AD) to patients and care providers, they are often not completed due to lack of patient awareness. The purpose of the current article is to advocate for creation and use of an innovative information visualization (infovisual) as a health communication tool aimed at improving AD dissemination and engagement. The infovisual would promote AD awareness by encouraging patients to learn about their options and inspire contemplation and conversation regarding their end-of-life (EOL) journey. An infovisual may be able to communicate insights that are often communicated in words, but are much more powerfully communicated by example. Furthermore, an infovisual could facilitate vivid understanding of options and inspire the beginning of often difficult conversations among care providers, patients, and loved ones. It may also save clinicians time, as care providers may be able to spend less time explaining details of EOL care options. Use of an infovisual could assist in ensuring a well-planned EOL journey. Copyright 2016, SLACK Incorporated.
Iridescence: a functional perspective

PubMed Central

Doucet, Stéphanie M.; Meadows, Melissa G.

2009-01-01

In animals, iridescence is generated by the interaction of light with biological tissues that are nanostructured to produce thin films or diffraction gratings. Uniquely among animal visual signals, the study of iridescent coloration contributes to biological and physical sciences by enhancing our understanding of the evolution of communication strategies, and by providing insights into physical optics and inspiring biomimetic technologies useful to humans. Iridescent colours are found in a broad diversity of animal taxa ranging from diminutive marine copepods to terrestrial insects and birds. Iridescent coloration has received a surge of research interest of late, and studies have focused on both characterizing the nanostructures responsible for producing iridescence and identifying the behavioural functions of iridescent colours. In this paper, we begin with a brief description of colour production mechanisms in animals and provide a general overview of the taxonomic distribution of iridescent colours. We then highlight unique properties of iridescent signals and review the proposed functions of iridescent coloration, focusing, in particular, on the ways in which iridescent colours allow animals to communicate with conspecifics and avoid predators. We conclude with a brief overview of non-communicative functions of iridescence in animals. Despite the vast amount of recent work on animal iridescence, our review reveals that many proposed functions of iridescent coloration remain virtually unexplored, and this area is clearly ripe for future research. PMID:19336344
AnnoLnc: a web server for systematically annotating novel human lncRNAs.

PubMed

Hou, Mei; Tang, Xing; Tian, Feng; Shi, Fangyuan; Liu, Fenglin; Gao, Ge

2016-11-16

Long noncoding RNAs (lncRNAs) have been shown to play essential roles in almost every important biological process through multiple mechanisms. Although the repertoire of human lncRNAs has rapidly expanded, their biological function and regulation remain largely elusive, calling for a systematic and integrative annotation tool. Here we present AnnoLnc ( http://annolnc.cbi.pku.edu.cn ), a one-stop portal for systematically annotating novel human lncRNAs. Based on more than 700 data sources and various tool chains, AnnoLnc enables a systematic annotation covering genomic location, secondary structure, expression patterns, transcriptional regulation, miRNA interaction, protein interaction, genetic association and evolution. An intuitive web interface is available for interactive analysis through both desktops and mobile devices, and programmers can further integrate AnnoLnc into their pipeline through standard JSON-based Web Service APIs. To the best of our knowledge, AnnoLnc is the only web server to provide on-the-fly and systematic annotation for newly identified human lncRNAs. Compared with similar tools, the annotation generated by AnnoLnc covers a much wider spectrum with intuitive visualization. Case studies demonstrate the power of AnnoLnc in not only rediscovering known functions of human lncRNAs but also inspiring novel hypotheses.
Education Catching Up with Science: Preparing Students for Three-Dimensional Literacy in Cell Biology

PubMed Central

Kramer, IJsbrand M.; Dahmani, Hassen-Reda; Delouche, Pamina; Bidabe, Marissa; Schneeberger, Patricia

2012-01-01

The large number of experimentally determined molecular structures has led to the development of a new semiotic system in the life sciences, with increasing use of accurate molecular representations. To determine how this change impacts students’ learning, we incorporated image tests into our introductory cell biology course. Groups of students used a single text dealing with signal transduction, which was supplemented with images made in one of three iconographic styles. Typically, we employed realistic renderings, using computer-generated Protein Data Bank (PDB) structures; realistic-schematic renderings, using shapes inspired by PDB structures; or schematic renderings, using simple geometric shapes to represent cellular components. The control group received a list of keywords. When students were asked to draw and describe the process in their own style and to reply to multiple-choice questions, the three iconographic approaches equally improved the overall outcome of the tests (relative to keywords). Students found the three approaches equally useful but, when asked to select a preferred style, they largely favored a realistic-schematic style. When students were asked to annotate “raw” realistic images, both keywords and schematic representations failed to prepare them for this task. We conclude that supplementary images facilitate the comprehension process and despite their visual clutter, realistic representations do not hinder learning in an introductory course. PMID:23222839
Bioarchitecture: bioinspired art and architecture--a perspective.

PubMed

Ripley, Renee L; Bhushan, Bharat

2016-08-06

Art and architecture can be an obvious choice to pair with science though historically this has not always been the case. This paper is an attempt to interact across disciplines, define a new genre, bioarchitecture, and present opportunities for further research, collaboration and professional cooperation. Biomimetics, or the copying of living nature, is a field that is highly interdisciplinary, involving the understanding of biological functions, structures and principles of various objects found in nature by scientists. Biomimetics can lead to biologically inspired design, adaptation or derivation from living nature. As applied to engineering, bioinspiration is a more appropriate term, involving interpretation, rather than direct copying. Art involves the creation of discrete visual objects intended by their creators to be appreciated by others. Architecture is a design practice that makes a theoretical argument and contributes to the discourse of the discipline. Bioarchitecture is a blending of art/architecture and biomimetics/bioinspiration, and incorporates a bioinspired design from the outset in all parts of the work at all scales. Herein, we examine various attempts to date of art and architecture to incorporate bioinspired design into their practice, and provide an outlook and provocation to encourage collaboration among scientists and designers, with the aim of achieving bioarchitecture.This article is part of the themed issue 'Bioinspired hierarchically structured surfaces for green science'. © 2016 The Author(s).
Education catching up with science: preparing students for three-dimensional literacy in cell biology.

PubMed

Kramer, Ijsbrand M; Dahmani, Hassen-Reda; Delouche, Pamina; Bidabe, Marissa; Schneeberger, Patricia

2012-01-01

The large number of experimentally determined molecular structures has led to the development of a new semiotic system in the life sciences, with increasing use of accurate molecular representations. To determine how this change impacts students' learning, we incorporated image tests into our introductory cell biology course. Groups of students used a single text dealing with signal transduction, which was supplemented with images made in one of three iconographic styles. Typically, we employed realistic renderings, using computer-generated Protein Data Bank (PDB) structures; realistic-schematic renderings, using shapes inspired by PDB structures; or schematic renderings, using simple geometric shapes to represent cellular components. The control group received a list of keywords. When students were asked to draw and describe the process in their own style and to reply to multiple-choice questions, the three iconographic approaches equally improved the overall outcome of the tests (relative to keywords). Students found the three approaches equally useful but, when asked to select a preferred style, they largely favored a realistic-schematic style. When students were asked to annotate "raw" realistic images, both keywords and schematic representations failed to prepare them for this task. We conclude that supplementary images facilitate the comprehension process and despite their visual clutter, realistic representations do not hinder learning in an introductory course.
Biomimetics--using nature to inspire human innovation.

PubMed

Bar-Cohen, Yoseph

2006-03-01

Evolution has resolved many of nature's challenges leading to lasting solutions. Nature has always inspired human achievements and has led to effective materials, structures, tools, mechanisms, processes, algorithms, methods, systems, and many other benefits (Bar-Cohen Y (ed) 2005 Biomimetics-Biologically Inspired Technologies (Boca Raton, FL: CRC Press) pp 1-552). This field, which is known as biomimetics, offers enormous potential for inspiring new capabilities for exciting future technologies. There are numerous examples of biomimetic successes that involve making simple copies, such as the use of fins for swimming. Others examples involved greater mimicking complexity including the mastery of flying that became possible only after the principles of aerodynamics were better understood. Some commercial implementations of biomimetics, including robotic toys and movie subjects, are increasingly appearing and behaving like living creatures. More substantial benefits of biomimetics include the development of prosthetics that closely mimic real limbs and sensory-enhancing microchips that are interfaced with the brain to assist in hearing, seeing and controlling instruments. A review is given of selected areas that were inspired by nature, and an outlook for potential development in biomimetics is presented.
Mobile robots for localizing gas emission sources on landfill sites: is bio-inspiration the way to go?

PubMed

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?

PubMed Central

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. PMID:22319493
Interactive and coordinated visualization approaches for biological data analysis.

PubMed

Cruz, António; Arrais, Joel P; Machado, Penousal

2018-03-26

The field of computational biology has become largely dependent on data visualization tools to analyze the increasing quantities of data gathered through the use of new and growing technologies. Aside from the volume, which often results in large amounts of noise and complex relationships with no clear structure, the visualization of biological data sets is hindered by their heterogeneity, as data are obtained from different sources and contain a wide variety of attributes, including spatial and temporal information. This requires visualization approaches that are able to not only represent various data structures simultaneously but also provide exploratory methods that allow the identification of meaningful relationships that would not be perceptible through data analysis algorithms alone. In this article, we present a survey of visualization approaches applied to the analysis of biological data. We focus on graph-based visualizations and tools that use coordinated multiple views to represent high-dimensional multivariate data, in particular time series gene expression, protein-protein interaction networks and biological pathways. We then discuss how these methods can be used to help solve the current challenges surrounding the visualization of complex biological data sets.
Indole diterpenoid natural products as the inspiration for new synthetic methods and strategies.

PubMed

Corsello, Michael A; Kim, Junyong; Garg, Neil K

2017-09-01

Indole terpenoids comprise a large class of natural products with diverse structural topologies and a broad range of biological activities. Accordingly, indole terpenoids have and continue to serve as attractive targets for chemical synthesis. Many synthetic efforts over the past few years have focused on a subclass of this family, the indole diterpenoids. This minireview showcases the role indole diterpenoids have played in inspiring the recent development of clever synthetic strategies, and new chemical reactions.
Additive Layer Manufacturing of Biologically Inspired Short Fibre Reinforced Composites

DTIC Science & Technology

2014-03-01

combination. It is frequently the determining factor for the type of fracture mechanism observed [9...Thin Solid Films, 1998. 334(1–2): p. 60-64. 56. Cannas, A., Fracture Mechanics and Failure Analysis of Hollow Shaped Fibre GFRP Composites, in ACCIS...architectures inspired by nature for improving the mechanical and functional properties of engineered materials. The study was advanced on two fronts: (1
Bio-inspired smart single asymmetric hourglass nanochannels for continuous shape and ion transport control.

PubMed

Zhang, Huacheng; Hou, Xu; Yang, Zhe; Yan, Dadong; Li, Lin; Tian, Ye; Wang, Huanting; Jiang, Lei

2015-02-18

Inspired by biological asymmetric ion channels, new shape-tunable and pH-responsive asymmetric hourglass single nanochannel systems demonstrate unique ion-transport properties. It is found that the change in shape and pH cooperatively control the ion transport within the nanochannel ranging from asymmetric shape with asymmetric ion transport, to asymmetric shape with symmetric ion transport and symmetric shape with symmetric ion transport. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Orientation selectivity based structure for texture classification

NASA Astrophysics Data System (ADS)

Wu, Jinjian; Lin, Weisi; Shi, Guangming; Zhang, Yazhong; Lu, Liu

2014-10-01

Local structure, e.g., local binary pattern (LBP), is widely used in texture classification. However, LBP is too sensitive to disturbance. In this paper, we introduce a novel structure for texture classification. Researches on cognitive neuroscience indicate that the primary visual cortex presents remarkable orientation selectivity for visual information extraction. Inspired by this, we investigate the orientation similarities among neighbor pixels, and propose an orientation selectivity based pattern for local structure description. Experimental results on texture classification demonstrate that the proposed structure descriptor is quite robust to disturbance.
Implementation of a Project-Based Molecular Biology Laboratory Emphasizing Protein Structure-Function Relationships in a Large Introductory Biology Laboratory Course

ERIC Educational Resources Information Center

Treacy, Daniel J.; Sankaran, Saumya M.; Gordon-Messer, Susannah; Saly, Danielle; Miller, Rebecca; Isaac, R. Stefan; Kosinski-Collins, Melissa S.

2011-01-01

In introductory laboratory courses, many universities are turning from traditional laboratories with predictable outcomes to inquiry-inspired, project-based laboratory curricula. In these labs, students are allowed to design at least some portion of their own experiment and interpret new, undiscovered data. We have redesigned the introductory…
Classification capacity of a modular neural network implementing neurally inspired architecture and training rules.

PubMed

Poirazi, Panayiota; Neocleous, Costas; Pattichis, Costantinos S; Schizas, Christos N

2004-05-01

A three-layer neural network (NN) with novel adaptive architecture has been developed. The hidden layer of the network consists of slabs of single neuron models, where neurons within a slab--but not between slabs--have the same type of activation function. The network activation functions in all three layers have adaptable parameters. The network was trained using a biologically inspired, guided-annealing learning rule on a variety of medical data. Good training/testing classification performance was obtained on all data sets tested. The performance achieved was comparable to that of SVM classifiers. It was shown that the adaptive network architecture, inspired from the modular organization often encountered in the mammalian cerebral cortex, can benefit classification performance.
Video Inspired the Radio Star: Interdisciplinary Projects for Media Arts and Music

ERIC Educational Resources Information Center

Giebelhausen, Robin

2017-01-01

Interdisciplinary arts education in music has often included connective lines toward drama, dance, and visual arts. This article will suggest five different projects that could be used to link music to video in order to develop media arts and music interdisciplinary connections.
Wilderness Vision Quest: A Journey of Transformation.

ERIC Educational Resources Information Center

Brown, Michael H.

The Wilderness Vision Quest is an outdoor retreat which helps participants touch, explore, and develop important latent human resources such as imagination, intuition, creativity, inspiration, and insight. Through the careful and focused use of techniques such as deep relaxation, reflective writing, visualization, guided imagery, symbolic drawing,…
HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition.

PubMed

Lagorce, Xavier; Orchard, Garrick; Galluppi, Francesco; Shi, Bertram E; Benosman, Ryad B

2017-07-01

This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.
Dopamine signaling and myopia development: What are the key challenges.

PubMed

Zhou, Xiangtian; Pardue, Machelle T; Iuvone, P Michael; Qu, Jia

2017-11-01

In the face of an "epidemic" increase in myopia over the last decades and myopia prevalence predicted to reach 2.5 billion people by the end of this decade, there is an urgent need to develop effective and safe therapeutic interventions to slow down this "myopia booming" and prevent myopia-related complications and vision loss. Dopamine (DA) is an important neurotransmitter in the retina and mediates diverse functions including retina development, visual signaling, and refractive development. Inspired by the convergence of epidemiological and animal studies in support of the inverse relationship between outdoor activity and risk of developing myopia and by the close biological relationship between light exposure and dopamine release/signaling, we felt it is timely and important to critically review the role of DA in myopia development. This review will revisit several key points of evidence for and against DA mediating light control of myopia: 1) the causal role of extracellular retinal DA levels, 2) the mechanism and action of dopamine D1 and D2 receptors and 3) the roles of cellular/circuit retinal pathways. We examine the experiments that show causation by altering DA, DA receptors and visual pathways using pharmacological, transgenic, or visual environment approaches. Furthermore, we critically evaluate the safety issues of a DA-based treatment strategy and some approaches to address these issues. The review identifies the key questions and challenges in translating basic knowledge on DA signaling and myopia from animal studies into effective pharmacological treatments for myopia in children. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
The Effects of Explicit Visual Cues in Reading Biological Diagrams

ERIC Educational Resources Information Center

Ge, Yun-Ping; Unsworth, Len; Wang, Kuo-Hua

2017-01-01

Drawing on cognitive theories, this study intends to investigate the effects of explicit visual cues which have been proposed as a critical factor in facilitating understanding of biological images. Three diagrams from Taiwanese textbooks with implicit visual cues, involving the concepts of biological classification systems, fish taxonomy, and…
A biologically inspired meta-control navigation system for the Psikharpax rat robot.

PubMed

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

2012-06-01

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

PubMed Central

Lin, Jingjing; Jing, Honglei

2016-01-01

Artificial immune system is one of the most recently introduced intelligence methods which was inspired by biological immune system. Most immune system inspired algorithms are based on the clonal selection principle, known as clonal selection algorithms (CSAs). When coping with complex optimization problems with the characteristics of multimodality, high dimension, rotation, and composition, the traditional CSAs often suffer from the premature convergence and unsatisfied accuracy. To address these concerning issues, a recombination operator inspired by the biological combinatorial recombination is proposed at first. The recombination operator could generate the promising candidate solution to enhance search ability of the CSA by fusing the information from random chosen parents. Furthermore, a modified hypermutation operator is introduced to construct more promising and efficient candidate solutions. A set of 16 common used benchmark functions are adopted to test the effectiveness and efficiency of the recombination and hypermutation operators. The comparisons with classic CSA, CSA with recombination operator (RCSA), and CSA with recombination and modified hypermutation operator (RHCSA) demonstrate that the proposed algorithm significantly improves the performance of classic CSA. Moreover, comparison with the state-of-the-art algorithms shows that the proposed algorithm is quite competitive. PMID:27698662
Maneuvering control and configuration adaptation of a biologically inspired morphing aircraft

NASA Astrophysics Data System (ADS)

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.
A bio-inspired flying robot sheds light on insect piloting abilities.

PubMed

Franceschini, Nicolas; Ruffier, Franck; Serres, Julien

2007-02-20

When insects are flying forward, the image of the ground sweeps backward across their ventral viewfield and forms an "optic flow," which depends on both the groundspeed and the groundheight. To explain how these animals manage to avoid the ground by using this visual motion cue, we suggest that insect navigation hinges on a visual-feedback loop we have called the optic-flow regulator, which controls the vertical lift. To test this idea, we built a micro-helicopter equipped with an optic-flow regulator and a bio-inspired optic-flow sensor. This fly-by-sight micro-robot can perform exacting tasks such as take-off, level flight, and landing. Our control scheme accounts for many hitherto unexplained findings published during the last 70 years on insects' visually guided performances; for example, it accounts for the fact that honeybees descend in a headwind, land with a constant slope, and drown when travelling over mirror-smooth water. Our control scheme explains how insects manage to fly safely without any of the instruments used onboard aircraft to measure the groundheight, groundspeed, and descent speed. An optic-flow regulator is quite simple in terms of its neural implementation and just as appropriate for insects as it would be for aircraft.
Fusion of nacre, mussel, and lotus leaf: bio-inspired graphene composite paper with multifunctional integration

NASA Astrophysics Data System (ADS)

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-cleaning, anti-corrosion, and remarkable mechanical properties underwater. Electronic supplementary information (ESI) available. See DOI: 10.1039/c3nr33632h
Computational evolution: taking liberties.

PubMed

Correia, Luís

2010-09-01

Evolution has, for a long time, inspired computer scientists to produce computer models mimicking its behavior. Evolutionary algorithm (EA) is one of the areas where this approach has flourished. EAs have been used to model and study evolution, but they have been especially developed for their aptitude as optimization tools for engineering. Developed models are quite simple in comparison with their natural sources of inspiration. However, since EAs run on computers, we have the freedom, especially in optimization models, to test approaches both realistic and outright speculative, from the biological point of view. In this article, we discuss different common evolutionary algorithm models, and then present some alternatives of interest. These include biologically inspired models, such as co-evolution and, in particular, symbiogenetics and outright artificial operators and representations. In each case, the advantages of the modifications to the standard model are identified. The other area of computational evolution, which has allowed us to study basic principles of evolution and ecology dynamics, is the development of artificial life platforms for open-ended evolution of artificial organisms. With these platforms, biologists can test theories by directly manipulating individuals and operators, observing the resulting effects in a realistic way. An overview of the most prominent of such environments is also presented. If instead of artificial platforms we use the real world for evolving artificial life, then we are dealing with evolutionary robotics (ERs). A brief description of this area is presented, analyzing its relations to biology. Finally, we present the conclusions and identify future research avenues in the frontier of computation and biology. Hopefully, this will help to draw the attention of more biologists and computer scientists to the benefits of such interdisciplinary research.
Limited Bandwidth Recognition of Collective Behaviors in Bio-Inspired Swarms

DTIC Science & Technology

2014-05-01

Nevai, K. M. Passino, and P. Srinivasan. Stability of choice in the honey bee nest-site selection processs. Journal of Theoretical Biology , 263(1):93...and N. Franks. Collective memory and spatial sorting in animal groups. Journal of Theoretical Biology , 218(1):1–11, 2002. [4] D. Cvetkovic, P...motion from local attraction. Journal of Theoretical Biology , 283(1):145–151, 2011. [18] G. Sukthankar and K. Sycara. Robust recognition of physical team
A Day in the Life

ERIC Educational Resources Information Center

Dunn, Tracie

2009-01-01

High-school students often tie the definition of art to a two-dimensional surface, obstructing possible solutions to visual problem-solving and restricting creative thinking. In this article, the author describes a project that inspired students to view arts as a social event: installation art. From a contemporary point of view, installation art…
Chicken Art

ERIC Educational Resources Information Center

Bickett, Marianne

2009-01-01

In this article, the author describes how a visit from a flock of chickens provided inspiration for the children's chicken art. The gentle clucking of the hens, the rooster crowing, and the softness of the feathers all provided rich aural, tactile, visual, and emotional experiences. The experience affirms the importance and value of direct…
Adhesion control by inflation: implications from biology to artificial attachment device

NASA Astrophysics Data System (ADS)

Dening, Kirstin; Heepe, Lars; Afferrante, Luciano; Carbone, Giuseppe; Gorb, Stanislav N.

2014-08-01

There is an increasing demand for materials that incorporate advanced adhesion properties, such as an ability to adhere in a reversible and controllable manner. In biological systems, these features are known from adhesive pads of the tree frog, Litoria caerulea, and the bush-cricket, Tettigonia viridissima. These species have convergently developed soft, hemispherically shaped pads that might be able to control their adhesion through active changing the curvature of the pad. Inspired by these biological systems, an artificial model system is developed here. It consists of an inflatable membrane clamped to the metallic cylinder and filled with air. Pull-off force measurements of the membrane surface were conducted in contact with the membrane at five different radii of curvature r c with (1) a smooth polyvinylsiloxane membrane and (2) mushroom-shaped adhesive microstructured membrane made of the same polymer. The hypothesis that an increased internal pressure, acting on the membrane, reduces the radius of the membrane curvature, resulting in turn in a lower pull-off force, is verified. Such an active control of adhesion, inspired by biological models, will lead to the development of industrial pick-and-drop devices with controllable adhesive properties.
A taxonomy of visualization tasks for the analysis of biological pathway data.

PubMed

Murray, Paul; McGee, Fintan; Forbes, Angus G

2017-02-15

Understanding complicated networks of interactions and chemical components is essential to solving contemporary problems in modern biology, especially in domains such as cancer and systems research. In these domains, biological pathway data is used to represent chains of interactions that occur within a given biological process. Visual representations can help researchers understand, interact with, and reason about these complex pathways in a number of ways. At the same time, these datasets offer unique challenges for visualization, due to their complexity and heterogeneity. Here, we present taxonomy of tasks that are regularly performed by researchers who work with biological pathway data. The generation of these tasks was done in conjunction with interviews with several domain experts in biology. These tasks require further classification than is provided by existing taxonomies. We also examine existing visualization techniques that support each task, and we discuss gaps in the existing visualization space revealed by our taxonomy. Our taxonomy is designed to support the development and design of future biological pathway visualization applications. We conclude by suggesting future research directions based on our taxonomy and motivated by the comments received by our domain experts.
A bio-inspired design of live cell biosensors

NASA Astrophysics Data System (ADS)

Marcek Chorvatova, A.; Teplicky, T.; Pavlinska, Z.; Kronekova, Z.; Trelova, D.; Razga, F.; Nemethova, V.; Uhelska, L.; Lacik, I.; Chorvat, D.

2018-02-01

The last decade has witnessed a rapid growth of nanoscale-oriented biosensors that becomes one of the most promising and rapidly growing areas of modern research. Despite significant advancements in conception of such biosensors, most are based at evaluation of molecular, or protein interactions. It is however becoming increasingly evident that functionality of a living system does not reside in genome or in individual proteins, as no real biological functionality is expressed at these levels. Instead, to comprehend the true functioning of a biological system, it is essential to understand the integrative physiological behavior of the complex molecular interactions in their natural environment and precise spatio-temporal topology. In this contribution we therefore present a new concept for creation of biosensors, bio-inspired from true functioning of living cells, while monitoring their endogenous fluorescence, or autofluorescence.

Fabrication of Nanochannels

PubMed Central

Zhang, Yuqi; Kong, Xiang-Yu; Gao, Loujun; Tian, Ye; Wen, Liping; Jiang, Lei

2015-01-01

Nature has inspired the fabrication of intelligent devices to meet the needs of the advanced community and better understand the imitation of biology. As a biomimetic nanodevice, nanochannels/nanopores aroused increasing interest because of their potential applications in nanofluidic fields. In this review, we have summarized some recent results mainly focused on the design and fabrication of one-dimensional nanochannels, which can be made of many materials, including polymers, inorganics, biotic materials, and composite materials. These nanochannels have some properties similar to biological channels, such as selectivity, voltage-dependent current fluctuations, ionic rectification current and ionic gating, etc. Therefore, they show great potential for the fields of biosensing, filtration, and energy conversions. These advances can not only help people to understand the living processes in nature, but also inspire scientists to develop novel nanodevices with better performance for mankind. PMID:28793564
Wet self-cleaning of superhydrophobic microfiber adhesives formed from high density polyethylene.

PubMed

Lee, Jongho; Fearing, Ronald S

2012-10-30

Biologically inspired adhesives developed for switchable and controllable adhesion often require repetitive uses in general, dirty, environments. Superhydrophobic microstructures on the lotus leaf lead to exceptional self-cleaning of dirt particles on nonadhesive surfaces with water droplets. This paper describes the self-cleaning properties of a hard-polymer-based adhesive formed with high-aspect-ratio microfibers from high-density polyethylene (HDPE). The microfiber adhesive shows almost complete wet self-cleaning of dirt particles with water droplets, recovering 98% of the adhesion of the pristine microfiber adhesives. The low contact angle hysteresis indicates that the surface of microfiber adhesives is superhydrophobic. Theoretical and experimental studies reveal a design parameter, length, which can control the adhesion without affecting the superhydrophobicity. The results suggest some properties of biologically inspired adhesives can be controlled independently by adjusting design parameters.
Biologically inspired artificial compound eyes.

PubMed

Jeong, Ki-Hun; Kim, Jaeyoun; Lee, Luke P

2006-04-28

This work presents the fabrication of biologically inspired artificial compound eyes. The artificial ommatidium, like that of an insect's compound eyes, consists of a refractive polymer microlens, a light-guiding polymer cone, and a self-aligned waveguide to collect light with a small angular acceptance. The ommatidia are omnidirectionally arranged along a hemispherical polymer dome such that they provide a wide field of view similar to that of a natural compound eye. The spherical configuration of the microlenses is accomplished by reconfigurable microtemplating, that is, polymer replication using the deformed elastomer membrane with microlens patterns. The formation of polymer waveguides self-aligned with microlenses is also realized by a self-writing process in a photosensitive polymer resin. The angular acceptance is directly measured by three-dimensional optical sectioning with a confocal microscope, and the detailed optical characteristics are studied in comparison with a natural compound eye.
Nanofibers of Human Tropoelastin-inspired peptides: Structural characterization and biological properties.

PubMed

Secchi, Valeria; Franchi, Stefano; Fioramonti, Marco; Polzonetti, Giovanni; Iucci, Giovanna; Bochicchio, Brigida; Battocchio, Chiara

2017-08-01

Regenerative medicine is taking great advantage from the use of biomaterials in the treatments of a wide range of diseases and injuries. Among other biomaterials, self-assembling peptides are appealing systems due to their ability to spontaneously form nanostructured hydrogels that can be directly injected into lesions. Indeed, self-assembling peptide scaffolds are expected to behave as biomimetic matrices able to surround cells, to promote specific interactions, and to control and modify cell behavior by mimicking the native environment as well. We selected three pentadecapeptides inspired by Human Tropoelastin, a natural protein of the extracellular matrix, expected to show high biocompatibility. Moreover, the here proposed self-assembling peptides (SAPs) are able to spontaneously aggregate in nanofibers in biological environment, as revealed by AFM (Atomic Force Microscopy). Peptides were characterized by XPS (X-ray Photoelectron Spectroscopy) and IRRAS (Infrared Reflection Absorption Spectroscopy) both as lyophilized (not aggregated) and as aggregated (nanofibers) samples in order to investigate some potential differences in their chemical composition and intermolecular interactions, and to analyze the surface and interface of nanofibers. Finally, an accurate investigation of the biological properties of the SAPs and of their interaction with cells was performed by culturing for the first time human Mesenchymal Stem Cells (hMSCs) in presence of SAPs. The final aim of this work was to assess if Human Tropoelastin-inspired nanostructured fibers could exert a cytotoxic effect and to evaluate their biocompatibility, cellular adhesion and proliferation. Copyright © 2017 Elsevier B.V. All rights reserved.
Student Interpretations of Phylogenetic Trees in an Introductory Biology Course

ERIC Educational Resources Information Center

Dees, Jonathan; Momsen, Jennifer L.; Niemi, Jarad; Montplaisir, Lisa

2014-01-01

Phylogenetic trees are widely used visual representations in the biological sciences and the most important visual representations in evolutionary biology. Therefore, phylogenetic trees have also become an important component of biology education. We sought to characterize reasoning used by introductory biology students in interpreting taxa…
Model-based setting of inspiratory pressure and respiratory rate in pressure-controlled ventilation.

PubMed

Schranz, C; Becher, T; Schädler, D; Weiler, N; Möller, K

2014-03-01

Mechanical ventilation carries the risk of ventilator-induced-lung-injury (VILI). To minimize the risk of VILI, ventilator settings should be adapted to the individual patient properties. Mathematical models of respiratory mechanics are able to capture the individual physiological condition and can be used to derive personalized ventilator settings. This paper presents model-based calculations of inspiration pressure (pI), inspiration and expiration time (tI, tE) in pressure-controlled ventilation (PCV) and a retrospective evaluation of its results in a group of mechanically ventilated patients. Incorporating the identified first order model of respiratory mechanics in the basic equation of alveolar ventilation yielded a nonlinear relation between ventilation parameters during PCV. Given this patient-specific relation, optimized settings in terms of minimal pI and adequate tE can be obtained. We then retrospectively analyzed data from 16 ICU patients with mixed pathologies, whose ventilation had been previously optimized by ICU physicians with the goal of minimization of inspiration pressure, and compared the algorithm's 'optimized' settings to the settings that had been chosen by the physicians. The presented algorithm visualizes the patient-specific relations between inspiration pressure and inspiration time. The algorithm's calculated results highly correlate to the physician's ventilation settings with r = 0.975 for the inspiration pressure, and r = 0.902 for the inspiration time. The nonlinear patient-specific relations of ventilation parameters become transparent and support the determination of individualized ventilator settings according to therapeutic goals. Thus, the algorithm is feasible for a variety of ventilated ICU patients and has the potential of improving lung-protective ventilation by minimizing inspiratory pressures and by helping to avoid the build-up of clinically significant intrinsic positive end-expiratory pressure.
Bio-inspired optical rotation sensor

NASA Astrophysics Data System (ADS)

O'Carroll, David C.; Shoemaker, Patrick A.; Brinkworth, Russell S. A.

2007-01-01

Traditional approaches to calculating self-motion from visual information in artificial devices have generally relied on object identification and/or correlation of image sections between successive frames. Such calculations are computationally expensive and real-time digital implementation requires powerful processors. In contrast flies arrive at essentially the same outcome, the estimation of self-motion, in a much smaller package using vastly less power. Despite the potential advantages and a few notable successes, few neuromorphic analog VLSI devices based on biological vision have been employed in practical applications to date. This paper describes a hardware implementation in aVLSI of our recently developed adaptive model for motion detection. The chip integrates motion over a linear array of local motion processors to give a single voltage output. Although the device lacks on-chip photodetectors, it includes bias circuits to use currents from external photodiodes, and we have integrated it with a ring-array of 40 photodiodes to form a visual rotation sensor. The ring configuration reduces pattern noise and combined with the pixel-wise adaptive characteristic of the underlying circuitry, permits a robust output that is proportional to image rotational velocity over a large range of speeds, and is largely independent of either mean luminance or the spatial structure of the image viewed. In principle, such devices could be used as an element of a velocity-based servo to replace or augment inertial guidance systems in applications such as mUAVs.
Automated, on-board terrain analysis for precision landings

NASA Technical Reports Server (NTRS)

Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.; Hines, Glenn D.

2006-01-01

Advances in space robotics technology hinge to a large extent upon the development and deployment of sophisticated new vision-based methods for automated in-space mission operations and scientific survey. To this end, we have developed a new concept for automated terrain analysis that is based upon a generic image enhancement platform|multi-scale retinex (MSR) and visual servo (VS) processing. This pre-conditioning with the MSR and the vs produces a "canonical" visual representation that is largely independent of lighting variations, and exposure errors. Enhanced imagery is then processed with a biologically inspired two-channel edge detection process, followed by a smoothness based criteria for image segmentation. Landing sites can be automatically determined by examining the results of the smoothness-based segmentation which shows those areas in the image that surpass a minimum degree of smoothness. Though the msr has proven to be a very strong enhancement engine, the other elements of the approach|the vs, terrain map generation, and smoothness-based segmentation|are in early stages of development. Experimental results on data from the Mars Global Surveyor show that the imagery can be processed to automatically obtain smooth landing sites. In this paper, we describe the method used to obtain these landing sites, and also examine the smoothness criteria in terms of the imager and scene characteristics. Several examples of applying this method to simulated and real imagery are shown.
Visual saliency detection based on modeling the spatial Gaussianity

NASA Astrophysics Data System (ADS)

Ju, Hongbin

2015-04-01

In this paper, a novel salient object detection method based on modeling the spatial anomalies is presented. The proposed framework is inspired by the biological mechanism that human eyes are sensitive to the unusual and anomalous objects among complex background. It is supposed that a natural image can be seen as a combination of some similar or dissimilar basic patches, and there is a direct relationship between its saliency and anomaly. Some patches share high degree of similarity and have a vast number of quantity. They usually make up the background of an image. On the other hand, some patches present strong rarity and specificity. We name these patches "anomalies". Generally, anomalous patch is a reflection of the edge or some special colors and textures in an image, and these pattern cannot be well "explained" by their surroundings. Human eyes show great interests in these anomalous patterns, and will automatically pick out the anomalous parts of an image as the salient regions. To better evaluate the anomaly degree of the basic patches and exploit their nonlinear statistical characteristics, a multivariate Gaussian distribution saliency evaluation model is proposed. In this way, objects with anomalous patterns usually appear as the outliers in the Gaussian distribution, and we identify these anomalous objects as salient ones. Experiments are conducted on the well-known MSRA saliency detection dataset. Compared with other recent developed visual saliency detection methods, our method suggests significant advantages.
Development of multifunctional materials exhibiting distributed sensing and actuation inspired by fish

NASA Astrophysics Data System (ADS)

Philen, Michael

2011-04-01

This manuscript is an overview of the research that is currently being performed as part of a 2009 NSF Office of Emerging Frontiers in Research and Innnovation (EFRI) grant on BioSensing and BioActuation (BSBA). The objectives of this multi-university collaborative research are to achieve a greater understanding of the hierarchical organization and structure of the sensory, muscular, and control systems of fish, and to develop advanced biologically-inspired material systems having distributed sensing, actuation, and intelligent control. New experimental apparatus have been developed for performing experiments involving live fish and robotic devices, and new bio-inspired haircell sensors and artificial muscles are being developed using carbonaceous nanomaterials, bio-derived molecules, and composite technology. Results demonstrating flow sensing and actuation are presented.
Inspiring future experimental scientists through questions related to colour

NASA Astrophysics Data System (ADS)

Fairchild, Mark D.; Melgosa, Manuel

2014-07-01

In general, it can be stated that unfortunately in most countries the number of students interested in traditional scientific disciplines (e.g. physics, chemistry, biology, mathematics, etc.) for his/her future professional careers has considerably decreased during the past years. It is likely that among the reasons of this trend we can find that many students feel that these disciplines are particularly difficult, complex, abstract, and even boring, while they consider applied sciences (e.g. engineering) as much more attractive options to them. Here we aim to attract people of very different ages to traditional scientific disciplines, and promote scientific knowledge, using a set of colour questions related to everyday experiences. From our answers to these questions we hope that people can understand and learn science in a rigorous, relaxed and amusing way, and hopefully they will be inspired to continue exploring on their own. Examples of such colour questions can be found at the free website http://whyiscolor.org from Mark D. Fairchild. For a wider dissemination, most contents of this website have been recently translated into Spanish language by the authors, and published in the book entitled "La tienda de las curiosidades sobre el color" (Editorial University of Granada, Spain, ISBN: 9788433853820). Colour is certainly multidisciplinary, and while it can be said that it is mainly a perception, optics is a key discipline to understand colour stimuli and phenomena. The classical first approach in colour science as the result of the interaction of light, objects, and the human visual system will be also reviewed.
Bio-Inspired Multi-Functional Drug Transport Design Concept and Simulations.

PubMed

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.
NASA, Engineering, and Swarming Robots

NASA Technical Reports Server (NTRS)

Leucht, Kurt

2015-01-01

This presentation is an introduction to NASA, to science and engineering, to biologically inspired robotics, and to the Swarmie ant-inspired robot project at KSC. This presentation is geared towards elementary school students, middle school students, and also high school students. This presentation is suitable for use in STEM (science, technology, engineering, and math) outreach events. The first use of this presentation will be on Oct 28, 2015 at Madison Middle School in Titusville, Florida where the author has been asked by the NASA-KSC Speakers Bureau to speak to the students about the Swarmie robots.
The neuropsychology of visual artistic production.

PubMed

Chatterjee, Anjan

2004-01-01

What happens to visual artists with neuropsychological deficits? This review will examine artistic production in individuals with a variety of syndromes including achromatopsia, neglect, visual agnosia, aphasia, epilepsy, migraine, dementia and autism. From this review it appears that artists are not spared visual-motor deficits despite their special graphic abilities. Rather their talents allow them to express visual deficits with particular eloquence. By contrast, the effects of aphasia on art are variable. In addition to deficits, neuropsychological syndromes may be associated with positive phenomena. Such phenomena induced by epilepsy or migraines can serve to inspire artists. This review also makes clear that artists with neuropsychological deficits do not necessarily produce art of lesser quality. Rather, their art may change in content or in style, sometimes in surprising and aesthetically pleasing ways. The neuropsychology of visual art also touches on a few central questions about the nature of artistic expression itself. For example, what forms can artistic representations take? How are visual features used descriptively and expressively? What roles do knowing and seeing play in depiction?
Benefits to society of bioinspired flight capabilities

NASA Technical Reports Server (NTRS)

Thakoor, S.; Zornetzer, S.; Lay, N.; Chahl, J.; Hine, B.

2003-01-01

This paper highlights how in just about 100 years since the first successful flight took place at Kitty Hawk, our recent developments using inspiration from biology are enabling us to demonstrate flight capability for Mars exploration.
Communicating catalysts

NASA Astrophysics Data System (ADS)

Weckhuysen, Bert M.

2018-06-01

The beauty and activity of enzymes inspire chemists to tailor new and better non-biological catalysts. Now, a study reveals that the active sites within heterogeneous catalysts actively cooperate in a fashion phenomenologically similar to, but mechanistically distinct, from enzymes.
On the role of emotion in biological and robotic autonomy.

PubMed

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.
Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines

ERIC Educational Resources Information Center

Mirel, Barbara; Kumar, Anuj; Nong, Paige; Su, Gang; Meng, Fan

2016-01-01

Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors…
Cognitive approaches for patterns analysis and security applications

NASA Astrophysics Data System (ADS)

Ogiela, Marek R.; Ogiela, Lidia

2017-08-01

In this paper will be presented new opportunities for developing innovative solutions for semantic pattern classification and visual cryptography, which will base on cognitive and bio-inspired approaches. Such techniques can be used for evaluation of the meaning of analyzed patterns or encrypted information, and allow to involve such meaning into the classification task or encryption process. It also allows using some crypto-biometric solutions to extend personalized cryptography methodologies based on visual pattern analysis. In particular application of cognitive information systems for semantic analysis of different patterns will be presented, and also a novel application of such systems for visual secret sharing will be described. Visual shares for divided information can be created based on threshold procedure, which may be dependent on personal abilities to recognize some image details visible on divided images.
GODIVA2: interactive visualization of environmental data on the Web.

PubMed

Blower, J D; Haines, K; Santokhee, A; Liu, C L

2009-03-13

GODIVA2 is a dynamic website that provides visual access to several terabytes of physically distributed, four-dimensional environmental data. It allows users to explore large datasets interactively without the need to install new software or download and understand complex data. Through the use of open international standards, GODIVA2 maintains a high level of interoperability with third-party systems, allowing diverse datasets to be mutually compared. Scientists can use the system to search for features in large datasets and to diagnose the output from numerical simulations and data processing algorithms. Data providers around Europe have adopted GODIVA2 as an INSPIRE-compliant dynamic quick-view system for providing visual access to their data.

Joint Force Quarterly. Issue 58, 3rd Quarter

DTIC Science & Technology

2010-06-01

rise to concerns over the future security of the Soviet nuclear arsenal. Anticipating the possibility of loosely controlled nuclear weapons inside...broader Cooperative Threat Reduction program—an unprecedented effort to reduce nuclear dangers by secur- ing or eliminating Russian weapons systems and...volume is about applications of the biological sciences, here called “biologi- cally inspired innovations,” to the military. Rather than treating
Using parallel evolutionary development for a biologically-inspired computer vision system for mobile robots.

PubMed

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

2005-01-01

We describe a new approach to attacking the problem of robust computer vision for mobile robots. The overall strategy is to mimic the biological evolution of animal vision systems. Our basic imaging sensor is based upon the eye of the common house fly, Musca domestica. The computational algorithms are a mix of traditional image processing, subspace techniques, and multilayer neural networks.
Raising Levels of Student Interest in Less Popular Areas of the Biology Curriculum: Can Teacher CPD Help?

ERIC Educational Resources Information Center

Goodger, Bev

2013-01-01

An opportunity for teachers to join 80 outstanding biological sciences undergraduates in a series of practical sessions and lectures at the 2010 Gatsby Plant Science Summer School has inspired the development of teaching and learning resources for use in schools. Plant scientists have a crucial role to play in society and it is hoped that the…
Biology-Inspired Autonomous Control

DTIC Science & Technology

2011-08-31

from load sensing in a turbulent flow field with high levels of plant uncertainty and optical feedback latency. The results of this paper suggest... Mimicry of biological systems, in the form of precise mathematical or physical dynamical modeling, is yielding impressive insight into the underlying...processing and plants , the aerospace industry has been slow to accept adaptive control. In the past decade however, newer methods for design of adaptive
Recent advances in biomimetic sensing technologies.

PubMed

Johnson, E A C; Bonser, R H C; Jeronimidis, G

2009-04-28

The importance of biological materials has long been recognized from the molecular level to higher levels of organization. Whereas, in traditional engineering, hardness and stiffness are considered desirable properties in a material, biology makes considerable and advantageous use of softer, more pliable resources. The development, structure and mechanics of these materials are well documented and will not be covered here. The purpose of this paper is, however, to demonstrate the importance of such materials and, in particular, the functional structures they form. Using only a few simple building blocks, nature is able to develop a plethora of diverse materials, each with a very different set of mechanical properties and from which a seemingly impossibly large number of assorted structures are formed. There is little doubt that this is made possible by the fact that the majority of biological 'materials' or 'structures' are based on fibres and that these fibres provide opportunities for functional hierarchies. We show how these structures have inspired a new generation of innovative technologies in the science and engineering community. Particular attention is given to the use of insects as models for biomimetically inspired innovations.
Biologically Inspired Purification and Dispersion of SWCNTs

NASA Technical Reports Server (NTRS)

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

2009-01-01

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

ERIC Educational Resources Information Center

Samuels, Jason

2010-01-01

This study was inspired by a history of student difficulties in calculus, and innovation in response to those difficulties. The goals of the study were fourfold. First, to design a mathlet for students to explore local linearity. Second, to redesign the curriculum of first semester calculus around the use of technology, an emphasis on…
Possessing New Worlds: Eliciting Abstract Thought and Empathic Response through Image Construction

ERIC Educational Resources Information Center

Noonan, Nancy

2010-01-01

In this study, secondary students' responses to literature were examined in the context of a visually rich curriculum. Working within a conceptual framework inspired by Rosenblatt's theories about aesthetic transactions with text, two groups of tenth grade readers negotiated and responded to shared class readings of works by John Steinbeck using…
Visualizing Neuroscience: Learning about the Brain through Art

ERIC Educational Resources Information Center

Chudler, Eric H.; Konrady, Paula

2006-01-01

Neuroscience is a subject that can motivate, excite, and stimulate the curiosity of everyone However, the study of the brain is made difficult by an abundance of new vocabulary words and abstract concepts. Although neuroscience has the potential to inspire students, many teachers find it difficult to include a study of the brain in their…
Transforming Ideas: The Design Process

ERIC Educational Resources Information Center

Nicol, Candace

2004-01-01

In this article, the author discusses how to teach students to think creatively. In the author's search for a way to teach students that there are multiple approaches to visual problems, she found inspiration from advertising. The author asserts students first need permission to explore their latent ideas, and second, they need the tools to…
Art Meets Science

ERIC Educational Resources Information Center

Rohs, C. Renee

2007-01-01

Numerous connections between the visual arts and sciences are evident if we choose to look for them. In February 2006, students and faculty from the Art and Geol/Geog departments at NW Missouri State University put together an exhibit at a local art gallery featuring works that were born out of science, inspired by science, or exploring the…
Teaching Conversations, Contemporary Art, and Figure Drawing

ERIC Educational Resources Information Center

Graham, Mark A.

2012-01-01

An important problem for high school art teachers is deciding what belongs in the art curriculum. What works of art, media, or ideas will inspire their students to more fully develop their own artistic potential and critically engage with contemporary art and culture? What artifacts of art, visual culture, or material culture should be included…
World Myths & Legends in Art.

ERIC Educational Resources Information Center

2002

Myths are stories that explain why the world is the way it is. All cultures have them. Throughout history, artists have been inspired by myths and legends and have given them visual form. Sometimes these works of art are the only surviving record of what particular cultures believed and valued. But even where written records or oral traditions…
Tying Theory To Practice: Cognitive Aspects of Computer Interaction in the Design Process.

ERIC Educational Resources Information Center

Mikovec, Amy E.; Dake, Dennis M.

The new medium of computer-aided design requires changes to the creative problem-solving methodologies typically employed in the development of new visual designs. Most theoretical models of creative problem-solving suggest a linear progression from preparation and incubation to some type of evaluative study of the "inspiration." These…
Media/Visual Literacy Art Education: Sexism in Hip-Hop Music Videos

ERIC Educational Resources Information Center

Chung, Sheng Kuan

2007-01-01

Media programs like hip-hop music videos are powerful aesthetic agents that inspire teenagers. Thus, they have tremendous influence on young people's identity formation, lifestyle choices, and knowledge construction which are manifested in the ways teens dress, express themselves, behave, and interact with each other. However, because of the…
Bio-inspired 3D microenvironments: a new dimension in tissue engineering.

PubMed

Magin, Chelsea M; Alge, Daniel L; Anseth, Kristi S

2016-03-04

Biomaterial scaffolds have been a foundational element of the tissue engineering paradigm since the inception of the field. Over the years there has been a progressive move toward the rational design and fabrication of bio-inspired materials that mimic the composition as well as the architecture and 3D structure of tissues. In this review, we chronicle advances in the field that address key challenges in tissue engineering as well as some emerging applications. Specifically, a summary of the materials and chemistries used to engineer bio-inspired 3D matrices that mimic numerous aspects of the extracellular matrix is provided, along with an overview of bioprinting, an additive manufacturing approach, for the fabrication of engineered tissues with precisely controlled 3D structures and architectures. To emphasize the potential clinical impact of the bio-inspired paradigm in biomaterials engineering, some applications of bio-inspired matrices are discussed in the context of translational tissue engineering. However, focus is also given to recent advances in the use of engineered 3D cellular microenvironments for fundamental studies in cell biology, including photoresponsive systems that are shedding new light on how matrix properties influence cell phenotype and function. In an outlook for future work, the need for high-throughput methods both for screening and fabrication is highlighted. Finally, microscale organ-on-a-chip technologies are highlighted as a promising area for future investment in the application of bio-inspired microenvironments.
A multilevel layout algorithm for visualizing physical and genetic interaction networks, with emphasis on their modular organization.

PubMed

Tuikkala, Johannes; Vähämaa, Heidi; Salmela, Pekka; Nevalainen, Olli S; Aittokallio, Tero

2012-03-26

Graph drawing is an integral part of many systems biology studies, enabling visual exploration and mining of large-scale biological networks. While a number of layout algorithms are available in popular network analysis platforms, such as Cytoscape, it remains poorly understood how well their solutions reflect the underlying biological processes that give rise to the network connectivity structure. Moreover, visualizations obtained using conventional layout algorithms, such as those based on the force-directed drawing approach, may become uninformative when applied to larger networks with dense or clustered connectivity structure. We implemented a modified layout plug-in, named Multilevel Layout, which applies the conventional layout algorithms within a multilevel optimization framework to better capture the hierarchical modularity of many biological networks. Using a wide variety of real life biological networks, we carried out a systematic evaluation of the method in comparison with other layout algorithms in Cytoscape. The multilevel approach provided both biologically relevant and visually pleasant layout solutions in most network types, hence complementing the layout options available in Cytoscape. In particular, it could improve drawing of large-scale networks of yeast genetic interactions and human physical interactions. In more general terms, the biological evaluation framework developed here enables one to assess the layout solutions from any existing or future graph drawing algorithm as well as to optimize their performance for a given network type or structure. By making use of the multilevel modular organization when visualizing biological networks, together with the biological evaluation of the layout solutions, one can generate convenient visualizations for many network biology applications.
Nonlinear dimensionality reduction methods for synthetic biology biobricks' visualization.

PubMed

Yang, Jiaoyun; Wang, Haipeng; Ding, Huitong; An, Ning; Alterovitz, Gil

2017-01-19

Visualizing data by dimensionality reduction is an important strategy in Bioinformatics, which could help to discover hidden data properties and detect data quality issues, e.g. data noise, inappropriately labeled data, etc. As crowdsourcing-based synthetic biology databases face similar data quality issues, we propose to visualize biobricks to tackle them. However, existing dimensionality reduction methods could not be directly applied on biobricks datasets. Hereby, we use normalized edit distance to enhance dimensionality reduction methods, including Isomap and Laplacian Eigenmaps. By extracting biobricks from synthetic biology database Registry of Standard Biological Parts, six combinations of various types of biobricks are tested. The visualization graphs illustrate discriminated biobricks and inappropriately labeled biobricks. Clustering algorithm K-means is adopted to quantify the reduction results. The average clustering accuracy for Isomap and Laplacian Eigenmaps are 0.857 and 0.844, respectively. Besides, Laplacian Eigenmaps is 5 times faster than Isomap, and its visualization graph is more concentrated to discriminate biobricks. By combining normalized edit distance with Isomap and Laplacian Eigenmaps, synthetic biology biobircks are successfully visualized in two dimensional space. Various types of biobricks could be discriminated and inappropriately labeled biobricks could be determined, which could help to assess crowdsourcing-based synthetic biology databases' quality, and make biobricks selection.
Normal form from biological motion despite impaired ventral stream function.

PubMed

Gilaie-Dotan, S; Bentin, S; Harel, M; Rees, G; Saygin, A P

2011-04-01

We explored the extent to which biological motion perception depends on ventral stream integration by studying LG, an unusual case of developmental visual agnosia. LG has significant ventral stream processing deficits but no discernable structural cortical abnormality. LG's intermediate visual areas and object-sensitive regions exhibit abnormal activation during visual object perception, in contrast to area V5/MT+ which responds normally to visual motion (Gilaie-Dotan, Perry, Bonneh, Malach, & Bentin, 2009). Here, in three studies we used point light displays, which require visual integration, in adaptive threshold experiments to examine LG's ability to detect form from biological and non-biological motion cues. LG's ability to detect and discriminate form from biological motion was similar to healthy controls. In contrast, he was significantly deficient in processing form from non-biological motion. Thus, LG can rely on biological motion cues to perceive human forms, but is considerably impaired in extracting form from non-biological motion. Finally, we found that while LG viewed biological motion, activity in a network of brain regions associated with processing biological motion was functionally correlated with his V5/MT+ activity, indicating that normal inputs from V5/MT+ might suffice to activate his action perception system. These results indicate that processing of biologically moving form can dissociate from other form processing in the ventral pathway. Furthermore, the present results indicate that integrative ventral stream processing is necessary for uncompromised processing of non-biological form from motion. Copyright © 2011 Elsevier Ltd. All rights reserved.
Signal-transducing proteins for nanoelectronics.

PubMed

Pichierri, Fabio

2006-12-01

This aim of this article is to provide novel paradigms for 21st century nanoelectronics by taking inspiration from the biology of signal transduction events where Nature has solved many complex problems, particularly those concerned with signal integration and amplification.

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

PubMed

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 Concepts for Autonomic Self-Protection in Multiagent Systems

NASA Technical Reports Server (NTRS)

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

PubMed

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

2013-07-07

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.
A biologically inspired immunization strategy for network epidemiology.

PubMed

Liu, Yang; Deng, Yong; Jusup, Marko; Wang, Zhen

2016-07-07

Well-known immunization strategies, based on degree centrality, betweenness centrality, or closeness centrality, either neglect the structural significance of a node or require global information about the network. We propose a biologically inspired immunization strategy that circumvents both of these problems by considering the number of links of a focal node and the way the neighbors are connected among themselves. The strategy thus measures the dependence of the neighbors on the focal node, identifying the ability of this node to spread the disease. Nodes with the highest ability in the network are the first to be immunized. To test the performance of our method, we conduct numerical simulations on several computer-generated and empirical networks, using the susceptible-infected-recovered (SIR) model. The results show that the proposed strategy largely outperforms the existing well-known strategies. Copyright © 2016 Elsevier Ltd. All rights reserved.
Natural products as an inspiration in the diversity-oriented synthesis of bioactive compound libraries

PubMed Central

Cordier, Christopher; Morton, Daniel; Murrison, Sarah; O'Leary-Steele, Catherine

2008-01-01

The purpose of diversity-oriented synthesis is to drive the discovery of small molecules with previously unknown biological functions. Natural products necessarily populate biologically relevant chemical space, since they bind both their biosynthetic enzymes and their target macromolecules. Natural product families are, therefore, libraries of pre-validated, functionally diverse structures in which individual compounds selectively modulate unrelated macromolecular targets. This review describes examples of diversity-oriented syntheses which have, to some extent, been inspired by the structures of natural products. Particular emphasis is placed on innovations that allow the synthesis of compound libraries that, like natural products, are skeletally diverse. Mimicking the broad structural features of natural products may allow the discovery of compounds that modulate the functions of macromolecules for which ligands are not known. The ability of innovations in diversity-oriented synthesis to deliver such compounds is critically assessed. PMID:18663392
Accelerating the design of biomimetic materials by integrating RNA-seq with proteomics and materials science.

PubMed

Guerette, Paul A; Hoon, Shawn; Seow, Yiqi; Raida, Manfred; Masic, Admir; Wong, Fong T; Ho, Vincent H B; Kong, Kiat Whye; Demirel, Melik C; Pena-Francesch, Abdon; Amini, Shahrouz; Tay, Gavin Z; Ding, Dawei; Miserez, Ali

2013-10-01

Efforts to engineer new materials inspired by biological structures are hampered by the lack of genomic data from many model organisms studied in biomimetic research. Here we show that biomimetic engineering can be accelerated by integrating high-throughput RNA-seq with proteomics and advanced materials characterization. This approach can be applied to a broad range of systems, as we illustrate by investigating diverse high-performance biological materials involved in embryo protection, adhesion and predation. In one example, we rapidly engineer recombinant squid sucker ring teeth proteins into a range of structural and functional materials, including nanopatterned surfaces and photo-cross-linked films that exceed the mechanical properties of most natural and synthetic polymers. Integrating RNA-seq with proteomics and materials science facilitates the molecular characterization of natural materials and the effective translation of their molecular designs into a wide range of bio-inspired materials.
Disappearance of the inversion effect during memory-guided tracking of scrambled biological motion.

PubMed

Jiang, Changhao; Yue, Guang H; Chen, Tingting; Ding, Jinhong

2016-08-01

The human visual system is highly sensitive to biological motion. Even when a point-light walker is temporarily occluded from view by other objects, our eyes are still able to maintain tracking continuity. To investigate how the visual system establishes a correspondence between the biological-motion stimuli visible before and after the disruption, we used the occlusion paradigm with biological-motion stimuli that were intact or scrambled. The results showed that during visually guided tracking, both the observers' predicted times and predictive smooth pursuit were more accurate for upright biological motion (intact and scrambled) than for inverted biological motion. During memory-guided tracking, however, the processing advantage for upright as compared with inverted biological motion was not found in the scrambled condition, but in the intact condition only. This suggests that spatial location information alone is not sufficient to build and maintain the representational continuity of the biological motion across the occlusion, and that the object identity may act as an important information source in visual tracking. The inversion effect disappeared when the scrambled biological motion was occluded, which indicates that when biological motion is temporarily occluded and there is a complete absence of visual feedback signals, an oculomotor prediction is executed to maintain the tracking continuity, which is established not only by updating the target's spatial location, but also by the retrieval of identity information stored in long-term memory.
From Bearing Witness to Art Exhibitions to Inspiring the Understanding of Climate Change

NASA Astrophysics Data System (ADS)

Burko, D.

2016-12-01

I intend to demonstrate how artists such as myself can influence the public discourse on climate change. I believe aesthetically compelling visualizations can transcend data and language. I will speak specifically to how I communicate scientific research to diverse populations. I have much to share since first speaking in 2012 on the Panel "Communication of Science through Art: Raison d'Etre for Interdisciplinary Communication". I then illustrated how I utilized visual cues such as archival evidence in the form of repeats, geological charts of recessional lines, graphs, symbols and Landsat maps in my large scale paintings and photographs and inspired learning. I continue to develop visual strategies delivering information on an emotional/non-verbal level. Now 4 years later, I've added the most dramatic layer to my creative process: bearing witness. I've been to the three largest ice fields in the world: Greenland, Antarctica and Argentina's Patagonia, observing the unprecedented pace of glacial melt. Those expeditions feed my practice, leading to exhibitions that begin a dialog with an audience not initially interested in science. In the past 5 years my work has appeared in 6 solo and 19 group exhibits all devoted to the environment. I make myself present in universities, museums and galleries to explain what the images are about. I require universities to include a public component: an all-college lecture or panel where the geography/environmental/sociology/geology departments participate with broad student involvement. I believe that such endeavors are worthwhile and can be models for further efforts to educate an unsuspecting audience. Artists can bridge the gap communicating to a public of art appreciators, nonscientists - how easy it is to understand geology and global warming. I believe we can even inspire attitudinal change. Aside from personal examples I will include other artists and exhibition venues contributing to this phenomenon.
Cell-free biology: exploiting the interface between synthetic biology and synthetic chemistry

PubMed Central

Harris, D. Calvin; Jewett, Michael C.

2014-01-01

Just as synthetic organic chemistry once revolutionized the ability of chemists to build molecules (including those that did not exist in nature) following a basic set of design rules, cell-free synthetic biology is beginning to provide an improved toolbox and faster process for not only harnessing but also expanding the chemistry of life. At the interface between chemistry and biology, research in cell-free synthetic systems is proceeding in two different directions: using synthetic biology for synthetic chemistry and using synthetic chemistry to reprogram or mimic biology. In the coming years, the impact of advances inspired by these approaches will make possible the synthesis of non-biological polymers having new backbone compositions, new chemical properties, new structures, and new functions. PMID:22483202
Biomimetics inspired surfaces for drag reduction and oleophobicity/philicity.

PubMed

Bhushan, Bharat

2011-01-01

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

PubMed Central

2011-01-01

Summary 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. PMID:21977417
Propulsion of swimming microrobots inspired by metachronal waves in ciliates: from biology to material specifications.

PubMed

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 probabilistic model of overt visual attention for cognitive robots.

PubMed

Begum, Momotaz; Karray, Fakhri; Mann, George K I; Gosine, Raymond G

2010-10-01

Visual attention is one of the major requirements for a robot to serve as a cognitive companion for human. The robotic visual attention is mostly concerned with overt attention which accompanies head and eye movements of a robot. In this case, each movement of the camera head triggers a number of events, namely transformation of the camera and the image coordinate systems, change of content of the visual field, and partial appearance of the stimuli. All of these events contribute to the reduction in probability of meaningful identification of the next focus of attention. These events are specific to overt attention with head movement and, therefore, their effects are not addressed in the classical models of covert visual attention. This paper proposes a Bayesian model as a robot-centric solution for the overt visual attention problem. The proposed model, while taking inspiration from the primates visual attention mechanism, guides a robot to direct its camera toward behaviorally relevant and/or visually demanding stimuli. A particle filter implementation of this model addresses the challenges involved in overt attention with head movement. Experimental results demonstrate the performance of the proposed model.
Controlled biological and biomimetic systems for landmine detection.

PubMed

Habib, Maki K

2007-08-30

Humanitarian demining requires to accurately detect, locate and deactivate every single landmine and other buried mine-like objects as safely and as quickly as possible, and in the most non-invasive manner. The quality of landmine detection affects directly the efficiency and safety of this process. Most of the available methods to detect explosives and landmines are limited by their sensitivity and/or operational complexities. All landmines leak with time small amounts of their explosives that can be found on surrounding ground and plant life. Hence, explosive signatures represent the robust primary indicator of landmines. Accordingly, developing innovative technologies and efficient techniques to identify in real-time explosives residue in mined areas represents an attractive and promising approach. Biological and biologically inspired detection technology has the potential to compete with or be used in conjunction with other artificial technology to complement performance strengths. Biological systems are sensitive to many different scents concurrently, a property that has proven difficult to replicate artificially. Understanding biological systems presents unique opportunities for developing new capabilities through direct use of trained bio-systems, integration of living and non-living components, or inspiring new design by mimicking biological capabilities. It is expected that controlled bio-systems, biotechnology and microbial techniques will contribute to the advancement of mine detection and other application domains. This paper provides directions, evaluation and analysis on the progress of controlled biological and biomimetic systems for landmine detection. It introduces and discusses different approaches developed, underlining their relative advantages and limitations, and highlighting trends, safety and ecology concern, and possible future directions.
Sparse Contextual Activation for Efficient Visual Re-Ranking.

PubMed

Bai, Song; Bai, Xiang

2016-03-01

In this paper, we propose an extremely efficient algorithm for visual re-ranking. By considering the original pairwise distance in the contextual space, we develop a feature vector called sparse contextual activation (SCA) that encodes the local distribution of an image. Hence, re-ranking task can be simply accomplished by vector comparison under the generalized Jaccard metric, which has its theoretical meaning in the fuzzy set theory. In order to improve the time efficiency of re-ranking procedure, inverted index is successfully introduced to speed up the computation of generalized Jaccard metric. As a result, the average time cost of re-ranking for a certain query can be controlled within 1 ms. Furthermore, inspired by query expansion, we also develop an additional method called local consistency enhancement on the proposed SCA to improve the retrieval performance in an unsupervised manner. On the other hand, the retrieval performance using a single feature may not be satisfactory enough, which inspires us to fuse multiple complementary features for accurate retrieval. Based on SCA, a robust feature fusion algorithm is exploited that also preserves the characteristic of high time efficiency. We assess our proposed method in various visual re-ranking tasks. Experimental results on Princeton shape benchmark (3D object), WM-SRHEC07 (3D competition), YAEL data set B (face), MPEG-7 data set (shape), and Ukbench data set (image) manifest the effectiveness and efficiency of SCA.
High-resolution remotely sensed small target detection by imitating fly visual perception mechanism.

PubMed

Huang, Fengchen; Xu, Lizhong; Li, Min; Tang, Min

2012-01-01

The difficulty and limitation of small target detection methods for high-resolution remote sensing data have been a recent research hot spot. Inspired by the information capture and processing theory of fly visual system, this paper endeavors to construct a characterized model of information perception and make use of the advantages of fast and accurate small target detection under complex varied nature environment. The proposed model forms a theoretical basis of small target detection for high-resolution remote sensing data. After the comparison of prevailing simulation mechanism behind fly visual systems, we propose a fly-imitated visual system method of information processing for high-resolution remote sensing data. A small target detector and corresponding detection algorithm are designed by simulating the mechanism of information acquisition, compression, and fusion of fly visual system and the function of pool cell and the character of nonlinear self-adaption. Experiments verify the feasibility and rationality of the proposed small target detection model and fly-imitated visual perception method.
Biomimetics: using nature as an inspiring model for human innovation

NASA Technical Reports Server (NTRS)

Bar-Cohen, Yoseph

2006-01-01

The evolution of nature over 3.8 billion years led to the highly effective and power efficient biological mechanisms. Imitating these mechanisms offers enormous potentials for the improvement of our life and the tools we use.
Biologically Inspired Network (BiONet) Authentication using Logical and Pathological RF DNA Credential Pairs

DTIC Science & Technology

2017-09-14

e.g. 000111) may be emitted along an ultra- high frequency (UHF) communications path as a possible waveform state generated by some circuit...Positive Rate TN True Negative TNR True Negative Rate TVR True Verification Rate Tx Transmitter UHF Ultra High Frequency 21 BIOLOGICALLY...otherwise healthy RF networks. More specifically, a representative miniaturized ultra- high frequency (UHF) CubeSat uplink access boundary, protected
Synthesis of thin films and materials utilizing a gaseous catalyst

DOEpatents

Morse, Daniel E; Schwenzer, Birgit; Gomm, John R; Roth, Kristian M; Heiken, Brandon; Brutchey, Richard

2013-10-29

A method for the fabrication of nanostructured semiconducting, photoconductive, photovoltaic, optoelectronic and electrical battery thin films and materials at low temperature, with no molecular template and no organic contaminants. High-quality metal oxide semiconductor, photovoltaic and optoelectronic materials can be fabricated with nanometer-scale dimensions and high dopant densities through the use of low-temperature biologically inspired synthesis routes, without the use of any biological or biochemical templates.
Bio-Inspired Materials and Devices for Chemical and Biological Defense

DTIC Science & Technology

2010-09-01

Assembled Soft Matter for in vivo Optical Imaging. PNAS 2005, 102(8), pp 2922-2927. 37 Reiner, J.E.; Wells, J.M.; Kishore, R.B.; Pfefferkorn, C...materials ex- vivo as well as the more common standpoint of using nonbiological materials in biological environments, i.e., biocompatibility. Many...tube constitute a MWCNT . In comparison with SWCNTs, multiwalled tubes sacrifice electrical properties in favor of stability and ease of manufacture

Biologically Inspired Behavioral Strategies for Autonomous Aerial Explorers on Mars

NASA Technical Reports Server (NTRS)

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

2002-01-01

The natural world is a rich source of problem- solving approaches. This paper discusses the feasibility and technical challenges underlying mimicking, or analogously adapting, biological behavioral strategies to mission/flight planning for aerial vehicles engaged in planetary exploration. Two candidate concepts based on natural resource utilization and searching behaviors are adapted io technological applications. Prototypes and test missions addressing the difficulties of implementation and their solutions are also described.
Nanoscale platforms for messenger RNA delivery.

PubMed

Li, Bin; Zhang, Xinfu; Dong, Yizhou

2018-05-04

Messenger RNA (mRNA) has become a promising class of drugs for diverse therapeutic applications in the past few years. A series of clinical trials are ongoing or will be initiated in the near future for the treatment of a variety of diseases. Currently, mRNA-based therapeutics mainly focuses on ex vivo transfection and local administration in clinical studies. Efficient and safe delivery of therapeutically relevant mRNAs remains one of the major challenges for their broad applications in humans. Thus, effective delivery systems are urgently needed to overcome this limitation. In recent years, numerous nanoscale biomaterials have been constructed for mRNA delivery in order to protect mRNA from extracellular degradation and facilitate endosomal escape after cellular uptake. Nanoscale platforms have expanded the feasibility of mRNA-based therapeutics, and enabled its potential applications to protein replacement therapy, cancer immunotherapy, therapeutic vaccines, regenerative medicine, and genome editing. This review focuses on recent advances, challenges, and future directions in nanoscale platforms designed for mRNA delivery, including lipid and lipid-derived nanoparticles, polymer-based nanoparticles, protein derivatives mRNA complexes, and other types of nanomaterials. This article is categorized under: Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Biology-Inspired Nanomaterials > Lipid-Based Structures Biology-Inspired Nanomaterials > Nucleic Acid-Based Structures. © 2018 Wiley Periodicals, Inc.
The Wyss institute: A new model for medical technology innovation and translation across the academic-industrial interface.

PubMed

Tolikas, Mary; Antoniou, Ayis; Ingber, Donald E

2017-09-01

The Wyss Institute for Biologically Inspired Engineering at Harvard University was formed based on the recognition that breakthrough discoveries cannot change the world if they never leave the laboratory. The Institute's mission is to discover the biological principles that Nature uses to build living things, and to harness these insights to create biologically inspired engineering innovations to advance human health and create a more sustainable world. Since its launch in 2009, the Institute has developed a new model for innovation, collaboration, and technology translation within academia, breaking "silos" to enable collaborations that cross institutional and disciplinary barriers. Institute faculty and staff engage in high-risk research that leads to transformative breakthroughs. The biological principles uncovered are harnessed to develop new engineering solutions for medicine and healthcare, as well as nonmedical areas, such as energy, architecture, robotics, and manufacturing. These technologies are translated into commercial products and therapies through collaborations with clinical investigators, corporate alliances, and the formation of new start-ups that are driven by a unique internal business development team including entrepreneurs-in-residence with domain-specific expertise. Here, we describe this novel organizational model that the Institute has developed to change the paradigm of how fundamental discovery, medical technology innovation, and commercial translation are carried out at the academic-industrial interface.
Sparing of Sensitivity to Biological Motion but Not of Global Motion after Early Visual Deprivation

ERIC Educational Resources Information Center

Hadad, Bat-Sheva; Maurer, Daphne; Lewis, Terri L.

2012-01-01

Patients deprived of visual experience during infancy by dense bilateral congenital cataracts later show marked deficits in the perception of global motion (dorsal visual stream) and global form (ventral visual stream). We expected that they would also show marked deficits in sensitivity to biological motion, which is normally processed in the…
On Biological Network Visualization: Understanding Challenges, Measuring the Status Quo, and Estimating Saliency of Visual Attributes

ERIC Educational Resources Information Center

Gopal, Nikhil

2017-01-01

Biomedical research increasingly relies on the analysis and visualization of a wide range of collected data. However, for certain research questions, such as those investigating the interconnectedness of biological elements, the sheer quantity and variety of data results in rather uninterpretable--this is especially true for network visualization,…
Motion Estimation Using the Single-row Superposition-type Planar Compound-like Eye

PubMed Central

Cheng, Chi-Cheng; Lin, Gwo-Long

2007-01-01

How can the compound eye of insects capture the prey so accurately and quickly? This interesting issue is explored from the perspective of computer vision instead of from the viewpoint of biology. The focus is on performance evaluation of noise immunity for motion recovery using the single-row superposition-type planar compound like eye (SPCE). The SPCE owns a special symmetrical framework with tremendous amount of ommatidia inspired by compound eye of insects. The noise simulates possible ambiguity of image patterns caused by either environmental uncertainty or low resolution of CCD devices. Results of extensive simulations indicate that this special visual configuration provides excellent motion estimation performance regardless of the magnitude of the noise. Even when the noise interference is serious, the SPCE is able to dramatically reduce errors of motion recovery of the ego-translation without any type of filters. In other words, symmetrical, regular, and multiple vision sensing devices of the compound-like eye have statistical averaging advantage to suppress possible noises. This discovery lays the basic foundation in terms of engineering approaches for the secret of the compound eye of insects.
Clustering document fragments using background color and texture information

NASA Astrophysics Data System (ADS)

Chanda, Sukalpa; Franke, Katrin; Pal, Umapada

2012-01-01

Forensic analysis of questioned documents sometimes can be extensively data intensive. A forensic expert might need to analyze a heap of document fragments and in such cases to ensure reliability he/she should focus only on relevant evidences hidden in those document fragments. Relevant document retrieval needs finding of similar document fragments. One notion of obtaining such similar documents could be by using document fragment's physical characteristics like color, texture, etc. In this article we propose an automatic scheme to retrieve similar document fragments based on visual appearance of document paper and texture. Multispectral color characteristics using biologically inspired color differentiation techniques are implemented here. This is done by projecting document color characteristics to Lab color space. Gabor filter-based texture analysis is used to identify document texture. It is desired that document fragments from same source will have similar color and texture. For clustering similar document fragments of our test dataset we use a Self Organizing Map (SOM) of dimension 5×5, where the document color and texture information are used as features. We obtained an encouraging accuracy of 97.17% from 1063 test images.
Jumping hoops on water

NASA Astrophysics Data System (ADS)

Yang, Eunjin; Kim, Ho-Young

2015-11-01

Small aquatic arthropods, such as water striders and fishing spiders, are able to jump off water to a height several times their body length. Inspired by the unique biological motility on water, we study a simple model using a flexible hoop to provide fundamental understanding and a mimicking principle of small jumpers on water. Behavior of a hoop on water, which is coated with superhydrophobic particles and initially bent into an ellipse from an equilibrium circular shape, is visualized with a high speed camera upon launching it into air by releasing its initial elastic strain energy. We observe that jumping of our hoops is dominated by the dynamic pressure of water rather than surface tension, and thus it corresponds to the dynamic condition experienced by fishing spiders. We calculate the reaction forces provided by water adopting the unsteady Bernoulli equation as well as the momentum loss into liquid inertia and viscous friction. Our analysis allows us to predict the jumping efficiency of the hoop on water in comparison to that on ground, and to discuss the evolutionary pressure rendering fishing spiders select such dynamic behavior.
A stochastic vision-based model inspired by zebrafish collective behaviour in heterogeneous environments

PubMed Central

Collignon, Bertrand; Séguret, Axel; Halloy, José

2016-01-01

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

PubMed

Köhler, T; Röchter, F; Lindemann, J P; Möller, R

2009-03-01

Flying insects, despite their relatively coarse vision and tiny nervous system, are capable of carrying out elegant and fast aerial manoeuvres. Studies of the fly visual system have shown that this is accomplished by the integration of signals from a large number of elementary motion detectors (EMDs) in just a few global flow detector cells. We developed an FPGA-based smart camera module with more than 10,000 single EMDs, which is closely modelled after insect motion-detection circuits with respect to overall architecture, resolution and inter-receptor spacing. Input to the EMD array is provided by a CMOS camera with a high frame rate. Designed as an adaptable solution for different engineering applications and as a testbed for biological models, the EMD detector type and parameters such as the EMD time constants, the motion-detection directions and the angle between correlated receptors are reconfigurable online. This allows a flexible and simultaneous detection of complex motion fields such as translation, rotation and looming, such that various tasks, e.g., obstacle avoidance, height/distance control or speed regulation can be performed by the same compact device.
Thrust augmentation in tandem flapping foils by foil-wake interaction

NASA Astrophysics Data System (ADS)

Anderson, Erik; Lauder, George

2006-11-01

Propulsion by pitching and heaving airfoils and hydrofoils has been a focus of much research in the field of biologically inspired propulsion. Organisms that use this sort of propulsion are self-propelled, so it is difficult to use standard experimental metrics such as thrust and drag to characterize performance. We have constructed a flapping foil robot mounted in a flume on air-bearings that allows for the determination of self-propelled speed as a metric of performance. We have used a pair of these robots to examine the impact of an upstream flapping foil on a downstream flapping foil as might apply to tandem fins of a swimming organism or in-line swimming of schooling organisms. Self-propelled speed and a force transducer confirmed significant thrust augmentation for particular foil-to-foil spacings, phase differences, and flapping frequencies. Flow visualization shows the mechanism to be related to the effective angle of attack of the downstream foil due to the structure of the wake of the upstream foil. This confirms recent computational work and the hypotheses by early investigators of fish fluid dynamics.
A multilevel layout algorithm for visualizing physical and genetic interaction networks, with emphasis on their modular organization

PubMed Central

2012-01-01

Background Graph drawing is an integral part of many systems biology studies, enabling visual exploration and mining of large-scale biological networks. While a number of layout algorithms are available in popular network analysis platforms, such as Cytoscape, it remains poorly understood how well their solutions reflect the underlying biological processes that give rise to the network connectivity structure. Moreover, visualizations obtained using conventional layout algorithms, such as those based on the force-directed drawing approach, may become uninformative when applied to larger networks with dense or clustered connectivity structure. Methods We implemented a modified layout plug-in, named Multilevel Layout, which applies the conventional layout algorithms within a multilevel optimization framework to better capture the hierarchical modularity of many biological networks. Using a wide variety of real life biological networks, we carried out a systematic evaluation of the method in comparison with other layout algorithms in Cytoscape. Results The multilevel approach provided both biologically relevant and visually pleasant layout solutions in most network types, hence complementing the layout options available in Cytoscape. In particular, it could improve drawing of large-scale networks of yeast genetic interactions and human physical interactions. In more general terms, the biological evaluation framework developed here enables one to assess the layout solutions from any existing or future graph drawing algorithm as well as to optimize their performance for a given network type or structure. Conclusions By making use of the multilevel modular organization when visualizing biological networks, together with the biological evaluation of the layout solutions, one can generate convenient visualizations for many network biology applications. PMID:22448851
Seven-spot ladybird optimization: a novel and efficient metaheuristic algorithm for numerical optimization.

PubMed

Wang, Peng; Zhu, Zhouquan; Huang, Shuai

2013-01-01

This paper presents a novel biologically inspired metaheuristic algorithm called seven-spot ladybird optimization (SLO). The SLO is inspired by recent discoveries on the foraging behavior of a seven-spot ladybird. In this paper, the performance of the SLO is compared with that of the genetic algorithm, particle swarm optimization, and artificial bee colony algorithms by using five numerical benchmark functions with multimodality. The results show that SLO has the ability to find the best solution with a comparatively small population size and is suitable for solving optimization problems with lower dimensions.
Seven-Spot Ladybird Optimization: A Novel and Efficient Metaheuristic Algorithm for Numerical Optimization

PubMed Central

Zhu, Zhouquan

2013-01-01

This paper presents a novel biologically inspired metaheuristic algorithm called seven-spot ladybird optimization (SLO). The SLO is inspired by recent discoveries on the foraging behavior of a seven-spot ladybird. In this paper, the performance of the SLO is compared with that of the genetic algorithm, particle swarm optimization, and artificial bee colony algorithms by using five numerical benchmark functions with multimodality. The results show that SLO has the ability to find the best solution with a comparatively small population size and is suitable for solving optimization problems with lower dimensions. PMID:24385879
Bio-Inspired Multi-Functional Drug Transport Design Concept and Simulations †

PubMed Central

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

2017-01-01

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. PMID:28952516
Neuroscience-Inspired Artificial Intelligence.

PubMed

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.
Neural Mechanisms of Cortical Motion Computation Based on a Neuromorphic Sensory System

PubMed Central

Abdul-Kreem, Luma Issa; Neumann, Heiko

2015-01-01

The visual cortex analyzes motion information along hierarchically arranged visual areas that interact through bidirectional interconnections. This work suggests a bio-inspired visual model focusing on the interactions of the cortical areas in which a new mechanism of feedforward and feedback processing are introduced. The model uses a neuromorphic vision sensor (silicon retina) that simulates the spike-generation functionality of the biological retina. Our model takes into account two main model visual areas, namely V1 and MT, with different feature selectivities. The initial motion is estimated in model area V1 using spatiotemporal filters to locally detect the direction of motion. Here, we adapt the filtering scheme originally suggested by Adelson and Bergen to make it consistent with the spike representation of the DVS. The responses of area V1 are weighted and pooled by area MT cells which are selective to different velocities, i.e. direction and speed. Such feature selectivity is here derived from compositions of activities in the spatio-temporal domain and integrating over larger space-time regions (receptive fields). In order to account for the bidirectional coupling of cortical areas we match properties of the feature selectivity in both areas for feedback processing. For such linkage we integrate the responses over different speeds along a particular preferred direction. Normalization of activities is carried out over the spatial as well as the feature domains to balance the activities of individual neurons in model areas V1 and MT. Our model was tested using different stimuli that moved in different directions. The results reveal that the error margin between the estimated motion and synthetic ground truth is decreased in area MT comparing with the initial estimation of area V1. In addition, the modulated V1 cell activations shows an enhancement of the initial motion estimation that is steered by feedback signals from MT cells. PMID:26554589
A Review of Natural Joint Systems and Numerical Investigation of Bio-Inspired GFRP-to-Steel Joints

PubMed Central

Avgoulas, Evangelos I.; Sutcliffe, Michael P. F.

2016-01-01

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. PMID:28773688
Material requirements for bio-inspired sensing systems

NASA Astrophysics Data System (ADS)

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

PubMed

Avgoulas, Evangelos I; Sutcliffe, Michael P F

2016-07-12

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.

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

PubMed

Layher, Georg; Brosch, Tobias; Neumann, Heiko

2017-01-01

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

PubMed Central

Layher, Georg; Brosch, Tobias; Neumann, Heiko

2017-01-01

Intelligent agents, such as robots, have to serve a multitude of autonomous functions. Examples are, e.g., collision avoidance, navigation and route planning, active sensing of its environment, or the interaction and non-verbal communication with people in the extended reach space. Here, we focus on the recognition of the action of a human agent based on a biologically inspired visual architecture of analyzing articulated movements. The proposed processing architecture builds upon coarsely segregated streams of sensory processing along different pathways which separately process form and motion information (Layher et al., 2014). Action recognition is performed in an event-based scheme by identifying representations of characteristic pose configurations (key poses) in an image sequence. In line with perceptual studies, key poses are selected unsupervised utilizing a feature-driven criterion which combines extrema in the motion energy with the horizontal and the vertical extendedness of a body shape. Per class representations of key pose frames are learned using a deep convolutional neural network consisting of 15 convolutional layers. The network is trained using the energy-efficient deep neuromorphic networks (Eedn) framework (Esser et al., 2016), which realizes the mapping of the trained synaptic weights onto the IBM Neurosynaptic System platform (Merolla et al., 2014). After the mapping, the trained network achieves real-time capabilities for processing input streams and classify input images at about 1,000 frames per second while the computational stages only consume about 70 mW of energy (without spike transduction). Particularly regarding mobile robotic systems, a low energy profile might be crucial in a variety of application scenarios. Cross-validation results are reported for two different datasets and compared to state-of-the-art action recognition approaches. The results demonstrate, that (I) the presented approach is on par with other key pose based methods described in the literature, which select key pose frames by optimizing classification accuracy, (II) compared to the training on the full set of frames, representations trained on key pose frames result in a higher confidence in class assignments, and (III) key pose representations show promising generalization capabilities in a cross-dataset evaluation. PMID:28381998
Structural biological composites: An overview

NASA Astrophysics Data System (ADS)

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.
The Effects of Single and Dual Coded Multimedia Instructional Methods on Chinese Character Learning

ERIC Educational Resources Information Center

Wang, Ling

2013-01-01

Learning Chinese characters is a difficult task for adult English native speakers due to the significant differences between the Chinese and English writing system. The visuospatial properties of Chinese characters have inspired the development of instructional methods using both verbal and visual information based on the Dual Coding Theory. This…
Word on the Street: Investigating Linguistic Landscapes with Urban Canadian Youth

ERIC Educational Resources Information Center

Burwell, Catherine; Lenters, Kimberly

2015-01-01

This article reports on a case study inspired by the concept of "linguistic landscapes." We collaborated with a group of Humanities teachers to design and implement the "Word on the Street" project, in which Grade 10 students took on the role of researchers to explore the linguistic, visual and spatial texts of their…
Mars Public Engagement Overview

NASA Technical Reports Server (NTRS)

Johnson, Christine

2009-01-01

This viewgraph presentation reviews the Mars public engagement goal to understand and protect our home planet, explore the Universe and search for life, and to inspire the next generation of explorers. Teacher workshops, robotics education, Mars student imaging and analysis programs, MARS Student Imaging Project (MSIP), Russian student participation, MARS museum visualization alliance, and commercialization concepts are all addressed in this project.
Ekphrastic Poetry: Entering and Giving Voice to Works of Art.

ERIC Educational Resources Information Center

Blackhawk, Terry

2002-01-01

Discusses a survey of ekphrastic writing (poetry that takes its inspiration from visual art) by contemporary poets that "barely scratches the surface" of a genre as varied as the writers who employ it. Points to the rich interactions and crossovers that occur when "word-folk" try to express their encounters with the work of "image-folk." (SG)
A new biology for a new century.

PubMed

Woese, Carl R

2004-06-01

Biology today is at a crossroads. The molecular paradigm, which so successfully guided the discipline throughout most of the 20th century, is no longer a reliable guide. Its vision of biology now realized, the molecular paradigm has run its course. Biology, therefore, has a choice to make, between the comfortable path of continuing to follow molecular biology's lead or the more invigorating one of seeking a new and inspiring vision of the living world, one that addresses the major problems in biology that 20th century biology, molecular biology, could not handle and, so, avoided. The former course, though highly productive, is certain to turn biology into an engineering discipline. The latter holds the promise of making biology an even more fundamental science, one that, along with physics, probes and defines the nature of reality. This is a choice between a biology that solely does society's bidding and a biology that is society's teacher.
Computational mechanisms underlying cortical responses to the affordance properties of visual scenes

PubMed Central

Epstein, Russell A.

2018-01-01

Biologically inspired deep convolutional neural networks (CNNs), trained for computer vision tasks, have been found to predict cortical responses with remarkable accuracy. However, the internal operations of these models remain poorly understood, and the factors that account for their success are unknown. Here we develop a set of techniques for using CNNs to gain insights into the computational mechanisms underlying cortical responses. We focused on responses in the occipital place area (OPA), a scene-selective region of dorsal occipitoparietal cortex. In a previous study, we showed that fMRI activation patterns in the OPA contain information about the navigational affordances of scenes; that is, information about where one can and cannot move within the immediate environment. We hypothesized that this affordance information could be extracted using a set of purely feedforward computations. To test this idea, we examined a deep CNN with a feedforward architecture that had been previously trained for scene classification. We found that responses in the CNN to scene images were highly predictive of fMRI responses in the OPA. Moreover the CNN accounted for the portion of OPA variance relating to the navigational affordances of scenes. The CNN could thus serve as an image-computable candidate model of affordance-related responses in the OPA. We then ran a series of in silico experiments on this model to gain insights into its internal operations. These analyses showed that the computation of affordance-related features relied heavily on visual information at high-spatial frequencies and cardinal orientations, both of which have previously been identified as low-level stimulus preferences of scene-selective visual cortex. These computations also exhibited a strong preference for information in the lower visual field, which is consistent with known retinotopic biases in the OPA. Visualizations of feature selectivity within the CNN suggested that affordance-based responses encoded features that define the layout of the spatial environment, such as boundary-defining junctions and large extended surfaces. Together, these results map the sensory functions of the OPA onto a fully quantitative model that provides insights into its visual computations. More broadly, they advance integrative techniques for understanding visual cortex across multiple level of analysis: from the identification of cortical sensory functions to the modeling of their underlying algorithms. PMID:29684011
Astronomical Video Suites

NASA Astrophysics Data System (ADS)

Francisco Salgado, Jose

2010-01-01

Astronomer and visual artist Jose Francisco Salgado has directed two astronomical video suites to accompany live performances of classical music works. The suites feature awe-inspiring images, historical illustrations, and visualizations produced by NASA, ESA, and the Adler Planetarium. By the end of 2009, his video suites Gustav Holst's The Planets and Astronomical Pictures at an Exhibition will have been presented more than 40 times in over 10 countries. Lately Salgado, an avid photographer, has been experimenting with high dynamic range imaging, time-lapse, infrared, and fisheye photography, as well as with stereoscopic photography and video to enhance his multimedia works.
Learning visual balance from large-scale datasets of aesthetically highly rated images

NASA Astrophysics Data System (ADS)

Jahanian, Ali; Vishwanathan, S. V. N.; Allebach, Jan P.

2015-03-01

The concept of visual balance is innate for humans, and influences how we perceive visual aesthetics and cognize harmony. Although visual balance is a vital principle of design and taught in schools of designs, it is barely quantified. On the other hand, with emergence of automantic/semi-automatic visual designs for self-publishing, learning visual balance and computationally modeling it, may escalate aesthetics of such designs. In this paper, we present how questing for understanding visual balance inspired us to revisit one of the well-known theories in visual arts, the so called theory of "visual rightness", elucidated by Arnheim. We define Arnheim's hypothesis as a design mining problem with the goal of learning visual balance from work of professionals. We collected a dataset of 120K images that are aesthetically highly rated, from a professional photography website. We then computed factors that contribute to visual balance based on the notion of visual saliency. We fitted a mixture of Gaussians to the saliency maps of the images, and obtained the hotspots of the images. Our inferred Gaussians align with Arnheim's hotspots, and confirm his theory. Moreover, the results support the viability of the center of mass, symmetry, as well as the Rule of Thirds in our dataset.
BiNA: A Visual Analytics Tool for Biological Network Data

PubMed Central

Gerasch, Andreas; Faber, Daniel; Küntzer, Jan; Niermann, Peter; Kohlbacher, Oliver; Lenhof, Hans-Peter; Kaufmann, Michael

2014-01-01

Interactive visual analysis of biological high-throughput data in the context of the underlying networks is an essential task in modern biomedicine with applications ranging from metabolic engineering to personalized medicine. The complexity and heterogeneity of data sets require flexible software architectures for data analysis. Concise and easily readable graphical representation of data and interactive navigation of large data sets are essential in this context. We present BiNA - the Biological Network Analyzer - a flexible open-source software for analyzing and visualizing biological networks. Highly configurable visualization styles for regulatory and metabolic network data offer sophisticated drawings and intuitive navigation and exploration techniques using hierarchical graph concepts. The generic projection and analysis framework provides powerful functionalities for visual analyses of high-throughput omics data in the context of networks, in particular for the differential analysis and the analysis of time series data. A direct interface to an underlying data warehouse provides fast access to a wide range of semantically integrated biological network databases. A plugin system allows simple customization and integration of new analysis algorithms or visual representations. BiNA is available under the 3-clause BSD license at http://bina.unipax.info/. PMID:24551056
A bio-inspired system for spatio-temporal recognition in static and video imagery

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Moore, Christopher K.; Chelian, Suhas

2007-04-01

This paper presents a bio-inspired method for spatio-temporal recognition in static and video imagery. It builds upon and extends our previous work on a bio-inspired Visual Attention and object Recognition System (VARS). The VARS approach locates and recognizes objects in a single frame. This work presents two extensions of VARS. The first extension is a Scene Recognition Engine (SCE) that learns to recognize spatial relationships between objects that compose a particular scene category in static imagery. This could be used for recognizing the category of a scene, e.g., office vs. kitchen scene. The second extension is the Event Recognition Engine (ERE) that recognizes spatio-temporal sequences or events in sequences. This extension uses a working memory model to recognize events and behaviors in video imagery by maintaining and recognizing ordered spatio-temporal sequences. The working memory model is based on an ARTSTORE1 neural network that combines an ART-based neural network with a cascade of sustained temporal order recurrent (STORE)1 neural networks. A series of Default ARTMAP classifiers ascribes event labels to these sequences. Our preliminary studies have shown that this extension is robust to variations in an object's motion profile. We evaluated the performance of the SCE and ERE on real datasets. The SCE module was tested on a visual scene classification task using the LabelMe2 dataset. The ERE was tested on real world video footage of vehicles and pedestrians in a street scene. Our system is able to recognize the events in this footage involving vehicles and pedestrians.
A compact bio-inspired visible/NIR imager for image-guided surgery (Conference Presentation)

NASA Astrophysics Data System (ADS)

Gao, Shengkui; Garcia, Missael; Edmiston, Chris; York, Timothy; Marinov, Radoslav; Mondal, Suman B.; Zhu, Nan; Sudlow, Gail P.; Akers, Walter J.; Margenthaler, Julie A.; Liang, Rongguang; Pepino, Marta; Achilefu, Samuel; Gruev, Viktor

2016-03-01

Inspired by the visual system of the morpho butterfly, we have designed, fabricated, tested and clinically translated an ultra-sensitive, light weight and compact imaging sensor capable of simultaneously capturing near infrared (NIR) and visible spectrum information. The visual system of the morpho butterfly combines photosensitive cells with spectral filters at the receptor level. The spectral filters are realized by alternating layers of high and low dielectric constant, such as air and cytoplasm. We have successfully mimicked this concept by integrating pixelated spectral filters, realized by alternating silicon dioxide and silicon nitrate layers, with an array of CCD detectors. There are four different types of pixelated spectral filters in the imaging plane: red, green, blue and NIR. The high optical density (OD) of all spectral filters (OD>4) allow for efficient rejections of photons from unwanted bands. The single imaging chip weighs 20 grams with form factor of 5mm by 5mm. The imaging camera is integrated with a goggle display system. A tumor targeted agent, LS301, is used to identify all spontaneous tumors in a transgenic PyMT murine model of breast cancer. The imaging system achieved sensitivity of 98% and selectivity of 95%. We also used our imaging sensor to locate sentinel lymph nodes (SLNs) in patients with breast cancer using indocyanine green tracer. The surgeon was able to identify 100% of SLNs when using our bio-inspired imaging system, compared to 93% when using information from the lymphotropic dye and 96% when using information from the radioactive tracer.
Supporting Representational Competence in High School Biology with Computer-Based Biomolecular Visualizations

ERIC Educational Resources Information Center

Wilder, Anna; Brinkerhoff, Jonathan

2007-01-01

This study assessed the effectiveness of computer-based biomolecular visualization activities on the development of high school biology students' representational competence as a means of understanding and visualizing protein structure/function relationships. Also assessed were students' attitudes toward these activities. Sixty-nine students…
Scallop-Inspired DNA Nanomachine: A Ratiometric Nanothermometer for Intracellular Temperature Sensing.

PubMed

Xie, Nuli; Huang, Jin; Yang, Xiaohai; He, Xiaoxiao; Liu, Jianbo; Huang, Jiaqi; Fang, Hongmei; Wang, Kemin

2017-11-21

Accurate measurement of intracellular temperature is of great significance in biology and medicine. With use of DNA nanotechnology and inspiration by nature's examples of "protective and reversible responses" exoskeletons, a scallop-inspired DNA nanomachine (SDN) is desgined as a ratiometric nanothermometer for intracellular temperature sensing. The SDN is composed of a rigid DNA tetrahedron, where a thermal-sensitive molecular beacon (MB) is embedded in one edge of the DNA tetrahedron. Relying on the thermal-sensitive MB and fluorescence resonance energy transfer (FRET) signaling mechanism, the "On" to "Off" signal is reversibly responding to "below" and "over" the melting temperature. Mimicking the functional anatomy of a scallop, the SDN exhibits high cellular permeability and resistance to enzymatic degradation, good reversibility, and tunable response range. Furthermore, FRET ratiometric signal that allows the simultaneous recording of two emission intensities at different wavelengths can provide a feasible approach for precise detection, minimizing the effect of system fluctuations.
Self-* properties through gossiping.

PubMed

Babaoglu, Ozalp; Jelasity, Márk

2008-10-28

As computer systems have become more complex, numerous competing approaches have been proposed for these systems to self-configure, self-manage, self-repair, etc. such that human intervention in their operation can be minimized. In ubiquitous systems, this has always been a central issue as well. In this paper, we overview techniques to implement self-* properties in large-scale, decentralized networks through bio-inspired techniques in general, and gossip-based algorithms in particular. We believe that gossip-based algorithms could be an important inspiration for solving problems in ubiquitous computing as well. As an example, we outline a novel approach to arrange large numbers of mobile agents (e.g. vehicles, rescue teams carrying mobile devices) into different formations in a totally decentralized manner. The approach is inspired by the biological mechanism of cell sorting via differential adhesion, as well as by our earlier work in self-organizing peer-to-peer overlay networks.
Bio-Inspired Networking — Self-Organizing Networked Embedded Systems

NASA Astrophysics Data System (ADS)

Dressler, Falko

The turn to nature has brought us many unforeseen great concepts and solutions. This course seems to hold on for many research domains. In this article, we study the applicability of biological mechanisms and techniques in the domain of communications. In particular, we study the behavior and the challenges in networked embedded systems that are meant to self-organize in large groups of nodes. Application examples include wireless sensor networks and sensor/actuator networks. Based on a review of the needs and requirements in such networks, we study selected bio-inspired networking approaches that claim to outperform other methods in specific domains. We study mechanisms in swarm intelligence, the artificial immune system, and approaches based on investigations on the cellular signaling pathways. As a major conclusion, we derive that bio-inspired networking techniques do have advantages compared to engineering methods. Nevertheless, selection and employment must be done carefully to achieve the desired performance gains.
Biologically-Inspired Microrobots. Volume 3. Micro-Robot Based on Abstracted Biological Principles

DTIC Science & Technology

2006-04-01

Roy E. Ritzmann, Jeremy Morrey and Andrew Horchler Se. TASK NUMBER Sf. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME( S ) AND ADDRESS(ES) 8...SPONSORING/MONITORING AGENCY NAME( S ) AND ADDRESS(ES) 10. SPONSOR/MONITOR’S ACRONYM( S ) Sponsor: Defense Advanced Research Projects Agency (DARPA...Microsystems Technology Office (Elana Ethridge) 3701 North Fairfax Drive Arlington, VA 22203-1714 11. SPONSOR/MONITOR’S REPORT NUMBER( S ) NATICK/TR-05
The role of mechanics in biological and bio-inspired systems.

PubMed

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.

Maximising information recovery from rank-order codes

NASA Astrophysics Data System (ADS)

Sen, B.; Furber, S.

2007-04-01

The central nervous system encodes information in sequences of asynchronously generated voltage spikes, but the precise details of this encoding are not well understood. Thorpe proposed rank-order codes as an explanation of the observed speed of information processing in the human visual system. The work described in this paper is inspired by the performance of SpikeNET, a biologically inspired neural architecture using rank-order codes for information processing, and is based on the retinal model developed by VanRullen and Thorpe. This model mimics retinal information processing by passing an input image through a bank of Difference of Gaussian (DoG) filters and then encoding the resulting coefficients in rank-order. To test the effectiveness of this encoding in capturing the information content of an image, the rank-order representation is decoded to reconstruct an image that can be compared with the original. The reconstruction uses a look-up table to infer the filter coefficients from their rank in the encoded image. Since the DoG filters are approximately orthogonal functions, they are treated as their own inverses in the reconstruction process. We obtained a quantitative measure of the perceptually important information retained in the reconstructed image relative to the original using a slightly modified version of an objective metric proposed by Petrovic. It is observed that around 75% of the perceptually important information is retained in the reconstruction. In the present work we reconstruct the input using a pseudo-inverse of the DoG filter-bank with the aim of improving the reconstruction and thereby extracting more information from the rank-order encoded stimulus. We observe that there is an increase of 10 - 15% in the information retrieved from a reconstructed stimulus as a result of inverting the filter-bank.
Regulating Cortical Oscillations in an Inhibition-Stabilized Network.

PubMed

Jadi, Monika P; Sejnowski, Terrence J

2014-04-21

Understanding the anatomical and functional architecture of the brain is essential for designing neurally inspired intelligent systems. Theoretical and empirical studies suggest a role for narrowband oscillations in shaping the functional architecture of the brain through their role in coding and communication of information. Such oscillations are ubiquitous signals in the electrical activity recorded from the brain. In the cortex, oscillations detected in the gamma range (30-80 Hz) are modulated by behavioral states and sensory features in complex ways. How is this regulation achieved? Although several underlying principles for the genesis of these oscillations have been proposed, a unifying account for their regulation has remained elusive. In a network of excitatory and inhibitory neurons operating in an inhibition-stabilized regime, we show that strongly superlinear responses of inhibitory neurons facilitate bidirectional regulation of oscillation frequency and power. In such a network, the balance of drives to the excitatory and inhibitory populations determines how the power and frequency of oscillations are modulated. The model accounts for the puzzling increase in their frequency with the salience of visual stimuli, and a decrease with their size. Oscillations in our model grow stronger as the mean firing level is reduced, accounting for the size dependence of visually evoked gamma rhythms, and suggesting a role for oscillations in improving the signal-to-noise ratio (SNR) of signals in the brain. Empirically testing such predictions is still challenging, and implementing the proposed coding and communication strategies in neuromorphic systems could assist in our understanding of the biological system.
Morphogenesis of the Terrarium

ERIC Educational Resources Information Center

Brinker, Andrew

2012-01-01

Terrariums have decorated the shelves and counters of biology offices and classrooms for centuries. Living organisms inspire students and teachers alike. These wonderful ecosystems allow for both experimentation and observation of living systems. Here, I outline a new approach to building classroom terrariums. Historically, terrariums have been…
Noun and knowledge retrieval for biological and non-biological entities following right occipitotemporal lesions.

PubMed

Bruffaerts, Rose; De Weer, An-Sofie; De Grauwe, Sophie; Thys, Miek; Dries, Eva; Thijs, Vincent; Sunaert, Stefan; Vandenbulcke, Mathieu; De Deyne, Simon; Storms, Gerrit; Vandenberghe, Rik

2014-09-01

We investigated the critical contribution of right ventral occipitotemporal cortex to knowledge of visual and functional-associative attributes of biological and non-biological entities and how this relates to category-specificity during confrontation naming. In a consecutive series of 7 patients with lesions confined to right ventral occipitotemporal cortex, we conducted an extensive assessment of oral generation of visual-sensory and functional-associative features in response to the names of biological and nonbiological entities. Subjects also performed a confrontation naming task for these categories. Our main novel finding related to a unique case with a small lesion confined to right medial fusiform gyrus who showed disproportionate naming impairment for nonbiological versus biological entities, specifically for tools. Generation of visual and functional-associative features was preserved for biological and non-biological entities. In two other cases, who had a relatively small posterior lesion restricted to primary visual and posterior fusiform cortex, retrieval of visual attributes was disproportionately impaired compared to functional-associative attributes, in particular for biological entities. However, these cases did not show a category-specific naming deficit. Two final cases with the largest lesions showed a classical dissociation between biological versus nonbiological entities during naming, with normal feature generation performance. This is the first lesion-based evidence of a critical contribution of the right medial fusiform cortex to tool naming. Second, dissociations along the dimension of attribute type during feature generation do not co-occur with category-specificity during naming in the current patient sample. Copyright © 2014 Elsevier Ltd. All rights reserved.
Microgravity Fluids for Biology, Workshop

NASA Technical Reports Server (NTRS)

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.
Evidence for auditory-visual processing specific to biological motion.

PubMed

Wuerger, Sophie M; Crocker-Buque, Alexander; Meyer, Georg F

2012-01-01

Biological motion is usually associated with highly correlated sensory signals from more than one modality: an approaching human walker will not only have a visual representation, namely an increase in the retinal size of the walker's image, but also a synchronous auditory signal since the walker's footsteps will grow louder. We investigated whether the multisensorial processing of biological motion is subject to different constraints than ecologically invalid motion. Observers were presented with a visual point-light walker and/or synchronised auditory footsteps; the walker was either approaching the observer (looming motion) or walking away (receding motion). A scrambled point-light walker served as a control. Observers were asked to detect the walker's motion as quickly and as accurately as possible. In Experiment 1 we tested whether the reaction time advantage due to redundant information in the auditory and visual modality is specific for biological motion. We found no evidence for such an effect: the reaction time reduction was accounted for by statistical facilitation for both biological and scrambled motion. In Experiment 2, we dissociated the auditory and visual information and tested whether inconsistent motion directions across the auditory and visual modality yield longer reaction times in comparison to consistent motion directions. Here we find an effect specific to biological motion: motion incongruency leads to longer reaction times only when the visual walker is intact and recognisable as a human figure. If the figure of the walker is abolished by scrambling, motion incongruency has no effect on the speed of the observers' judgments. In conjunction with Experiment 1 this suggests that conflicting auditory-visual motion information of an intact human walker leads to interference and thereby delaying the response.
Attraction of posture and motion-trajectory elements of conspecific biological motion in medaka fish.

PubMed

Shibai, Atsushi; Arimoto, Tsunehiro; Yoshinaga, Tsukasa; Tsuchizawa, Yuta; Khureltulga, Dashdavaa; Brown, Zuben P; Kakizuka, Taishi; Hosoda, Kazufumi

2018-06-05

Visual recognition of conspecifics is necessary for a wide range of social behaviours in many animals. Medaka (Japanese rice fish), a commonly used model organism, are known to be attracted by the biological motion of conspecifics. However, biological motion is a composite of both body-shape motion and entire-field motion trajectory (i.e., posture or motion-trajectory elements, respectively), and it has not been revealed which element mediates the attractiveness. Here, we show that either posture or motion-trajectory elements alone can attract medaka. We decomposed biological motion of the medaka into the two elements and synthesized visual stimuli that contain both, either, or none of the two elements. We found that medaka were attracted by visual stimuli that contain at least one of the two elements. In the context of other known static visual information regarding the medaka, the potential multiplicity of information regarding conspecific recognition has further accumulated. Our strategy of decomposing biological motion into these partial elements is applicable to other animals, and further studies using this technique will enhance the basic understanding of visual recognition of conspecifics.
Neuromorphic VLSI vision system for real-time texture segregation.

PubMed

Shimonomura, Kazuhiro; Yagi, Tetsuya

2008-10-01

The visual system of the brain can perceive an external scene in real-time with extremely low power dissipation, although the response speed of an individual neuron is considerably lower than that of semiconductor devices. The neurons in the visual pathway generate their receptive fields using a parallel and hierarchical architecture. This architecture of the visual cortex is interesting and important for designing a novel perception system from an engineering perspective. The aim of this study is to develop a vision system hardware, which is designed inspired by a hierarchical visual processing in V1, for real time texture segregation. The system consists of a silicon retina, orientation chip, and field programmable gate array (FPGA) circuit. The silicon retina emulates the neural circuits of the vertebrate retina and exhibits a Laplacian-Gaussian-like receptive field. The orientation chip selectively aggregates multiple pixels of the silicon retina in order to produce Gabor-like receptive fields that are tuned to various orientations by mimicking the feed-forward model proposed by Hubel and Wiesel. The FPGA circuit receives the output of the orientation chip and computes the responses of the complex cells. Using this system, the neural images of simple cells were computed in real-time for various orientations and spatial frequencies. Using the orientation-selective outputs obtained from the multi-chip system, a real-time texture segregation was conducted based on a computational model inspired by psychophysics and neurophysiology. The texture image was filtered by the two orthogonally oriented receptive fields of the multi-chip system and the filtered images were combined to segregate the area of different texture orientation with the aid of FPGA. The present system is also useful for the investigation of the functions of the higher-order cells that can be obtained by combining the simple and complex cells.
Research Review: Principles of Possibility--Considerations for a 21st-Century Art & Culture

ERIC Educational Resources Information Center

Brown, Susannah

2007-01-01

In this article, the reviewer focuses on a study of a professional development workshop and visual art studio workshops for adolescents. It is her hope that teaching artists will draw new ideas about curriculum and content from the discussion of this work and that the issues discussed here may provide inspiration for their own shift in thinking…
Painting and Poetry: Third Graders' Free-Form Poems Inspired by Their Paintings

ERIC Educational Resources Information Center

Sears, Emilie

2012-01-01

It is important to find the means by which struggling writers can find success in the English Language Arts. For students struggling with reading and writing, the visual arts may be a way of accessing and expressing their ideas and ultimately opening up a world of creative possibilities. This article explores drawing and painting as a pre-writing…
A Unique Way of Learning: Teaching Young Children with Optic Nerve Hypoplasia

ERIC Educational Resources Information Center

Mendiola, Rosalinda; Bahar, Cheryl; Brody, Jill; Slott, Gayle L.

2005-01-01

This booklet was inspired by the need of educators and therapists of preschool students who are blind and visually impaired to share their observations of children with Optic Nerve Hypoplasia (ONH) and the therapies found to be helpful when working with these children. The work done at the Blind Childrens Center is very rewarding, and these…
A specialized face-processing model inspired by the organization of monkey face patches explains several face-specific phenomena observed in humans.

PubMed

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

2016-04-26

Converging reports indicate that face images are processed through specialized neural networks in the brain -i.e. face patches in monkeys and the fusiform face area (FFA) in humans. These studies were designed to find out how faces are processed in visual system compared to other objects. Yet, the underlying mechanism of face processing is not completely revealed. Here, we show that a hierarchical computational model, inspired by electrophysiological evidence on face processing in primates, is able to generate representational properties similar to those observed in monkey face patches (posterior, middle and anterior patches). Since the most important goal of sensory neuroscience is linking the neural responses with behavioral outputs, we test whether the proposed model, which is designed to account for neural responses in monkey face patches, is also able to predict well-documented behavioral face phenomena observed in humans. We show that the proposed model satisfies several cognitive face effects such as: composite face effect and the idea of canonical face views. Our model provides insights about the underlying computations that transfer visual information from posterior to anterior face patches.
A specialized face-processing model inspired by the organization of monkey face patches explains several face-specific phenomena observed in humans

PubMed Central

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

2016-01-01

Converging reports indicate that face images are processed through specialized neural networks in the brain –i.e. face patches in monkeys and the fusiform face area (FFA) in humans. These studies were designed to find out how faces are processed in visual system compared to other objects. Yet, the underlying mechanism of face processing is not completely revealed. Here, we show that a hierarchical computational model, inspired by electrophysiological evidence on face processing in primates, is able to generate representational properties similar to those observed in monkey face patches (posterior, middle and anterior patches). Since the most important goal of sensory neuroscience is linking the neural responses with behavioral outputs, we test whether the proposed model, which is designed to account for neural responses in monkey face patches, is also able to predict well-documented behavioral face phenomena observed in humans. We show that the proposed model satisfies several cognitive face effects such as: composite face effect and the idea of canonical face views. Our model provides insights about the underlying computations that transfer visual information from posterior to anterior face patches. PMID:27113635
Biology Modules for the Visually Handicapped.

ERIC Educational Resources Information Center

Allan, Douglas M.

The instructional materials presented and described in this document were prepared as part of a project to develop enrichment materials for visually impaired biology students. A wide range of biology topics are presented, including most subjects covered in a one-semester course for nonmajors. Typewritten handouts, duplicating the content of…
Premotor cortex is sensitive to auditory-visual congruence for biological motion.

PubMed

Wuerger, Sophie M; Parkes, Laura; Lewis, Penelope A; Crocker-Buque, Alex; Rutschmann, Roland; Meyer, Georg F

2012-03-01

The auditory and visual perception systems have developed special processing strategies for ecologically valid motion stimuli, utilizing some of the statistical properties of the real world. A well-known example is the perception of biological motion, for example, the perception of a human walker. The aim of the current study was to identify the cortical network involved in the integration of auditory and visual biological motion signals. We first determined the cortical regions of auditory and visual coactivation (Experiment 1); a conjunction analysis based on unimodal brain activations identified four regions: middle temporal area, inferior parietal lobule, ventral premotor cortex, and cerebellum. The brain activations arising from bimodal motion stimuli (Experiment 2) were then analyzed within these regions of coactivation. Auditory footsteps were presented concurrently with either an intact visual point-light walker (biological motion) or a scrambled point-light walker; auditory and visual motion in depth (walking direction) could either be congruent or incongruent. Our main finding is that motion incongruency (across modalities) increases the activity in the ventral premotor cortex, but only if the visual point-light walker is intact. Our results extend our current knowledge by providing new evidence consistent with the idea that the premotor area assimilates information across the auditory and visual modalities by comparing the incoming sensory input with an internal representation.
Biomimetic vibrissal sensing for robots

PubMed Central

Pearson, Martin J.; Mitchinson, Ben; Sullivan, J. Charles; Pipe, Anthony G.; Prescott, Tony J.

2011-01-01

Active vibrissal touch can be used to replace or to supplement sensory systems such as computer vision and, therefore, improve the sensory capacity of mobile robots. This paper describes how arrays of whisker-like touch sensors have been incorporated onto mobile robot platforms taking inspiration from biology for their morphology and control. There were two motivations for this work: first, to build a physical platform on which to model, and therefore test, recent neuroethological hypotheses about vibrissal touch; second, to exploit the control strategies and morphology observed in the biological analogue to maximize the quality and quantity of tactile sensory information derived from the artificial whisker array. We describe the design of a new whiskered robot, Shrewbot, endowed with a biomimetic array of individually controlled whiskers and a neuroethologically inspired whisking pattern generation mechanism. We then present results showing how the morphology of the whisker array shapes the sensory surface surrounding the robot's head, and demonstrate the impact of active touch control on the sensory information that can be acquired by the robot. We show that adopting bio-inspired, low latency motor control of the rhythmic motion of the whiskers in response to contact-induced stimuli usefully constrains the sensory range, while also maximizing the number of whisker contacts. The robot experiments also demonstrate that the sensory consequences of active touch control can be usefully investigated in biomimetic robots. PMID:21969690
Soft robotic arm inspired by the octopus: I. From biological functions to artificial requirements.

PubMed

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.
Biomimetic vibrissal sensing for robots.

PubMed

Pearson, Martin J; Mitchinson, Ben; Sullivan, J Charles; Pipe, Anthony G; Prescott, Tony J

2011-11-12

Active vibrissal touch can be used to replace or to supplement sensory systems such as computer vision and, therefore, improve the sensory capacity of mobile robots. This paper describes how arrays of whisker-like touch sensors have been incorporated onto mobile robot platforms taking inspiration from biology for their morphology and control. There were two motivations for this work: first, to build a physical platform on which to model, and therefore test, recent neuroethological hypotheses about vibrissal touch; second, to exploit the control strategies and morphology observed in the biological analogue to maximize the quality and quantity of tactile sensory information derived from the artificial whisker array. We describe the design of a new whiskered robot, Shrewbot, endowed with a biomimetic array of individually controlled whiskers and a neuroethologically inspired whisking pattern generation mechanism. We then present results showing how the morphology of the whisker array shapes the sensory surface surrounding the robot's head, and demonstrate the impact of active touch control on the sensory information that can be acquired by the robot. We show that adopting bio-inspired, low latency motor control of the rhythmic motion of the whiskers in response to contact-induced stimuli usefully constrains the sensory range, while also maximizing the number of whisker contacts. The robot experiments also demonstrate that the sensory consequences of active touch control can be usefully investigated in biomimetic robots.
A proposed intracortical visual prosthesis image processing system.

PubMed

Srivastava, N R; Troyk, P

2005-01-01

It has been a goal of neuroprosthesis researchers to develop a system, which could provide artifical vision to a large population of individuals with blindness. It has been demonstrated by earlier researches that stimulating the visual cortex area electrically can evoke spatial visual percepts, i.e. phosphenes. The goal of visual cortex prosthesis is to stimulate the visual cortex area and generate a visual perception in real time to restore vision. Even though the normal working of the visual system is not been completely understood, the existing knowledge has inspired research groups to develop strategies to develop visual cortex prosthesis which can help blind patients in their daily activities. A major limitation in this work is the development of an image proceessing system for converting an electronic image, as captured by a camera, into a real-time data stream for stimulation of the implanted electrodes. This paper proposes a system, which will capture the image using a camera and use a dedicated hardware real time image processor to deliver electrical pulses to intracortical electrodes. This system has to be flexible enough to adapt to individual patients and to various strategies of image reconstruction. Here we consider a preliminary architecture for this system.
CTViz: A tool for the visualization of transport in nanocomposites.

PubMed

Beach, Benjamin; Brown, Joshua; Tarlton, Taylor; Derosa, Pedro A

2016-05-01

A visualization tool (CTViz) for charge transport processes in 3-D hybrid materials (nanocomposites) was developed, inspired by the need for a graphical application to assist in code debugging and data presentation of an existing in-house code. As the simulation code grew, troubleshooting problems grew increasingly difficult without an effective way to visualize 3-D samples and charge transport in those samples. CTViz is able to produce publication and presentation quality visuals of the simulation box, as well as static and animated visuals of the paths of individual carriers through the sample. CTViz was designed to provide a high degree of flexibility in the visualization of the data. A feature that characterizes this tool is the use of shade and transparency levels to highlight important details in the morphology or in the transport paths by hiding or dimming elements of little relevance to the current view. This is fundamental for the visualization of 3-D systems with complex structures. The code presented here provides these required capabilities, but has gone beyond the original design and could be used as is or easily adapted for the visualization of other particulate transport where transport occurs on discrete paths. Copyright © 2016 Elsevier Inc. All rights reserved.

Harnessing the potential of natural products in drug discovery from a cheminformatics vantage point.

PubMed

Rodrigues, Tiago

2017-11-15

Natural products (NPs) present a privileged source of inspiration for chemical probe and drug design. Despite the biological pre-validation of the underlying molecular architectures and their relevance in drug discovery, the poor accessibility to NPs, complexity of the synthetic routes and scarce knowledge of their macromolecular counterparts in phenotypic screens still hinder their broader exploration. Cheminformatics algorithms now provide a powerful means of circumventing the abovementioned challenges and unlocking the full potential of NPs in a drug discovery context. Herein, I discuss recent advances in the computer-assisted design of NP mimics and how artificial intelligence may accelerate future NP-inspired molecular medicine.
Biomimicry and the culinary arts.

PubMed

Burton, Lisa J; Cheng, Nadia; Vega, César; Andrés, José; Bush, John W M

2013-12-01

We present the results of a recent collaboration between scientists, engineers and chefs. Two particular devices are developed, both inspired by natural phenomena reliant on surface tension. The cocktail boat is a drink accessory, a self-propelled edible boat powered by alcohol-induced surface tension gradients, whose propulsion mechanism is analogous to that employed by a class of water-walking insects. The floral pipette is a novel means of serving small volumes of fluid in an elegant fashion, an example of capillary origami modeled after a class of floating flowers. The biological inspiration and mechanics of these two devices are detailed, along with the process that led to their development and deployment.
Product and technology innovation: what can biomimicry inspire?

PubMed

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

NASA Astrophysics Data System (ADS)

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.
The cocktail boat.

PubMed

Burton, Lisa J; Cheng, Nadia; Bush, John W M

2014-12-01

We describe the inspiration, development, and deployment of a novel cocktail device modeled after a class of water-walking insects. Semi-aquatic insects like Microvelia and Velia evade predators by releasing a surfactant that quickly propels them across the water. We exploit an analogous propulsion mechanism in the design of an edible cocktail boat. We discuss how gradients in surface tension lead to motion across the water's surface, and detail the design considerations associated with the insect-inspired cocktail boat. © The Author 2014. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.
Biologically-inspired navigation and flight control for Mars flyer missions

NASA Technical Reports Server (NTRS)

Thakoor, S.; Chahl, J.; Hine, B.; Zornetzer, S.

2003-01-01

Bioinspired Engineering Exploration Systems (BEES), is enabling new bioinspired sensors for autonomous exploration of Mars. The steps towards autonomy in development of these BEES flyers are described. A future set of Mars mission that are uniquely enabled by surch flyers are finally described.
NCT and Culture-Conscious Developmental Science

ERIC Educational Resources Information Center

Downing-Wilson, Deborah; Pelaprat, Etienne; Rosero, Ivan; Vadeboncoeur, Jennifer; Packer, Martin; Cole, Michael

2013-01-01

The authors share the belief that there is great potential for developmental science in bringing the ideas of Niche Construction Theory (NCT), as developed in evolutionary biology, into conversation with Vygotskian-inspired theories such as cultural-historical and activity theories, distributed cognition, and embodied cognition, although from…
Reassembling biological machinery in vitro.

PubMed

Hess, Henry

2009-09-25

Inspired by the specialized glycolytic system of flagella of mammalian sperm, Mukai et al. (2009) describe the controlled immobilization of two enzymes constituting the first steps in the glycolytic pathway. Extension of this work may provide "power converters" for bionanodevices, which transduce chemical energy from glucose to ATP.
Intelligent detectors modelled from the cat's eye

NASA Astrophysics Data System (ADS)

Lindblad, Th.; Becanovic, V.; Lindsey, C. S.; Szekely, G.

1997-02-01

Biologically inspired image/signal processing, in particular neural networks like the Pulse-Coupled Neural Network (PCNN), are revisited. Their use with high granularity high-energy physics detectors, as well as optical sensing devices, for filtering, de-noising, segmentation, object isolation and edge detection is discussed.
Methodology for designing and manufacturing complex biologically inspired soft robotic fluidic actuators: prosthetic hand case study.

PubMed

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

PubMed

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

PubMed Central

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

2014-01-01

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. PMID:25338507
Three-dimensional nano-biointerface as a new platform for guiding cell fate.

PubMed

Liu, Xueli; Wang, Shutao

2014-04-21

Three-dimensional nano-biointerface has been emerging as an important topic for chemistry, nanotechnology, and life sciences in recent years. Understanding the exchanges of materials, signals, and energy at biological interfaces has inspired and helped the serial design of three-dimensional nano-biointerfaces. The intimate interactions between cells and nanostructures bring many novel properties, making three-dimensional nano-biointerfaces a powerful platform to guide cell fate in a controllable and accurate way. These advantages and capabilities endow three-dimensional nano-biointerfaces with an indispensable role in developing advanced biological science and technology. This tutorial review is mainly focused on the recent progress of three-dimensional nano-biointerfaces and highlights the new explorations and unique phenomena of three-dimensional nano-biointerfaces for cell-related fundamental studies and biomedical applications. Some basic bio-inspired principles for the design and creation of three-dimensional nano-biointerfaces are also delivered in this review. Current and further challenges of three-dimensional nano-biointerfaces are finally addressed and proposed.
Novel High Integrity Bio-Inspired Systems with On-Line Self-Test and Self-Repair Properties

NASA Astrophysics Data System (ADS)

Samie, Mohammad; Dragffy, Gabriel; Pipe, Tony

2011-08-01

Since the beginning of life nature has been developing some remarkable solutions to the problem of creating reliable systems that can operate under difficult environmental and fault conditions. Yet, no matter how sophisticated our systems are, we are still unable to match the high degree of reliability that biological organisms posses. Since the early '90s attempts have been made to adapt biological properties and processes to the design of electronic systems but the results have always been unduly complex.This paper, proposes a novel model using a radically new approach to construct highly reliable electronic systems with online fault repair properties. It uses the characteristics and behaviour of unicellular bacteria and bacterial communities to achieve this. The result is a configurable bio-inspired cellular array architecture that, with built-in self-diagnostic and self-repair properties, can implement any application specific electronic system but is particularly suited for safety critical environments, such as space.
Biologically inspired flexible quasi-single-mode random laser: An integration of Pieris canidia butterfly wing and semiconductors

NASA Astrophysics Data System (ADS)

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

PubMed

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.
Consistent design schematics for biological systems: standardization of representation in biological engineering

PubMed Central

Matsuoka, Yukiko; Ghosh, Samik; Kitano, Hiroaki

2009-01-01

The discovery by design paradigm driving research in synthetic biology entails the engineering of de novo biological constructs with well-characterized input–output behaviours and interfaces. The construction of biological circuits requires iterative phases of design, simulation and assembly, leading to the fabrication of a biological device. In order to represent engineered models in a consistent visual format and further simulating them in silico, standardization of representation and model formalism is imperative. In this article, we review different efforts for standardization, particularly standards for graphical visualization and simulation/annotation schemata adopted in systems biology. We identify the importance of integrating the different standardization efforts and provide insights into potential avenues for developing a common framework for model visualization, simulation and sharing across various tools. We envision that such a synergistic approach would lead to the development of global, standardized schemata in biology, empowering deeper understanding of molecular mechanisms as well as engineering of novel biological systems. PMID:19493898
The Wyss institute: A new model for medical technology innovation and translation across the academic‐industrial interface

PubMed Central

Tolikas, Mary; Antoniou, Ayis

2017-01-01

Abstract The Wyss Institute for Biologically Inspired Engineering at Harvard University was formed based on the recognition that breakthrough discoveries cannot change the world if they never leave the laboratory. The Institute's mission is to discover the biological principles that Nature uses to build living things, and to harness these insights to create biologically inspired engineering innovations to advance human health and create a more sustainable world. Since its launch in 2009, the Institute has developed a new model for innovation, collaboration, and technology translation within academia, breaking “silos” to enable collaborations that cross institutional and disciplinary barriers. Institute faculty and staff engage in high‐risk research that leads to transformative breakthroughs. The biological principles uncovered are harnessed to develop new engineering solutions for medicine and healthcare, as well as nonmedical areas, such as energy, architecture, robotics, and manufacturing. These technologies are translated into commercial products and therapies through collaborations with clinical investigators, corporate alliances, and the formation of new start‐ups that are driven by a unique internal business development team including entrepreneurs‐in‐residence with domain‐specific expertise. Here, we describe this novel organizational model that the Institute has developed to change the paradigm of how fundamental discovery, medical technology innovation, and commercial translation are carried out at the academic‐industrial interface. PMID:29313034
Learning by stimulation avoidance: A principle to control spiking neural networks dynamics

PubMed Central

Sinapayen, Lana; Ikegami, Takashi

2017-01-01

Learning based on networks of real neurons, and learning based on biologically inspired models of neural networks, have yet to find general learning rules leading to widespread applications. In this paper, we argue for the existence of a principle allowing to steer the dynamics of a biologically inspired neural network. Using carefully timed external stimulation, the network can be driven towards a desired dynamical state. We term this principle “Learning by Stimulation Avoidance” (LSA). We demonstrate through simulation that the minimal sufficient conditions leading to LSA in artificial networks are also sufficient to reproduce learning results similar to those obtained in biological neurons by Shahaf and Marom, and in addition explains synaptic pruning. We examined the underlying mechanism by simulating a small network of 3 neurons, then scaled it up to a hundred neurons. We show that LSA has a higher explanatory power than existing hypotheses about the response of biological neural networks to external simulation, and can be used as a learning rule for an embodied application: learning of wall avoidance by a simulated robot. In other works, reinforcement learning with spiking networks can be obtained through global reward signals akin simulating the dopamine system; we believe that this is the first project demonstrating sensory-motor learning with random spiking networks through Hebbian learning relying on environmental conditions without a separate reward system. PMID:28158309
Learning by stimulation avoidance: A principle to control spiking neural networks dynamics.

PubMed

Sinapayen, Lana; Masumori, Atsushi; Ikegami, Takashi

2017-01-01

Learning based on networks of real neurons, and learning based on biologically inspired models of neural networks, have yet to find general learning rules leading to widespread applications. In this paper, we argue for the existence of a principle allowing to steer the dynamics of a biologically inspired neural network. Using carefully timed external stimulation, the network can be driven towards a desired dynamical state. We term this principle "Learning by Stimulation Avoidance" (LSA). We demonstrate through simulation that the minimal sufficient conditions leading to LSA in artificial networks are also sufficient to reproduce learning results similar to those obtained in biological neurons by Shahaf and Marom, and in addition explains synaptic pruning. We examined the underlying mechanism by simulating a small network of 3 neurons, then scaled it up to a hundred neurons. We show that LSA has a higher explanatory power than existing hypotheses about the response of biological neural networks to external simulation, and can be used as a learning rule for an embodied application: learning of wall avoidance by a simulated robot. In other works, reinforcement learning with spiking networks can be obtained through global reward signals akin simulating the dopamine system; we believe that this is the first project demonstrating sensory-motor learning with random spiking networks through Hebbian learning relying on environmental conditions without a separate reward system.

Bio-inspired fabrication of stimuli-responsive photonic crystals with hierarchical structures and their applications

NASA Astrophysics Data System (ADS)

Lu, Tao; Peng, Wenhong; Zhu, Shenmin; Zhang, Di

2016-03-01

When the constitutive materials of photonic crystals (PCs) are stimuli-responsive, the resultant PCs exhibit optical properties that can be tuned by the stimuli. This can be exploited for promising applications in colour displays, biological and chemical sensors, inks and paints, and many optically active components. However, the preparation of the required photonic structures is the first issue to be solved. In the past two decades, approaches such as microfabrication and self-assembly have been developed to incorporate stimuli-responsive materials into existing periodic structures for the fabrication of PCs, either as the initial building blocks or as the surrounding matrix. Generally, the materials that respond to thermal, pH, chemical, optical, electrical, or magnetic stimuli are either soft or aggregate, which is why the manufacture of three-dimensional hierarchical photonic structures with responsive properties is a great challenge. Recently, inspired by biological PCs in nature which exhibit both flexible and responsive properties, researchers have developed various methods to synthesize metals and metal oxides with hierarchical structures by using a biological PC as the template. This review will focus on the recent developments in this field. In particular, PCs with biological hierarchical structures that can be tuned by external stimuli have recently been successfully fabricated. These findings offer innovative insights into the design of responsive PCs and should be of great importance for future applications of these materials.
Improved CORF model of simple cell combined with non-classical receptive field and its application on edge detection

NASA Astrophysics Data System (ADS)

Sun, Xiao; Chai, Guobei; Liu, Wei; Bao, Wenzhuo; Zhao, Xiaoning; Ming, Delie

2018-02-01

Simple cells in primary visual cortex are believed to extract local edge information from a visual scene. In this paper, inspired by different receptive field properties and visual information flow paths of neurons, an improved Combination of Receptive Fields (CORF) model combined with non-classical receptive fields was proposed to simulate the responses of simple cell's receptive fields. Compared to the classical model, the proposed model is able to better imitate simple cell's physiologic structure with consideration of facilitation and suppression of non-classical receptive fields. And on this base, an edge detection algorithm as an application of the improved CORF model was proposed. Experimental results validate the robustness of the proposed algorithm to noise and background interference.
OmicsNet: a web-based tool for creation and visual analysis of biological networks in 3D space.

PubMed

Zhou, Guangyan; Xia, Jianguo

2018-06-07

Biological networks play increasingly important roles in omics data integration and systems biology. Over the past decade, many excellent tools have been developed to support creation, analysis and visualization of biological networks. However, important limitations remain: most tools are standalone programs, the majority of them focus on protein-protein interaction (PPI) or metabolic networks, and visualizations often suffer from 'hairball' effects when networks become large. To help address these limitations, we developed OmicsNet - a novel web-based tool that allows users to easily create different types of molecular interaction networks and visually explore them in a three-dimensional (3D) space. Users can upload one or multiple lists of molecules of interest (genes/proteins, microRNAs, transcription factors or metabolites) to create and merge different types of biological networks. The 3D network visualization system was implemented using the powerful Web Graphics Library (WebGL) technology that works natively in most major browsers. OmicsNet supports force-directed layout, multi-layered perspective layout, as well as spherical layout to help visualize and navigate complex networks. A rich set of functions have been implemented to allow users to perform coloring, shading, topology analysis, and enrichment analysis. OmicsNet is freely available at http://www.omicsnet.ca.
Biological issues in materials science and engineering: Interdisciplinarity and the bio-materials paradigm

NASA Astrophysics Data System (ADS)

Murr, L. E.

2006-07-01

Biological systems and processes have had, and continue to have, important implications and applications in materials extraction, processing, and performance. This paper illustrates some interdisciplinary, biological issues in materials science and engineering. These include metal extraction involving bacterial catalysis, galvanic couples, bacterial-assisted corrosion and degradation of materials, biosorption and bioremediation of toxic and other heavy metals, metal and material implants and prostheses and related dental and medical biomaterials developments and applications, nanomaterials health benefits and toxicity issue, and biomimetics and biologically inspired materials developments. These and other examples provide compelling evidence and arguments for emphasizing biological sicences in materials science and engineering curricula and the implementation of a bio-materials paradigm to facilitate the emergence of innovative interdisciplinarity involving the biological sciences and materials sciences and engineering.
Communication analysis for feedback control of civil infrastructure using cochlea-inspired sensing nodes

NASA Astrophysics Data System (ADS)

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.
Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons.

PubMed

Burbank, Kendra S

2015-12-01

The autoencoder algorithm is a simple but powerful unsupervised method for training neural networks. Autoencoder networks can learn sparse distributed codes similar to those seen in cortical sensory areas such as visual area V1, but they can also be stacked to learn increasingly abstract representations. Several computational neuroscience models of sensory areas, including Olshausen & Field's Sparse Coding algorithm, can be seen as autoencoder variants, and autoencoders have seen extensive use in the machine learning community. Despite their power and versatility, autoencoders have been difficult to implement in a biologically realistic fashion. The challenges include their need to calculate differences between two neuronal activities and their requirement for learning rules which lead to identical changes at feedforward and feedback connections. Here, we study a biologically realistic network of integrate-and-fire neurons with anatomical connectivity and synaptic plasticity that closely matches that observed in cortical sensory areas. Our choice of synaptic plasticity rules is inspired by recent experimental and theoretical results suggesting that learning at feedback connections may have a different form from learning at feedforward connections, and our results depend critically on this novel choice of plasticity rules. Specifically, we propose that plasticity rules at feedforward versus feedback connections are temporally opposed versions of spike-timing dependent plasticity (STDP), leading to a symmetric combined rule we call Mirrored STDP (mSTDP). We show that with mSTDP, our network follows a learning rule that approximately minimizes an autoencoder loss function. When trained with whitened natural image patches, the learned synaptic weights resemble the receptive fields seen in V1. Our results use realistic synaptic plasticity rules to show that the powerful autoencoder learning algorithm could be within the reach of real biological networks.
Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons

PubMed Central

Burbank, Kendra S.

2015-01-01

The autoencoder algorithm is a simple but powerful unsupervised method for training neural networks. Autoencoder networks can learn sparse distributed codes similar to those seen in cortical sensory areas such as visual area V1, but they can also be stacked to learn increasingly abstract representations. Several computational neuroscience models of sensory areas, including Olshausen & Field’s Sparse Coding algorithm, can be seen as autoencoder variants, and autoencoders have seen extensive use in the machine learning community. Despite their power and versatility, autoencoders have been difficult to implement in a biologically realistic fashion. The challenges include their need to calculate differences between two neuronal activities and their requirement for learning rules which lead to identical changes at feedforward and feedback connections. Here, we study a biologically realistic network of integrate-and-fire neurons with anatomical connectivity and synaptic plasticity that closely matches that observed in cortical sensory areas. Our choice of synaptic plasticity rules is inspired by recent experimental and theoretical results suggesting that learning at feedback connections may have a different form from learning at feedforward connections, and our results depend critically on this novel choice of plasticity rules. Specifically, we propose that plasticity rules at feedforward versus feedback connections are temporally opposed versions of spike-timing dependent plasticity (STDP), leading to a symmetric combined rule we call Mirrored STDP (mSTDP). We show that with mSTDP, our network follows a learning rule that approximately minimizes an autoencoder loss function. When trained with whitened natural image patches, the learned synaptic weights resemble the receptive fields seen in V1. Our results use realistic synaptic plasticity rules to show that the powerful autoencoder learning algorithm could be within the reach of real biological networks. PMID:26633645
[Comparison study between biological vision and computer vision].

PubMed

Liu, W; Yuan, X G; Yang, C X; Liu, Z Q; Wang, R

2001-08-01

The development and bearing of biology vision in structure and mechanism were discussed, especially on the aspects including anatomical structure of biological vision, tentative classification of reception field, parallel processing of visual information, feedback and conformity effect of visual cortical, and so on. The new advance in the field was introduced through the study of the morphology of biological vision. Besides, comparison between biological vision and computer vision was made, and their similarities and differences were pointed out.
An expanded framework for biomolecular visualization in the classroom: Learning goals and competencies.

PubMed

Dries, Daniel R; Dean, Diane M; Listenberger, Laura L; Novak, Walter R P; Franzen, Margaret A; Craig, Paul A

2017-01-02

A thorough understanding of the molecular biosciences requires the ability to visualize and manipulate molecules in order to interpret results or to generate hypotheses. While many instructors in biochemistry and molecular biology use visual representations, few indicate that they explicitly teach visual literacy. One reason is the need for a list of core content and competencies to guide a more deliberate instruction in visual literacy. We offer here the second stage in the development of one such resource for biomolecular three-dimensional visual literacy. We present this work with the goal of building a community for online resource development and use. In the first stage, overarching themes were identified and submitted to the biosciences community for comment: atomic geometry; alternate renderings; construction/annotation; het group recognition; molecular dynamics; molecular interactions; monomer recognition; symmetry/asymmetry recognition; structure-function relationships; structural model skepticism; and topology and connectivity. Herein, the overarching themes have been expanded to include a 12th theme (macromolecular assemblies), 27 learning goals, and more than 200 corresponding objectives, many of which cut across multiple overarching themes. The learning goals and objectives offered here provide educators with a framework on which to map the use of molecular visualization in their classrooms. In addition, the framework may also be used by biochemistry and molecular biology educators to identify gaps in coverage and drive the creation of new activities to improve visual literacy. This work represents the first attempt, to our knowledge, to catalog a comprehensive list of explicit learning goals and objectives in visual literacy. © 2016 by The International Union of Biochemistry and Molecular Biology, 45(1):69-75, 2017. © 2016 The Authors Biochemistry and Molecular Biology Education published by Wiley Periodicals, Inc. on behalf of International Union of Biochemistry and Molecular Biology.
Superhydrophobic gecko feet with high adhesive forces towards water and their bio-inspired materials.

PubMed

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

2012-02-07

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. This journal is © The Royal Society of Chemistry 2012
From perceptive fields to Gestalt.

PubMed

Spillmann, Lothar

2006-01-01

Studies on visual psychophysics and perception conducted in the Freiburg psychophysics laboratory during the last 35 years are reviewed. Many of these were inspired by single-cell neurophysiology in cat and monkey. The aim was to correlate perceptual phenomena and their effects to possible neuronal mechanisms from retina to visual cortex and beyond. Topics discussed include perceptive field organization, figure-ground segregation and grouping, fading and filling-in, and long-range color interaction. While some of these studies succeeded in linking perception to neuronal response patterns, others require further investigation. The task of probing the human brain with perceptual phenomena continues to be a challenge for the future.
An Interpreted Language and System for the Visualization of Unstructured Meshes

NASA Technical Reports Server (NTRS)

Moran, Patrick J.; Gerald-Yamasaki, Michael (Technical Monitor)

1998-01-01

We present an interpreted language and system supporting the visualization of unstructured meshes and the manipulation of shapes defined in terms of mesh subsets. The language features primitives inspired by geometric modeling, mathematical morphology and algebraic topology. The adaptation of the topology ideas to an interpreted environment, along with support for programming constructs such, as user function definition, provide a flexible system for analyzing a mesh and for calculating with shapes defined in terms of the mesh. We present results demonstrating some of the capabilities of the language, based on an implementation called the Shape Calculator, for tetrahedral meshes in R^3.
Designing Biomimetic Materials from Marine Organisms.

PubMed

Nichols, William T

2015-01-01

Two biomimetic design approaches that apply biological solutions to engineering problems are discussed. In the first case, motivation comes from an engineering problem and the key challenge is to find analogous biological functions and map them into engineering materials. We illustrate with an example of water pollution remediation through appropriate design of a biomimetic sponge. In the second case, a biological function is already known and the challenge is to identify the appropriate engineering problem. We demonstrate the biological approach with marine diatoms that control energy and materials at their surface providing inspiration for a number of engineering applications. In both cases, it is essential to select materials and structures at the nanoscale to control energy and materials flows at interfaces.
Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines

NASA Astrophysics Data System (ADS)

Mirel, Barbara; Kumar, Anuj; Nong, Paige; Su, Gang; Meng, Fan

2016-02-01

Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors conducting exploratory analysis using the same interactive data visualizations as practicing scientists. We examined 22 upper level undergraduates in a genomics course as they engaged in a case-based inquiry with an interactive heat map. We qualitatively and quantitatively analyzed students' visual analytic behaviors, reasoning and outcomes to identify student performance patterns, commonly shared efficiencies and task completion. We analyzed students' successes and difficulties in applying knowledge and skills relevant to the visual analytics case and related gaps in knowledge and skill to associated tool designs. Findings show that undergraduate engagement in visual analytics is feasible and could be further strengthened through tool usability improvements. We identify these improvements. We speculate, as well, on instructional considerations that our findings suggested may also enhance visual analytics in case-based modules.
Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines

PubMed Central

Kumar, Anuj; Nong, Paige; Su, Gang; Meng, Fan

2016-01-01

Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors conducting exploratory analysis using the same interactive data visualizations as practicing scientists. We examined 22 upper level undergraduates in a genomics course as they engaged in a case-based inquiry with an interactive heat map. We qualitatively and quantitatively analyzed students’ visual analytic behaviors, reasoning and outcomes to identify student performance patterns, commonly shared efficiencies and task completion. We analyzed students’ successes and difficulties in applying knowledge and skills relevant to the visual analytics case and related gaps in knowledge and skill to associated tool designs. Findings show that undergraduate engagement in visual analytics is feasible and could be further strengthened through tool usability improvements. We identify these improvements. We speculate, as well, on instructional considerations that our findings suggested may also enhance visual analytics in case-based modules. PMID:26877625
Weather on Steroids: The Art of Climate Change Science.

NASA Astrophysics Data System (ADS)

Boudrias, M. A.; Gershunov, A.; Sizonenko, T.; Wiese, A.; Fox, H.

2017-12-01

There have been many different kinds of efforts to improve climate change literacy of diverse audiences in the past several years. The challenge has been to balance science content with audience-specific messaging that engages them in both rational and affective ways. In the San Diego Region, Climate Education Partners (CEP) has been working with business leaders, elected officials, tribal leaders, and other community leaders to develop a suite of programs and activities to enhance the channels of communication outside traditional settings. CEP has partnered with the La Jolla Historical Society and the Scripps Institution of Oceanography in a unique exhibition of art inspired by climate science, a project blending science and art to communicate the science of climate change in a new way and engage audiences more effectively. Weather on Steroids: the Art of Climate Change Science explores the question of consequences, challenges, and opportunities that arise from the changing climate on our planet. The exhibition merges the artistic and scientific to create a visual dialogue about the vexing problem of climate change, explores how weather variability affects the day-to-day life of local communities, and investigates Southern California vulnerability to climate change. Science serves as the inspiration for the creative responses from visual artists, who merge subjective images with empirical observation to reveal how climate variations upset the planet's balance with extreme weather impacts. Both the scientists and artists created didactic pages to explain their perspectives and each pair worked closely to incorporate the information into the creative piece so that the connection of each of 11 art installations to the science that inspired them is clear. By illuminating the reality of climate change, Weather on Steroids aspires to proactively stimulate public dialogue about one of the most important issues of our time.
Jim Thomas, 1946-2010

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

Stone, Maureen; Kasik, David; Bailey, Mike

Jim Thomas, a visionary scientist and inspirational leader, died on 6 August 2010 in Richland, Washington. His impact on the fields of computer graphics, user interface software, and visualization was extraordinary, his ability to personally change people’s lives even more so. He is remembered for his enthusiasm, his mentorship, his generosity, and, most of all, his laughter. This collection of remembrances images him through the eyes of his many friends.
MLC Libraries--A School Library's Journey with Students, Staff and Web 2.0 Technologies: Blogs, Wikis and E-Books--Where Are We Going Next?

ERIC Educational Resources Information Center

Viner, Jane; Lucas, Amanda; Ricchini, Tracey; Ri, Regina

2010-01-01

This workshop paper explores the Web 2.0 journey of the MLC Libraries' teacher-librarians, librarian, library and audio visual technicians. Our journey was initially inspired by Will Richardson and supported by the School Library Association of Victoria (SLAV) Web 2.0 professional development program. The 12 week technological skills program…
Voyage out of the Interior: Amateur Historian's Films from '60s Stir Imagination at LCO

ERIC Educational Resources Information Center

Nayquonabe, Thelma

2007-01-01

This article reports on the re-emergence of some historic films from the '60s which creates excitement amongst Lac Courte Oreilles Ojibwe people and inspires them to launch a project to digitize and edit the old media. The "Audio Visual Production Project" began to take shape in the fall of 2006 when the tribal vice chairman, Rusty Barber,…
Distortions in Distributions of Impact Estimates in Multi-Site Trials: The Central Limit Theorem Is Not Your Friend

ERIC Educational Resources Information Center

May, Henry

2014-01-01

Interest in variation in program impacts--How big is it? What might explain it?--has inspired recent work on the analysis of data from multi-site experiments. One critical aspect of this problem involves the use of random or fixed effect estimates to visualize the distribution of impact estimates across a sample of sites. Unfortunately, unless the…

Photonic structures in biology

NASA Astrophysics Data System (ADS)

Vukusic, Pete; Sambles, J. Roy

2003-08-01

Millions of years before we began to manipulate the flow of light using synthetic structures, biological systems were using nanometre-scale architectures to produce striking optical effects. An astonishing variety of natural photonic structures exists: a species of Brittlestar uses photonic elements composed of calcite to collect light, Morpho butterflies use multiple layers of cuticle and air to produce their striking blue colour and some insects use arrays of elements, known as nipple arrays, to reduce reflectivity in their compound eyes. Natural photonic structures are providing inspiration for technological applications.
Critical Point in Self-Organized Tissue Growth

NASA Astrophysics Data System (ADS)

Aguilar-Hidalgo, Daniel; Werner, Steffen; Wartlick, Ortrud; González-Gaitán, Marcos; Friedrich, Benjamin M.; Jülicher, Frank

2018-05-01

We present a theory of pattern formation in growing domains inspired by biological examples of tissue development. Gradients of signaling molecules regulate growth, while growth changes these graded chemical patterns by dilution and advection. We identify a critical point of this feedback dynamics, which is characterized by spatially homogeneous growth and proportional scaling of patterns with tissue length. We apply this theory to the biological model system of the developing wing of the fruit fly Drosophila melanogaster and quantitatively identify signatures of the critical point.
The -omics Era- Toward a Systems-Level Understanding of Streptomyces

PubMed Central

Zhou, Zhan; Gu, Jianying; Du, Yi-Ling; Li, Yong-Quan; Wang, Yufeng

2011-01-01

Streptomyces is a group of soil bacteria of medicinal, economic, ecological, and industrial importance. It is renowned for its complex biology in gene regulation, antibiotic production, morphological differentiation, and stress response. In this review, we provide an overview of the recent advances in Streptomyces biology inspired by -omics based high throughput technologies. In this post-genomic era, vast amounts of data have been integrated to provide significant new insights into the fundamental mechanisms of system control and regulation dynamics of Streptomyces. PMID:22379394
State-of-the-art technologies, current opinions and developments, and novel findings: news from the field of histochemistry and cell biology.

PubMed

Asan, Esther; Drenckhahn, Detlev

2008-12-01

Investigations of cell and tissue structure and function using innovative methods and approaches have again yielded numerous exciting findings in recent months and have added important data to current knowledge, inspiring new ideas and hypotheses in various fields of modern life sciences. Topics and contents of comprehensive expert reviews covering different aspects in methodological advances, cell biology, tissue function and morphology, and novel findings reported in original papers are summarized in the present review.
Discovery of a diazo-forming enzyme in cremeomycin biosynthesis.

PubMed

Waldman, Abraham J; Balskus, Emily P

2018-05-17

The molecular architectures and potent bioactivities of diazo-containing natural products have attracted the interest of synthetic and biological chemists. Despite this attention, the biosynthetic enzymes involved in diazo group construction have not been identified. Here, we show the ATP-dependent enzyme CreM installs the diazo group in cremeomycin via late-stage N-N bond formation using nitrite. This finding should inspire efforts to use diazo-forming enzymes in biocatalysis and synthetic biology and enable genome-based discovery of new diazo-containing metabolites.
Probing biological redox chemistry with large amplitude Fourier transformed ac voltammetry

PubMed Central

Adamson, Hope

2017-01-01

Biological electron-exchange reactions are fundamental to life on earth. Redox reactions underpin respiration, photosynthesis, molecular biosynthesis, cell signalling and protein folding. Chemical, biomedical and future energy technology developments are also inspired by these natural electron transfer processes. Further developments in techniques and data analysis are required to gain a deeper understanding of the redox biochemistry processes that power Nature. This review outlines the new insights gained from developing Fourier transformed ac voltammetry as a tool for protein film electrochemistry. PMID:28804798
Framework and algorithms for illustrative visualizations of time-varying flows on unstructured meshes

DOE PAGES

Rattner, Alexander S.; Guillen, Donna Post; Joshi, Alark; ...

2016-03-17

Photo- and physically realistic techniques are often insufficient for visualization of fluid flow simulations, especially for 3D and time-varying studies. Substantial research effort has been dedicated to the development of non-photorealistic and illustration-inspired visualization techniques for compact and intuitive presentation of such complex datasets. However, a great deal of work has been reproduced in this field, as many research groups have developed specialized visualization software. Additionally, interoperability between illustrative visualization software is limited due to diverse processing and rendering architectures employed in different studies. In this investigation, a framework for illustrative visualization is proposed, and implemented in MarmotViz, a ParaViewmore » plug-in, enabling its use on a variety of computing platforms with various data file formats and mesh geometries. Region-of-interest identification and feature-tracking algorithms incorporated into this tool are described. Implementations of multiple illustrative effect algorithms are also presented to demonstrate the use and flexibility of this framework. Here, by providing an integrated framework for illustrative visualization of CFD data, MarmotViz can serve as a valuable asset for the interpretation of simulations of ever-growing scale.« less
BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks.

PubMed

Maere, Steven; Heymans, Karel; Kuiper, Martin

2005-08-15

The Biological Networks Gene Ontology tool (BiNGO) is an open-source Java tool to determine which Gene Ontology (GO) terms are significantly overrepresented in a set of genes. BiNGO can be used either on a list of genes, pasted as text, or interactively on subgraphs of biological networks visualized in Cytoscape. BiNGO maps the predominant functional themes of the tested gene set on the GO hierarchy, and takes advantage of Cytoscape's versatile visualization environment to produce an intuitive and customizable visual representation of the results.
The challenges of informatics in synthetic biology: from biomolecular networks to artificial organisms

PubMed Central

Ramoni, Marco F.

2010-01-01

The field of synthetic biology holds an inspiring vision for the future; it integrates computational analysis, biological data and the systems engineering paradigm in the design of new biological machines and systems. These biological machines are built from basic biomolecular components analogous to electrical devices, and the information flow among these components requires the augmentation of biological insight with the power of a formal approach to information management. Here we review the informatics challenges in synthetic biology along three dimensions: in silico, in vitro and in vivo. First, we describe state of the art of the in silico support of synthetic biology, from the specific data exchange formats, to the most popular software platforms and algorithms. Next, we cast in vitro synthetic biology in terms of information flow, and discuss genetic fidelity in DNA manipulation, development strategies of biological parts and the regulation of biomolecular networks. Finally, we explore how the engineering chassis can manipulate biological circuitries in vivo to give rise to future artificial organisms. PMID:19906839
Media and the making of scientists

NASA Astrophysics Data System (ADS)

O'Keeffe, Moira

This dissertation explores how scientists and science students respond to fictional, visual media about science. I consider how scientists think about images of science in relation to their own career paths from childhood onwards. I am especially interested in the possibility that entertainment media can inspire young people to learn about science. Such inspiration is badly needed, as schools are failing to provide it. Science education in the United States is in a state of crisis. Studies repeatedly find low levels of science literacy in the U.S. This bleak situation exists during a boom in the popularity of science-oriented television shows and science fiction movies. How might entertainment media play a role in helping young people engage with science? To grapple with these questions, I interviewed a total of fifty scientists and students interested in science careers, representing a variety of scientific fields and demographic backgrounds, and with varying levels of interest in science fiction. Most respondents described becoming attracted to the sciences at a young age, and many were able to identify specific sources for this interest. The fact that interest in the sciences begins early in life, demonstrates a potentially important role for fictional media in the process of inspiration, perhaps especially for children without access to real-life scientists. One key aspect to the appeal of fiction about science is how scientists are portrayed as characters. Scientists from groups traditionally under-represented in the sciences often sought out fictional characters with whom they could identify, and viewers from all backgrounds preferred well-rounded characters to the extreme stereotypes of mad or dorky scientists. Genre is another aspect of appeal. Some respondents identified a specific role for science fiction: conveying a sense of wonder. Visual media introduce viewers to the beauty of science. Special effects, in particular, allow viewers to explore the unknown. Advocates of informal science learning initiatives suggest that media can be used as a tool for teaching science content. The potential of entertainment media to provide a sense of wonder is a powerful aspect of its potential to inspire the next generation of scientists.
ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining.

PubMed

Huan, Tianxiao; Sivachenko, Andrey Y; Harrison, Scott H; Chen, Jake Y

2008-08-12

New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellular and physiological functions. Many software tools have been developed in the past decade to help researchers visually navigate large networks of biomolecular interactions with built-in template-based query capabilities. To further advance researchers' ability to interrogate global physiological states of cells through multi-scale visual network explorations, new visualization software tools still need to be developed to empower the analysis. A robust visual data analysis platform driven by database management systems to perform bi-directional data processing-to-visualizations with declarative querying capabilities is needed. We developed ProteoLens as a JAVA-based visual analytic software tool for creating, annotating and exploring multi-scale biological networks. It supports direct database connectivity to either Oracle or PostgreSQL database tables/views, on which SQL statements using both Data Definition Languages (DDL) and Data Manipulation languages (DML) may be specified. The robust query languages embedded directly within the visualization software help users to bring their network data into a visualization context for annotation and exploration. ProteoLens supports graph/network represented data in standard Graph Modeling Language (GML) formats, and this enables interoperation with a wide range of other visual layout tools. The architectural design of ProteoLens enables the de-coupling of complex network data visualization tasks into two distinct phases: 1) creating network data association rules, which are mapping rules between network node IDs or edge IDs and data attributes such as functional annotations, expression levels, scores, synonyms, descriptions etc; 2) applying network data association rules to build the network and perform the visual annotation of graph nodes and edges according to associated data values. We demonstrated the advantages of these new capabilities through three biological network visualization case studies: human disease association network, drug-target interaction network and protein-peptide mapping network. The architectural design of ProteoLens makes it suitable for bioinformatics expert data analysts who are experienced with relational database management to perform large-scale integrated network visual explorations. ProteoLens is a promising visual analytic platform that will facilitate knowledge discoveries in future network and systems biology studies.
A Watery Whodunit: The Case of the Missing Zooxanthellae

ERIC Educational Resources Information Center

Thomas, Kimberley A.; Bruno, Barbara C.; Achilles, Kate; Sherman, Sarah B.

2011-01-01

Understanding coral reefs and the threats they face is an essential precondition in preserving them. This activity helps to educate middle school students about coral biology and the problem of coral bleaching. It will inspire students to participate in marine conservation initiatives. (Contains 10 figures and 3 resources.)
Quantification of turfgrass buffer performance in reducing transport of pesticides in surface runoff

USDA-ARS?s Scientific Manuscript database

Pesticides are used to control pests in managed biological system such as agricultural crops and golf course turf. Off-site transport of pesticides with runoff and their potential to adversely affect non-target aquatic organisms has inspired the evaluation of management practices to minimize pestic...
Scalable Kernel Methods and Algorithms for General Sequence Analysis

ERIC Educational Resources Information Center

Kuksa, Pavel

2011-01-01

Analysis of large-scale sequential data has become an important task in machine learning and pattern recognition, inspired in part by numerous scientific and technological applications such as the document and text classification or the analysis of biological sequences. However, current computational methods for sequence comparison still lack…
Bioinspired engineering of exploration systems for NASA and DoD: from bees to BEES

NASA Technical Reports Server (NTRS)

Thakoor, S.; Zornetzer, S.; Hine, B.; Chahl, J.; Werblin, F.; Srinivasan, M. V.; Young, L.

2003-01-01

The intent of Bio-inspired Engineering of Exploration Systems (BEES) is to distill the principles found in successful, nature-tested mechanisms of specific crucial functions that are hard to accomplish by conventional methods, but accomplished rather deftly in nature by biological organisms.
The Harmony Specialist

ERIC Educational Resources Information Center

Olson, Catherine Applefeld

2008-01-01

This article profiles Beth Gilbert, a veteran Arizona string teacher who finds inspiration in teamwork--and her students. Growing up in Ohio, Gilbert enjoyed participating in her high school orchestra. Nevertheless she entered the University of Arizona as a marine biology major, choosing a field of study that she had planned to parlay into a…
Scientific Teaching: Defining a Taxonomy of Observable Practices

ERIC Educational Resources Information Center

Couch, Brian A.; Brown, Tanya L.; Schelpat, Tyler J.; Graham, Mark J.; Knight, Jennifer K.

2015-01-01

Over the past several decades, numerous reports have been published advocating for changes to undergraduate science education. These national calls inspired the formation of the National Academies Summer Institutes on Undergraduate Education in Biology (SI), a group of regional workshops to help faculty members learn and implement interactive…
Metal-catalyzed Decarboxylative Fluoroalkylation Reactions.

PubMed

Ambler, Brett R; Yang, Ming-Hsiu; Altman, Ryan A

2016-12-01

Metal-catalyzed decarboxylative fluoroalkylation reactions enable the conversion of simple O-based substrates into biologically relevant fluorinated analogs. Herein, we present decarboxylative methods that facilitate the synthesis of trifluoromethyl- and difluoroketone-containing products. We highlight key mechanistic aspects that are critical for efficient catalysis, and that inspired our thinking while developing the reactions.
Cybernetics, Redux: An Outside-In Strategy for Unraveling Cellular Function.

PubMed

Malleshaiah, Mohan; Gunawardena, Jeremy

2016-01-11

A new paper in Science reveals how repetitive stimulation can identify and help to repair fragilities within a signaling network, while using linear mathematical models inspired by engineering, thereby suggesting how cybernetic methods can be integrated into systems and synthetic biology. Copyright © 2016 Elsevier Inc. All rights reserved.
The Scientist as Illustrator.

PubMed

Iwasa, Janet H

2016-04-01

Proficiency in art and illustration was once considered an essential skill for biologists, because text alone often could not suffice to describe observations of biological systems. With modern imaging technology, it is no longer necessary to illustrate what we can see by eye. However, in molecular and cellular biology, our understanding of biological processes is dependent on our ability to synthesize diverse data to generate a hypothesis. Creating visual models of these hypotheses is important for generating new ideas and for communicating to our peers and to the public. Here, I discuss the benefits of creating visual models in molecular and cellular biology and consider steps to enable researchers to become more effective visual communicators. Copyright © 2016 Elsevier Ltd. All rights reserved.

Tools for visually exploring biological networks.

PubMed

Suderman, Matthew; Hallett, Michael

2007-10-15

Many tools exist for visually exploring biological networks including well-known examples such as Cytoscape, VisANT, Pathway Studio and Patika. These systems play a key role in the development of integrative biology, systems biology and integrative bioinformatics. The trend in the development of these tools is to go beyond 'static' representations of cellular state, towards a more dynamic model of cellular processes through the incorporation of gene expression data, subcellular localization information and time-dependent behavior. We provide a comprehensive review of the relative advantages and disadvantages of existing systems with two goals in mind: to aid researchers in efficiently identifying the appropriate existing tools for data visualization; to describe the necessary and realistic goals for the next generation of visualization tools. In view of the first goal, we provide in the Supplementary Material a systematic comparison of more than 35 existing tools in terms of over 25 different features. Supplementary data are available at Bioinformatics online.
Tandem Repeat Proteins Inspired By Squid Ring Teeth

NASA Astrophysics Data System (ADS)

Pena-Francesch, Abdon

Proteins are large biomolecules consisting of long chains of amino acids that hierarchically assemble into complex structures, and provide a variety of building blocks for biological materials. The repetition of structural building blocks is a natural evolutionary strategy for increasing the complexity and stability of protein structures. However, the relationship between amino acid sequence, structure, and material properties of protein systems remains unclear due to the lack of control over the protein sequence and the intricacies of the assembly process. In order to investigate the repetition of protein building blocks, a recently discovered protein from squids is examined as an ideal protein system. Squid ring teeth are predatory appendages located inside the suction cups that provide a strong grasp of prey, and are solely composed of a group of proteins with tandem repetition of building blocks. The objective of this thesis is the understanding of sequence, structure and property relationship in repetitive protein materials inspired in squid ring teeth for the first time. Specifically, this work focuses on squid-inspired structural proteins with tandem repeat units in their sequence (i.e., repetition of alternating building blocks) that are physically cross-linked via beta-sheet structures. The research work presented here tests the hypothesis that, in these systems, increasing the number of building blocks in the polypeptide chain decreases the protein network defects and improves the material properties. Hence, the sequence, nanostructure, and properties (thermal, mechanical, and conducting) of tandem repeat squid-inspired protein materials are examined. Spectroscopic structural analysis, advanced materials characterization, and entropic elasticity theory are combined to elucidate the structure and material properties of these repetitive proteins. This approach is applied not only to native squid proteins but also to squid-inspired synthetic polypeptides that allow for a fine control of the sequence and network morphology. The results provided in this work establish a clear dependence between the repetitive building blocks, the network morphology, and the properties of squid-inspired repetitive protein materials. Increasing the number of tandem repeat units in SRT-inspired proteins led to more effective protein networks with superior properties. Through increasing tandem repetition and optimization of network morphology, highly efficient protein materials capable of withstanding deformations up to 400% of their original length, with MPa-GPa modulus, high energy absorption (50 MJ m-3), peak proton conductivity of 3.7 mS cm-1 (at pH 7, highest reported to date for biological materials), and peak thermal conductivity of 1.4 W m-1 K -1 (which exceeds that of most polymer materials) were developed. These findings introduce new design rules in the engineering of proteins based on tandem repetition and morphology control, and provide a novel framework for tailoring and optimizing the properties of protein-based materials.
Selecting islands and shoals for conservation based on biological and aesthetic criteria

USGS Publications Warehouse

Knutson, M.G.; Leopold, D.J.; Smardon, R.C.

1993-01-01

Consideration of biological quality has long been an important component of rating areas for conservation. Often these same areas are highly valued by people for aesthetic reasons, creating demands for housing and recreation that may conflict with protection plans for these habitats. Most methods of selecting land for conservation purposes use biological factors alone. For some land areas, analysis of aesthetic qualities is also important in describing the scenic value of undisturbed land. A method for prioritizing small islands and shoals based on both biological and visual quality factors is presented here. The study included 169 undeveloped islands and shoals a??0.8 ha in the Thousand Islands Region of the St. Lawrence River, New York. Criteria such as critical habitat for uncommon plant and animal species were considered together with visual quality and incorporated into a rating system that ranked the islands and shoals according to their priority for conservation management and protection from development. Biological factors were determined based on previous research and a field survey. Visual quality was determined by visual diagnostic criteria developed from public responses to photographs of a sample of islands. Variables such as elevation, soil depth, and type of plant community can be used to classify islands into different categories of visual quality but are unsuccessful in classifying islands into categories of overall biological quality.
DeviceEditor visual biological CAD canvas

PubMed Central

2012-01-01

Background Biological Computer Aided Design (bioCAD) assists the de novo design and selection of existing genetic components to achieve a desired biological activity, as part of an integrated design-build-test cycle. To meet the emerging needs of Synthetic Biology, bioCAD tools must address the increasing prevalence of combinatorial library design, design rule specification, and scar-less multi-part DNA assembly. Results We report the development and deployment of web-based bioCAD software, DeviceEditor, which provides a graphical design environment that mimics the intuitive visual whiteboard design process practiced in biological laboratories. The key innovations of DeviceEditor include visual combinatorial library design, direct integration with scar-less multi-part DNA assembly design automation, and a graphical user interface for the creation and modification of design specification rules. We demonstrate how biological designs are rendered on the DeviceEditor canvas, and we present effective visualizations of genetic component ordering and combinatorial variations within complex designs. Conclusions DeviceEditor liberates researchers from DNA base-pair manipulation, and enables users to create successful prototypes using standardized, functional, and visual abstractions. Open and documented software interfaces support further integration of DeviceEditor with other bioCAD tools and software platforms. DeviceEditor saves researcher time and institutional resources through correct-by-construction design, the automation of tedious tasks, design reuse, and the minimization of DNA assembly costs. PMID:22373390
Bioinspired engineering of thermal materials.

PubMed

Tao, Peng; Shang, Wen; Song, Chengyi; Shen, Qingchen; Zhang, Fangyu; Luo, Zhen; Yi, Nan; Zhang, Di; Deng, Tao

2015-01-21

In the development of next-generation materials with enhanced thermal properties, biological systems in nature provide many examples that have exceptional structural designs and unparalleled performance in their thermal or nonthermal functions. Bioinspired engineering thus offers great promise in the synthesis and fabrication of thermal materials that are difficult to engineer through conventional approaches. In this review, recent progress in the emerging area of bioinspired advanced materials for thermal science and technology is summarized. State-of-the-art developments of bioinspired thermal-management materials, including materials for efficient thermal insulation and heat transfer, and bioinspired materials for thermal/infrared detection, are highlighted. The dynamic balance of bioinspiration and practical engineering, the correlation of inspiration approaches with the targeted applications, and the coexistence of molecule-based inspiration and structure-based inspiration are discussed in the overview of the development. The long-term outlook and short-term focus of this critical area of advanced materials engineering are also presented. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Biophysics and Thermodynamics: The Scientific Building Blocks of Bio-inspired Drug Delivery Nano Systems.

PubMed

Demetzos, Costas

2015-06-01

Biophysics and thermodynamics are considered as the scientific milestones for investigating the properties of materials. The relationship between the changes of temperature with the biophysical variables of biomaterials is important in the process of the development of drug delivery systems. Biophysics is a challenge sector of physics and should be used complementary with the biochemistry in order to discover new and promising technological platforms (i.e., drug delivery systems) and to disclose the 'silence functionality' of bio-inspired biological and artificial membranes. Thermal analysis and biophysical approaches in pharmaceuticals present reliable and versatile tools for their characterization and for the successful development of pharmaceutical products. The metastable phases of self-assembled nanostructures such as liposomes should be taken into consideration because they represent the thermal events can affect the functionality of advanced drug delivery nano systems. In conclusion, biophysics and thermodynamics are characterized as the building blocks for design and development of bio-inspired drug delivery systems.
Bio-Inspired Polarized Skylight-Based Navigation Sensors: A Review

PubMed Central

Karman, Salmah B.; Diah, S. Zaleha M.; Gebeshuber, Ille C.

2012-01-01

Animal senses cover a broad range of signal types and signal bandwidths and have inspired various sensors and bioinstrumentation devices for biological and medical applications. Insects, such as desert ants and honeybees, for example, utilize polarized skylight pattern-based information in their navigation activities. They reliably return to their nests and hives from places many kilometers away. The insect navigation system involves the dorsal rim area in their compound eyes and the corresponding polarization sensitive neurons in the brain. The dorsal rim area is equipped with photoreceptors, which have orthogonally arranged small hair-like structures termed microvilli. These are the specialized sensors for the detection of polarized skylight patterns (e-vector orientation). Various research groups have been working on the development of novel navigation systems inspired by polarized skylight-based navigation in animals. Their major contributions are critically reviewed. One focus of current research activities is on imitating the integration path mechanism in desert ants. The potential for simple, high performance miniaturized bioinstrumentation that can assist people in navigation will be explored. PMID:23202158
Bio-inspired polarized skylight-based navigation sensors: a review.

PubMed

Karman, Salmah B; Diah, S Zaleha M; Gebeshuber, Ille C

2012-10-24

Animal senses cover a broad range of signal types and signal bandwidths and have inspired various sensors and bioinstrumentation devices for biological and medical applications. Insects, such as desert ants and honeybees, for example, utilize polarized skylight pattern-based information in their navigation activities. They reliably return to their nests and hives from places many kilometers away. The insect navigation system involves the dorsal rim area in their compound eyes and the corresponding polarization sensitive neurons in the brain. The dorsal rim area is equipped with photoreceptors, which have orthogonally arranged small hair-like structures termed microvilli. These are the specialized sensors for the detection of polarized skylight patterns (e-vector orientation). Various research groups have been working on the development of novel navigation systems inspired by polarized skylight-based navigation in animals. Their major contributions are critically reviewed. One focus of current research activities is on imitating the integration path mechanism in desert ants. The potential for simple, high performance miniaturized bioinstrumentation that can assist people in navigation will be explored.
Structure-function relationship of skeletal muscle provides inspiration for design of new artificial muscle

NASA Astrophysics Data System (ADS)

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.
Biologically inspired collision avoidance system for unmanned vehicles

NASA Astrophysics Data System (ADS)

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.
How simple autonomous decisions evolve into robust behaviours? A review from neurorobotics, cognitive, self-organized and artificial immune systems fields.

PubMed

Fernandez-Leon, Jose A; Acosta, Gerardo G; Rozenfeld, Alejandro

2014-10-01

Researchers in diverse fields, such as in neuroscience, systems biology and autonomous robotics, have been intrigued by the origin and mechanisms for biological robustness. Darwinian evolution, in general, has suggested that adaptive mechanisms as a way of reaching robustness, could evolve by natural selection acting successively on numerous heritable variations. However, is this understanding enough for realizing how biological systems remain robust during their interactions with the surroundings? Here, we describe selected studies of bio-inspired systems that show behavioral robustness. From neurorobotics, cognitive, self-organizing and artificial immune system perspectives, our discussions focus mainly on how robust behaviors evolve or emerge in these systems, having the capacity of interacting with their surroundings. These descriptions are twofold. Initially, we introduce examples from autonomous robotics to illustrate how the process of designing robust control can be idealized in complex environments for autonomous navigation in terrain and underwater vehicles. We also include descriptions of bio-inspired self-organizing systems. Then, we introduce other studies that contextualize experimental evolution with simulated organisms and physical robots to exemplify how the process of natural selection can lead to the evolution of robustness by means of adaptive behaviors. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Progress and Opportunities in Soft Photonics and Biologically Inspired Optics.

PubMed

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

Yusufoglu, Yusuf

Nature offers many exciting ideas and inspiration for the development of new materials and processes. The toughness of spider silk, the strength and lightweight of bone, and the adhesion abilities of the gecko's feet are some of the many examples of highperformance natural materials, which have attracted the interest of scientist to duplicate their properties in man-made materials. Materials found in nature combine many inspiring properties such as miniaturization, sophistication, hierarchical organization, hybridization, and adaptability. In all biological systems, whether very basic or highly complex, nature provides a multiplicity of materials, architectures, systems and functions. Generally, the architectural configurations andmore » material characteristics are the important features that have been duplicated from nature for building synthetic structural composites.« less
Material science lesson from the biological photosystem.

PubMed

Kim, Younghye; Lee, Jun Ho; Ha, Heonjin; Im, Sang Won; Nam, Ki Tae

2016-01-01

Inspired by photosynthesis, artificial systems for a sustainable energy supply are being designed. Each sequential energy conversion process from light to biomass in natural photosynthesis is a valuable model for an energy collection, transport and conversion system. Notwithstanding the numerous lessons of nature that provide inspiration for new developments, the features of natural photosynthesis need to be reengineered to meet man's demands. This review describes recent strategies toward adapting key lessons from natural photosynthesis to artificial systems. We focus on the underlying material science in photosynthesis that combines photosystems as pivotal functional materials and a range of materials into an integrated system. Finally, a perspective on the future development of photosynthesis mimetic energy systems is proposed.
Development of new smart materials and spinning systems inspired by natural silks and their applications

NASA Astrophysics Data System (ADS)

Cheng, Jie; Lee, Sang-Hoon

2015-12-01

Silks produced by spiders and silkworms are charming natural biological materials with highly optimized hierarchical structures and outstanding physicomechanical properties. The superior performance of silks relies on the integration of a unique protein sequence, a distinctive spinning process, and complex hierarchical structures. Silks have been prepared to form a variety of morphologies and are widely used in diverse applications, for example, in the textile industry, as drug delivery vehicles, and as tissue engineering scaffolds. This review presents an overview of the organization of natural silks, in which chemical and physical functions are optimized, as well as a range of new materials inspired by the desire to mimic natural silk structure and synthesis.
On-chip phase-change photonic memory and computing

NASA Astrophysics Data System (ADS)

Cheng, Zengguang; Ríos, Carlos; Youngblood, Nathan; Wright, C. David; Pernice, Wolfram H. P.; Bhaskaran, Harish

2017-08-01

The use of photonics in computing is a hot topic of interest, driven by the need for ever-increasing speed along with reduced power consumption. In existing computing architectures, photonic data storage would dramatically improve the performance by reducing latencies associated with electrical memories. At the same time, the rise of `big data' and `deep learning' is driving the quest for non-von Neumann and brain-inspired computing paradigms. To succeed in both aspects, we have demonstrated non-volatile multi-level photonic memory avoiding the von Neumann bottleneck in the existing computing paradigm and a photonic synapse resembling the biological synapses for brain-inspired computing using phase-change materials (Ge2Sb2Te5).
Bio-inspired active materials

NASA Astrophysics Data System (ADS)

Fratzl, Peter

Biological tissues are naturally interactive and adaptive. In general, these features are due to the action of cells that provide sensing, actuation as well as tissue remodelling. There are also examples of materials synthesized by living organisms, such as plant seeds, which fulfil an active function without living cells working as mechanosensors and actuators. Thus the activity of these materials is based on physical principles alone, which provides inspiration for new concepts for artificial active materials. We will describe structural principles leading to movement in seed capsules triggered by ambient humidity and discuss the influence of internal architecture on the overall mechanical behaviour of materials, including actuation and motility. Several conceptual systems for actuating planar structures will be discussed.
When eyes drive hand: Influence of non-biological motion on visuo-motor coupling.

PubMed

Thoret, Etienne; Aramaki, Mitsuko; Bringoux, Lionel; Ystad, Sølvi; Kronland-Martinet, Richard

2016-01-26

Many studies stressed that the human movement execution but also the perception of motion are constrained by specific kinematics. For instance, it has been shown that the visuo-manual tracking of a spotlight was optimal when the spotlight motion complies with biological rules such as the so-called 1/3 power law, establishing the co-variation between the velocity and the trajectory curvature of the movement. The visual or kinesthetic perception of a geometry induced by motion has also been shown to be constrained by such biological rules. In the present study, we investigated whether the geometry induced by the visuo-motor coupling of biological movements was also constrained by the 1/3 power law under visual open loop control, i.e. without visual feedback of arm displacement. We showed that when someone was asked to synchronize a drawing movement with a visual spotlight following a circular shape, the geometry of the reproduced shape was fooled by visual kinematics that did not respect the 1/3 power law. In particular, elliptical shapes were reproduced when the circle is trailed with a kinematics corresponding to an ellipse. Moreover, the distortions observed here were larger than in the perceptual tasks stressing the role of motor attractors in such a visuo-motor coupling. Finally, by investigating the direct influence of visual kinematics on the motor reproduction, our result conciliates previous knowledge on sensorimotor coupling of biological motions with external stimuli and gives evidence to the amodal encoding of biological motion. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
c-Mantic: A Cytoscape plugin for Semantic Web

EPA Science Inventory

Semantic Web tools can streamline the process of storing, analyzing and sharing biological information. Visualization is important for communicating such complex biological relationships. Here we use the flexibility and speed of the Cytoscape platform to interactively visualize s...
A brain-controlled lower-limb exoskeleton for human gait training.

PubMed

Liu, Dong; Chen, Weihai; Pei, Zhongcai; Wang, Jianhua

2017-10-01

Brain-computer interfaces have been a novel approach to translate human intentions into movement commands in robotic systems. This paper describes an electroencephalogram-based brain-controlled lower-limb exoskeleton for gait training, as a proof of concept towards rehabilitation with human-in-the-loop. Instead of using conventional single electroencephalography correlates, e.g., evoked P300 or spontaneous motor imagery, we propose a novel framework integrated two asynchronous signal modalities, i.e., sensorimotor rhythms (SMRs) and movement-related cortical potentials (MRCPs). We executed experiments in a biologically inspired and customized lower-limb exoskeleton where subjects (N = 6) actively controlled the robot using their brain signals. Each subject performed three consecutive sessions composed of offline training, online visual feedback testing, and online robot-control recordings. Post hoc evaluations were conducted including mental workload assessment, feature analysis, and statistics test. An average robot-control accuracy of 80.16% ± 5.44% was obtained with the SMR-based method, while estimation using the MRCP-based method yielded an average performance of 68.62% ± 8.55%. The experimental results showed the feasibility of the proposed framework with all subjects successfully controlled the exoskeleton. The current paradigm could be further extended to paraplegic patients in clinical trials.

A brain-controlled lower-limb exoskeleton for human gait training

NASA Astrophysics Data System (ADS)

Liu, Dong; Chen, Weihai; Pei, Zhongcai; Wang, Jianhua

2017-10-01

Brain-computer interfaces have been a novel approach to translate human intentions into movement commands in robotic systems. This paper describes an electroencephalogram-based brain-controlled lower-limb exoskeleton for gait training, as a proof of concept towards rehabilitation with human-in-the-loop. Instead of using conventional single electroencephalography correlates, e.g., evoked P300 or spontaneous motor imagery, we propose a novel framework integrated two asynchronous signal modalities, i.e., sensorimotor rhythms (SMRs) and movement-related cortical potentials (MRCPs). We executed experiments in a biologically inspired and customized lower-limb exoskeleton where subjects (N = 6) actively controlled the robot using their brain signals. Each subject performed three consecutive sessions composed of offline training, online visual feedback testing, and online robot-control recordings. Post hoc evaluations were conducted including mental workload assessment, feature analysis, and statistics test. An average robot-control accuracy of 80.16% ± 5.44% was obtained with the SMR-based method, while estimation using the MRCP-based method yielded an average performance of 68.62% ± 8.55%. The experimental results showed the feasibility of the proposed framework with all subjects successfully controlled the exoskeleton. The current paradigm could be further extended to paraplegic patients in clinical trials.
1 kHz 2D Visual Motion Sensor Using 20 × 20 Silicon Retina Optical Sensor and DSP Microcontroller.

PubMed

Liu, Shih-Chii; Yang, MinHao; Steiner, Andreas; Moeckel, Rico; Delbruck, Tobi

2015-04-01

Optical flow sensors have been a long running theme in neuromorphic vision sensors which include circuits that implement the local background intensity adaptation mechanism seen in biological retinas. This paper reports a bio-inspired optical motion sensor aimed towards miniature robotic and aerial platforms. It combines a 20 × 20 continuous-time CMOS silicon retina vision sensor with a DSP microcontroller. The retina sensor has pixels that have local gain control and adapt to background lighting. The system allows the user to validate various motion algorithms without building dedicated custom solutions. Measurements are presented to show that the system can compute global 2D translational motion from complex natural scenes using one particular algorithm: the image interpolation algorithm (I2A). With this algorithm, the system can compute global translational motion vectors at a sample rate of 1 kHz, for speeds up to ±1000 pixels/s, using less than 5 k instruction cycles (12 instructions per pixel) per frame. At 1 kHz sample rate the DSP is 12% occupied with motion computation. The sensor is implemented as a 6 g PCB consuming 170 mW of power.
Polybenzoxazole Nanofiber-Reinforced Moisture-Responsive Soft Actuators.

PubMed

Chen, Meiling; Frueh, Johannes; Wang, Daolin; Lin, Xiankun; Xie, Hui; He, Qiang

2017-04-10

Hydromorphic biological systems, such as morning glory flowers, pinecones, and awns, have inspired researchers to design moisture-sensitive soft actuators capable of directly converting the change of moisture into motion or mechanical work. Here, we report a moisture-sensitive poly(p-phenylene benzobisoxazole) nanofiber (PBONF)-reinforced carbon nanotube/poly(vinyl alcohol) (CNT/PVA) bilayer soft actuator with fine performance on conductivity and mechanical properties. The embedded PBONFs not only assist CNTs to form a continuous, conductive film, but also enhance the mechanical performance of the actuators. The PBONF-reinforced CNT/PVA bilayer actuators can unsymmetrically adsorb and desorb water, resulting in a reversible deformation. More importantly, the actuators show a pronounced increase of conductivity due to the deformation induced by the moisture change, which allows the integration of a moisture-sensitive actuator and a humidity sensor. Upon changing the environmental humidity, the actuators can respond by the deformation for shielding and report the humidity change in a visual manner, which has been demonstrated by a tweezer and a curtain. Such nanofiber-reinforced bilayer actuators with the sensing capability should hold considerable promise for the applications such as soft robots, sensors, intelligent switches, integrated devices, and material storage.
Magnetic Actuation of Self-assembled Bacteria Inspired Nanoswimmers

NASA Astrophysics Data System (ADS)

Ali, Jamel; Cheang, U. Kei; Martindale, James D.; Jabbarzadeh, Mehdi; Fu, Henry C.; Kim, Min Jun

2017-11-01

Currently, there is growing interest in developing nanoscale swimmers for biological and biomedical tasks. Of particular interest is the development of soft stimuli-responsive nanorobots to probe cellular and sub-cellular environments. While there have been a few reports of nanoscale robotic swimmers, which have shown potential to be used for these tasks, they often lack multifuctionality. In particular, no man-made soft nanoscale material has been able to match the ability of natural bacterial flagella to undergo rapid and reversible morphological changes in response to multiple forms of environmental stimuli. Towards this end, we report self-assembled stimuli-responsive nanoscale robotic swimmers composed of single or multiple bacterial flagella and attached to magnetic nanoparticles. We visualize the movement of flagella using high resolution fluorescence microscopy while controlling these swimmers via a magnetic control system. Differences in in propulsion before and after the change in flagellar form are observed. Furthermore, we demonstrate the ability to induce flagellar bundling in multiflagellated nanoswimmers. This work was funded by the National Science Foundation (DMR 1712061 and CMMI 1737682 to M.J.K. and DMR 1650970 and CBET 1651031 to H.C.F.), and the Korea Evaluation Institute of Industrial Technology (MOTIE) (NO. 10052980) award to M.J.K.
Visual event-related potentials to biological motion stimuli in autism spectrum disorders

PubMed Central

Bletsch, Anke; Krick, Christoph; Siniatchkin, Michael; Jarczok, Tomasz A.; Freitag, Christine M.; Bender, Stephan

2014-01-01

Atypical visual processing of biological motion contributes to social impairments in autism spectrum disorders (ASD). However, the exact temporal sequence of deficits of cortical biological motion processing in ASD has not been studied to date. We used 64-channel electroencephalography to study event-related potentials associated with human motion perception in 17 children and adolescents with ASD and 21 typical controls. A spatio-temporal source analysis was performed to assess the brain structures involved in these processes. We expected altered activity already during early stimulus processing and reduced activity during subsequent biological motion specific processes in ASD. In response to both, random and biological motion, the P100 amplitude was decreased suggesting unspecific deficits in visual processing, and the occipito-temporal N200 showed atypical lateralization in ASD suggesting altered hemispheric specialization. A slow positive deflection after 400 ms, reflecting top-down processes, and human motion-specific dipole activation differed slightly between groups, with reduced and more diffuse activation in the ASD-group. The latter could be an indicator of a disrupted neuronal network for biological motion processing in ADS. Furthermore, early visual processing (P100) seems to be correlated to biological motion-specific activation. This emphasizes the relevance of early sensory processing for higher order processing deficits in ASD. PMID:23887808
New course in bioengineering and bioinspired design.

PubMed

Erickson, Jonathan C

2012-01-01

The past two years, a new interdisciplinary course has been offered at Washington and Lee University (Lexington, VA, USA), which seeks to surmount barriers that have traditionally existed between the physical and life sciences. The course explores the physiology leading to the physical mechanisms and engineering principles that endow the astonishing navigation abilities and sensory mechanisms of animal systems. The course also emphasizes how biological systems are inspiring novel engineering designs. Two (among many) examples are how the adhesion of the gecko foot inspired a new class of adhesives based on Van der Waals forces; and how the iridophore protein plates found in mimic octopus and squid act as tunable ¼ wave stacks, thus inspiring the engineering of optically tunable block copolymer gels for sensing temperature, pressure, or chemical gradients. A major component of this course is the integration of a 6-8 week long research project. To date, projects have included engineering: a soft-body robot whose motion mimics the inchworm; an electrical circuit to sense minute electric fields in aqueous environments based on the shark electrosensory system; and cyborg grasshoppers whose jump motion is controlled via an electronic-neural interface. Initial feedback has indicated that this course has served to increase student interaction and cross-pollination of ideas between the physical and life sciences. Student feedback also indicated a marked increase in desire and confidence to continue to pursue problems at the boundary of biology and engineeringbioengineering.
BATMAV: a 2-DOF bio-inspired flapping flight platform

NASA Astrophysics Data System (ADS)

Bunget, Gheorghe; Seelecke, Stefan

2010-04-01

Due to the availability of small sensors, Micro-Aerial Vehicles (MAVs) can be used for detection missions of biological, chemical and nuclear agents. Traditionally these devices used fixed or rotary wings, actuated with electric DC motortransmission, a system which brings the disadvantage of a heavier platform. The overall objective of the BATMAV project is to develop a biologically inspired bat-like MAV with flexible and foldable wings for flapping flight. This paper presents a flight platform that features bat-inspired wings which are able to actively fold their elbow joints. A previous analysis of the flight physics for small birds, bats and large insects, revealed that the mammalian flight anatomy represents a suitable flight platform that can be actuated efficiently using Shape Memory Alloy (SMA) artificial-muscles. A previous study of the flight styles in bats based on the data collected by Norberg [1] helped to identify the required joint angles as relevant degrees of freedom for wing actuation. Using the engineering theory of robotic manipulators, engineering kinematic models of wings with 2 and 3-DOFs were designed to mimic the wing trajectories of the natural flier Plecotus auritus. Solid models of the bat-like skeleton were designed based on the linear and angular dimensions resulted from the kinematic models. This structure of the flight platform was fabricated using rapid prototyping technologies and assembled to form a desktop prototype with 2-DOFs wings. Preliminary flapping test showed suitable trajectories for wrist and wingtip that mimic the flapping cycle of the natural flyer.
Propulsive performance of biologically inspired flapping foils at high Reynolds numbers.

PubMed

Techet, Alexandra H

2008-01-01

Propulsion and maneuvering underwater by flapping foil motion, optimized through years of evolution, is ubiquitous in nature, yet marine propulsors inspired by examples of highly maneuverable marine life or aquatic birds are not widely implemented in engineering. Performance data from flapping foils, moving in a rolling and pitching motion, are presented at high Reynolds numbers, Re=Uc/nu, or O(10(4)), where U is the relative inflow velocity, c is the chord length of the foil, and nu is the kinematic viscosity of the fluid, from water tunnel experiments using a foil actuator module designed after an aquatic penguin or turtle fin. The average thrust coefficients and efficiency measurements are recorded over a range of kinematic flapping amplitudes and frequencies. Results reveal a maximum thrust coefficient of 2.09, and for low values of angle of attack the thrust generally increases with Strouhal number, without much penalty to efficiency. Strouhal number is defined as St=2h(0)f/U, where f is the frequency of flapping, and 2h(0) is the peak-to-peak amplitude of flapping. The thrust and efficiency contour plots also present a useful performance trend where, at low angles of attack, high thrust and efficiency can be gained at sufficiently high Strouhal numbers. Understanding the motion of aquatic penguins and turtle wings and emulating these motions mechanically can yield insight into the hydrodynamics of how these animals swim and also improve performance of biologically inspired propulsive devices.
If it walks like a duck: nanosensor threat assessment

NASA Astrophysics Data System (ADS)

Chachis, George C.

2003-09-01

A convergence of technologies is making deployment of unattended ground nanosensors operationally feasible in terms of energy, communications for both arbitrated and self-organizing distributed, collective behaviors. A number of nano communications technologies are already making network-centric systems possible for MicroElectrical Mechanical (MEM) sensor devices today. Similar technologies may make NanoElectrical Mechanical (NEM) sensor devices operationally feasible a few years from now. Just as organizational behaviors of large numbers of nanodevices can derive strategies from social insects and other group-oriented animals, bio-inspired heuristics for threat assessment provide a conceptual approach for successful integration of nanosensors into unattended smart sensor networks. Biological models such as the organization of social insects or the dynamics of immune systems show promise as biologically-inspired paradigms for protecting nanosensor networks for security scene analysis and battlespace awareness. The paradox of nanosensors is that the smaller the device is the more useful it is but the smaller it is the more vulnerable it is to a variety of threats. In other words simpler means networked nanosensors are more likely to fall prey to a wide-range of attacks including jamming, spoofing, Janisserian recruitment, Pied-Piper distraction, as well as typical attacks computer network security. Thus, unattended sensor technologies call for network architectures that include security and countermeasures to provide reliable scene analysis or battlespace awareness information. Such network centric architectures may well draw upon a variety of bio-inspired approaches to safeguard, validate and make sense of large quantities of information.
PATIKAweb: a Web interface for analyzing biological pathways through advanced querying and visualization.

PubMed

Dogrusoz, U; Erson, E Z; Giral, E; Demir, E; Babur, O; Cetintas, A; Colak, R

2006-02-01

Patikaweb provides a Web interface for retrieving and analyzing biological pathways in the Patika database, which contains data integrated from various prominent public pathway databases. It features a user-friendly interface, dynamic visualization and automated layout, advanced graph-theoretic queries for extracting biologically important phenomena, local persistence capability and exporting facilities to various pathway exchange formats.
Visual Literacy Skills of Students in College-Level Biology: Learning Outcomes Following Digital or Hand-Drawing Activities

ERIC Educational Resources Information Center

Bell, Justine C.

2014-01-01

To test the claim that digital learning tools enhance the acquisition of visual literacy in this generation of biology students, a learning intervention was carried out with 33 students enrolled in an introductory college biology course. This study compared learning outcomes following two types of learning tools: a traditional drawing activity, or…
Identification of the connections in biologically inspired neural networks

NASA Technical Reports Server (NTRS)

Demuth, H.; Leung, K.; Beale, M.; Hicklin, J.

1990-01-01

We developed an identification method to find the strength of the connections between neurons from their behavior in small biologically-inspired artificial neural networks. That is, given the network external inputs and the temporal firing pattern of the neurons, we can calculate a solution for the strengths of the connections between neurons and the initial neuron activations if a solution exists. The method determines directly if there is a solution to a particular neural network problem. No training of the network is required. It should be noted that this is a first pass at the solution of a difficult problem. The neuron and network models chosen are related to biology but do not contain all of its complexities, some of which we hope to add to the model in future work. A variety of new results have been obtained. First, the method has been tailored to produce connection weight matrix solutions for networks with important features of biological neural (bioneural) networks. Second, a computationally efficient method of finding a robust central solution has been developed. This later method also enables us to find the most consistent solution in the presence of noisy data. Prospects of applying our method to identify bioneural network connections are exciting because such connections are almost impossible to measure in the laboratory. Knowledge of such connections would facilitate an understanding of bioneural networks and would allow the construction of the electronic counterparts of bioneural networks on very large scale integrated (VLSI) circuits.
Mimicking/extracting structure and functions of natural products: synthetic approaches that address unexplored needs in chemical biology.

PubMed

Hirai, Go

2015-04-01

Natural products are often attractive and challenging targets for synthetic chemists, and many have interesting biological activities. However, synthetic chemists need to be more than simply suppliers of compounds to biologists. Therefore, we have been seeking ways to actively apply organic synthetic methods to chemical biology studies of natural products and their activities. In this personal review, I would like to introduce our work on the development of new biologically active compounds inspired by, or extracted from, the structures of natural products, focusing on enhancement of functional activity and specificity and overcoming various drawbacks of the parent natural products. Copyright © 2014 The Chemical Society of Japan and Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Bioinspired engineering of exploration systems for NASA and DoD

NASA Technical Reports Server (NTRS)

Thakoor, Sarita; Chahl, Javaan; Srinivasan, M. V.; Young, L.; Werblin, Frank; Hine, Butler; Zornetzer, Steven

2002-01-01

A new approach called bioinspired engineering of exploration systems (BEES) and its value for solving pressing NASA and DoD needs are described. Insects (for example honeybees and dragonflies) cope remarkably well with their world, despite possessing a brain containing less than 0.01% as many neurons as the human brain. Although most insects have immobile eyes with fixed focus optics and lack stereo vision, they use a number of ingenious, computationally simple strategies for perceiving their world in three dimensions and navigating successfully within it. We are distilling selected insect-inspired strategies to obtain novel solutions for navigation, hazard avoidance, altitude hold, stable flight, terrain following, and gentle deployment of payload. Such functionality provides potential solutions for future autonomous robotic space and planetary explorers. A BEES approach to developing lightweight low-power autonomous flight systems should be useful for flight control of such biomorphic flyers for both NASA and DoD needs. Recent biological studies of mammalian retinas confirm that representations of multiple features of the visual world are systematically parsed and processed in parallel. Features are mapped to a stack of cellular strata within the retina. Each of these representations can be efficiently modeled in semiconductor cellular nonlinear network (CNN) chips. We describe recent breakthroughs in exploring the feasibility of the unique blending of insect strategies of navigation with mammalian visual search, pattern recognition, and image understanding into hybrid biomorphic flyers for future planetary and terrestrial applications. We describe a few future mission scenarios for Mars exploration, uniquely enabled by these newly developed biomorphic flyers.
OpinionFlow: Visual Analysis of Opinion Diffusion on Social Media.

PubMed

Wu, Yingcai; Liu, Shixia; Yan, Kai; Liu, Mengchen; Wu, Fangzhao

2014-12-01

It is important for many different applications such as government and business intelligence to analyze and explore the diffusion of public opinions on social media. However, the rapid propagation and great diversity of public opinions on social media pose great challenges to effective analysis of opinion diffusion. In this paper, we introduce a visual analysis system called OpinionFlow to empower analysts to detect opinion propagation patterns and glean insights. Inspired by the information diffusion model and the theory of selective exposure, we develop an opinion diffusion model to approximate opinion propagation among Twitter users. Accordingly, we design an opinion flow visualization that combines a Sankey graph with a tailored density map in one view to visually convey diffusion of opinions among many users. A stacked tree is used to allow analysts to select topics of interest at different levels. The stacked tree is synchronized with the opinion flow visualization to help users examine and compare diffusion patterns across topics. Experiments and case studies on Twitter data demonstrate the effectiveness and usability of OpinionFlow.
Seminar in Flow Visualization at Lafayette College: Variations on the Hertzberg Effect

NASA Astrophysics Data System (ADS)

Rossmann, Jenn Stroud

2013-11-01

Flow visualization reveals an invisible world of fluid dynamics, blending scientific investigation and artistic exploration. The resulting images have inspired, and in some cases themselves become appreciated as, art. At Lafayette College, a sophomore-level seminar in The Art and Science of Flow Visualization exposes students to these techniques and the science of fluid mechanics, and to the photographic methods needed to create effective images that are successful both scientifically and artistically. Unlike other courses in flow visualization, this course assumes no a priori familiarity with fluid flow or with photography. The fundamentals of both are taught and practiced in a studio setting. Students are engaged in an interdisciplinary discourse about fluids and physics, photography, scientific ethics, and historical societal responses to science and art. Relevant texts from several disciplines are read, discussed, and responded to in student writing. This seminar approach makes flow visualization and fluid dynamics a natural part of a liberal education. The development, implementation, and assessment of this team-taught course at Lafayette College will be discussed. Support provided by National Science Foundation.
Associated impairment of the categories of conspecifics and biological entities: cognitive and neuroanatomical aspects of a new case.

PubMed

Capitani, Erminio; Chieppa, Francesca; Laiacona, Marcella

2010-05-01

Case A.C.A. presented an associated impairment of visual recognition and semantic knowledge for celebrities and biological objects. This case was relevant for (a) the neuroanatomical correlations, and (b) the relationship between visual recognition and semantics within the biological domain and the conspecifics domain. A.C.A. was not affected by anterior temporal damage. Her bilateral vascular lesions were localized on the medial and inferior temporal gyrus on the right and on the intermediate fusiform gyrus on the left, without concomitant lesions of the parahippocampal gyrus or posterior fusiform. Data analysis was based on a novel methodology developed to estimate the rate of stored items in the visual structural description system (SDS) or in the face recognition unit. For each biological object, no particular correlation was found between the visual information accessed through the semantic system and that tapped by the picture reality judgement. Findings are discussed with reference to whether a putative resource commonality is likely between biological objects and conspecifics, and whether or not either category may depend on an exclusive neural substrate.
Parallel and serial grouping of image elements in visual perception.

PubMed

Houtkamp, Roos; Roelfsema, Pieter R

2010-12-01

The visual system groups image elements that belong to an object and segregates them from other objects and the background. Important cues for this grouping process are the Gestalt criteria, and most theories propose that these are applied in parallel across the visual scene. Here, we find that Gestalt grouping can indeed occur in parallel in some situations, but we demonstrate that there are also situations where Gestalt grouping becomes serial. We observe substantial time delays when image elements have to be grouped indirectly through a chain of local groupings. We call this chaining process incremental grouping and demonstrate that it can occur for only a single object at a time. We suggest that incremental grouping requires the gradual spread of object-based attention so that eventually all the object's parts become grouped explicitly by an attentional labeling process. Our findings inspire a new incremental grouping theory that relates the parallel, local grouping process to feedforward processing and the serial, incremental grouping process to recurrent processing in the visual cortex.
Asymmetric latent semantic indexing for gene expression experiments visualization.

PubMed

González, Javier; Muñoz, Alberto; Martos, Gabriel

2016-08-01

We propose a new method to visualize gene expression experiments inspired by the latent semantic indexing technique originally proposed in the textual analysis context. By using the correspondence word-gene document-experiment, we define an asymmetric similarity measure of association for genes that accounts for potential hierarchies in the data, the key to obtain meaningful gene mappings. We use the polar decomposition to obtain the sources of asymmetry of the similarity matrix, which are later combined with previous knowledge. Genetic classes of genes are identified by means of a mixture model applied in the genes latent space. We describe the steps of the procedure and we show its utility in the Human Cancer dataset.
Real-Time Cognitive Computing Architecture for Data Fusion in a Dynamic Environment

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Duong, Vu A.

2012-01-01

A novel cognitive computing architecture is conceptualized for processing multiple channels of multi-modal sensory data streams simultaneously, and fusing the information in real time to generate intelligent reaction sequences. This unique architecture is capable of assimilating parallel data streams that could be analog, digital, synchronous/asynchronous, and could be programmed to act as a knowledge synthesizer and/or an "intelligent perception" processor. In this architecture, the bio-inspired models of visual pathway and olfactory receptor processing are combined as processing components, to achieve the composite function of "searching for a source of food while avoiding the predator." The architecture is particularly suited for scene analysis from visual data and odorant.

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