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.

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

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.

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…

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.

A Spiking Neural Simulator Integrating Event-Driven and Time-Driven Computation Schemes Using Parallel CPU-GPU Co-Processing: A Case Study.

PubMed

Naveros, Francisco; Luque, Niceto R; Garrido, Jesús A; Carrillo, Richard R; Anguita, Mancia; Ros, Eduardo

2015-07-01

Time-driven simulation methods in traditional CPU architectures perform well and precisely when simulating small-scale spiking neural networks. Nevertheless, they still have drawbacks when simulating large-scale systems. Conversely, event-driven simulation methods in CPUs and time-driven simulation methods in graphic processing units (GPUs) can outperform CPU time-driven methods under certain conditions. With this performance improvement in mind, we have developed an event-and-time-driven spiking neural network simulator suitable for a hybrid CPU-GPU platform. Our neural simulator is able to efficiently simulate bio-inspired spiking neural networks consisting of different neural models, which can be distributed heterogeneously in both small layers and large layers or subsystems. For the sake of efficiency, the low-activity parts of the neural network can be simulated in CPU using event-driven methods while the high-activity subsystems can be simulated in either CPU (a few neurons) or GPU (thousands or millions of neurons) using time-driven methods. In this brief, we have undertaken a comparative study of these different simulation methods. For benchmarking the different simulation methods and platforms, we have used a cerebellar-inspired neural-network model consisting of a very dense granular layer and a Purkinje layer with a smaller number of cells (according to biological ratios). Thus, this cerebellar-like network includes a dense diverging neural layer (increasing the dimensionality of its internal representation and sparse coding) and a converging neural layer (integration) similar to many other biologically inspired and also artificial neural networks.

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.

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.

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.

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

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 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.

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.

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.

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.

Bioinspired principles for large-scale networked sensor systems: an overview.

PubMed

Jacobsen, Rune Hylsberg; Zhang, Qi; Toftegaard, Thomas Skjødeberg

2011-01-01

Biology has often been used as a source of inspiration in computer science and engineering. Bioinspired principles have found their way into network node design and research due to the appealing analogies between biological systems and large networks of small sensors. This paper provides an overview of bioinspired principles and methods such as swarm intelligence, natural time synchronization, artificial immune system and intercellular information exchange applicable for sensor network design. Bioinspired principles and methods are discussed in the context of routing, clustering, time synchronization, optimal node deployment, localization and security and privacy.

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.

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.

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 immune-inspired semi-supervised algorithm for breast cancer diagnosis.

PubMed

Peng, Lingxi; Chen, Wenbin; Zhou, Wubai; Li, Fufang; Yang, Jin; Zhang, Jiandong

2016-10-01

Breast cancer is the most frequently and world widely diagnosed life-threatening cancer, which is the leading cause of cancer death among women. Early accurate diagnosis can be a big plus in treating breast cancer. Researchers have approached this problem using various data mining and machine learning techniques such as support vector machine, artificial neural network, etc. The computer immunology is also an intelligent method inspired by biological immune system, which has been successfully applied in pattern recognition, combination optimization, machine learning, etc. However, most of these diagnosis methods belong to a supervised diagnosis method. It is very expensive to obtain labeled data in biology and medicine. In this paper, we seamlessly integrate the state-of-the-art research on life science with artificial intelligence, and propose a semi-supervised learning algorithm to reduce the need for labeled data. We use two well-known benchmark breast cancer datasets in our study, which are acquired from the UCI machine learning repository. Extensive experiments are conducted and evaluated on those two datasets. Our experimental results demonstrate the effectiveness and efficiency of our proposed algorithm, which proves that our algorithm is a promising automatic diagnosis method for breast cancer. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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.

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.

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.

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.

Bioinspired Functional Materials

DOE PAGES

Zheng, Yongmei; Wang, Jingxia; Hou, Yongping; ...

2014-11-25

This special issue is focused on the nanoscale or micro-/nanoscale structures similar to the biological features in multilevels or hierarchy and so on. Research by mimicking biological systems has shown more impact on many applications due to the well-designed micro-/nanostructures inspired from the biological surfaces or interfaces; therefore, the materials may achieve the fascinating functionality. In conclusion, the bioinspired functional materials may be fabricated by developing novel technology or methods such as synthesis, self-assembly, and soft lithography at micro- or nanolevel or multilevels and, in addition, the multidisciplinary procedures of physical or chemical methods and nanotechnology to mimic the biologicalmore » multiscale micro-/nanostructures onto one-/two-dimensional surface materials.« less

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.

Method of improving system performance and survivability through changing function

NASA Technical Reports Server (NTRS)

Hinchey, Michael G. (Inventor); Vassev, Emil I. (Inventor)

2012-01-01

A biologically-inspired system and method is provided for self-adapting behavior of swarm-based exploration missions, whereby individual components, for example, spacecraft, in the system can sacrifice themselves for the greater good of the entire system. The swarm-based system can exhibit emergent self-adapting behavior. Each component can be configured to exhibit self-sacrifice behavior based on Autonomic System Specification Language (ASSL).

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.

Bioinspired Principles for Large-Scale Networked Sensor Systems: An Overview

PubMed Central

Jacobsen, Rune Hylsberg; Zhang, Qi; Toftegaard, Thomas Skjødeberg

2011-01-01

Biology has often been used as a source of inspiration in computer science and engineering. Bioinspired principles have found their way into network node design and research due to the appealing analogies between biological systems and large networks of small sensors. This paper provides an overview of bioinspired principles and methods such as swarm intelligence, natural time synchronization, artificial immune system and intercellular information exchange applicable for sensor network design. Bioinspired principles and methods are discussed in the context of routing, clustering, time synchronization, optimal node deployment, localization and security and privacy. PMID:22163841

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.

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.

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

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.

Unity and disunity in evolutionary sciences: process-based analogies open common research avenues for biology and linguistics.

PubMed

List, Johann-Mattis; Pathmanathan, Jananan Sylvestre; Lopez, Philippe; Bapteste, Eric

2016-08-20

For a long time biologists and linguists have been noticing surprising similarities between the evolution of life forms and languages. Most of the proposed analogies have been rejected. Some, however, have persisted, and some even turned out to be fruitful, inspiring the transfer of methods and models between biology and linguistics up to today. Most proposed analogies were based on a comparison of the research objects rather than the processes that shaped their evolution. Focusing on process-based analogies, however, has the advantage of minimizing the risk of overstating similarities, while at the same time reflecting the common strategy to use processes to explain the evolution of complexity in both fields. We compared important evolutionary processes in biology and linguistics and identified processes specific to only one of the two disciplines as well as processes which seem to be analogous, potentially reflecting core evolutionary processes. These new process-based analogies support novel methodological transfer, expanding the application range of biological methods to the field of historical linguistics. We illustrate this by showing (i) how methods dealing with incomplete lineage sorting offer an introgression-free framework to analyze highly mosaic word distributions across languages; (ii) how sequence similarity networks can be used to identify composite and borrowed words across different languages; (iii) how research on partial homology can inspire new methods and models in both fields; and (iv) how constructive neutral evolution provides an original framework for analyzing convergent evolution in languages resulting from common descent (Sapir's drift). Apart from new analogies between evolutionary processes, we also identified processes which are specific to either biology or linguistics. This shows that general evolution cannot be studied from within one discipline alone. In order to get a full picture of evolution, biologists and linguists need to complement their studies, trying to identify cross-disciplinary and discipline-specific evolutionary processes. The fact that we found many process-based analogies favoring transfer from biology to linguistics further shows that certain biological methods and models have a broader scope than previously recognized. This opens fruitful paths for collaboration between the two disciplines. This article was reviewed by W. Ford Doolittle and Eugene V. Koonin.

Algorithms in nature: the convergence of systems biology and computational thinking

PubMed Central

Navlakha, Saket; Bar-Joseph, Ziv

2011-01-01

Computer science and biology have enjoyed a long and fruitful relationship for decades. Biologists rely on computational methods to analyze and integrate large data sets, while several computational methods were inspired by the high-level design principles of biological systems. Recently, these two directions have been converging. In this review, we argue that thinking computationally about biological processes may lead to more accurate models, which in turn can be used to improve the design of algorithms. We discuss the similar mechanisms and requirements shared by computational and biological processes and then present several recent studies that apply this joint analysis strategy to problems related to coordination, network analysis, and tracking and vision. We also discuss additional biological processes that can be studied in a similar manner and link them to potential computational problems. With the rapid accumulation of data detailing the inner workings of biological systems, we expect this direction of coupling biological and computational studies to greatly expand in the future. PMID:22068329

Bioinspired engineering of exploration systems: a horizon sensor/attitude reference system based on the dragonfly Ocelli for Mars exploration applications

NASA Technical Reports Server (NTRS)

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

2002-01-01

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 oganisms.

Handwritten-word spotting using biologically inspired features.

PubMed

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

2008-11-01

For quick access to new handwritten collections, current handwriting recognition methods are too cumbersome. They cannot deal with the lack of labeled data and would require extensive laboratory training for each individual script, style, language and collection. We propose a biologically inspired whole-word recognition method which is used to incrementally elicit word labels in a live, web-based annotation system, named Monk. Since human labor should be minimized given the massive amount of image data, it becomes important to rely on robust perceptual mechanisms in the machine. Recent computational models of the neuro-physiology of vision are applied to isolated word classification. A primate cortex-like mechanism allows to classify text-images that have a low frequency of occurrence. Typically these images are the most difficult to retrieve and often contain named entities and are regarded as the most important to people. Usually standard pattern-recognition technology cannot deal with these text-images if there are not enough labeled instances. The results of this retrieval system are compared to normalized word-image matching and appear to be very promising.

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

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.

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.

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.

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.

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.

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.

CPG-inspired workspace trajectory generation and adaptive locomotion control for quadruped robots.

PubMed

Liu, Chengju; Chen, Qijun; Wang, Danwei

2011-06-01

This paper deals with the locomotion control of quadruped robots inspired by the biological concept of central pattern generator (CPG). A control architecture is proposed with a 3-D workspace trajectory generator and a motion engine. The workspace trajectory generator generates adaptive workspace trajectories based on CPGs, and the motion engine realizes joint motion imputes. The proposed architecture is able to generate adaptive workspace trajectories online by tuning the parameters of the CPG network to adapt to various terrains. With feedback information, a quadruped robot can walk through various terrains with adaptive joint control signals. A quadruped platform AIBO is used to validate the proposed locomotion control system. The experimental results confirm the effectiveness of the proposed control architecture. A comparison by experiments shows the superiority of the proposed method against the traditional CPG-joint-space control method.

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.

On extracting design principles from biology: I. Method-General answers to high-level design questions for bioinspired robots.

PubMed

Haberland, M; Kim, S

2015-02-02

When millions of years of evolution suggest a particular design solution, we may be tempted to abandon traditional design methods and copy the biological example. However, biological solutions do not often translate directly into the engineering domain, and even when they do, copying eliminates the opportunity to improve. A better approach is to extract design principles relevant to the task of interest, incorporate them in engineering designs, and vet these candidates against others. This paper presents the first general framework for determining whether biologically inspired relationships between design input variables and output objectives and constraints are applicable to a variety of engineering systems. Using optimization and statistics to generalize the results beyond a particular system, the framework overcomes shortcomings observed of ad hoc methods, particularly those used in the challenging study of legged locomotion. The utility of the framework is demonstrated in a case study of the relative running efficiency of rotary-kneed and telescoping-legged robots.

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.

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.

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.

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

Nitrate removal from drinking water with a focus on biological methods: a review.

PubMed

Rezvani, Fariba; Sarrafzadeh, Mohammad-Hossein; Ebrahimi, Sirous; Oh, Hee-Mock

2017-05-31

This article summarizes several developed and industrial technologies for nitrate removal from drinking water, including physicochemical and biological techniques, with a focus on autotrophic nitrate removal. Approaches are primarily classified into separation-based and elimination-based methods according to the fate of the nitrate in water treatment. Biological denitrification as a cost-effective and promising method of biological nitrate elimination is reviewed in terms of its removal process, applicability, efficiency, and associated disadvantages. The various pathways during biological nitrate removal, including assimilatory and dissimilatory nitrate reduction, are also explained. A comparative study was carried out to provide a better understanding of the advantages and disadvantages of autotrophic and heterotrophic denitrification. Sulfur-based and hydrogen-based denitrifications, which are the most common autotrophic processes of nitrate removal, are reviewed with the aim of presenting the salient features of hydrogenotrophic denitrification along with some drawbacks of the technology and research areas in which it could be used but currently is not. The application of algae-based water treatment is also introduced as a nature-inspired approach that may broaden future horizons of nitrate removal technology.

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.

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.

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.

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…

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.

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.

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.

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.

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.

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.

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.

Bio-Inspired Extreme Wetting Surfaces for Biomedical Applications

PubMed Central

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

2016-01-01

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

From biological and social network metaphors to coupled bio-social wireless networks

PubMed Central

Barrett, Christopher L.; Eubank, Stephen; Anil Kumar, V.S.; Marathe, Madhav V.

2010-01-01

Biological and social analogies have been long applied to complex systems. Inspiration has been drawn from biological solutions to solve problems in engineering products and systems, ranging from Velcro to camouflage to robotics to adaptive and learning computing methods. In this paper, we present an overview of recent advances in understanding biological systems as networks and use this understanding to design and analyse wireless communication networks. We expand on two applications, namely cognitive sensing and control and wireless epidemiology. We discuss how our work in these two applications is motivated by biological metaphors. We believe that recent advances in computing and communications coupled with advances in health and social sciences raise the possibility of studying coupled bio-social communication networks. We argue that we can better utilise the advances in our understanding of one class of networks to better our understanding of the other. PMID:21643462

Physarum solver: A biologically inspired method of road-network navigation

NASA Astrophysics Data System (ADS)

Tero, Atsushi; Kobayashi, Ryo; Nakagaki, Toshiyuki

2006-04-01

We have proposed a mathematical model for the adaptive dynamics of the transport network in an amoeba-like organism, the true slime mold Physarum polycephalum. The model is based on physiological observations of this species, but can also be used for path-finding in the complicated networks of mazes and road maps. In this paper, we describe the physiological basis and the formulation of the model, as well as the results of simulations of some complicated networks. The path-finding method used by Physarum is a good example of cellular computation.

Power Provision Based on Self-Sacrificing Craft

NASA Technical Reports Server (NTRS)

Hinchey, Michael G. (Inventor); Sterrit, Roy (Inventor); Vassev, Emil I. (Inventor); Hinchey, Bridget (Inventor)

2015-01-01

A biologically-inspired system and method is provided for self-adapting behavior of swarm-based exploration missions, whereby individual components, for example, spacecraft, in the system can sacrifice themselves for the greater good of the entire system. The self-sacrifice can involve donating resources or assets, such as power provisions, to a different component of an autonomous system. A receiving component of the system can benefit from receiving the donated resource or power provision.

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.

Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science.

PubMed

Mocanu, Decebal Constantin; Mocanu, Elena; Stone, Peter; Nguyen, Phuong H; Gibescu, Madeleine; Liotta, Antonio

2018-06-19

Through the success of deep learning in various domains, artificial neural networks are currently among the most used artificial intelligence methods. Taking inspiration from the network properties of biological neural networks (e.g. sparsity, scale-freeness), we argue that (contrary to general practice) artificial neural networks, too, should not have fully-connected layers. Here we propose sparse evolutionary training of artificial neural networks, an algorithm which evolves an initial sparse topology (Erdős-Rényi random graph) of two consecutive layers of neurons into a scale-free topology, during learning. Our method replaces artificial neural networks fully-connected layers with sparse ones before training, reducing quadratically the number of parameters, with no decrease in accuracy. We demonstrate our claims on restricted Boltzmann machines, multi-layer perceptrons, and convolutional neural networks for unsupervised and supervised learning on 15 datasets. Our approach has the potential to enable artificial neural networks to scale up beyond what is currently possible.

Optimization of a tensegrity wing for biomimetic applications

NASA Astrophysics Data System (ADS)

Moored, Keith W., III; Taylor, Stuart A.; Bart-Smith, Hilary

2006-03-01

Current attempts to build fast, efficient, and maneuverable underwater vehicles have looked to nature for inspiration. However, they have all been based on traditional propulsive techniques, i.e. rotary motors. In the current study a promising and potentially revolutionary approach is taken that overcomes the limitations of these traditional methods-morphing structure concepts with integrated actuation and sensing. Inspiration for this work comes from the manta ray (Manta birostris) and other batoid fish. These creatures are highly maneuverable but are also able to cruise at high speeds over long distances. In this paper, the structural foundation for the biomimetic morphing wing is a tensegrity structure. A preliminary procedure is presented for developing morphing tensegrity structures that include actuating elements. A shape optimization method is used that determines actuator placement and actuation amount necessary to achieve the measured biological displacement field of a ray. Lastly, an experimental manta ray wing is presented that measures the static and dynamic pressure field acting on the ray's wings during a normal flapping cycle.

Bio-inspired voltage-dependent calcium channel blockers.

PubMed

Yang, Tingting; He, Lin-Ling; Chen, Ming; Fang, Kun; Colecraft, Henry M

2013-01-01

Ca(2+) influx via voltage-dependent CaV1/CaV2 channels couples electrical signals to biological responses in excitable cells. CaV1/CaV2 channel blockers have broad biotechnological and therapeutic applications. Here we report a general method for developing novel genetically encoded calcium channel blockers inspired by Rem, a small G-protein that constitutively inhibits CaV1/CaV2 channels. We show that diverse cytosolic proteins (CaVβ, 14-3-3, calmodulin and CaMKII) that bind pore-forming α1-subunits can be converted into calcium channel blockers with tunable selectivity, kinetics and potency, simply by anchoring them to the plasma membrane. We term this method 'channel inactivation induced by membrane-tethering of an associated protein' (ChIMP). ChIMP is potentially extendable to small-molecule drug discovery, as engineering FK506-binding protein into intracellular sites within CaV1.2-α1C permits heterodimerization-initiated channel inhibition with rapamycin. The results reveal a universal method for developing novel calcium channel blockers that may be extended to develop probes for a broad cohort of unrelated ion channels.

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.

Poly(lactic-co-glycolic acid) devices: Production and applications for sustained protein delivery.

PubMed

Lee, Parker W; Pokorski, Jonathan K

2018-03-13

Injectable or implantable poly(lactic-co-glycolic acid) (PLGA) devices for the sustained delivery of proteins have been widely studied and utilized to overcome the necessity of repeated administrations for therapeutic proteins due to poor pharmacokinetic profiles of macromolecular therapies. These devices can come in the form of microparticles, implants, or patches depending on the disease state and route of administration. Furthermore, the release rate can be tuned from weeks to months by controlling the polymer composition, geometry of the device, or introducing additives during device fabrication. Slow-release devices have become a very powerful tool for modern medicine. Production of these devices has initially focused on emulsion-based methods, relying on phase separation to encapsulate proteins within polymeric microparticles. Process parameters and the effect of additives have been thoroughly researched to ensure protein stability during device manufacturing and to control the release profile. Continuous fluidic production methods have also been utilized to create protein-laden PLGA devices through spray drying and electrospray production. Thermal processing of PLGA with solid proteins is an emerging production method that allows for continuous, high-throughput manufacturing of PLGA/protein devices. Overall, polymeric materials for protein delivery remain an emerging field of research for the creation of single administration treatments for a wide variety of disease. This review describes, in detail, methods to make PLGA devices, comparing traditional emulsion-based methods to emerging methods to fabricate protein-laden devices. This article is categorized under: Biology-Inspired Nanomaterials > Protein and Virus-Based Structures Implantable Materials and Surgical Technologies > Nanomaterials and Implants Biology-Inspired Nanomaterials > Peptide-Based Structures. © 2018 Wiley Periodicals, Inc.

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.

Using neuromorphic optical sensors for spacecraft absolute and relative navigation

NASA Astrophysics Data System (ADS)

Shake, Christopher M.

We develop a novel attitude determination system (ADS) for use on nano spacecraft using neuromorphic optical sensors. The ADS intends to support nano-satellite operations by providing low-cost, low-mass, low-volume, low-power, and redundant attitude determination capabilities with quick and straightforward onboard programmability for real time spacecraft operations. The ADS is experimentally validated with commercial-off-the-shelf optical devices that perform sensing and image processing on the same circuit board and are biologically inspired by insects' vision systems, which measure optical flow while navigating in the environment. The firmware on the devices is modified to both perform the additional biologically inspired task of tracking objects and communicate with a PC/104 form-factor embedded computer running Real Time Application Interface Linux used on a spacecraft simulator. Algorithms are developed for operations using optical flow, point tracking, and hybrid modes with the sensors, and the performance of the system in all three modes is assessed using a spacecraft simulator in the Advanced Autonomous Multiple Spacecraft (ADAMUS) laboratory at Rensselaer. An existing relative state determination method is identified to be combined with the novel ADS to create a self-contained navigation system for nano spacecraft. The performance of the method is assessed in simulation and found not to match the results from its authors using only conditions and equations already published. An improved target inertia tensor method is proposed as an update to the existing relative state method, but found not to perform as expected, but is presented for others to build upon.

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.

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…

Evolutionary game theory for physical and biological scientists. I. Training and validating population dynamics equations.

PubMed

Liao, David; Tlsty, Thea D

2014-08-06

Failure to understand evolutionary dynamics has been hypothesized as limiting our ability to control biological systems. An increasing awareness of similarities between macroscopic ecosystems and cellular tissues has inspired optimism that game theory will provide insights into the progression and control of cancer. To realize this potential, the ability to compare game theoretic models and experimental measurements of population dynamics should be broadly disseminated. In this tutorial, we present an analysis method that can be used to train parameters in game theoretic dynamics equations, used to validate the resulting equations, and used to make predictions to challenge these equations and to design treatment strategies. The data analysis techniques in this tutorial are adapted from the analysis of reaction kinetics using the method of initial rates taught in undergraduate general chemistry courses. Reliance on computer programming is avoided to encourage the adoption of these methods as routine bench activities.

Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data.

PubMed

Ching, Travers; Zhu, Xun; Garmire, Lana X

2018-04-01

Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN framework called Cox-nnet to predict patient prognosis from high throughput transcriptomics data. In 10 TCGA RNA-Seq data sets, Cox-nnet achieves the same or better predictive accuracy compared to other methods, including Cox-proportional hazards regression (with LASSO, ridge, and mimimax concave penalty), Random Forests Survival and CoxBoost. Cox-nnet also reveals richer biological information, at both the pathway and gene levels. The outputs from the hidden layer node provide an alternative approach for survival-sensitive dimension reduction. In summary, we have developed a new method for accurate and efficient prognosis prediction on high throughput data, with functional biological insights. The source code is freely available at https://github.com/lanagarmire/cox-nnet.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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.

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.

Biology-inspired Architecture for Situation Management

NASA Technical Reports Server (NTRS)

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

2006-01-01

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

Bio-inspired heterogeneous composites for broadband vibration mitigation.

PubMed

Chen, Yanyu; Wang, Lifeng

2015-12-08

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

Bio-inspired heterogeneous composites for broadband vibration mitigation

NASA Astrophysics Data System (ADS)

Chen, Yanyu; Wang, Lifeng

2015-12-01

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

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.

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.

A laser-engraved glass duplicating the structure, mechanics and performance of natural nacre.

PubMed

Valashani, Seyed Mohammad Mirkhalaf; Barthelat, Francois

2015-03-30

Highly mineralized biological materials such as nacre (mother of pearl), tooth enamel or conch shell boast unique and attractive combinations of stiffness, strength and toughness. The structures of these biological materials and their associated mechanisms are now inspiring new types of advanced structural materials. However, despite significant efforts, no bottom up fabrication method could so far match biological materials in terms of microstructural organization and mechanical performance. Here we present a new 'top down' strategy to tackling this fabrication problem, which consists in carving weak interfaces within a brittle material using a laser engraving technique. We demonstrate the method by fabricating and testing borosilicate glasses containing nacre-like microstructures infiltrated with polyurethane. When deformed, these materials properly duplicate the mechanisms of natural nacre: combination of controlled sliding of the tablets, accompanied with geometric hardening, strain hardening and strain rate hardening. The nacre-like glass is composed of 93 volume % (vol%) glass, yet 700 times tougher and breaks at strains as high as 20%.

Bioart.

PubMed

Yetisen, Ali K; Davis, Joe; Coskun, Ahmet F; Church, George M; Yun, Seok Hyun

2015-12-01

Bioart is a creative practice that adapts scientific methods and draws inspiration from the philosophical, societal, and environmental implications of recombinant genetics, molecular biology, and biotechnology. Some bioartists foster inter- disciplinary relationships that blur distinctions between art and science. Others emphasize critical responses to emerging trends in the life sciences. Since bioart can be combined with realistic views of scientific developments, it may help inform the public about science. Artistic responses to biotechnology also integrate cultural commentary resembling political activism. Art is not only about ‘responses’, however. Bioart can also initiate new science and engineer- ing concepts, foster openness to collaboration and increasing scientific literacy, and help to form the basis of artists’ future relationships with the communities of biology and the life sciences.

Climbing with adhesion: from bioinspiration to biounderstanding

PubMed Central

Cutkosky, Mark R.

2015-01-01

Bioinspiration is an increasingly popular design paradigm, especially as robots venture out of the laboratory and into the world. Animals are adept at coping with the variability that the world imposes. With advances in scientific tools for understanding biological structures in detail, we are increasingly able to identify design features that account for animals' robust performance. In parallel, advances in fabrication methods and materials are allowing us to engineer artificial structures with similar properties. The resulting robots become useful platforms for testing hypotheses about which principles are most important. Taking gecko-inspired climbing as an example, we show that the process of extracting principles from animals and adapting them to robots provides insights for both robotics and biology. PMID:26464786

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…

Bioinspired Design: Magnetic Freeze Casting

NASA Astrophysics Data System (ADS)

Porter, Michael Martin

Nature is the ultimate experimental scientist, having billions of years of evolution to design, test, and adapt a variety of multifunctional systems for a plethora of diverse applications. Next-generation materials that draw inspiration from the structure-property-function relationships of natural biological materials have led to many high-performance structural materials with hybrid, hierarchical architectures that fit form to function. In this dissertation, a novel materials processing method, magnetic freeze casting, is introduced to develop porous scaffolds and hybrid composites with micro-architectures that emulate bone, abalone nacre, and other hard biological materials. This method uses ice as a template to form ceramic-based materials with continuously, interconnected microstructures and magnetic fields to control the alignment of these structures in multiple directions. The resulting materials have anisotropic properties with enhanced mechanical performance that have potential applications as bone implants or lightweight structural composites, among others.

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.

A biologically inspired neural network for dynamic programming.

PubMed

Francelin Romero, R A; Kacpryzk, J; Gomide, F

2001-12-01

An artificial neural network with a two-layer feedback topology and generalized recurrent neurons, for solving nonlinear discrete dynamic optimization problems, is developed. A direct method to assign the weights of neural networks is presented. The method is based on Bellmann's Optimality Principle and on the interchange of information which occurs during the synaptic chemical processing among neurons. The neural network based algorithm is an advantageous approach for dynamic programming due to the inherent parallelism of the neural networks; further it reduces the severity of computational problems that can occur in methods like conventional methods. Some illustrative application examples are presented to show how this approach works out including the shortest path and fuzzy decision making problems.

Amoeba-inspired nanoarchitectonic computing: solving intractable computational problems using nanoscale photoexcitation transfer dynamics.

PubMed

Aono, Masashi; Naruse, Makoto; Kim, Song-Ju; Wakabayashi, Masamitsu; Hori, Hirokazu; Ohtsu, Motoichi; Hara, Masahiko

2013-06-18

Biologically inspired computing devices and architectures are expected to overcome the limitations of conventional technologies in terms of solving computationally demanding problems, adapting to complex environments, reducing energy consumption, and so on. We previously demonstrated that a primitive single-celled amoeba (a plasmodial slime mold), which exhibits complex spatiotemporal oscillatory dynamics and sophisticated computing capabilities, can be used to search for a solution to a very hard combinatorial optimization problem. We successfully extracted the essential spatiotemporal dynamics by which the amoeba solves the problem. This amoeba-inspired computing paradigm can be implemented by various physical systems that exhibit suitable spatiotemporal dynamics resembling the amoeba's problem-solving process. In this Article, we demonstrate that photoexcitation transfer phenomena in certain quantum nanostructures mediated by optical near-field interactions generate the amoebalike spatiotemporal dynamics and can be used to solve the satisfiability problem (SAT), which is the problem of judging whether a given logical proposition (a Boolean formula) is self-consistent. SAT is related to diverse application problems in artificial intelligence, information security, and bioinformatics and is a crucially important nondeterministic polynomial time (NP)-complete problem, which is believed to become intractable for conventional digital computers when the problem size increases. We show that our amoeba-inspired computing paradigm dramatically outperforms a conventional stochastic search method. These results indicate the potential for developing highly versatile nanoarchitectonic computers that realize powerful solution searching with low energy consumption.

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.

A novel single neuron perceptron with universal approximation and XOR computation properties.

PubMed

Lotfi, Ehsan; Akbarzadeh-T, M-R

2014-01-01

We propose a biologically motivated brain-inspired single neuron perceptron (SNP) with universal approximation and XOR computation properties. This computational model extends the input pattern and is based on the excitatory and inhibitory learning rules inspired from neural connections in the human brain's nervous system. The resulting architecture of SNP can be trained by supervised excitatory and inhibitory online learning rules. The main features of proposed single layer perceptron are universal approximation property and low computational complexity. The method is tested on 6 UCI (University of California, Irvine) pattern recognition and classification datasets. Various comparisons with multilayer perceptron (MLP) with gradient decent backpropagation (GDBP) learning algorithm indicate the superiority of the approach in terms of higher accuracy, lower time, and spatial complexity, as well as faster training. Hence, we believe the proposed approach can be generally applicable to various problems such as in pattern recognition and classification.

BSA modification to reduce CTAB induced nonspecificity and cytotoxicity of aptamer-conjugated gold nanorods

NASA Astrophysics Data System (ADS)

Yasun, Emir; Li, Chunmei; Barut, Inci; Janvier, Denisse; Qiu, Liping; Cui, Cheng; Tan, Weihong

2015-05-01

Aptamer-conjugated gold nanorods (AuNRs) are excellent candidates for targeted hyperthermia therapy of cancer cells. However, in high concentrations of AuNRs, aptamer conjugation alone fails to result in highly cell-specific AuNRs due to the presence of positively charged cetyltrimethylammonium bromide (CTAB) as a templating surfactant. Besides causing nonspecific electrostatic interactions with the cell surfaces, CTAB can also be cytotoxic, leading to uncontrolled cell death. To avoid the nonspecific interactions and cytotoxicity triggered by CTAB, we report the further biologically inspired modification of aptamer-conjugated AuNRs with bovine serum albumin (BSA) protein. Following this modification, interaction between CTAB and the cell surface was efficiently blocked, thereby dramatically reducing the side effects of CTAB. This approach may provide a general and simple method to avoid one of the most serious issues in biomedical applications of nanomaterials: nonspecific binding of the nanomaterials with biological cells.Aptamer-conjugated gold nanorods (AuNRs) are excellent candidates for targeted hyperthermia therapy of cancer cells. However, in high concentrations of AuNRs, aptamer conjugation alone fails to result in highly cell-specific AuNRs due to the presence of positively charged cetyltrimethylammonium bromide (CTAB) as a templating surfactant. Besides causing nonspecific electrostatic interactions with the cell surfaces, CTAB can also be cytotoxic, leading to uncontrolled cell death. To avoid the nonspecific interactions and cytotoxicity triggered by CTAB, we report the further biologically inspired modification of aptamer-conjugated AuNRs with bovine serum albumin (BSA) protein. Following this modification, interaction between CTAB and the cell surface was efficiently blocked, thereby dramatically reducing the side effects of CTAB. This approach may provide a general and simple method to avoid one of the most serious issues in biomedical applications of nanomaterials: nonspecific binding of the nanomaterials with biological cells. Electronic supplementary information (ESI) available: Fig. S-1 to S-6 are included. See DOI: 10.1039/c5nr01704a

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…

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

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.

Novel Magnetic Nanomaterials Inspired by Magnetotactic Baterial: Topical Review

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

Prozorov, Tanya; Bazylinki, Dennis A.; Mallapragada, Surya K.

2013-05-14

Magnetotactic bacteria, known to produce magnetic nanocrystals with uniform shapes and sizes at physiological conditions, serve as an inspiration and source of a number of biological macromolecules used for the biomimetic synthesis of a variety of magnetic nanomaterials. This review discusses the current state of understanding of magnetosome biomineralization in magnetotactic bacteria, as well as the ways in which iron biomineralization processes can be utilized for tailored in vivo formation of complex magnetic nanomaterials, not occurring in magnetotactic bacteria naturally. The review assesses the current efforts on in vitro synthesis of a variety of magnetic nanoparticles using bioinspired approaches bymore » utilizing mineralization proteins from magnetotactic bacteria, and surveys biomimetic strategies for the rational synthesis of various magnetic nanomaterials under ambient conditions. Finally, this review presents magnetic characterization of nanoparticles, highlighting differences in magnetic behavior between magnetic nanoparticles produced using bioinspired in vivo and in vitro strategies, compared to those produced using conventional methods. This in turn impacts their utility in a wide range of applications for magnetic nanoparticles, which are examined in detail, where bioinspired synthesis methods have potentially provided added advantages.« less

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.

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.

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.

Design and Fabrication of Tunable Nanoparticles for Biomedical Applications

NASA Astrophysics Data System (ADS)

Sun, Leming

In this dissertation, we first reviewed the naturally occurring nanoparticles and their limitations (Chapter 1). We then discussed the need and the parameters to design and fabricate bio-inspired tunable nanoparticles for wound healing, Alzheimer's disease (AD) diagnosis and progression monitoring. Tunable nanoparticles enhanced adhesive was inspired from the self-assembly processes, nanocomposite and chemical structures. Fluorescent peptide nanoparticles were inspired from the biological peptide self-assembly and naturally occurring fluorescent proteins. Then we reported the development of an in situ synthesis approach for fabricating tunable nanoparticle enhanced adhesives inspired from the strong adhesive produced by English ivy in Chapter 2. Special attention was given to tunable features of the adhesive produced by the biological process. Parameters that may be used to tune properties of the adhesive were proposed. To illustrate and validate the proposed approach, an experimental platform was presented for fabricating tunable chitosan adhesive enhanced by Au nanoparticles synthesized in situ. This study contributes to a bio-inspired approach for in situ synthesis of tunable nanocomposite adhesives by mimicking the natural biological processes of ivy adhesive synthesis. Using a bio-inspired 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 in Chapter 3. 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. While tremendous efforts have been spent in investigating scalable approaches for fabricating nanoparticles, less progress has been made in scalable synthesizing cyclic peptide nanoparticles and nanotubes, despite their great potential for broader biomedical applications. In Chapter 4, tunable synthesis of self-assembled cyclic peptide nanotubes and nanoparticles using three different methods, phase equilibrium, pH-driven, and pH-sensitive methods were proposed and investigated. The goal is for scalable nano-manufacturing of cyclic peptide nanoparticles and nanotubes with different sizes in large quality by controlling multiple process parameters. The dimensions of self-assembled nanostructures were found to be strongly influenced by the cyclic peptides concentration, side chains modification, pH value, reaction time, stirring intensity, and sonication time. This study proposed an overall strategy to integrate all the parameters to achieve optimal synthesis outputs. AD is associated with the accumulation of insoluble forms of amyloid-beta (Abeta) in plaques in extracellular spaces, as well as in the walls of blood vessels, and aggregation of microtubule protein tau in neurofibrillary tangles in neurons. In Chapter 5, we designed and synthesized a series of fluorescent cyclic peptide nanoparticles that can be used to detect Abeta aggregates in both the cerebrospinal fluid (CSF) and serum, which were obtained from healthy people and AD patients in different disease stages. Our experimental studies indicate that the fluorescence intensities and wavelengths generated from the interactions between the negatively charged fluorescent cyclic peptide nanoparticles and Abeta aggregates in both the CSF and serum changed with disease status, as compared to healthy individuals. The morphological and cytotoxicity studies demonstrated a potential inhibitory effect of the negatively charged nanoparticles on amyloid fibril growth. The underlying mechanisms leading to these changes are interpreted based on the aromatic, hydrophobic, and electrostatic interactions between c-PNPs and Abeta peptides. There is a critical need to diagnose and monitor the progression of AD using blood-based biomarkers. At present, it is believed that no single biomarker can be utilized to reliably detect AD. Combined biomarkers using multimodal techniques are highly sought after for AD diagnosis and progression monitoring. For this purpose, we developed a fluorescent peptide nanoparticles arrayed microfluidic chip that is capable of detecting multiple blood-based AD biomarkers simultaneously in Chapter 6. The concentration, aggregation stages, and Young's modulus of biomarkers could be analyzed by monitoring the changes of multimodal fluorescence intensity, nano-morphological, and nano-mechanical properties of the f-PNPs array. In this study, Abeta polypeptides and tau proteins were used to verify the proposed idea. To conclude, we demonstrate that how to design and fabrication of tunable nanoparticles for biomedical applications. Inspired from English ivy and sundew nanoadhesive, tunable nanoparticles enhanced adhesive hydrogels were prepared and validated for wound healing applications. Moreover, fluorescent peptide nanoparticles were designed, synthesized, characterized, and validated for AD diagnosis and progression monitoring. (Abstract shortened by ProQuest.).

Cochlea-inspired sensing node for compressive sensing

NASA Astrophysics Data System (ADS)

Peckens, Courtney A.; Lynch, Jerome P.

2013-04-01

While sensing technologies for structural monitoring applications have made significant advances over the last several decades, there is still room for improvement in terms of computational efficiency, as well as overall energy consumption. The biological nervous system can offer a potential solution to address these current deficiencies. The nervous system is capable of sensing and aggregating information about the external environment through very crude processing units known as neurons. Neurons effectively communicate in an extremely condensed format by encoding information into binary electrical spike trains, thereby reducing the amount of raw information sent throughout a neural network. Due to its unique signal processing capabilities, the mammalian cochlea and its interaction with the biological nervous system is of particular interest for devising compressive sensing strategies for dynamic engineered systems. The cochlea uses a novel method of place theory and frequency decomposition, thereby allowing for rapid signal processing within the nervous system. In this study, a low-power sensing node is proposed that draws inspiration from the mechanisms employed by the cochlea and the biological nervous system. As such, the sensor is able to perceive and transmit a compressed representation of the external stimulus with minimal distortion. Each sensor represents a basic building block, with function similar to the neuron, and can form a network with other sensors, thus enabling a system that can convey input stimulus in an extremely condensed format. The proposed sensor is validated through a structural monitoring application of a single degree of freedom structure excited by seismic ground motion.

Philosophical Basis and Some Historical Aspects of Systems Biology: From Hegel to Noble - Applications for Bioenergetic Research

PubMed Central

Saks, Valdur; Monge, Claire; Guzun, Rita

2009-01-01

We live in times of paradigmatic changes for the biological sciences. Reductionism, that for the last six decades has been the philosophical basis of biochemistry and molecular biology, is being displaced by Systems Biology, which favors the study of integrated systems. Historically, Systems Biology - defined as the higher level analysis of complex biological systems - was pioneered by Claude Bernard in physiology, Norbert Wiener with the development of cybernetics, and Erwin Schrödinger in his thermodynamic approach to the living. Systems Biology applies methods inspired by cybernetics, network analysis, and non-equilibrium dynamics of open systems. These developments follow very precisely the dialectical principles of development from thesis to antithesis to synthesis discovered by Hegel. Systems Biology opens new perspectives for studies of the integrated processes of energy metabolism in different cells. These integrated systems acquire new, system-level properties due to interaction of cellular components, such as metabolic compartmentation, channeling and functional coupling mechanisms, which are central for regulation of the energy fluxes. State of the art of these studies in the new area of Molecular System Bioenergetics is analyzed. PMID:19399243

Honey Bees Inspired Optimization Method: The Bees Algorithm.

PubMed

Yuce, Baris; Packianather, Michael S; Mastrocinque, Ernesto; Pham, Duc Truong; Lambiase, Alfredo

2013-11-06

Optimization algorithms are search methods where the goal is to find an optimal solution to a problem, in order to satisfy one or more objective functions, possibly subject to a set of constraints. Studies of social animals and social insects have resulted in a number of computational models of swarm intelligence. Within these swarms their collective behavior is usually very complex. The collective behavior of a swarm of social organisms emerges from the behaviors of the individuals of that swarm. Researchers have developed computational optimization methods based on biology such as Genetic Algorithms, Particle Swarm Optimization, and Ant Colony. The aim of this paper is to describe an optimization algorithm called the Bees Algorithm, inspired from the natural foraging behavior of honey bees, to find the optimal solution. The algorithm performs both an exploitative neighborhood search combined with random explorative search. In this paper, after an explanation of the natural foraging behavior of honey bees, the basic Bees Algorithm and its improved versions are described and are implemented in order to optimize several benchmark functions, and the results are compared with those obtained with different optimization algorithms. The results show that the Bees Algorithm offering some advantage over other optimization methods according to the nature of the problem.

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

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.

Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data

PubMed Central

Ching, Travers; Zhu, Xun

2018-01-01

Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN framework called Cox-nnet to predict patient prognosis from high throughput transcriptomics data. In 10 TCGA RNA-Seq data sets, Cox-nnet achieves the same or better predictive accuracy compared to other methods, including Cox-proportional hazards regression (with LASSO, ridge, and mimimax concave penalty), Random Forests Survival and CoxBoost. Cox-nnet also reveals richer biological information, at both the pathway and gene levels. The outputs from the hidden layer node provide an alternative approach for survival-sensitive dimension reduction. In summary, we have developed a new method for accurate and efficient prognosis prediction on high throughput data, with functional biological insights. The source code is freely available at https://github.com/lanagarmire/cox-nnet. PMID:29634719

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.

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.

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

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.

Leveraging advances in biology to design biomaterials

NASA Astrophysics Data System (ADS)

Darnell, Max; Mooney, David J.

2017-12-01

Biomaterials have dramatically increased in functionality and complexity, allowing unprecedented control over the cells that interact with them. From these engineering advances arises the prospect of improved biomaterial-based therapies, yet practical constraints favour simplicity. Tools from the biology community are enabling high-resolution and high-throughput bioassays that, if incorporated into a biomaterial design framework, could help achieve unprecedented functionality while minimizing the complexity of designs by identifying the most important material parameters and biological outputs. However, to avoid data explosions and to effectively match the information content of an assay with the goal of the experiment, material screens and bioassays must be arranged in specific ways. By borrowing methods to design experiments and workflows from the bioprocess engineering community, we outline a framework for the incorporation of next-generation bioassays into biomaterials design to effectively optimize function while minimizing complexity. This framework can inspire biomaterials designs that maximize functionality and translatability.

In-Gel Direct Laser Writing for 3D-Designed Hydrogel Composites That Undergo Complex Self-Shaping.

PubMed

Nishiguchi, Akihiro; Mourran, Ahmed; Zhang, Hang; Möller, Martin

2018-01-01

Self-shaping and actuating materials inspired by biological system have enormous potential for biosensor, microrobotics, and optics. However, the control of 3D-complex microactuation is still challenging due to the difficulty in design of nonuniform internal stress of micro/nanostructures. Here, we develop in-gel direct laser writing (in-gel DLW) procedure offering a high resolution inscription whereby the two materials, resin and hydrogel, are interpenetrated on a scale smaller than the wavelength of the light. The 3D position and mechanical properties of the inscribed structures could be tailored to a resolution better than 100 nm over a wide density range. These provide an unparalleled means of inscribing a freely suspended microstructures of a second material like a skeleton into the hydrogel body and also to direct isotropic volume changes to bending and distortion motions. In the combination with a thermosensitive hydrogel rather small temperature variations could actuate large amplitude motions. This generates complex modes of motion through the rational engineering of the stresses present in the multicomponent material. More sophisticated folding design would realize a multiple, programmable actuation of soft materials. This method inspired by biological system may offer the possibility for functional soft materials capable of biomimetic actuation and photonic crystal application.

A Bio-Inspired Glucose Controller Based on Pancreatic β-Cell Physiology

PubMed Central

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

2012-01-01

Introduction Control algorithms for closed-loop insulin delivery in type 1 diabetes have been mainly based on control engineering or artificial intelligence techniques. These, however, are not based on the physiology of the pancreas but seek to implement engineering solutions to biology. Developments in mathematical models of the β-cell physiology of the pancreas have described the glucose-induced insulin release from pancreatic β cells at a molecular level. This has facilitated development of a new class of bio-inspired glucose control algorithms that replicate the functionality of the biological pancreas. However, technologies for sensing glucose levels and delivering insulin use the subcutaneous route, which is nonphysiological and introduces some challenges. In this article, a novel glucose controller is presented as part of a bio-inspired artificial pancreas. Methods A mathematical model of β-cell physiology was used as the core of the proposed controller. In order to deal with delays and lack of accuracy introduced by the subcutaneous route, insulin feedback and a gain scheduling strategy were employed. A United States Food and Drug Administration-accepted type 1 diabetes mellitus virtual population was used to validate the presented controller. Results Premeal and postmeal mean ± standard deviation blood glucose levels for the adult and adolescent populations were well within the target range set for the controller [(70, 180) mg/dl], with a percent time in range of 92.8 ± 7.3% for the adults and 83.5 ± 14% for the adolescents. Conclusions This article shows for the first time very good glucose control in a virtual population with type 1 diabetes mellitus using a controller based on a subcellular β-cell model. PMID:22768892

A biologically inspired model of bat echolocation in a cluttered environment with inputs designed from field Recordings

NASA Astrophysics Data System (ADS)

Loncich, Kristen Teczar

Bat echolocation strategies and neural processing of acoustic information, with a focus on cluttered environments, is investigated in this study. How a bat processes the dense field of echoes received while navigating and foraging in the dark is not well understood. While several models have been developed to describe the mechanisms behind bat echolocation, most are based in mathematics rather than biology, and focus on either peripheral or neural processing---not exploring how these two levels of processing are vitally connected. Current echolocation models also do not use habitat specific acoustic input, or account for field observations of echolocation strategies. Here, a new approach to echolocation modeling is described capturing the full picture of echolocation from signal generation to a neural picture of the acoustic scene. A biologically inspired echolocation model is developed using field research measurements of the interpulse interval timing used by a frequency modulating (FM) bat in the wild, with a whole method approach to modeling echolocation including habitat specific acoustic inputs, a biologically accurate peripheral model of sound processing by the outer, middle, and inner ear, and finally a neural model incorporating established auditory pathways and neuron types with echolocation adaptations. Field recordings analyzed underscore bat sonar design differences observed in the laboratory and wild, and suggest a correlation between interpulse interval groupings and increased clutter. The scenario model provides habitat and behavior specific echoes and is a useful tool for both modeling and behavioral studies, and the peripheral and neural model show that spike-time information and echolocation specific neuron types can produce target localization in the midbrain.

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

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.

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

Heterofunctional nanomaterials: fabrication, properties and applications in nanobiotechnology.

PubMed

Kumart, S Anil; Khan, M I

2010-07-01

Nanotechnology and nanoengineering includes a novel class of materials that are gaining significant recognition to pursuit technological/biological advances in diverse fields including, biology, medicine, electronics, engineering etc. due to their unique size- and shape-dependent intrinsic physicochemical, optoelectronic and biological properties. Characteristics such as high surface to volume ratios and quantum confinement results in materials that are qualitatively different from their bulk counterparts. These properties not only make them suitable for numerous applications in existing and emerging technologies, but also have outstanding role in many fields that provide inspiration for their fabrication. In Today's trend nanotechnology is spreading vigorously where researchers all over the world are focusing towards their synthesis and applications. Therefore, this review is helpful for the researchers in the field of nanobiotechnology/nanomedicine, providing a brief overview of nanotechnology, covering nanomaterial synthesis methods (with emphasis on environmentally benign greener approaches), their properties, and applications; such as drug delivery, bio-labeling, nanotoxicity etc. The influence of synthesis methods and surface coatings/stabilizing agents and their subsequent applications is discussed, and a broad outline on the biomedical applications into which they have been implemented is also presented.

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.

Nasal and Oral Inspiration During Natural Speech Breathing

PubMed Central

Lester, Rosemary A.; Hoit, Jeannette D.

2015-01-01

Purpose The purpose of this study was to determine the typical pattern for inspiration during speech breathing in healthy adults, as well as the factors that might influence it. Method Ten healthy adults, 18–45 years of age, performed a variety of speaking tasks while nasal ram pressure, audio, and video recordings were obtained. Inspirations were categorized as a nasal only, oral only, simultaneous nasal and oral, or alternating nasal and oral inspiration. The method was validated using nasal airflow, oral airflow, audio, and video recordings for two participants. Results The predominant pattern was simultaneous nasal and oral inspirations for all speaking tasks. This pattern was not affected by the nature of the speaking task or by the phonetic context surrounding the inspiration. The validation procedure confirmed that nearly all inspirations during counting and paragraph reading were simultaneous nasal and oral inspirations; whereas for sentence reading, the predominant pattern was alternating nasal and oral inspirations across the three phonetic contexts. Conclusions Healthy adults inspire through both the nose and mouth during natural speech breathing. This pattern of inspiration is likely beneficial in reducing pathway resistance while preserving some of the benefits of nasal breathing. PMID:24129013

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.

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.

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

NASA Astrophysics Data System (ADS)

Štolc, Svorad; Bajla, Ivan

2010-01-01

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

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.

Neuron-Inspired Interpenetrative Network Composed of Cobalt-Phosphorus-Derived Nanoparticles Embedded within Porous Carbon Nanotubes for Efficient Hydrogen Production.

PubMed

Shen, Juanxia; Yang, Zhi; Ge, Mengzhan; Li, Ping; Nie, Huagui; Cai, Qiran; Gu, Cancan; Yang, Keqin; Huang, Shaoming

2016-07-13

The ongoing search for cheap and efficient hydrogen evolution reaction (HER) electrocatalysts to replace currently used catalysts based on Pt or its alloys has been considered as an prevalent strategy to produce renewable and clean hydrogen energy. Herein, inspired by the neuron structure in biological systems, we demonstrate a novel fabrication strategy via a simple two-step method for the synthesis of a neuronlike interpenetrative nanocomposite network of Co-P embedded in porous carbon nanotubes (NIN-Co-P/PCNTs). It is found that the interpenetrative network provides a natural transport path to accelerate the hydrogen production process. The embedded-type structure improves the utilization ratio of Co-P and the hollow, tubelike, and porous structure of PCNTs further promote charge and reactant transport. These factors allow the as-prepared NIN-Co-P/PCNTs to achieve a onset potential low to 43 mV, a Tafel slope as small as 40 mV/decade, an excellent stability, and a high turnover frequency value of 3.2 s(-1) at η = 0.2 V in acidic conditions. These encouraging properties derived from the neuronlike interpenetrative network structure might offer new inspiration for the preparation of more nanocomposites for applications in other catalytic and optoelectronic field.

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.

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.

On "being inspired" by Husserl's Phenomenology: reflections on Omery's exposition of phenomenology as a method of nursing research.

PubMed

Porter, E J

1998-09-01

The impact of Omery's article, "Phenomenology: A Method for Nursing Research," on nursing science is appraised. In particular, the influence of her emphasis on "being inspired" was compared with that of her detailed reviews of psychological phenomenologic methods. The author's experience of "being inspired" by Husserl's book, Ideas, is described. The author also discusses the tapping of this resource during three phases of her development as a researcher: (1) appraising methods derived from Husserl's phenomenology; (2) spelling out an approach, with help; and (3) "making clearer while glancing-toward." Omery's proposed linkage between philosophic inspiration and methodologic development is highlighted as a challenge to nurse researchers.

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…

Rapid preparation process of antiparkinsonian drug Mucuna pruriens silver nanoparticle by bioreduction and their characterization

PubMed Central

Arulkumar, Subramanian; Sabesan, Muthukumaran

2010-01-01

Backgorund: Development of biologically inspired experimental processes for the synthesis of nanoparticles is evolving an important branch of nanotechnology. Methods: The bioreduction behavior of plant seed extract of Mucuna pruriens in the synthesis of silver nanoparticles was investigated employing UV/visible spectrophotometry, X-ray diffraction (XRD), and transmission electron microscopy (TEM), Fourier transform – infra red (FT- IR). Result: M. pruriens was found to exhibit strong potential for rapid reduction of silver ions. The formation of nanoparticles by this method is extremely rapid, requires no toxic chemicals, and the nanoparticles are stable for several months. Conclusion: The main conclusion is that the bioreduction method to produce nanoparticles is a good alternative to the electrochemical methods and it is expected to be biocompatible. PMID:21808573

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

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.

Constructive biology and approaches to temporal grounding in postreactive robotics

NASA Astrophysics Data System (ADS)

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

1999-08-01

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

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.

The Inspiration of Hope in Substance Abuse Counseling

ERIC Educational Resources Information Center

Koehn, Corinne; Cutcliffe, John R.

2012-01-01

This study used a grounded theory method to explore how counselors inspire hope in clients struggling with substance abuse. Findings from 10 participants revealed that hope inspiration occurred in 3 phases and consisted of several categories of hope-inspiring processes. Implications for counseling practice, counselor education, and research are…

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.

Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems

PubMed Central

Rodriguez-Fernandez, Maria; Egea, Jose A; Banga, Julio R

2006-01-01

Background We consider the problem of parameter estimation (model calibration) in nonlinear dynamic models of biological systems. Due to the frequent ill-conditioning and multi-modality of many of these problems, traditional local methods usually fail (unless initialized with very good guesses of the parameter vector). In order to surmount these difficulties, global optimization (GO) methods have been suggested as robust alternatives. Currently, deterministic GO methods can not solve problems of realistic size within this class in reasonable computation times. In contrast, certain types of stochastic GO methods have shown promising results, although the computational cost remains large. Rodriguez-Fernandez and coworkers have presented hybrid stochastic-deterministic GO methods which could reduce computation time by one order of magnitude while guaranteeing robustness. Our goal here was to further reduce the computational effort without loosing robustness. Results We have developed a new procedure based on the scatter search methodology for nonlinear optimization of dynamic models of arbitrary (or even unknown) structure (i.e. black-box models). In this contribution, we describe and apply this novel metaheuristic, inspired by recent developments in the field of operations research, to a set of complex identification problems and we make a critical comparison with respect to the previous (above mentioned) successful methods. Conclusion Robust and efficient methods for parameter estimation are of key importance in systems biology and related areas. The new metaheuristic presented in this paper aims to ensure the proper solution of these problems by adopting a global optimization approach, while keeping the computational effort under reasonable values. This new metaheuristic was applied to a set of three challenging parameter estimation problems of nonlinear dynamic biological systems, outperforming very significantly all the methods previously used for these benchmark problems. PMID:17081289

Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems.

PubMed

Rodriguez-Fernandez, Maria; Egea, Jose A; Banga, Julio R

2006-11-02

We consider the problem of parameter estimation (model calibration) in nonlinear dynamic models of biological systems. Due to the frequent ill-conditioning and multi-modality of many of these problems, traditional local methods usually fail (unless initialized with very good guesses of the parameter vector). In order to surmount these difficulties, global optimization (GO) methods have been suggested as robust alternatives. Currently, deterministic GO methods can not solve problems of realistic size within this class in reasonable computation times. In contrast, certain types of stochastic GO methods have shown promising results, although the computational cost remains large. Rodriguez-Fernandez and coworkers have presented hybrid stochastic-deterministic GO methods which could reduce computation time by one order of magnitude while guaranteeing robustness. Our goal here was to further reduce the computational effort without loosing robustness. We have developed a new procedure based on the scatter search methodology for nonlinear optimization of dynamic models of arbitrary (or even unknown) structure (i.e. black-box models). In this contribution, we describe and apply this novel metaheuristic, inspired by recent developments in the field of operations research, to a set of complex identification problems and we make a critical comparison with respect to the previous (above mentioned) successful methods. Robust and efficient methods for parameter estimation are of key importance in systems biology and related areas. The new metaheuristic presented in this paper aims to ensure the proper solution of these problems by adopting a global optimization approach, while keeping the computational effort under reasonable values. This new metaheuristic was applied to a set of three challenging parameter estimation problems of nonlinear dynamic biological systems, outperforming very significantly all the methods previously used for these benchmark problems.

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

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.

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…

High-performance flexible strain sensor with bio-inspired crack arrays.

PubMed

Han, Zhiwu; Liu, Linpeng; Zhang, Junqiu; Han, Qigang; Wang, Kejun; Song, Honglie; Wang, Ze; Jiao, Zhibin; Niu, Shichao; Ren, Luquan

2018-06-12

Biomimetic sensor technology is always superior to existing human technologies. The scorpion, especially the forest scorpion, has a unique ability to detect subtle vibrations, which is attributed to the microcrack-shaped slit sensillum on its legs. Here, the biological sensing mechanism of the typical scorpion (Heterometrus petersii) was intensively studied in order to newly design and significantly improve the flexible strain sensors. Benefiting from the easy-crack property of polystyrene (PS) and using the solvent-induced swelling as well as double template transferring method, regular and controllable microcrack arrays were successfully fabricated on top of polydimethylsiloxane (PDMS). Using this method, any physical damage to PDMS could be effectively avoided. More fortunately, this bio-inspired crack arrays fabricated in this work also had a radial-like pattern similar to the slit sensillum of the scorpion, which was another unexpected imitation. The gauge factor (GF) of the sensor was conservatively evaluated at 5888.89 upon 2% strain and the response time was 297 ms. Afterward, it was demonstrated that the bio-inspired regular microcrack arrays could also significantly enhance the performance of traditional strain sensors, especially in terms of the sensitivity and response time. The practical applications, such as the detection of human motions and surface folding, were also tested in this work, with the results showing significant potential applications in numerous fields. This work changes the traditional waste cracks on some damaged products into valuable things for ultrasensitive mechanical sensors. Moreover, with this manufacturing technique, we could easily realize the simple, low cost and large-scale fabrication of advanced bioinpired sensors.

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.

Integrating valve-inspired design features into poly(ethylene glycol) hydrogel scaffolds for heart valve tissue engineering.

PubMed

Zhang, Xing; Xu, Bin; Puperi, Daniel S; Yonezawa, Aline L; Wu, Yan; Tseng, Hubert; Cuchiara, Maude L; West, Jennifer L; Grande-Allen, K Jane

2015-03-01

The development of advanced scaffolds that recapitulate the anisotropic mechanical behavior and biological functions of the extracellular matrix in leaflets would be transformative for heart valve tissue engineering. In this study, anisotropic mechanical properties were established in poly(ethylene glycol) (PEG) hydrogels by crosslinking stripes of 3.4 kDa PEG diacrylate (PEGDA) within 20 kDa PEGDA base hydrogels using a photolithographic patterning method. Varying the stripe width and spacing resulted in a tensile elastic modulus parallel to the stripes that was 4.1-6.8 times greater than that in the perpendicular direction, comparable to the degree of anisotropy between the circumferential and radial orientations in native valve leaflets. Biomimetic PEG-peptide hydrogels were prepared by tethering the cell-adhesive peptide RGDS and incorporating the collagenase-degradable peptide PQ (GGGPQG↓IWGQGK) into the polymer network. The specific amounts of RGDS and PEG-PQ within the resulting hydrogels influenced the elongation, de novo extracellular matrix deposition and hydrogel degradation behavior of encapsulated valvular interstitial cells (VICs). In addition, the morphology and activation of VICs grown atop PEG hydrogels could be modulated by controlling the concentration or micro-patterning profile of PEG-RGDS. These results are promising for the fabrication of PEG-based hydrogels using anatomically and biologically inspired scaffold design features for heart valve tissue engineering. Copyright © 2014 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

A novel pipeline based FPGA implementation of a genetic algorithm

NASA Astrophysics Data System (ADS)

Thirer, Nonel

2014-05-01

To solve problems when an analytical solution is not available, more and more bio-inspired computation techniques have been applied in the last years. Thus, an efficient algorithm is the Genetic Algorithm (GA), which imitates the biological evolution process, finding the solution by the mechanism of "natural selection", where the strong has higher chances to survive. A genetic algorithm is an iterative procedure which operates on a population of individuals called "chromosomes" or "possible solutions" (usually represented by a binary code). GA performs several processes with the population individuals to produce a new population, like in the biological evolution. To provide a high speed solution, pipelined based FPGA hardware implementations are used, with a nstages pipeline for a n-phases genetic algorithm. The FPGA pipeline implementations are constraints by the different execution time of each stage and by the FPGA chip resources. To minimize these difficulties, we propose a bio-inspired technique to modify the crossover step by using non identical twins. Thus two of the chosen chromosomes (parents) will build up two new chromosomes (children) not only one as in classical GA. We analyze the contribution of this method to reduce the execution time in the asynchronous and synchronous pipelines and also the possibility to a cheaper FPGA implementation, by using smaller populations. The full hardware architecture for a FPGA implementation to our target ALTERA development card is presented and analyzed.

Printing soft matter in three dimensions.

PubMed

Truby, Ryan L; Lewis, Jennifer A

2016-12-14

Light- and ink-based three-dimensional (3D) printing methods allow the rapid design and fabrication of materials without the need for expensive tooling, dies or lithographic masks. They have led to an era of manufacturing in which computers can control the fabrication of soft matter that has tunable mechanical, electrical and other functional properties. The expanding range of printable materials, coupled with the ability to programmably control their composition and architecture across various length scales, is driving innovation in myriad applications. This is illustrated by examples of biologically inspired composites, shape-morphing systems, soft sensors and robotics that only additive manufacturing can produce.

Printing soft matter in three dimensions

NASA Astrophysics Data System (ADS)

Truby, Ryan L.; Lewis, Jennifer A.

2016-12-01

Light- and ink-based three-dimensional (3D) printing methods allow the rapid design and fabrication of materials without the need for expensive tooling, dies or lithographic masks. They have led to an era of manufacturing in which computers can control the fabrication of soft matter that has tunable mechanical, electrical and other functional properties. The expanding range of printable materials, coupled with the ability to programmably control their composition and architecture across various length scales, is driving innovation in myriad applications. This is illustrated by examples of biologically inspired composites, shape-morphing systems, soft sensors and robotics that only additive manufacturing can produce.

Mix-and-match nanobiosensor design: Logical and spatial programming of biosensors using self-assembled DNA nanostructures.

PubMed

Liu, Ying; Kumar, Sriram; Taylor, Rebecca E

2018-04-06

The evergrowing need to understand and engineer biological and biochemical mechanisms has led to the emergence of the field of nanobiosensing. Structural DNA nanotechnology, encompassing methods such as DNA origami and single-stranded tiles, involves the base pairing-driven knitting of DNA into discrete one-, two-, and three-dimensional shapes at nanoscale. Such nanostructures enable a versatile design and fabrication of nanobiosensors. These systems benefit from DNA's programmability, inherent biocompatibility, and the ability to incorporate and organize functional materials such as proteins and metallic nanoparticles. In this review, we present a mix-and-match taxonomy and approach to designing nanobiosensors in which the choices of bioanalyte and transduction mechanism are fully independent of each other. We also highlight opportunities for greater complexity and programmability of these systems that are built using structural DNA nanotechnology. This article is categorized under: Implantable Materials and Surgical Technologies > Nanomaterials and Implants Diagnostic Tools > Biosensing Biology-Inspired Nanomaterials > Nucleic Acid-Based Structures Nanotechnology Approaches to Biology > Nanoscale Systems in Biology. © 2018 Wiley Periodicals, Inc.

Biology teachers' dissection practices and the influences that lead to their adoption: An exploratory research

NASA Astrophysics Data System (ADS)

Milano, Regina Nicole

The lack of resolution in the on-going animal dissection debate inspired this mixed methods study to identify Connecticut secondary biology teachers' dissection practices and the influences that lead to their adoption. Qualitative findings indicate past experiences, managing objections to dissection, school culture, goals of biology teaching and ethics as major influences on dissection practices with 58.4% (n=7) of the sample dissecting and 41.6% not dissecting (n=5). Quantitative findings reveal gender, standards and curriculum, advantages of dissection and experiences as a student as major influences on dissection practices with 71.9% (n=92) of the sample dissecting and 28.1% (n=36) not dissecting. The study concludes that dissection policies are necessary and imminent in Connecticut school districts. Furthermore, it advises teacher-initiated, qualitative and quantitative assessments to expose disparities between student dissection perspectives and their own, prior to conducting dissection. Finally, it provides suggestions for addressing potential differences including administrative involvement.

Inverse statistical physics of protein sequences: a key issues review.

PubMed

Cocco, Simona; Feinauer, Christoph; Figliuzzi, Matteo; Monasson, Rémi; Weigt, Martin

2018-03-01

In the course of evolution, proteins undergo important changes in their amino acid sequences, while their three-dimensional folded structure and their biological function remain remarkably conserved. Thanks to modern sequencing techniques, sequence data accumulate at unprecedented pace. This provides large sets of so-called homologous, i.e. evolutionarily related protein sequences, to which methods of inverse statistical physics can be applied. Using sequence data as the basis for the inference of Boltzmann distributions from samples of microscopic configurations or observables, it is possible to extract information about evolutionary constraints and thus protein function and structure. Here we give an overview over some biologically important questions, and how statistical-mechanics inspired modeling approaches can help to answer them. Finally, we discuss some open questions, which we expect to be addressed over the next years.

Inverse statistical physics of protein sequences: a key issues review

NASA Astrophysics Data System (ADS)

Cocco, Simona; Feinauer, Christoph; Figliuzzi, Matteo; Monasson, Rémi; Weigt, Martin

2018-03-01

In the course of evolution, proteins undergo important changes in their amino acid sequences, while their three-dimensional folded structure and their biological function remain remarkably conserved. Thanks to modern sequencing techniques, sequence data accumulate at unprecedented pace. This provides large sets of so-called homologous, i.e. evolutionarily related protein sequences, to which methods of inverse statistical physics can be applied. Using sequence data as the basis for the inference of Boltzmann distributions from samples of microscopic configurations or observables, it is possible to extract information about evolutionary constraints and thus protein function and structure. Here we give an overview over some biologically important questions, and how statistical-mechanics inspired modeling approaches can help to answer them. Finally, we discuss some open questions, which we expect to be addressed over the next years.

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.

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.

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

Using dynamics to identify network topology

NASA Astrophysics Data System (ADS)

Rahi, Sahand Jamal; Tsaneva-Atanasova, Krasimira

2013-03-01

To elucidate the topology of a signaling pathway, generally, experimentalists manipulate a cell's molecular architecture, for example, by knocking out genes. Molecular biology techniques, though, are not only invasive and labor-intensive, they have also often been eluded by the complexity of biological networks, e.g., in the case of the gonadotropin-releasing hormone (GnRH) system. Inspired by the rapidly accumulating examples of oscillatory signaling in biology, we explored whether such dynamical stimuli can be used to discriminate different topologies of adaptive pathways, which are ubiquitous in biology. Responses to static inputs are nearly indistinguishable given strong measurement noise. Sine function stimuli, widely used in physics, are difficult to implement in standard microfluidics or optogenetics set-ups and do not simplify the mathematical analysis because of the nonlinearities in these systems. With periodic on-off pulses, which can be easily produced, however, simple adaptive circuit motifs and detailed models from the literature robustly reveal distinct output characteristics, which manifest in how the period of maximal output varies with pulse width. Our calculations provide a framework for using existing methods to discover difficult to reveal mechanisms. Furthermore, our results constrain the possible design principles of the presumed frequency decoders in biological systems where pulsatile signaling has recently been discovered.

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 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.

Neuroinspired control strategies with applications to flapping flight

NASA Astrophysics Data System (ADS)

Dorothy, Michael Ray

This dissertation is centered on a theoretical, simulation, and experimental study of control strategies which are inspired by biological systems. Biological systems, along with sufficiently complicated engineered systems, often have many interacting degrees of freedom and need to excite large-displacement oscillations in order to locomote. Combining these factors can make high-level control design difficult. This thesis revolves around three different levels of abstraction, providing tools for analysis and design. First, we consider central pattern generators (CPGs) to control flapping-flight dynamics. The key idea here is dimensional reduction - we want to convert complicated interactions of many degrees of freedom into a handful of parameters which have intuitive connections to the overall system behavior, leaving the control designer unconcerned with the details of particular motions. A rigorous mathematical and control theoretic framework to design complex three-dimensional wing motions is presented based on phase synchronization of nonlinear oscillators. In particular, we show that flapping-flying dynamics without a tail or traditional aerodynamic control surfaces can be effectively controlled by a reduced set of central pattern generator parameters that generate phase-synchronized or symmetry-breaking oscillatory motions of two main wings. Furthermore, by using a Hopf bifurcation, we show that tailless aircraft (inspired by bats) alternating between flapping and gliding can be effectively stabilized by smooth wing motions driven by the central pattern generator network. Results of numerical simulation with a full six-degree-of-freedom flight dynamic model validate the effectiveness of the proposed neurobiologically inspired control approach. Further, we present experimental micro aerial vehicle (MAV) research with low-frequency flapping and articulated wing gliding. The importance of phase difference control via an abstract mathematical model of central pattern generators is confirmed with a robotic bat on a 3-DOF pendulum platform. An aerodynamic model for the robotic bat based on the complex wing kinematics is presented. Closed loop experiments show that control dimension reduction is achievable - unstable longitudinal modes are stabilized and controlled using only two control parameters. A transition of flight modes, from flapping to gliding and vice-versa, is demonstrated within the CPG control scheme. The second major thrust is inspired by this idea that mode switching is useful. Many bats and birds adopt a mixed strategy of flapping and gliding to provide agility when necessary and to increase overall efficiency. This work explores dwell time constraints on switched systems with multiple, possibly disparate invariant limit sets. We show that, under suitable conditions, trajectories globally converge to a superset of the limit sets and then remain in a second, larger superset. We show the effectiveness of the dwell-time conditions by using examples of nonlinear switching limit cycles from our work on flapping flight. This level of abstraction has been found to be useful in many ways, but it also produces its own challenges. For example, we discuss death of oscillation which can occur for many limit-cycle controllers and the difficulty in incorporating fast, high-displacement reflex feedback. This leads us to our third major thrust - considering biologically realistic neuron circuits instead of a limit cycle abstraction. Biological neuron circuits are incredibly diverse in practice, giving us a convincing rationale that they can aid us in our quest for flexibility. Nevertheless, that flexibility provides its own challenges. It is not currently known how most biological neuron circuits work, and little work exists that connects the principles of a neuron circuit to the principles of control theory. We begin the process of trying to bridge this gap by considering the simplest of classical controllers, PD control. We propose a simple two-neuron, two-synapse circuit based on the concept that synapses provide attenuation and a delay. We present a simulation-based method of analysis, including a smoothing algorithm, a steady-state response curve, and a system identification procedure for capturing differentiation. There will never be One True Control Method that will solve all problems. Nature's solution to a diversity of systems and situations is equally diverse. This will inspire many strategies and require a multitude of analysis tools. This thesis is my contribution of a few.

Noise-Assisted Concurrent Multipath Traffic Distribution in Ad Hoc Networks

PubMed Central

Murata, Masayuki

2013-01-01

The concept of biologically inspired networking has been introduced to tackle unpredictable and unstable situations in computer networks, especially in wireless ad hoc networks where network conditions are continuously changing, resulting in the need of robustness and adaptability of control methods. Unfortunately, existing methods often rely heavily on the detailed knowledge of each network component and the preconfigured, that is, fine-tuned, parameters. In this paper, we utilize a new concept, called attractor perturbation (AP), which enables controlling the network performance using only end-to-end information. Based on AP, we propose a concurrent multipath traffic distribution method, which aims at lowering the average end-to-end delay by only adjusting the transmission rate on each path. We demonstrate through simulations that, by utilizing the attractor perturbation relationship, the proposed method achieves a lower average end-to-end delay compared to other methods which do not take fluctuations into account. PMID:24319375

[Pursed Lips Inspiration for Vocal Cord Dysfunction].

PubMed

Maruyama, Yumiko; Tsukada, Yayoi; Hirai, Nobuyuki; Nakanishi, Yosuke; Yoshizaki, Tomokazu

2015-01-01

Paradoxical vocal cord motion (PVCM) during vocal cord dysfunction (VCD) generally occurs spasmodically and transiently. After we had experienced 36 cases of VCD and successfully treated with conservative treatment including "pursed lips inspiration" method, we experienced a boy who had persistent PVCM. It was observed his PVCM vanished when he breathed in through pursed lips, while it appeared again when he stopped pursed lips inspiration. An airway reflex has been reported where the negative pressure in the subglottic space resulting from the inspiratory effort against a narrowed glottis activates the vocal cord adductor. VCD is considered to have both acceleration of laryngeal closure reflex against airway stimuli and active adductive movement of vocal cords against negative pressure in the subglottic space as underlying factors. The pursed lips inspiration method enables VCD patients not only to accomplish slow and light breathing but also to decrease the difference in the pressure between the supra--and subglottic space by occluding the nasal cavity and voluntary puckering up of the mouth which generate negative pressure in the supraglottic space. This is the first report of the pursed lips inspiration method as a treatment for VCD. Pursed lips inspiration is a simple method which is easy to perform anytime, anywhere without any special equipment, and is considered to be worth trying for VCD.

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.

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.

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.

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.

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…

Bio-Inspired Engineering of Exploration Systems

NASA Technical Reports Server (NTRS)

Thakoor, Sanita

2003-01-01

The multidisciplinary concept of "bioinspired engineering of exploration systems" (BEES) is described, which is a guiding principle of the continuing effort to develop biomorphic explorers as reported in a number of articles in the past issues of NASA Tech Briefs. The intent of BEES is to distill from the principles found in successful nature-tested mechanisms of specific crucial functions that are hard to accomplish by conventional methods but that are accomplished rather deftly in nature by biological organisms. The intent is not just to mimic operational mechanisms found in a specific biological organism but to imbibe the salient principles from a variety of diverse bio-organisms for the desired crucial function. Thereby, we can build explorer systems that have specific capabilities endowed beyond nature, as they will possess a combination of the best nature-tested mechanisms for that particular function. The approach consists of selecting a crucial function, for example, flight or some selected aspects of flight, and develop an explorer that combines the principles of those specific attributes as seen in diverse flying species into one artificial entity. This will allow going beyond biology and achieving unprecedented capability and adaptability needed in encountering and exploring what is as yet unknown. A classification of biomorphic flyers into two main classes of surface and aerial explorers is illustrated in the figure, with examples of a variety of biological organisms that provide the inspiration in each respective subclass. Such biomorphic explorers may possess varied mobility modes: surface-roving, burrowing, hopping, hovering, or flying, to accomplish surface, subsurface, and aerial exploration. Preprogrammed for a specific function, they could serve as one-way communicating beacons, spread over the exploration site, autonomously looking for/at the targets of interest. In a hierarchical organization, these biomorphic explorers would report to the next level of exploration mode (say, a large conventional lander/rover) in the vicinity. A widespread and affordable exploration of new/hazardous sites at lower cost and risk would thus become possible by utilizing a faster aerial flyer to cover long ranges and deploying a variety of function- specific, smaller biomorphic explorers for distributed sensing and local sample acquisition. Several conceptual biomorphic missions for planetary and terrestrial exploration applications have been illustrated in "Surface-Launched Explorers for Reconnaissance/ Scouting" (NPO-20871), NASA Tech Briefs, Vol. 26, No. 4 (April, 2002), page 69 and "Bio-Inspired Engineering of Exploration Systems," Journal of Space Mission Architecture, Issue 2, Fall 2000, pages 49-79.

Conditioning and Robustness of RNA Boltzmann Sampling under Thermodynamic Parameter Perturbations.

PubMed

Rogers, Emily; Murrugarra, David; Heitsch, Christine

2017-07-25

Understanding how RNA secondary structure prediction methods depend on the underlying nearest-neighbor thermodynamic model remains a fundamental challenge in the field. Minimum free energy (MFE) predictions are known to be "ill conditioned" in that small changes to the thermodynamic model can result in significantly different optimal structures. Hence, the best practice is now to sample from the Boltzmann distribution, which generates a set of suboptimal structures. Although the structural signal of this Boltzmann sample is known to be robust to stochastic noise, the conditioning and robustness under thermodynamic perturbations have yet to be addressed. We present here a mathematically rigorous model for conditioning inspired by numerical analysis, and also a biologically inspired definition for robustness under thermodynamic perturbation. We demonstrate the strong correlation between conditioning and robustness and use its tight relationship to define quantitative thresholds for well versus ill conditioning. These resulting thresholds demonstrate that the majority of the sequences are at least sample robust, which verifies the assumption of sampling's improved conditioning over the MFE prediction. Furthermore, because we find no correlation between conditioning and MFE accuracy, the presence of both well- and ill-conditioned sequences indicates the continued need for both thermodynamic model refinements and alternate RNA structure prediction methods beyond the physics-based ones. Copyright © 2017. Published by Elsevier Inc.

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.

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

PubMed

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

2017-10-01

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

Generation of structural topologies using efficient technique based on sorted compliances

NASA Astrophysics Data System (ADS)

Mazur, Monika; Tajs-Zielińska, Katarzyna; Bochenek, Bogdan

2018-01-01

Topology optimization, although well recognized is still widely developed. It has gained recently more attention since large computational ability become available for designers. This process is stimulated simultaneously by variety of emerging, innovative optimization methods. It is observed that traditional gradient-based mathematical programming algorithms, in many cases, are replaced by novel and e cient heuristic methods inspired by biological, chemical or physical phenomena. These methods become useful tools for structural optimization because of their versatility and easy numerical implementation. In this paper engineering implementation of a novel heuristic algorithm for minimum compliance topology optimization is discussed. The performance of the topology generator is based on implementation of a special function utilizing information of compliance distribution within the design space. With a view to cope with engineering problems the algorithm has been combined with structural analysis system Ansys.

Synthetic Self-Healing Methods

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

Bello, Mollie

Given enough time, pressure, temperature fluctuation, and stress any material will fail. Currently, synthesized materials make up a large part of our everyday lives, and are used in a number of important applications such as; space travel, under water devices, precise instrumentation, transportation, and infrastructure. Structural failure of these material scan lead to expensive and dangerous consequences. In an attempt to prolong the life spans of specific materials and reduce efforts put into repairing them, biologically inspired, self-healing systems have been extensively investigated. The current review explores recent advances in three methods of synthesized self-healing: capsule based, vascular, and intrinsic.more » Ideally, self-healing materials require no human intervention to promote healing, are capable of surviving all the steps of polymer processing, and heal the same location repeatedly. Only the vascular method holds up to all of these idealities.« less

A novel autonomous real-time position method based on polarized light and geomagnetic field.

PubMed

Wang, Yinlong; Chu, Jinkui; Zhang, Ran; Wang, Lu; Wang, Zhiwen

2015-04-08

Many animals exploit polarized light in order to calibrate their magnetic compasses for navigation. For example, some birds are equipped with biological magnetic and celestial compasses enabling them to migrate between the Western and Eastern Hemispheres. The Vikings' ability to derive true direction from polarized light is also widely accepted. However, their amazing navigational capabilities are still not completely clear. Inspired by birds' and Vikings' ancient navigational skills. Here we present a combined real-time position method based on the use of polarized light and geomagnetic field. The new method works independently of any artificial signal source with no accumulation of errors and can obtain the position and the orientation directly. The novel device simply consists of two polarized light sensors, a 3-axis compass and a computer. The field experiments demonstrate device performance.

A novel autonomous real-time position method based on polarized light and geomagnetic field

PubMed Central

Wang, Yinlong; Chu, Jinkui; Zhang, Ran; Wang, Lu; Wang, Zhiwen

2015-01-01

Many animals exploit polarized light in order to calibrate their magnetic compasses for navigation. For example, some birds are equipped with biological magnetic and celestial compasses enabling them to migrate between the Western and Eastern Hemispheres. The Vikings' ability to derive true direction from polarized light is also widely accepted. However, their amazing navigational capabilities are still not completely clear. Inspired by birds' and Vikings' ancient navigational skills. Here we present a combined real-time position method based on the use of polarized light and geomagnetic field. The new method works independently of any artificial signal source with no accumulation of errors and can obtain the position and the orientation directly. The novel device simply consists of two polarized light sensors, a 3-axis compass and a computer. The field experiments demonstrate device performance. PMID:25851793

A novel autonomous real-time position method based on polarized light and geomagnetic field

NASA Astrophysics Data System (ADS)

Wang, Yinlong; Chu, Jinkui; Zhang, Ran; Wang, Lu; Wang, Zhiwen

2015-04-01

Many animals exploit polarized light in order to calibrate their magnetic compasses for navigation. For example, some birds are equipped with biological magnetic and celestial compasses enabling them to migrate between the Western and Eastern Hemispheres. The Vikings' ability to derive true direction from polarized light is also widely accepted. However, their amazing navigational capabilities are still not completely clear. Inspired by birds' and Vikings' ancient navigational skills. Here we present a combined real-time position method based on the use of polarized light and geomagnetic field. The new method works independently of any artificial signal source with no accumulation of errors and can obtain the position and the orientation directly. The novel device simply consists of two polarized light sensors, a 3-axis compass and a computer. The field experiments demonstrate device performance.

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.

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.

Honey bee-inspired algorithms for SNP haplotype reconstruction problem

NASA Astrophysics Data System (ADS)

PourkamaliAnaraki, Maryam; Sadeghi, Mehdi

2016-03-01

Reconstructing haplotypes from SNP fragments is an important problem in computational biology. There have been a lot of interests in this field because haplotypes have been shown to contain promising data for disease association research. It is proved that haplotype reconstruction in Minimum Error Correction model is an NP-hard problem. Therefore, several methods such as clustering techniques, evolutionary algorithms, neural networks and swarm intelligence approaches have been proposed in order to solve this problem in appropriate time. In this paper, we have focused on various evolutionary clustering techniques and try to find an efficient technique for solving haplotype reconstruction problem. It can be referred from our experiments that the clustering methods relying on the behaviour of honey bee colony in nature, specifically bees algorithm and artificial bee colony methods, are expected to result in more efficient solutions. An application program of the methods is available at the following link. http://www.bioinf.cs.ipm.ir/software/haprs/

Magnetic Field Triggered Multicycle Damage Sensing and Self Healing.

PubMed

Ahmed, Anansa S; Ramanujan, R V

2015-09-08

Multifunctional materials inspired by biological structures have attracted great interest, e.g. for wearable/ flexible "skin" and smart coatings. A current challenge in this area is to develop an artificial material which mimics biological skin by simultaneously displaying color change on damage as well as self healing of the damaged region. Here we report, for the first time, the development of a damage sensing and self healing magnet-polymer composite (Magpol), which actively responds to an external magnetic field. We incorporated reversible sensing using mechanochromic molecules in a shape memory thermoplastic matrix. Exposure to an alternating magnetic field (AMF) triggers shape recovery and facilitates damage repair. Magpol exhibited a linear strain response upto 150% strain and complete recovery after healing. We have demonstrated the use of this concept in a reusable biomedical device i.e., coated guidewires. Our findings offer a new synergistic method to bestow multifunctionality for applications ranging from medical device coatings to adaptive wing structures.

Natural Products and Their Mimics as Targets of Opportunity for Discovery

PubMed Central

2017-01-01

Diverse structural types of natural products and their mimics have served as targets of opportunity in our laboratory to inspire the discovery and development of new methods and strategies to assemble polyfunctional and polycyclic molecular architectures. Furthermore, our efforts toward identifying novel compounds having useful biological properties led to the creation of new targets, many of which posed synthetic challenges that required the invention of new methodology. In this Perspective, selected examples of how we have exploited a diverse range of natural products and their mimics to create, explore, and solve a variety of problems in chemistry and biology will be discussed. The journey was not without its twists and turns, but the unexpected often led to new revelations and insights. Indeed, in our recent excursion into applications of synthetic organic chemistry to neuroscience, avoiding the more-traveled paths was richly rewarding. PMID:28738152

Dispersion-cancelled biological imaging with quantum-inspired interferometry

PubMed Central

Mazurek, M. D.; Schreiter, K. M.; Prevedel, R.; Kaltenbaek, R.; Resch, K. J.

2013-01-01

Quantum information science promises transformative impact over a range of key technologies in computing, communication, and sensing. A prominent example uses entangled photons to overcome the resolution-degrading effects of dispersion in the medical-imaging technology, optical coherence tomography. The quantum solution introduces new challenges: inherently low signal and artifacts, additional unwanted signal features. It has recently been shown that entanglement is not a requirement for automatic dispersion cancellation. Such classical techniques could solve the low-signal problem, however they all still suffer from artifacts. Here, we introduce a method of chirped-pulse interferometry based on shaped laser pulses, and use it to produce artifact-free, high-resolution, dispersion-cancelled images of the internal structure of a biological sample. Our work fulfills one of the promises of quantum technologies: automatic-dispersion-cancellation interferometry in biomedical imaging. It also shows how subtle differences between a quantum technique and its classical analogue may have unforeseen, yet beneficial, consequences. PMID:23545597

Bio-inspired band gap engineering of zinc oxide by intracrystalline incorporation of amino acids.

PubMed

Brif, Anastasia; Ankonina, Guy; Drathen, Christina; Pokroy, Boaz

2014-01-22

Bandgap engineering of zinc oxide semiconductors can be achieved using a bio-inspired method. During a bioInspired crystallization process, incorporation of amino acids into the crystal structure of ZnO induces lattice strain that leads to linear bandgap shifts. This allows for fine tuning of the bandgap in a bio-inspired route. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Robustness of a distributed neural network controller for locomotion in a hexapod robot

NASA Technical Reports Server (NTRS)

Chiel, Hillel J.; Beer, Randall D.; Quinn, Roger D.; Espenschied, Kenneth S.

1992-01-01

A distributed neural-network controller for locomotion, based on insect neurobiology, has been used to control a hexapod robot. How robust is this controller? Disabling any single sensor, effector, or central component did not prevent the robot from walking. Furthermore, statically stable gaits could be established using either sensor input or central connections. Thus, a complex interplay between central neural elements and sensor inputs is responsible for the robustness of the controller and its ability to generate a continuous range of gaits. These results suggest that biologically inspired neural-network controllers may be a robust method for robotic control.

Swarm intelligence metaheuristics for enhanced data analysis and optimization.

PubMed

Hanrahan, Grady

2011-09-21

The swarm intelligence (SI) computing paradigm has proven itself as a comprehensive means of solving complicated analytical chemistry problems by emulating biologically-inspired processes. As global optimum search metaheuristics, associated algorithms have been widely used in training neural networks, function optimization, prediction and classification, and in a variety of process-based analytical applications. The goal of this review is to provide readers with critical insight into the utility of swarm intelligence tools as methods for solving complex chemical problems. Consideration will be given to algorithm development, ease of implementation and model performance, detailing subsequent influences on a number of application areas in the analytical, bioanalytical and detection sciences.

Evolutionary crossroads in developmental biology: Cnidaria

PubMed Central

Technau, Ulrich; Steele, Robert E.

2011-01-01

There is growing interest in the use of cnidarians (corals, sea anemones, jellyfish and hydroids) to investigate the evolution of key aspects of animal development, such as the formation of the third germ layer (mesoderm), the nervous system and the generation of bilaterality. The recent sequencing of the Nematostella and Hydra genomes, and the establishment of methods for manipulating gene expression, have inspired new research efforts using cnidarians. Here, we present the main features of cnidarian models and their advantages for research, and summarize key recent findings using these models that have informed our understanding of the evolution of the developmental processes underlying metazoan body plan formation. PMID:21389047

Evolutionary crossroads in developmental biology: Cnidaria.

PubMed

Technau, Ulrich; Steele, Robert E

2011-04-01

There is growing interest in the use of cnidarians (corals, sea anemones, jellyfish and hydroids) to investigate the evolution of key aspects of animal development, such as the formation of the third germ layer (mesoderm), the nervous system and the generation of bilaterality. The recent sequencing of the Nematostella and Hydra genomes, and the establishment of methods for manipulating gene expression, have inspired new research efforts using cnidarians. Here, we present the main features of cnidarian models and their advantages for research, and summarize key recent findings using these models that have informed our understanding of the evolution of the developmental processes underlying metazoan body plan formation.

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.

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

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.

Feeling Is Believing: Inspiration Encourages Belief in God.

PubMed

Critcher, Clayton R; Lee, Chan Jean

2018-05-01

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

Evidence Combination From an Evolutionary Game Theory Perspective.

PubMed

Deng, Xinyang; Han, Deqiang; Dezert, Jean; Deng, Yong; Shyr, Yu

2016-09-01

Dempster-Shafer evidence theory is a primary methodology for multisource information fusion because it is good at dealing with uncertain information. This theory provides a Dempster's rule of combination to synthesize multiple evidences from various information sources. However, in some cases, counter-intuitive results may be obtained based on that combination rule. Numerous new or improved methods have been proposed to suppress these counter-intuitive results based on perspectives, such as minimizing the information loss or deviation. Inspired by evolutionary game theory, this paper considers a biological and evolutionary perspective to study the combination of evidences. An evolutionary combination rule (ECR) is proposed to help find the most biologically supported proposition in a multievidence system. Within the proposed ECR, we develop a Jaccard matrix game to formalize the interaction between propositions in evidences, and utilize the replicator dynamics to mimick the evolution of propositions. Experimental results show that the proposed ECR can effectively suppress the counter-intuitive behaviors appeared in typical paradoxes of evidence theory, compared with many existing methods. Properties of the ECR, such as solution's stability and convergence, have been mathematically proved as well.

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.

Efficient digital implementation of a conductance-based globus pallidus neuron and the dynamics analysis

NASA Astrophysics Data System (ADS)

Yang, Shuangming; Wei, Xile; Deng, Bin; Liu, Chen; Li, Huiyan; Wang, Jiang

2018-03-01

Balance between biological plausibility of dynamical activities and computational efficiency is one of challenging problems in computational neuroscience and neural system engineering. This paper proposes a set of efficient methods for the hardware realization of the conductance-based neuron model with relevant dynamics, targeting reproducing the biological behaviors with low-cost implementation on digital programmable platform, which can be applied in wide range of conductance-based neuron models. Modified GP neuron models for efficient hardware implementation are presented to reproduce reliable pallidal dynamics, which decode the information of basal ganglia and regulate the movement disorder related voluntary activities. Implementation results on a field-programmable gate array (FPGA) demonstrate that the proposed techniques and models can reduce the resource cost significantly and reproduce the biological dynamics accurately. Besides, the biological behaviors with weak network coupling are explored on the proposed platform, and theoretical analysis is also made for the investigation of biological characteristics of the structured pallidal oscillator and network. The implementation techniques provide an essential step towards the large-scale neural network to explore the dynamical mechanisms in real time. Furthermore, the proposed methodology enables the FPGA-based system a powerful platform for the investigation on neurodegenerative diseases and real-time control of bio-inspired neuro-robotics.

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.

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.

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.

Bio-steps beyond Turing.

PubMed

Calude, Cristian S; Păun, Gheorghe

2004-11-01

Are there 'biologically computing agents' capable to compute Turing uncomputable functions? It is perhaps tempting to dismiss this question with a negative answer. Quite the opposite, for the first time in the literature on molecular computing we contend that the answer is not theoretically negative. Our results will be formulated in the language of membrane computing (P systems). Some mathematical results presented here are interesting in themselves. In contrast with most speed-up methods which are based on non-determinism, our results rest upon some universality results proved for deterministic P systems. These results will be used for building "accelerated P systems". In contrast with the case of Turing machines, acceleration is a part of the hardware (not a quality of the environment) and it is realised either by decreasing the size of "reactors" or by speeding-up the communication channels. Consequently, two acceleration postulates of biological inspiration are introduced; each of them poses specific questions to biology. Finally, in a more speculative part of the paper, we will deal with Turing non-computability activity of the brain and possible forms of (extraterrestrial) intelligence.

Materiomics: biological protein materials, from nano to macro.

PubMed

Cranford, Steven; Buehler, Markus J

2010-11-12

Materiomics is an emerging field of science that provides a basis for multiscale material system characterization, inspired in part by natural, for example, protein-based materials. Here we outline the scope and explain the motivation of the field of materiomics, as well as demonstrate the benefits of a materiomic approach in the understanding of biological and natural materials as well as in the design of de novo materials. We discuss recent studies that exemplify the impact of materiomics - discovering Nature's complexity through a materials science approach that merges concepts of material and structure throughout all scales and incorporates feedback loops that facilitate sensing and resulting structural changes at multiple scales. The development and application of materiomics is illustrated for the specific case of protein-based materials, which constitute the building blocks of a variety of biological systems such as tendon, bone, skin, spider silk, cells, and tissue, as well as natural composite material systems (a combination of protein-based and inorganic constituents) such as nacre and mollusk shells, and other natural multiscale systems such as cellulose-based plant and wood materials. An important trait of these materials is that they display distinctive hierarchical structures across multiple scales, where molecular details are exhibited in macroscale mechanical responses. Protein materials are intriguing examples of materials that balance multiple tasks, representing some of the most sustainable material solutions that integrate structure and function despite severe limitations in the quality and quantity of material building blocks. However, up until now, our attempts to analyze and replicate Nature's materials have been hindered by our lack of fundamental understanding of these materials' intricate hierarchical structures, scale-bridging mechanisms, and complex material components that bestow protein-based materials their unique properties. Recent advances in analytical tools and experimental methods allow a holistic view of such a hierarchical biological material system. The integration of these approaches and amalgamation of material properties at all scale levels to develop a complete description of a material system falls within the emerging field of materiomics. Materiomics is the result of the convergence of engineering and materials science with experimental and computational biology in the context of natural and synthetic materials. Through materiomics, fundamental advances in our understanding of structure-property-process relations of biological systems contribute to the mechanistic understanding of certain diseases and facilitate the development of novel biological, biologically inspired, and completely synthetic materials for applications in medicine (biomaterials), nanotechnology, and engineering.

Materiomics: biological protein materials, from nano to macro

PubMed Central

Cranford, Steven; Buehler, Markus J

2010-01-01

Materiomics is an emerging field of science that provides a basis for multiscale material system characterization, inspired in part by natural, for example, protein-based materials. Here we outline the scope and explain the motivation of the field of materiomics, as well as demonstrate the benefits of a materiomic approach in the understanding of biological and natural materials as well as in the design of de novo materials. We discuss recent studies that exemplify the impact of materiomics – discovering Nature’s complexity through a materials science approach that merges concepts of material and structure throughout all scales and incorporates feedback loops that facilitate sensing and resulting structural changes at multiple scales. The development and application of materiomics is illustrated for the specific case of protein-based materials, which constitute the building blocks of a variety of biological systems such as tendon, bone, skin, spider silk, cells, and tissue, as well as natural composite material systems (a combination of protein-based and inorganic constituents) such as nacre and mollusk shells, and other natural multiscale systems such as cellulose-based plant and wood materials. An important trait of these materials is that they display distinctive hierarchical structures across multiple scales, where molecular details are exhibited in macroscale mechanical responses. Protein materials are intriguing examples of materials that balance multiple tasks, representing some of the most sustainable material solutions that integrate structure and function despite severe limitations in the quality and quantity of material building blocks. However, up until now, our attempts to analyze and replicate Nature’s materials have been hindered by our lack of fundamental understanding of these materials’ intricate hierarchical structures, scale-bridging mechanisms, and complex material components that bestow protein-based materials their unique properties. Recent advances in analytical tools and experimental methods allow a holistic view of such a hierarchical biological material system. The integration of these approaches and amalgamation of material properties at all scale levels to develop a complete description of a material system falls within the emerging field of materiomics. Materiomics is the result of the convergence of engineering and materials science with experimental and computational biology in the context of natural and synthetic materials. Through materiomics, fundamental advances in our understanding of structure–property–process relations of biological systems contribute to the mechanistic understanding of certain diseases and facilitate the development of novel biological, biologically inspired, and completely synthetic materials for applications in medicine (biomaterials), nanotechnology, and engineering. PMID:24198478

Pioneering topological methods for network-based drug-target prediction by exploiting a brain-network self-organization theory.

PubMed

Durán, Claudio; Daminelli, Simone; Thomas, Josephine M; Haupt, V Joachim; Schroeder, Michael; Cannistraci, Carlo Vittorio

2017-04-26

The bipartite network representation of the drug-target interactions (DTIs) in a biosystem enhances understanding of the drugs' multifaceted action modes, suggests therapeutic switching for approved drugs and unveils possible side effects. As experimental testing of DTIs is costly and time-consuming, computational predictors are of great aid. Here, for the first time, state-of-the-art DTI supervised predictors custom-made in network biology were compared-using standard and innovative validation frameworks-with unsupervised pure topological-based models designed for general-purpose link prediction in bipartite networks. Surprisingly, our results show that the bipartite topology alone, if adequately exploited by means of the recently proposed local-community-paradigm (LCP) theory-initially detected in brain-network topological self-organization and afterwards generalized to any complex network-is able to suggest highly reliable predictions, with comparable performance with the state-of-the-art-supervised methods that exploit additional (non-topological, for instance biochemical) DTI knowledge. Furthermore, a detailed analysis of the novel predictions revealed that each class of methods prioritizes distinct true interactions; hence, combining methodologies based on diverse principles represents a promising strategy to improve drug-target discovery. To conclude, this study promotes the power of bio-inspired computing, demonstrating that simple unsupervised rules inspired by principles of topological self-organization and adaptiveness arising during learning in living intelligent systems (like the brain) can efficiently equal perform complicated algorithms based on advanced, supervised and knowledge-based engineering. © The Author 2017. Published by Oxford University Press.

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

PubMed

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

2011-10-11

We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These results hold for both real and artificial data, for all observability scenarios considered, and for all amounts of noise added to the artificial data. In sum, the meta-heuristic methods considered are suitable for estimating the parameters in the ODE model of the dynamics of endocytosis under a range of conditions: With the model and conditions being representative of parameter estimation tasks in ODE models of biochemical systems, our results clearly highlight the promise of bio-inspired meta-heuristic methods for parameter estimation in dynamic system models within system biology.

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

PubMed Central

2011-01-01

Background We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. Results We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Conclusions Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These results hold for both real and artificial data, for all observability scenarios considered, and for all amounts of noise added to the artificial data. In sum, the meta-heuristic methods considered are suitable for estimating the parameters in the ODE model of the dynamics of endocytosis under a range of conditions: With the model and conditions being representative of parameter estimation tasks in ODE models of biochemical systems, our results clearly highlight the promise of bio-inspired meta-heuristic methods for parameter estimation in dynamic system models within system biology. PMID:21989196

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.

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.

Extraction of Blebs in Human Embryonic Stem Cell Videos.

PubMed

Guan, Benjamin X; Bhanu, Bir; Talbot, Prue; Weng, Nikki Jo-Hao

2016-01-01

Blebbing is an important biological indicator in determining the health of human embryonic stem cells (hESC). Especially, areas of a bleb sequence in a video are often used to distinguish two cell blebbing behaviors in hESC: dynamic and apoptotic blebbings. This paper analyzes various segmentation methods for bleb extraction in hESC videos and introduces a bio-inspired score function to improve the performance in bleb extraction. Full bleb formation consists of bleb expansion and retraction. Blebs change their size and image properties dynamically in both processes and between frames. Therefore, adaptive parameters are needed for each segmentation method. A score function derived from the change of bleb area and orientation between consecutive frames is proposed which provides adaptive parameters for bleb extraction in videos. In comparison to manual analysis, the proposed method provides an automated fast and accurate approach for bleb sequence extraction.

Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

NASA Technical Reports Server (NTRS)

Huntsberger, Terry

2011-01-01

The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

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…

Development of quadruped walking locomotion gait generator using a hybrid method

NASA Astrophysics Data System (ADS)

Jasni, F.; Shafie, A. A.

2013-12-01

The earth, in many areas is hardly reachable by the wheeled or tracked locomotion system. Thus, walking locomotion system is becoming a favourite option for mobile robot these days. This is because of the ability of walking locomotion to move on the rugged and unlevel terrains. However, to develop a walking locomotion gait for a robot is not a simple task. Central Pattern Generator (CPGs) method is a biological inspired method that is introduced as a method to develop the gait for the walking robot recently to tackle the issue faced by the conventional method of pre-designed trajectory based method. However, research shows that even the CPG method do have some limitations. Thus, in this paper, a hybrid method that combines CPG and the pre-designed trajectory based method is introduced to develop a walking gait for quadruped walking robot. The 3-D foot trajectories and the joint angle trajectories developed using the proposed method are compared with the data obtained via the conventional method of pre-designed trajectory to confirm the performance.

Natural products as inspiration for the development of new synthetic methods.

PubMed

Ma, Zhiqiang; Chen, Chuo

2018-01-01

Natural products have played an important role in shaping modern synthetic organic chemistry. In particular, their complex molecular skeletons have stimulated the development of many new synthetic methods. We highlight in this article some recent examples of synthetic design inspired by the biosynthesis of natural products.

Improving clustering with metabolic pathway data.

PubMed

Milone, Diego H; Stegmayer, Georgina; López, Mariana; Kamenetzky, Laura; Carrari, Fernando

2014-04-10

It is a common practice in bioinformatics to validate each group returned by a clustering algorithm through manual analysis, according to a-priori biological knowledge. This procedure helps finding functionally related patterns to propose hypotheses for their behavior and the biological processes involved. Therefore, this knowledge is used only as a second step, after data are just clustered according to their expression patterns. Thus, it could be very useful to be able to improve the clustering of biological data by incorporating prior knowledge into the cluster formation itself, in order to enhance the biological value of the clusters. A novel training algorithm for clustering is presented, which evaluates the biological internal connections of the data points while the clusters are being formed. Within this training algorithm, the calculation of distances among data points and neurons centroids includes a new term based on information from well-known metabolic pathways. The standard self-organizing map (SOM) training versus the biologically-inspired SOM (bSOM) training were tested with two real data sets of transcripts and metabolites from Solanum lycopersicum and Arabidopsis thaliana species. Classical data mining validation measures were used to evaluate the clustering solutions obtained by both algorithms. Moreover, a new measure that takes into account the biological connectivity of the clusters was applied. The results of bSOM show important improvements in the convergence and performance for the proposed clustering method in comparison to standard SOM training, in particular, from the application point of view. Analyses of the clusters obtained with bSOM indicate that including biological information during training can certainly increase the biological value of the clusters found with the proposed method. It is worth to highlight that this fact has effectively improved the results, which can simplify their further analysis.The algorithm is available as a web-demo at http://fich.unl.edu.ar/sinc/web-demo/bsom-lite/. The source code and the data sets supporting the results of this article are available at http://sourceforge.net/projects/sourcesinc/files/bsom.

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.

A VERSATILE SHARP INTERFACE IMMERSED BOUNDARY METHOD FOR INCOMPRESSIBLE FLOWS WITH COMPLEX BOUNDARIES

PubMed Central

Mittal, R.; Dong, H.; Bozkurttas, M.; Najjar, F.M.; Vargas, A.; von Loebbecke, A.

2010-01-01

A sharp interface immersed boundary method for simulating incompressible viscous flow past three-dimensional immersed bodies is described. The method employs a multi-dimensional ghost-cell methodology to satisfy the boundary conditions on the immersed boundary and the method is designed to handle highly complex three-dimensional, stationary, moving and/or deforming bodies. The complex immersed surfaces are represented by grids consisting of unstructured triangular elements; while the flow is computed on non-uniform Cartesian grids. The paper describes the salient features of the methodology with special emphasis on the immersed boundary treatment for stationary and moving boundaries. Simulations of a number of canonical two- and three-dimensional flows are used to verify the accuracy and fidelity of the solver over a range of Reynolds numbers. Flow past suddenly accelerated bodies are used to validate the solver for moving boundary problems. Finally two cases inspired from biology with highly complex three-dimensional bodies are simulated in order to demonstrate the versatility of the method. PMID:20216919

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

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

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.

Utilizing knowledge base of amino acids structural neighborhoods to predict protein-protein interaction sites.

PubMed

Jelínek, Jan; Škoda, Petr; Hoksza, David

2017-12-06

Protein-protein interactions (PPI) play a key role in an investigation of various biochemical processes, and their identification is thus of great importance. Although computational prediction of which amino acids take part in a PPI has been an active field of research for some time, the quality of in-silico methods is still far from perfect. We have developed a novel prediction method called INSPiRE which benefits from a knowledge base built from data available in Protein Data Bank. All proteins involved in PPIs were converted into labeled graphs with nodes corresponding to amino acids and edges to pairs of neighboring amino acids. A structural neighborhood of each node was then encoded into a bit string and stored in the knowledge base. When predicting PPIs, INSPiRE labels amino acids of unknown proteins as interface or non-interface based on how often their structural neighborhood appears as interface or non-interface in the knowledge base. We evaluated INSPiRE's behavior with respect to different types and sizes of the structural neighborhood. Furthermore, we examined the suitability of several different features for labeling the nodes. Our evaluations showed that INSPiRE clearly outperforms existing methods with respect to Matthews correlation coefficient. In this paper we introduce a new knowledge-based method for identification of protein-protein interaction sites called INSPiRE. Its knowledge base utilizes structural patterns of known interaction sites in the Protein Data Bank which are then used for PPI prediction. Extensive experiments on several well-established datasets show that INSPiRE significantly surpasses existing PPI approaches.

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.

MIANN models in medicinal, physical and organic chemistry.

PubMed

González-Díaz, Humberto; Arrasate, Sonia; Sotomayor, Nuria; Lete, Esther; Munteanu, Cristian R; Pazos, Alejandro; Besada-Porto, Lina; Ruso, Juan M

2013-01-01

Reducing costs in terms of time, animal sacrifice, and material resources with computational methods has become a promising goal in Medicinal, Biological, Physical and Organic Chemistry. There are many computational techniques that can be used in this sense. In any case, almost all these methods focus on few fundamental aspects including: type (1) methods to quantify the molecular structure, type (2) methods to link the structure with the biological activity, and others. In particular, MARCH-INSIDE (MI), acronym for Markov Chain Invariants for Networks Simulation and Design, is a well-known method for QSAR analysis useful in step (1). In addition, the bio-inspired Artificial-Intelligence (AI) algorithms called Artificial Neural Networks (ANNs) are among the most powerful type (2) methods. We can combine MI with ANNs in order to seek QSAR models, a strategy which is called herein MIANN (MI & ANN models). One of the first applications of the MIANN strategy was in the development of new QSAR models for drug discovery. MIANN strategy has been expanded to the QSAR study of proteins, protein-drug interactions, and protein-protein interaction networks. In this paper, we review for the first time many interesting aspects of the MIANN strategy including theoretical basis, implementation in web servers, and examples of applications in Medicinal and Biological chemistry. We also report new applications of the MIANN strategy in Medicinal chemistry and the first examples in Physical and Organic Chemistry, as well. In so doing, we developed new MIANN models for several self-assembly physicochemical properties of surfactants and large reaction networks in organic synthesis. In some of the new examples we also present experimental results which were not published up to date.

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.

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.

A bio-molecular inspired electronic architecture: bio-based device concepts for enhanced sensing (Invited Paper)

NASA Astrophysics Data System (ADS)

Woolard, Dwight L.; Luo, Ying; Gelmont, Boris L.; Globus, Tatiana; Jensen, James O.

2005-05-01

A biological(bio)-molecular inspired electronic architecture is presented that offers the potential for defining nanoscale sensor platforms with enhanced capabilities for sensing terahertz (THz) frequency bio-signatures. This architecture makes strategic use of integrated biological elements to enable communication and high-level function within densely-packed nanoelectronic systems. In particular, this architecture introduces a new paradigm for establishing hybrid Electro-THz-Optical (ETO) communication channels where the THz-frequency spectral characteristics that are uniquely associated with the embedded bio-molecules are utilized directly. Since the functionality of this architecture is built upon the spectral characteristics of bio-molecules, this immediately allows for defining new methods for enhanced sensing of THz bio-signatures. First, this integrated sensor concept greatly facilitates the collection of THz bio-signatures associated with embedded bio-molecules via interactions with the time-dependent signals propagating through the nanoelectronic circuit. Second, it leads to a new Multi-State Spectral Sensing (MS3) approach where bio-signature information can be collected from multiple metastable state conformations. This paper will also introduce a new class of prototype devices that utilize THz-sensitive bio-molecules to achieve molecular-level sensing and functionality. Here, new simulation results are presented for a class of bio-molecular components that exhibit the prescribed type of ETO characteristics required for realizing integrated sensor platforms. Most noteworthy, this research derives THz spectral bio-signatures for organic molecules that are amenable to photo-induced metastable-state conformations and establishes an initial scientific foundation and design blueprint for an enhanced THz bio-signature sensing capability.

Supporting Creative Responses in Design Education--The Development and Application of the Graphic Design Composition Method

ERIC Educational Resources Information Center

Lu, Hui-Ping; Chen, Jun-Hong; Lee, Chang-Franw

2016-01-01

Inspiration is the primary element of good design. Designers, however, also risk not being able to find inspiration. Novice designers commonly find themselves to be depressed during the conceptual design phase when they fail to find inspiration and the information to be creative. Accordingly, under the graphic design parameter, we have developed…

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.

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.

Hydroxyapatite crystals biologically inspired on titanium by using an organic template based on the copolymer of acrylic acid and itaconic acid.

PubMed

Zhang, Chao; Li, Zhi-An; Cheng, Xiang-Rong; Xiao, Qun; Li, Hong-Bo

2010-01-01

Hydroxyapatite coating on metal implants is an effective method to enhance bioactive properties of the metal surface. We report here a method to coat the Ti-6Al-4V alloy with hydroxyapatite crystals. After alkaline/heat treatment, the spontaneous growth of organoapatite on titanium alloy surface involves sequential preadsorption of titanium isopropoxide (TIPO) and the copolymer of acrylic acid and itaconic acid on the metal, followed by exposure to simulated body fluid (SBF). The organoapatite characterization of the coating was carried out by scanning electron microscopy, energy dispersive spectrometer, and X-ray diffraction. The copolymer of acrylic acid and itaconic acid overlayer which is rich of carboxylate groups can lead to the deposition of needle-like and homogeneous HA on the surface after immersion in SBF.

Paper-Based MicroRNA Expression Profiling from Plasma and Circulating Tumor Cells.

PubMed

Leong, Sai Mun; Tan, Karen Mei-Ling; Chua, Hui Wen; Huang, Mo-Chao; Cheong, Wai Chye; Li, Mo-Huang; Tucker, Steven; Koay, Evelyn Siew-Chuan

2017-03-01

Molecular characterization of circulating tumor cells (CTCs) holds great promise for monitoring metastatic progression and characterizing metastatic disease. However, leukocyte and red blood cell contamination of routinely isolated CTCs makes CTC-specific molecular characterization extremely challenging. Here we report the use of a paper-based medium for efficient extraction of microRNAs (miRNAs) from limited amounts of biological samples such as rare CTCs harvested from cancer patient blood. Specifically, we devised a workflow involving the use of Flinders Technology Associates (FTA) ® Elute Card with a digital PCR-inspired "partitioning" method to extract and purify miRNAs from plasma and CTCs. We demonstrated the sensitivity of this method to detect miRNA expression from as few as 3 cancer cells spiked into human blood. Using this method, background miRNA expression was excluded from contaminating blood cells, and CTC-specific miRNA expression profiles were derived from breast and colorectal cancer patients. Plasma separated out during purification of CTCs could likewise be processed using the same paper-based method for miRNA detection, thereby maximizing the amount of patient-specific information that can be derived from a single blood draw. Overall, this paper-based extraction method enables an efficient, cost-effective workflow for maximized recovery of small RNAs from limited biological samples for downstream molecular analyses. © 2016 American Association for Clinical Chemistry.

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.

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

Body composition of university students by hydrostatic weighing and skinfold measurement.

PubMed

Jürimäe, T; Jagomägi, G; Lepp, T

1992-12-01

The body composition of 124 male and 70 female Tartu University students was measured by three different methods: hydrostatic weighing by maximal expiration, hydrostatic weighing by maximal inspiration and subcutaneous fat thickness measurements. Our results show that the proposed body density measuring method by maximal expiration is simple, reliable and applicable not only in indoor swimming pools but in field conditions as well. The second new hydrostatic weighing apparatus is more comfortable for the subjects where the body density is measured at maximal inspiration. The mean body density of males was somewhat higher when measured by the maximal inspiration (1.066 +/- 0.012 g.ml-1) than when measured by the maximal expiration (1.063 +/- 0.009 g.ml-1, p < 0.05). For females, on the contrary, the maximal expiration method (1.044 +/- 0.010 g.ml-1) yielded a higher body density value than when measured by the maximal inspiration (1.040 +/- 0.011 g.ml-1, p > 0.05). The body fat percentage measured by skinfold thickness correlated significantly with the body fat percentage calculated by body density by maximal expiration (males r = 0.420, females r = 0.531) and inspiration (males r = 0.507, females r = 0.663). We must conclude that the presented two methods of measuring body density offer new possibilities for densitometric analysis without the need for expensive laboratory equipment.

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.

Artificial Immune System for Recognizing Patterns

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance

2005-01-01

A method of recognizing or classifying patterns is based on an artificial immune system (AIS), which includes an algorithm and a computational model of nonlinear dynamics inspired by the behavior of a biological immune system. The method has been proposed as the theoretical basis of the computational portion of a star-tracking system aboard a spacecraft. In that system, a newly acquired star image would be treated as an antigen that would be matched by an appropriate antibody (an entry in a star catalog). The method would enable rapid convergence, would afford robustness in the face of noise in the star sensors, would enable recognition of star images acquired in any sensor or spacecraft orientation, and would not make an excessive demand on the computational resources of a typical spacecraft. Going beyond the star-tracking application, the AIS-based pattern-recognition method is potentially applicable to pattern- recognition and -classification processes for diverse purposes -- for example, reconnaissance, detecting intruders, and mining data.

Three-Dimensional-Printing of Bio-Inspired Composites.

PubMed

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

2016-02-01

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

Three-Dimensional-Printing of Bio-Inspired Composites

PubMed Central

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

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

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

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

Wave study of compound eyes for efficient infrared detection

NASA Astrophysics Data System (ADS)

Kilinc, Takiyettin Oytun; Hayran, Zeki; Kocer, Hasan; Kurt, Hamza

2017-08-01

Improving sensitivity in the infrared spectrum is a challenging task. Detecting infrared light over a wide bandwidth and at low power consumption is very important. Novel solutions can be acquired by mimicking biological eyes such as compound eye with many individual lenses inspired from the nature. The nature provides many ingenious approaches of sensing and detecting the surrounding environment. Even though compound eye consists of small optical units, it can detect wide-angle electromagnetic waves and it has high transmission and low reflection loss. Insects have eyes that are superior compared to human eyes (single-aperture eyes) in terms of compactness, robustness, wider field of view, higher sensitivity of light intensity and being cheap vision systems. All these desired properties are accompanied by an important drawback: lower spatial resolution. The first step to investigate the feasibility of bio-inspired optics in photodetectors is to perform light interaction with the optical system that gather light and detect it. The most common method used in natural vision systems is the ray analysis. Light wave characteristics are not taken into consideration in such analyses, such as the amount of energy at the focal point or photoreceptor site, the losses caused by reflection at the interfaces and absorption cannot be investigated. In this study, we present a bio-inspired optical detection system investigated by wave analysis. We numerically model the wave analysis based on Maxwell equations from the viewpoint of efficient light detection and revealing the light propagation after intercepting the first interface of the eye towards the photoreceptor site.

Chemical ubiquitination for decrypting a cellular code.

PubMed

Stanley, Mathew; Virdee, Satpal

2016-05-15

The modification of proteins with ubiquitin (Ub) is an important regulator of eukaryotic biology and deleterious perturbation of this process is widely linked to the onset of various diseases. The regulatory capacity of the Ub signal is high and, in part, arises from the capability of Ub to be enzymatically polymerised to form polyubiquitin (polyUb) chains of eight different linkage types. These distinct polyUb topologies can then be site-specifically conjugated to substrate proteins to elicit a number of cellular outcomes. Therefore, to further elucidate the biological significance of substrate ubiquitination, methodologies that allow the production of defined polyUb species, and substrate proteins that are site-specifically modified with them, are essential to progress our understanding. Many chemically inspired methods have recently emerged which fulfil many of the criteria necessary for achieving deeper insight into Ub biology. With a view to providing immediate impact in traditional biology research labs, the aim of this review is to provide an overview of the techniques that are available for preparing Ub conjugates and polyUb chains with focus on approaches that use recombinant protein building blocks. These approaches either produce a native isopeptide, or analogue thereof, that can be hydrolysable or non-hydrolysable by deubiquitinases. The most significant biological insights that have already been garnered using such approaches will also be summarized. © 2016 Authors; published by Portland Press Limited.

Magnetic Field Triggered Multicycle Damage Sensing and Self Healing

NASA Astrophysics Data System (ADS)

Ahmed, Anansa S.; Ramanujan, R. V.

2015-09-01

Multifunctional materials inspired by biological structures have attracted great interest, e.g. for wearable/ flexible “skin” and smart coatings. A current challenge in this area is to develop an artificial material which mimics biological skin by simultaneously displaying color change on damage as well as self healing of the damaged region. Here we report, for the first time, the development of a damage sensing and self healing magnet-polymer composite (Magpol), which actively responds to an external magnetic field. We incorporated reversible sensing using mechanochromic molecules in a shape memory thermoplastic matrix. Exposure to an alternating magnetic field (AMF) triggers shape recovery and facilitates damage repair. Magpol exhibited a linear strain response upto 150% strain and complete recovery after healing. We have demonstrated the use of this concept in a reusable biomedical device i.e., coated guidewires. Our findings offer a new synergistic method to bestow multifunctionality for applications ranging from medical device coatings to adaptive wing structures.

Holonic Rationale and Bio-inspiration on Design of Complex Emergent and Evolvable Systems

NASA Astrophysics Data System (ADS)

Leitao, Paulo

Traditional centralized and rigid control structures are becoming inflexible to face the requirements of reconfigurability, responsiveness and robustness, imposed by customer demands in the current global economy. The Holonic Manufacturing Systems (HMS) paradigm, which was pointed out as a suitable solution to face these requirements, translates the concepts inherited from social organizations and biology to the manufacturing world. It offers an alternative way of designing adaptive systems where the traditional centralized control is replaced by decentralization over distributed and autonomous entities organized in hierarchical structures formed by intermediate stable forms. In spite of its enormous potential, methods regarding the self-adaptation and self-organization of complex systems are still missing. This paper discusses how the insights from biology in connection with new fields of computer science can be useful to enhance the holonic design aiming to achieve more self-adaptive and evolvable systems. Special attention is devoted to the discussion of emergent behavior and self-organization concepts, and the way they can be combined with the holonic rationale.

Reversible manipulation of the G-quadruplex structures and enzymatic reactions through supramolecular host–guest interactions

PubMed Central

Tian, Tian; Song, Yanyan; Wei, Lai; Wang, Jiaqi; Fu, Boshi; He, Zhiyong; Yang, Xi-Ran; Wu, Fan; Xu, Guohua; Liu, Si-Min; Li, Conggang

2017-01-01

Abstract Supramolecular chemistry addresses intermolecular forces and consequently promises great flexibility and precision. Biological systems are often the inspirations for supramolecular research. The G-quadruplex (G4) belongs to one of the most important secondary structures in nucleic acids. Until recently, the supramolecular manipulation of the G4 has not been reported. The present study is the first to disclose a supramolecular switch for the reversible control of human telomere G4s. Moreover, this supramolecular switch has been successfully used to manipulate an enzymatic reaction. Using various methods, we show that cucurbit[7]uril preferably locks and encapsulates the positively charged piperidines of Razo through supramolecular interactions. They can switch the conformations of the DNA inhibitor between a flexible state and the rigid G4 and are therefore responsible for the reversible control of the thrombin activity. Thus, our findings open a promising route and exhibit potential applications in future studies of chemical biology. PMID:28115627

Magnetic Field Triggered Multicycle Damage Sensing and Self Healing

PubMed Central

Ahmed, Anansa S.; Ramanujan, R. V.

2015-01-01

Multifunctional materials inspired by biological structures have attracted great interest, e.g. for wearable/ flexible “skin” and smart coatings. A current challenge in this area is to develop an artificial material which mimics biological skin by simultaneously displaying color change on damage as well as self healing of the damaged region. Here we report, for the first time, the development of a damage sensing and self healing magnet-polymer composite (Magpol), which actively responds to an external magnetic field. We incorporated reversible sensing using mechanochromic molecules in a shape memory thermoplastic matrix. Exposure to an alternating magnetic field (AMF) triggers shape recovery and facilitates damage repair. Magpol exhibited a linear strain response upto 150% strain and complete recovery after healing. We have demonstrated the use of this concept in a reusable biomedical device i.e., coated guidewires. Our findings offer a new synergistic method to bestow multifunctionality for applications ranging from medical device coatings to adaptive wing structures. PMID:26348284

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

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

Smart Nacre-inspired Nanocomposites.

PubMed

Peng, Jingsong; Cheng, Qunfeng

2018-03-15

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

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

A multi-scaled approach for simulating chemical reaction systems.

PubMed

Burrage, Kevin; Tian, Tianhai; Burrage, Pamela

2004-01-01

In this paper we give an overview of some very recent work, as well as presenting a new approach, on the stochastic simulation of multi-scaled systems involving chemical reactions. In many biological systems (such as genetic regulation and cellular dynamics) there is a mix between small numbers of key regulatory proteins, and medium and large numbers of molecules. In addition, it is important to be able to follow the trajectories of individual molecules by taking proper account of the randomness inherent in such a system. We describe different types of simulation techniques (including the stochastic simulation algorithm, Poisson Runge-Kutta methods and the balanced Euler method) for treating simulations in the three different reaction regimes: slow, medium and fast. We then review some recent techniques on the treatment of coupled slow and fast reactions for stochastic chemical kinetics and present a new approach which couples the three regimes mentioned above. We then apply this approach to a biologically inspired problem involving the expression and activity of LacZ and LacY proteins in E. coli, and conclude with a discussion on the significance of this work. Copyright 2004 Elsevier Ltd.

Evidence Combination From an Evolutionary Game Theory Perspective

PubMed Central

Deng, Xinyang; Han, Deqiang; Dezert, Jean; Deng, Yong; Shyr, Yu

2017-01-01

Dempster-Shafer evidence theory is a primary methodology for multi-source information fusion because it is good at dealing with uncertain information. This theory provides a Dempster’s rule of combination to synthesize multiple evidences from various information sources. However, in some cases, counter-intuitive results may be obtained based on that combination rule. Numerous new or improved methods have been proposed to suppress these counter-intuitive results based on perspectives, such as minimizing the information loss or deviation. Inspired by evolutionary game theory, this paper considers a biological and evolutionary perspective to study the combination of evidences. An evolutionary combination rule (ECR) is proposed to help find the most biologically supported proposition in a multi-evidence system. Within the proposed ECR, we develop a Jaccard matrix game (JMG) to formalize the interaction between propositions in evidences, and utilize the replicator dynamics to mimick the evolution of propositions. Experimental results show that the proposed ECR can effectively suppress the counter-intuitive behaviors appeared in typical paradoxes of evidence theory, compared with many existing methods. Properties of the ECR, such as solution’s stability and convergence, have been mathematically proved as well. PMID:26285231

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...

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…

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.

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.

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

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.

Ernst Mach, George Sarton and the Empiry of Teaching Science Part I

ERIC Educational Resources Information Center

Siemsen, Hayo

2012-01-01

George Sarton had a strong influence on modern history of science. The method he pursued throughout his life was the method he had discovered in Ernst Mach's "Mechanics" when he was a student in Ghent. Sarton was in fact throughout his life implementing a research program inspired by the epistemology of Mach. Sarton in turn inspired many…

42 CFR 84.97 - Test for carbon dioxide in inspired gas; open- and closed-circuit apparatus; maximum allowable...

Code of Federal Regulations, 2013 CFR

2013-10-01

... machine. An acceptable method for measuring the concentration of carbon dioxide is described in Bureau of Mines Report of Investigations 6865, A Machine-Test Method for Measuring Carbon Dioxide in the Inspired... of 10.5 liters. (3) A sedentary breathing machine cam will be used. (4) The apparatus will be tested...

42 CFR 84.97 - Test for carbon dioxide in inspired gas; open- and closed-circuit apparatus; maximum allowable...

Code of Federal Regulations, 2012 CFR

2012-10-01

... machine. An acceptable method for measuring the concentration of carbon dioxide is described in Bureau of Mines Report of Investigations 6865, A Machine-Test Method for Measuring Carbon Dioxide in the Inspired... of 10.5 liters. (3) A sedentary breathing machine cam will be used. (4) The apparatus will be tested...

42 CFR 84.97 - Test for carbon dioxide in inspired gas; open- and closed-circuit apparatus; maximum allowable...

Code of Federal Regulations, 2014 CFR

2014-10-01

... machine. An acceptable method for measuring the concentration of carbon dioxide is described in Bureau of Mines Report of Investigations 6865, A Machine-Test Method for Measuring Carbon Dioxide in the Inspired... of 10.5 liters. (3) A sedentary breathing machine cam will be used. (4) The apparatus will be tested...

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 engineering—bioengineering.

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.

Biologically Inspired Synthesis Route to Three-Dimensionally Structured Inorganic Thin Films

DOE PAGES

Schwenzer, Birgit; Morse, Daniel E.

2008-01-01

Inorganic thin films (hydroxide, oxide, and phosphate materials) that are textured on a submicron scale have been prepared from aqueous metal salt solutions at room temperature using vapor-diffusion catalysis. This generic synthesis approach mimics the essential advantages of the catalytic and structure-directing mechanisms observed for the formation of silica skeletons of marine sponges. Chemical composition, crystallinity, and the three-dimensional morphology of films prepared by this method are extremely sensitive to changes in the synthesis conditions, such as concentrations, reaction times, and the presence and nature of substrate materials. Focusing on different materials systems, the reaction mechanism for the formation ofmore » these thin films and the influence of different reaction parameters on the product are explained.« less

Fine-Tuning Tomato Agronomic Properties by Computational Genome Redesign

PubMed Central

Carrera, Javier; Fernández del Carmen, Asun; Fernández-Muñoz, Rafael; Rambla, Jose Luis; Pons, Clara; Jaramillo, Alfonso; Elena, Santiago F.; Granell, Antonio

2012-01-01

Considering cells as biofactories, we aimed to optimize its internal processes by using the same engineering principles that large industries are implementing nowadays: lean manufacturing. We have applied reverse engineering computational methods to transcriptomic, metabolomic and phenomic data obtained from a collection of tomato recombinant inbreed lines to formulate a kinetic and constraint-based model that efficiently describes the cellular metabolism from expression of a minimal core of genes. Based on predicted metabolic profiles, a close association with agronomic and organoleptic properties of the ripe fruit was revealed with high statistical confidence. Inspired in a synthetic biology approach, the model was used for exploring the landscape of all possible local transcriptional changes with the aim of engineering tomato fruits with fine-tuned biotechnological properties. The method was validated by the ability of the proposed genomes, engineered for modified desired agronomic traits, to recapitulate experimental correlations between associated metabolites. PMID:22685389

High-resolution of particle contacts via fluorophore exclusion in deep-imaging of jammed colloidal packings

NASA Astrophysics Data System (ADS)

Kyeyune-Nyombi, Eru; Morone, Flaviano; Liu, Wenwei; Li, Shuiqing; Gilchrist, M. Lane; Makse, Hernán A.

2018-01-01

Understanding the structural properties of random packings of jammed colloids requires an unprecedented high-resolution determination of the contact network providing mechanical stability to the packing. Here, we address the determination of the contact network by a novel strategy based on fluorophore signal exclusion of quantum dot nanoparticles from the contact points. We use fluorescence labeling schemes on particles inspired by biology and biointerface science in conjunction with fluorophore exclusion at the contact region. The method provides high-resolution contact network data that allows us to measure structural properties of the colloidal packing near marginal stability. We determine scaling laws of force distributions, soft modes, correlation functions, coordination number and free volume that define the universality class of jammed colloidal packings and can be compared with theoretical predictions. The contact detection method opens up further experimental testing at the interface of jamming and glass physics.

Computational modeling of spiking neural network with learning rules from STDP and intrinsic plasticity

NASA Astrophysics Data System (ADS)

Li, Xiumin; Wang, Wei; Xue, Fangzheng; Song, Yongduan

2018-02-01

Recently there has been continuously increasing interest in building up computational models of spiking neural networks (SNN), such as the Liquid State Machine (LSM). The biologically inspired self-organized neural networks with neural plasticity can enhance the capability of computational performance, with the characteristic features of dynamical memory and recurrent connection cycles which distinguish them from the more widely used feedforward neural networks. Despite a variety of computational models for brain-like learning and information processing have been proposed, the modeling of self-organized neural networks with multi-neural plasticity is still an important open challenge. The main difficulties lie in the interplay among different forms of neural plasticity rules and understanding how structures and dynamics of neural networks shape the computational performance. In this paper, we propose a novel approach to develop the models of LSM with a biologically inspired self-organizing network based on two neural plasticity learning rules. The connectivity among excitatory neurons is adapted by spike-timing-dependent plasticity (STDP) learning; meanwhile, the degrees of neuronal excitability are regulated to maintain a moderate average activity level by another learning rule: intrinsic plasticity (IP). Our study shows that LSM with STDP+IP performs better than LSM with a random SNN or SNN obtained by STDP alone. The noticeable improvement with the proposed method is due to the better reflected competition among different neurons in the developed SNN model, as well as the more effectively encoded and processed relevant dynamic information with its learning and self-organizing mechanism. This result gives insights to the optimization of computational models of spiking neural networks with neural plasticity.

Bioinspired nanovalves with selective permeability and pH sensitivity

NASA Astrophysics Data System (ADS)

Zheng, Z.; Huang, X.; Schenderlein, M.; Moehwald, H.; Xu, G.-K.; Shchukin, D. G.

2015-01-01

Biological systems with controlled permeability and release functionality, which are among the successful examples of living beings to survive in evolution, have attracted intensive investigation and have been mimicked due to their broad spectrum of applications. We present in this work, for the first time, an example of nuclear pore complexes (NPCs)-inspired controlled release system that exhibits on-demand release of angstrom-sized molecules. We do so in a cost-effective way by stabilizing porous cobalt basic carbonates as nanovalves and realizing pH-sensitive release of entrapped subnano cargo. The proof-of-concept work also consists of the establishment of two mathematical models to explain the selective permeability of the nanovalves. Finally, gram-sized (or larger) quantities of the bio-inspired controlled release system can be synthesized through a scaling-up strategy, which opens up opportunities for controlled release of functional molecules in wider practical applications.Biological systems with controlled permeability and release functionality, which are among the successful examples of living beings to survive in evolution, have attracted intensive investigation and have been mimicked due to their broad spectrum of applications. We present in this work, for the first time, an example of nuclear pore complexes (NPCs)-inspired controlled release system that exhibits on-demand release of angstrom-sized molecules. We do so in a cost-effective way by stabilizing porous cobalt basic carbonates as nanovalves and realizing pH-sensitive release of entrapped subnano cargo. The proof-of-concept work also consists of the establishment of two mathematical models to explain the selective permeability of the nanovalves. Finally, gram-sized (or larger) quantities of the bio-inspired controlled release system can be synthesized through a scaling-up strategy, which opens up opportunities for controlled release of functional molecules in wider practical applications. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr06378c

Turning and Radius Deviation Correction for a Hexapod Walking Robot Based on an Ant-Inspired Sensory Strategy

PubMed Central

Guo, Tong; Liu, Qiong; Zhu, Qianwei; Zhao, Xiangmo; Jin, Bo

2017-01-01

In order to find a common approach to plan the turning of a bio-inspired hexapod robot, a locomotion strategy for turning and deviation correction of a hexapod walking robot based on the biological behavior and sensory strategy of ants. A series of experiments using ants were carried out where the gait and the movement form of ants was studied. Taking the results of the ant experiments as inspiration by imitating the behavior of ants during turning, an extended turning algorithm based on arbitrary gait was proposed. Furthermore, after the observation of the radius adjustment of ants during turning, a radius correction algorithm based on the arbitrary gait of the hexapod robot was raised. The radius correction surface function was generated by fitting the correction data, which made it possible for the robot to move in an outdoor environment without the positioning system and environment model. The proposed algorithm was verified on the hexapod robot experimental platform. The turning and radius correction experiment of the robot with several gaits were carried out. The results indicated that the robot could follow the ideal radius and maintain stability, and the proposed ant-inspired turning strategy could easily make free turns with an arbitrary gait. PMID:29168742

Turning and Radius Deviation Correction for a Hexapod Walking Robot Based on an Ant-Inspired Sensory Strategy.

PubMed

Zhu, Yaguang; Guo, Tong; Liu, Qiong; Zhu, Qianwei; Zhao, Xiangmo; Jin, Bo

2017-11-23

Abstract : In order to find a common approach to plan the turning of a bio-inspired hexapod robot, a locomotion strategy for turning and deviation correction of a hexapod walking robot based on the biological behavior and sensory strategy of ants. A series of experiments using ants were carried out where the gait and the movement form of ants was studied. Taking the results of the ant experiments as inspiration by imitating the behavior of ants during turning, an extended turning algorithm based on arbitrary gait was proposed. Furthermore, after the observation of the radius adjustment of ants during turning, a radius correction algorithm based on the arbitrary gait of the hexapod robot was raised. The radius correction surface function was generated by fitting the correction data, which made it possible for the robot to move in an outdoor environment without the positioning system and environment model. The proposed algorithm was verified on the hexapod robot experimental platform. The turning and radius correction experiment of the robot with several gaits were carried out. The results indicated that the robot could follow the ideal radius and maintain stability, and the proposed ant-inspired turning strategy could easily make free turns with an arbitrary gait.

Emerging Technologies for Assembly of Microscale Hydrogels

PubMed Central

Kavaz, Doga; Demirel, Melik C.; Demirci, Utkan

2013-01-01

Assembly of cell encapsulating building blocks (i.e., microscale hydrogels) has significant applications in areas including regenerative medicine, tissue engineering, and cell-based in vitro assays for pharmaceutical research and drug discovery. Inspired by the repeating functional units observed in native tissues and biological systems (e.g., the lobule in liver, the nephron in kidney), assembly technologies aim to generate complex tissue structures by organizing microscale building blocks. Novel assembly technologies enable fabrication of engineered tissue constructs with controlled properties including tunable microarchitectural and predefined compositional features. Recent advances in micro- and nano-scale technologies have enabled engineering of microgel based three dimensional (3D) constructs. There is a need for high-throughput and scalable methods to assemble microscale units with a complex 3D micro-architecture. Emerging assembly methods include novel technologies based on microfluidics, acoustic and magnetic fields, nanotextured surfaces, and surface tension. In this review, we survey emerging microscale hydrogel assembly methods offering rapid, scalable microgel assembly in 3D, and provide future perspectives and discuss potential applications. PMID:23184717

Winging It: Using Digital Imaging To Investigate Butterfly Metamorphosis

ERIC Educational Resources Information Center

Bowen, Anne; Bell, Randy L.

2004-01-01

One of the best ways to inspire interest in biology is through observations of living things. Unfortunately, this important component of science methodology is often left out because of the difficulty of including it in the classroom. Additionally, amazing processes occur in nature that few have the chance to observe. This article reviews a…

Students' Bibliographic Research: Competition Enhances Results.

ERIC Educational Resources Information Center

Engel, Nora; And Others

1996-01-01

Describes an approach to a course about the basics of genetics and molecular biology that utilizes a contest that involves students in accessing information about a topic such as sex determination, neural development, and gene therapy. The general objective of the approach is to inspire students to become familiar with the scientific literature.…

Cry, Baby, Cry: A Dialogic Response to Emotion

ERIC Educational Resources Information Center

White, E. Jayne

2013-01-01

This article challenges traditional approaches to emotion as a discreet biological or dialectic process in the early years. In doing so the proposition is made that emotion is an answerable social act of meaning-making and self-hood. Inspired by Bakhtinian philosophy, which resists separating emotion from cognition or the individual from their…

J D Bernal: the sage of science

NASA Astrophysics Data System (ADS)

Brown, Andrew P.

2007-02-01

John Desmond Bernal (1901-1971) was one of the most influential and original scientists of the twentieth century. No less an authority than James Watson has stated that Bernal's genius inspired the birth of molecular biology. By examining Bernal's interactions with others, I attempt to illustrate his personality, brilliance, breadth, foibles and essential humanity.

Ecological Consultancy

ERIC Educational Resources Information Center

Wilson, Scott McG.; Tattersfield, Peter

2004-01-01

This is the first of a new regular feature on careers, designed to provide those who teach biology with some inspiration when advising their students. In this issue, two consultant ecologists explain how their career paths developed. It is a misconception that there are few jobs in ecology. Over the past 20 or 30 years ecological consultancy has…

Dead Heroes: Surviving the Male Myth.

ERIC Educational Resources Information Center

O'Hara, Bruce

North American men die about 10 years younger than their female counterparts. This difference is not based on biological differences but on behavioral differences. Men are taught not to take care of themselves and to deaden themselves emotionally. Men are incurable romantics. They are addicted to the hero myth which is a wonderful inspiring,…

Gender Aspects of Participation, Support, and Success in a State Science Fair

ERIC Educational Resources Information Center

Sonnert, Gerhard; Sadler, Philip; Michaels, Mish

2013-01-01

This study of students competing in the 2009 Massachusetts State Science & Engineering Fair investigates the role gender played in students' participation, choice of science field, award of prizes, and mentioning inspiring teachers. Females made up 62 percent of the participants and were more likely to enter projects in biology and in…

Case Study: Guidelines for Producing Videos to Accompany Flipped Cases

ERIC Educational Resources Information Center

Prud'homme-Généreux, Annie; Schiller, Nancy A.; Wild, John H.; Herreid, Clyde Freeman

2017-01-01

Three years ago, the "National Center for Case Study Teaching in Science" (NCCSTS) was inspired to merge the case study and flipped classroom approaches. The resulting project aimed to create the materials required to teach a flipped course in introductory biology by assigning videos as homework and case studies in the classroom. Three…

Inspire Day

ERIC Educational Resources Information Center

Bohach, Barbara M.; Meade, Birgitta

2014-01-01

The authors collaborated on hosting a "Spring Inspire Day." planned and delivered by preservice elementary teachers as a social studies/science methods project. Projects that have authentic application opportunities can make learning meaningful for prospective teachers as well as elementary students. With the impetus for an integrated…

Bioinspiration: applying mechanical design to experimental biology.

PubMed

Flammang, Brooke E; Porter, Marianne E

2011-07-01

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

Building, using, and maximizing the impact of concept inventories in the biological sciences: report on a National Science Foundation sponsored conference on the construction of concept inventories in the biological sciences.

PubMed

Garvin-Doxas, Kathy; Klymkowsky, Michael; Elrod, Susan

2007-01-01

The meeting "Conceptual Assessment in the Biological Sciences" was held March 3-4, 2007, in Boulder, Colorado. Sponsored by the National Science Foundation and hosted by University of Colorado, Boulder's Biology Concept Inventory Team, the meeting drew together 21 participants from 13 institutions, all of whom had received National Science Foundation funding for biology education. Topics of interest included Introductory Biology, Genetics, Evolution, Ecology, and the Nature of Science. The goal of the meeting was to organize and leverage current efforts to develop concept inventories for each of these topics. These diagnostic tools are inspired by the success of the Force Concept Inventory, developed by the community of physics educators to identify student misconceptions about Newtonian mechanics. By working together, participants hope to lessen the risk that groups might develop competing rather than complementary inventories.

Privileged structures: efficient chemical "navigators" toward unexplored biologically relevant chemical spaces.

PubMed

Kim, Jonghoon; Kim, Heejun; Park, Seung Bum

2014-10-22

In the search for new therapeutic agents for currently incurable diseases, attention has turned to traditionally "undruggable" targets, and collections of drug-like small molecules with high diversity and quality have become a prerequisite for new breakthroughs. To generate such collections, the diversity-oriented synthesis (DOS) strategy was developed, which aims to populate new chemical space with drug-like compounds containing a high degree of molecular diversity. The resulting DOS-derived libraries have been of great value for the discovery of various bioactive small molecules and therapeutic agents, and thus DOS has emerged as an essential tool in chemical biology and drug discovery. However, the key challenge has become how to design and synthesize drug-like small-molecule libraries with improved biological relevancy as well as maximum molecular diversity. This Perspective presents the development of privileged substructure-based DOS (pDOS), an efficient strategy for the construction of polyheterocyclic compound libraries with high biological relevancy. We envisioned the specific interaction of drug-like small molecules with certain biopolymers via the incorporation of privileged substructures into polyheterocyclic core skeletons. The importance of privileged substructures such as benzopyran, pyrimidine, and oxopiperazine in rigid skeletons was clearly demonstrated through the discovery of bioactive small molecules and the subsequent identification of appropriate target biomolecule using a method called "fluorescence difference in two-dimensional gel electrophoresis". Focusing on examples of pDOS-derived bioactive compounds with exceptional specificity, we discuss the capability of privileged structures to serve as chemical "navigators" toward biologically relevant chemical spaces. We also provide an outlook on chemical biology research and drug discovery using biologically relevant compound libraries constructed by pDOS, biology-oriented synthesis, or natural product-inspired DOS.

Design of two-channel filter bank using nature inspired optimization based fractional derivative constraints.

PubMed

Kuldeep, B; Singh, V K; Kumar, A; Singh, G K

2015-01-01

In this article, a novel approach for 2-channel linear phase quadrature mirror filter (QMF) bank design based on a hybrid of gradient based optimization and optimization of fractional derivative constraints is introduced. For the purpose of this work, recently proposed nature inspired optimization techniques such as cuckoo search (CS), modified cuckoo search (MCS) and wind driven optimization (WDO) are explored for the design of QMF bank. 2-Channel QMF is also designed with particle swarm optimization (PSO) and artificial bee colony (ABC) nature inspired optimization techniques. The design problem is formulated in frequency domain as sum of L2 norm of error in passband, stopband and transition band at quadrature frequency. The contribution of this work is the novel hybrid combination of gradient based optimization (Lagrange multiplier method) and nature inspired optimization (CS, MCS, WDO, PSO and ABC) and its usage for optimizing the design problem. Performance of the proposed method is evaluated by passband error (ϕp), stopband error (ϕs), transition band error (ϕt), peak reconstruction error (PRE), stopband attenuation (As) and computational time. The design examples illustrate the ingenuity of the proposed method. Results are also compared with the other existing algorithms, and it was found that the proposed method gives best result in terms of peak reconstruction error and transition band error while it is comparable in terms of passband and stopband error. Results show that the proposed method is successful for both lower and higher order 2-channel QMF bank design. A comparative study of various nature inspired optimization techniques is also presented, and the study singles out CS as a best QMF optimization technique. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

The Biological Relevance of Artificial Life: Lessons from Artificial Intelligence

NASA Technical Reports Server (NTRS)

Colombano, Silvano

2000-01-01

There is no fundamental reason why A-life couldn't simply be a branch of computer science that deals with algorithms that are inspired by, or emulate biological phenomena. However, if these are the limits we place on this field, we miss the opportunity to help advance Theoretical Biology and to contribute to a deeper understanding of the nature of life. The history of Artificial Intelligence provides a good example, in that early interest in the nature of cognition quickly was lost to the process of building tools, such as "expert systems" that, were certainly useful, but provided little insight in the nature of cognition. Based on this lesson, I will discuss criteria for increasing the biological relevance of A-life and the probability that this field may provide a theoretical foundation for Biology.

CURE Scholar Spotlight - Dr. Brady

Cancer.gov

Donita C. Brady, a Research Associate Senior at the Department of Pharmacology and Cancer Biology at Duke University, is investigating the role that copper plays in cell growth and tumor biology. Inspired by her mentor Christopher Counter, a cancer biologist, and Dennis Thiele, a copper biologist, at Duke University, Brady has a unique interest in the way copper interacts with protein pathways, such as the BRAF (a human gene that directs cell growth)-MEK-ERK pathway, which is a major target for targeted cancer therapies because the BRAF gene is mutated 60% of the time in melanoma.

Biologically inspired circuitry that mimics mammalian hearing

NASA Astrophysics Data System (ADS)

Hubbard, Allyn; Cohen, Howard; Karl, Christian; Freedman, David; Mountain, David; Ziph-Schatzberg, Leah; Nourzad Karl, Marianne; Kelsall, Sarah; Gore, Tyler; Pu, Yirong; Yang, Zibing; Xing, Xinyu; Deligeorges, Socrates

2009-05-01

We are developing low-power microcircuitry that implements classification and direction finding systems of very small size and small acoustic aperture. Our approach was inspired by the fact that small mammals are able to localize sounds despite their ears may be separated by as little as a centimeter. Gerbils, in particular are good low-frequency localizers, which is a particularly difficult task, since a wavelength at 500 Hz is on the order of two feet. Given such signals, crosscorrelation- based methods to determine direction fail badly in the presence of a small amount of noise, e.g. wind noise and noise clutter common to almost any realistic environment. Circuits are being developed using both analog and digital techniques, each of which process signals in fundamentally the same way the peripheral auditory system of mammals processes sound. A filter bank represents filtering done by the cochlea. The auditory nerve is implemented using a combination of an envelope detector, an automatic gain stage, and a unique one-bit A/D, which creates what amounts to a neural impulse. These impulses are used to extract pitch characteristics, which we use to classify sounds such as vehicles, small and large weaponry from AK-47s to 155mm cannon, including mortar launches and impacts. In addition to the pitchograms, we also use neural nets for classification.

Artificial intelligence and synthetic biology: A tri-temporal contribution.

PubMed

Bianchini, Francesco

2016-10-01

Artificial intelligence can make numerous contributions to synthetic biology. I would like to suggest three that are related to the past, present and future of artificial intelligence. From the past, works in biology and artificial systems by Turing and von Neumann prove highly interesting to explore within the new framework of synthetic biology, especially with regard to the notions of self-modification and self-replication and their links to emergence and the bottom-up approach. The current epistemological inquiry into emergence and research on swarm intelligence, superorganisms and biologically inspired cognitive architecture may lead to new achievements on the possibilities of synthetic biology in explaining cognitive processes. Finally, the present-day discussion on the future of artificial intelligence and the rise of superintelligence may point to some research trends for the future of synthetic biology and help to better define the boundary of notions such as "life", "cognition", "artificial" and "natural", as well as their interconnections in theoretical synthetic biology. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Bio-inspired Edible Superhydrophobic Interface for Reducing Residual Liquid Food.

PubMed

Li, Yao; Bi, Jingran; Wang, Siqi; Zhang, Tan; Xu, Xiaomeng; Wang, Haitao; Cheng, Shasha; Zhu, Bei-Wei; Tan, Mingqian

2018-03-07

Significant wastage of residual liquid food, such as milk, yogurt, and honey, in food containers has attracted great attention. In this work, a bio-inspired edible superhydrophobic interface was fabricated using U.S. Food and Drug Administration-approved and edible honeycomb wax, arabic gum, and gelatin by a simple and low-cost method. The bio-inspired edible superhydrophobic interface showed multiscale structures, which were similar to that of a lotus leaf surface. This bio-inspired edible superhydrophobic interface displayed high contact angles for a variety of liquid foods, and the residue of liquid foods could be effectively reduced using the bio-inspired interface. To improve the adhesive force of the superhydrophobic interface, a flexible edible elastic film was fabricated between the interface and substrate material. After repeated folding and flushing for a long time, the interface still maintained excellent superhydrophobic property. The bio-inspired edible superhydrophobic interface showed good biocompatibility, which may have potential applications as a functional packaging interface material.

INSPIRE and SPIRES Log File Analysis

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

Adams, Cole; /Wheaton Coll. /SLAC

2012-08-31

SPIRES, an aging high-energy physics publication data base, is in the process of being replaced by INSPIRE. In order to ease the transition from SPIRES to INSPIRE it is important to understand user behavior and the drivers for adoption. The goal of this project was to address some questions in regards to the presumed two-thirds of the users still using SPIRES. These questions are answered through analysis of the log files from both websites. A series of scripts were developed to collect and interpret the data contained in the log files. The common search patterns and usage comparisons are mademore » between INSPIRE and SPIRES, and a method for detecting user frustration is presented. The analysis reveals a more even split than originally thought as well as the expected trend of user transition to INSPIRE.« less

A Survey of Memristive Threshold Logic Circuits.

PubMed

Maan, Akshay Kumar; Jayadevi, Deepthi Anirudhan; James, Alex Pappachen

2017-08-01

In this paper, we review different memristive threshold logic (MTL) circuits that are inspired from the synaptic action of the flow of neurotransmitters in the biological brain. The brainlike generalization ability and the area minimization of these threshold logic circuits aim toward crossing Moore's law boundaries at device, circuits, and systems levels. Fast switching memory, signal processing, control systems, programmable logic, image processing, reconfigurable computing, and pattern recognition are identified as some of the potential applications of MTL systems. The physical realization of nanoscale devices with memristive behavior from materials, such as TiO 2 , ferroelectrics, silicon, and polymers, has accelerated research effort in these application areas, inspiring the scientific community to pursue the design of high-speed, low-cost, low-power, and high-density neuromorphic architectures.

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

Aytug, Tolga; Simpson, John T.; Lupini, Andrew R.

Inspired by highly non-wetting natural biological surfaces (e.g., lotus leaves and water strider legs), artificial superhydrophobic surfaces that exhibit water droplet contact angles exceeding 150o have previously been constructed by utilizing various synthesis strategies.[ , , ] Such bio-inspired, water-repellent surfaces offer significant potential for numerous uses ranging from marine applications (e.g., anti-biofouling, anti-corrosion), anti-condensation (e.g., anti-icing, anti-fogging), membranes for selective separation (e.g., oil-water, gas-liquid), microfluidic systems, surfaces requiring reduced maintenance and cleaning, to applications involving glasses and optical materials.[ ] In addition to superhydrophobic attributes, for integration into device systems that have extended operational limits and overall improved performance,more » surfaces that also possess multifunctional characteristics are desired, where the functionality should match to the application-specific requirements.« less

Ernst Mach and George Sarton's Successors: The Implicit Role Model of Teaching Science in USA and Elsewhere, Part II

ERIC Educational Resources Information Center

Siemsen, Hayo

2013-01-01

George Sarton had a strong influence on modern history of science. The method he pursued throughout his life was the method he had discovered in Ernst Mach's "Mechanics" when he was a student in Ghent. Sarton was in fact throughout his life implementing a research program inspired by the epistemology of Mach. Sarton in turn inspired many…

A neurally inspired musical instrument classification system based upon the sound onset.

PubMed

Newton, Michael J; Smith, Leslie S

2012-06-01

Physiological evidence suggests that sound onset detection in the auditory system may be performed by specialized neurons as early as the cochlear nucleus. Psychoacoustic evidence shows that the sound onset can be important for the recognition of musical sounds. Here the sound onset is used in isolation to form tone descriptors for a musical instrument classification task. The task involves 2085 isolated musical tones from the McGill dataset across five instrument categories. A neurally inspired tone descriptor is created using a model of the auditory system's response to sound onset. A gammatone filterbank and spiking onset detectors, built from dynamic synapses and leaky integrate-and-fire neurons, create parallel spike trains that emphasize the sound onset. These are coded as a descriptor called the onset fingerprint. Classification uses a time-domain neural network, the echo state network. Reference strategies, based upon mel-frequency cepstral coefficients, evaluated either over the whole tone or only during the sound onset, provide context to the method. Classification success rates for the neurally-inspired method are around 75%. The cepstral methods perform between 73% and 76%. Further testing with tones from the Iowa MIS collection shows that the neurally inspired method is considerably more robust when tested with data from an unrelated dataset.

Discovery of a new method for potent drug development using power function of stoichiometry ofhomomeric biocomplexes or biological nanomotors

PubMed Central

Pi, Fengmei; Vieweger, Mario; Zhao, Zhengyi; Wang, Shaoying; Guo, Peixuan

2015-01-01

Introduction Multidrug resistance and the appearance of incurable diseases inspire the quest for potent therapeutics. Areas Covered We review a new methodology in designing potent drugs by targeting multi-subunit homomeric biological motors, machines, or complexes with Z>1 and K=1, where Z is the stoichiometry of the target, and K is the number of drugged subunits required to block the function of the complex. The condition is similar to a series, electrical circuit of Christmas decorations; failure of one light bulb causes the entire lighting system to lose power. In most multisubunit, homomeric biological systems, a sequential coordination or cooperative action mechanism is utilized, thus K equals 1. Drug inhibition depends on the ratio of drugged to nondrugged complexes. When K=1, and Z>1, the inhibition effect follows a power law with respect to Z, leading to enhanced drug potency. The hypothesis that the potency of drug inhibition depends on the stoichiometry of the targeted biological complexes was recently quantified by Yang-Hui's Triangle (or binomial distribution), and proved using a highly sensitive in vitro phi29 viral DNA packaging system. Examples of targeting homomeric bio-complexes with high stoichiometry for potent drug discovery are discussed. Expert Opinion Biomotors with multiple subunits are widespread in viruses, bacteria, and cells, making this approach generally applicable in the development of inhibition drugs with high efficiency. PMID:26307193

System impairment compensation in coherent optical communications by using a bio-inspired detector based on artificial neural network and genetic algorithm

NASA Astrophysics Data System (ADS)

Wang, Danshi; Zhang, Min; Li, Ze; Song, Chuang; Fu, Meixia; Li, Jin; Chen, Xue

2017-09-01

A bio-inspired detector based on the artificial neural network (ANN) and genetic algorithm is proposed in the context of a coherent optical transmission system. The ANN is designed to mitigate 16-quadrature amplitude modulation system impairments, including linear impairment: Gaussian white noise, laser phase noise, in-phase/quadrature component imbalance, and nonlinear impairment: nonlinear phase. Without prior information or heuristic assumptions, the ANN, functioning as a machine learning algorithm, can learn and capture the characteristics of impairments from observed data. Numerical simulations were performed, and dispersion-shifted, dispersion-managed, and dispersion-unmanaged fiber links were investigated. The launch power dynamic range and maximum transmission distance for the bio-inspired method were 2.7 dBm and 240 km greater, respectively, than those of the maximum likelihood estimation algorithm. Moreover, the linewidth tolerance of the bio-inspired technique was 170 kHz greater than that of the k-means method, demonstrating its usability for digital signal processing in coherent systems.

Synthetic biology of antimicrobial discovery

PubMed Central

Zakeri, Bijan; Lu, Timothy K.

2012-01-01

Antibiotic discovery has a storied history. From the discovery of penicillin by Sir Alexander Fleming to the relentless quest for antibiotics by Selman Waksman, the stories have become like folklore, used to inspire future generations of scientists. However, recent discovery pipelines have run dry at a time when multidrug resistant pathogens are on the rise. Nature has proven to be a valuable reservoir of antimicrobial agents, which are primarily produced by modularized biochemical pathways. Such modularization is well suited to remodeling by an interdisciplinary approach that spans science and engineering. Herein, we discuss the biological engineering of small molecules, peptides, and non-traditional antimicrobials and provide an overview of the growing applicability of synthetic biology to antimicrobials discovery. PMID:23654251

Synthetic biology of antimicrobial discovery.

PubMed

Zakeri, Bijan; Lu, Timothy K

2013-07-19

Antibiotic discovery has a storied history. From the discovery of penicillin by Sir Alexander Fleming to the relentless quest for antibiotics by Selman Waksman, the stories have become like folklore used to inspire future generations of scientists. However, recent discovery pipelines have run dry at a time when multidrug-resistant pathogens are on the rise. Nature has proven to be a valuable reservoir of antimicrobial agents, which are primarily produced by modularized biochemical pathways. Such modularization is well suited to remodeling by an interdisciplinary approach that spans science and engineering. Herein, we discuss the biological engineering of small molecules, peptides, and non-traditional antimicrobials and provide an overview of the growing applicability of synthetic biology to antimicrobials discovery.

Interdisciplinary training in mathematical biology through team-based undergraduate research and courses.

PubMed

Miller, Jason E; Walston, Timothy

2010-01-01

Inspired by BIO2010 and leveraging institutional and external funding, Truman State University built an undergraduate program in mathematical biology with high-quality, faculty-mentored interdisciplinary research experiences at its core. These experiences taught faculty and students to bridge the epistemological gap between the mathematical and life sciences. Together they created the infrastructure that currently supports several interdisciplinary courses, an innovative minor degree, and long-term interdepartmental research collaborations. This article describes how the program was built with support from the National Science Foundation's Interdisciplinary Training for Undergraduates in Biology and Mathematics program, and it shares lessons learned that will help other undergraduate institutions build their own program.

Lipid Nanotechnology

PubMed Central

Mashaghi, Samaneh; Jadidi, Tayebeh; Koenderink, Gijsje; Mashaghi, Alireza

2013-01-01

Nanotechnology is a multidisciplinary field that covers a vast and diverse array of devices and machines derived from engineering, physics, materials science, chemistry and biology. These devices have found applications in biomedical sciences, such as targeted drug delivery, bio-imaging, sensing and diagnosis of pathologies at early stages. In these applications, nano-devices typically interface with the plasma membrane of cells. On the other hand, naturally occurring nanostructures in biology have been a source of inspiration for new nanotechnological designs and hybrid nanostructures made of biological and non-biological, organic and inorganic building blocks. Lipids, with their amphiphilicity, diversity of head and tail chemistry, and antifouling properties that block nonspecific binding to lipid-coated surfaces, provide a powerful toolbox for nanotechnology. This review discusses the progress in the emerging field of lipid nanotechnology. PMID:23429269

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.

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

NASA Astrophysics Data System (ADS)

Steinberg, Marc

2011-06-01

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

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

PubMed

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

1996-06-01

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

Teaching Green and Sustainable Chemistry: A Revised One-Semester Course Based on Inspirations and Challenges

ERIC Educational Resources Information Center

Marteel-Parrish, Anne E.

2014-01-01

An elective course, "Toward the Greening of Our Minds": Green and Sustainable Chemistry, has been offered at Washington College since 2005. This new course without laboratory is designed for chemistry and biology majors and minors who have previously taken two semesters of general chemistry and organic chemistry. Due to the popularity of…

School-University Action Research: Impacts on Teaching Practices and Pupil Learning

ERIC Educational Resources Information Center

Attorps, Iiris; Kellner, Eva

2017-01-01

The aim of this article is to describe a design and implementation of a school-university action research project about teaching and learning biology and mathematics in primary school. Nine teachers in grades 1 to 6, in collaboration with two researchers, were using content representation (CoRe) in learning study (LS)-inspired cycle as pedagogical…

Bio-Inspired Nanomaterials: Protein Cage Nano-Architectures

DTIC Science & Technology

2008-04-01

chemical modification of protein cage materials and controlled chemical synthesis under mild biological conditions. High- resolution structural...properties based on a combination of controlled mobility and metal ligand interactions. Using the exterior surface of the CCMV viral cage we have chemically ...follows: Patterning by microplotter was achieved by depositing a preselected antibody solution directly onto chemically activated silicon or gold

The Art-Science Connection: Students Create Art Inspired by Extracurricular Lab Investigations

ERIC Educational Resources Information Center

Hegedus, Tess; Segarra, Verónica A.; Allen, Tawannah G.; Wilson, Hillary; Garr, Casey; Budzinski, Christina

2016-01-01

The authors developed an integrated science-and-art program to engage science students from a performing arts high school in hands-on, inquiry based lab experiences. The students participated in eight biology-focused investigations at a local university with undergraduate mentors. After the laboratory phase of the project, the high school students…

The Potential of Peer Robots to Assist Human Creativity in Finding Problems and Problem Solving

ERIC Educational Resources Information Center

Okita, Sandra

2015-01-01

Many technological artifacts (e.g., humanoid robots, computer agents) consist of biologically inspired features of human-like appearance and behaviors that elicit a social response. The strong social components of technology permit people to share information and ideas with these artifacts. As robots cross the boundaries between humans and…

Trusted computation through biologically inspired processes

NASA Astrophysics Data System (ADS)

Anderson, Gustave W.

2013-05-01

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

Digital and biological computing in organizations.

PubMed

Kampfner, Roberto R

2002-01-01

Michael Conrad unveiled many of the fundamental characteristics of biological computing. Underlying the behavioral variability and the adaptability of biological systems are these characteristics, including the ability of biological information processing to exploit quantum features at the atomic level, the powerful 3-D pattern recognition capabilities of macromolecules, the computational efficiency, and the ability to support biological function. Among many other things, Conrad formalized and explicated the underlying principles of biological adaptability, characterized the differences between biological and digital computing in terms of a fundamental tradeoff between adaptability and programmability of information processing, and discussed the challenges of interfacing digital computers and human society. This paper is about the encounter of biological and digital computing. The focus is on the nature of the biological information processing infrastructure of organizations and how it can be extended effectively with digital computing. In order to achieve this goal effectively, however, we need to embed properly digital computing into the information processing aspects of human and social behavior and intelligence, which are fundamentally biological. Conrad's legacy provides a firm, strong, and inspiring foundation for this endeavor.

Quality of Life Theory II. Quality of Life as the Realization of Life Potential: A Biological Theory of Human Being

PubMed Central

Ventegodt, Soren; Merrick, Joav; Andersen, Niels Jorgen

2003-01-01

This review presents one of the eight theories of the quality of life (QOL) used for making the SEQOL (self-evaluation of quality of life) questionnaire or the quality of life as realizing life potential. This theory is strongly inspired by Maslow and the review furthermore serves as an example on how to fulfill the demand for an overall theory of life (or philosophy of life), which we believe is necessary for global and generic quality-of-life research.Whereas traditional medical science has often been inspired by mechanical models in its attempts to understand human beings, this theory takes an explicitly biological starting point. The purpose is to take a close view of life as a unique entity, which mechanical models are unable to do. This means that things considered to be beyond the individual's purely biological nature, notably the quality of life, meaning in life, and aspirations in life, are included under this wider, biological treatise. Our interpretation of the nature of all living matter is intended as an alternative to medical mechanism, which dates back to the beginning of the 20th century. New ideas such as the notions of the human being as nestled in an evolutionary and ecological context, the spontaneous tendency of self-organizing systems for realization and concord, and the central role of consciousness in interpreting, planning, and expressing human reality are unavoidable today in attempts to scientifically understand all living matter, including human life. PMID:14570994

Solid-State and Biological Nanopore for Real-Time Sensing of Single Chemical and Sequencing of DNA.

PubMed

Haque, Farzin; Li, Jinghong; Wu, Hai-Chen; Liang, Xing-Jie; Guo, Peixuan

2013-02-01

Sensitivity and specificity are two most important factors to take into account for molecule sensing, chemical detection and disease diagnosis. A perfect sensitivity is to reach the level where a single molecule can be detected. An ideal specificity is to reach the level where the substance can be detected in the presence of many contaminants. The rapidly progressing nanopore technology is approaching this threshold. A wide assortment of biomotors and cellular pores in living organisms perform diverse biological functions. The elegant design of these transportation machineries has inspired the development of single molecule detection based on modulations of the individual current blockage events. The dynamic growth of nanotechnology and nanobiotechnology has stimulated rapid advances in the study of nanopore based instrumentation over the last decade, and inspired great interest in sensing of single molecules including ions, nucleotides, enantiomers, drugs, and polymers such as PEG, RNA, DNA, and polypeptides. This sensing technology has been extended to medical diagnostics and third generation high throughput DNA sequencing. This review covers current nanopore detection platforms including both biological pores and solid state counterparts. Several biological nanopores have been studied over the years, but this review will focus on the three best characterized systems including α-hemolysin and MspA, both containing a smaller channel for the detection of single-strand DNA, as well as bacteriophage phi29 DNA packaging motor connector that contains a larger channel for the passing of double stranded DNA. The advantage and disadvantage of each system are compared; their current and potential applications in nanomedicine, biotechnology, and nanotechnology are discussed.

Solid-State and Biological Nanopore for Real-Time Sensing of Single Chemical and Sequencing of DNA

PubMed Central

Haque, Farzin; Li, Jinghong; Wu, Hai-Chen; Liang, Xing-Jie; Guo, Peixuan

2013-01-01

Sensitivity and specificity are two most important factors to take into account for molecule sensing, chemical detection and disease diagnosis. A perfect sensitivity is to reach the level where a single molecule can be detected. An ideal specificity is to reach the level where the substance can be detected in the presence of many contaminants. The rapidly progressing nanopore technology is approaching this threshold. A wide assortment of biomotors and cellular pores in living organisms perform diverse biological functions. The elegant design of these transportation machineries has inspired the development of single molecule detection based on modulations of the individual current blockage events. The dynamic growth of nanotechnology and nanobiotechnology has stimulated rapid advances in the study of nanopore based instrumentation over the last decade, and inspired great interest in sensing of single molecules including ions, nucleotides, enantiomers, drugs, and polymers such as PEG, RNA, DNA, and polypeptides. This sensing technology has been extended to medical diagnostics and third generation high throughput DNA sequencing. This review covers current nanopore detection platforms including both biological pores and solid state counterparts. Several biological nanopores have been studied over the years, but this review will focus on the three best characterized systems including α-hemolysin and MspA, both containing a smaller channel for the detection of single-strand DNA, as well as bacteriophage phi29 DNA packaging motor connector that contains a larger channel for the passing of double stranded DNA. The advantage and disadvantage of each system are compared; their current and potential applications in nanomedicine, biotechnology, and nanotechnology are discussed. PMID:23504223

Maintaining and Enhancing Diversity of Sampled Protein Conformations in Robotics-Inspired Methods.

PubMed

Abella, Jayvee R; Moll, Mark; Kavraki, Lydia E

2018-01-01

The ability to efficiently sample structurally diverse protein conformations allows one to gain a high-level view of a protein's energy landscape. Algorithms from robot motion planning have been used for conformational sampling, and several of these algorithms promote diversity by keeping track of "coverage" in conformational space based on the local sampling density. However, large proteins present special challenges. In particular, larger systems require running many concurrent instances of these algorithms, but these algorithms can quickly become memory intensive because they typically keep previously sampled conformations in memory to maintain coverage estimates. In addition, robotics-inspired algorithms depend on defining useful perturbation strategies for exploring the conformational space, which is a difficult task for large proteins because such systems are typically more constrained and exhibit complex motions. In this article, we introduce two methodologies for maintaining and enhancing diversity in robotics-inspired conformational sampling. The first method addresses algorithms based on coverage estimates and leverages the use of a low-dimensional projection to define a global coverage grid that maintains coverage across concurrent runs of sampling. The second method is an automatic definition of a perturbation strategy through readily available flexibility information derived from B-factors, secondary structure, and rigidity analysis. Our results show a significant increase in the diversity of the conformations sampled for proteins consisting of up to 500 residues when applied to a specific robotics-inspired algorithm for conformational sampling. The methodologies presented in this article may be vital components for the scalability of robotics-inspired approaches.

Prosecutors' Perspectives on Biological Evidence and Injury Evidence in Sexual Assault Cases.

PubMed

Alderden, Megan; Cross, Theodore P; Vlajnic, Maja; Siller, Laura

2018-06-01

Little prior research has explored how prosecutors perceive and utilize biological and injury evidences in sexual assault cases. In this qualitative study, semistructured interviews were conducted with assistant district attorneys (ADAs) working in an urban district attorney's office in the northeastern United States. ADAs were asked to describe how biological and injury evidences could be probative and their strategies for using this evidence. The interviews suggest that prosecutors perceive the probative value of biological and injury evidences on a continuum, varying based on case characteristics. Prosecutors felt that undergoing a forensic medical examination in itself supported victims' credibility. Biological evidence bolstered victims' credibility if it matched the victim's account better than the defendant's. They perceived DNA evidence as helpful when it identified unknown suspects, confirmed identification of suspects by other means, or rebutted defendants' denial of sexual contact. DNA evidence was also helpful when victims were incapacitated, too traumatized to recall or talk about the assault, or too young to identify assailants, and when police used the information in interrogating suspects. The biggest limitation to biological evidence prosecutors cited was overcoming the consent defense. The ADAs reported they used DNA evidence even when it was not particularly probative, because it confirms the correct person is being prosecuted, it communicates the victim's and prosecution's seriousness, and it meets jury expectations in trials. Prosecutors found injury evidence useful because it corroborated victims' accounts and helped refute defendant claims of consensual sex. The findings may assist in educating others about biological and injury evidences in these cases, and could inspire professionals and advocates to work to develop and support a broad range of investigative methods.

Microfabrication of IPMC cilia for bio-inspired flow sensing

NASA Astrophysics Data System (ADS)

Lei, Hong; Li, Wen; Tan, Xiaobo

2012-04-01

As the primary flow sensing organ for fishes, the lateral line system plays a critical role in fish behavior. Analogous to its biological counterpart, an artificial lateral line system, consisting of arrays of micro flow sensors, is expected to be instrumental in the navigation and control of underwater robots. In this paper we investigate the microfabrication of ionic polymer-metal composite (IPMC) cilia for the purpose of flow sensing. While existing macro- and microfabrication methods for IPMCs have predominantly focused on planar structures, we propose a device where micro IPMC beams stand upright on a substrate to effectively interact with the flow. Challenges in the casting of 3D Nafion structure and selective formation of electrodes are discussed, and potential solutions for addressing these challenges are presented together with preliminary microfabrication results.

Damage properties simulations of self-healing composites.

PubMed

Chen, Cheng; Ji, Hongwei; Wang, Huaiwen

2013-10-01

Self-healing materials are inspired by biological systems in which damage triggers an autonomic healing response. The damage properties of a self-healing polymer composite were investigated by numerical simulation in this paper. Unit cell models with single-edge centered crack and single-edge off-centered crack were employed to investigate the damage initiation and crack evolution by the extended finite element method (XFEM) modeling. The effect of microcapsule's Young's modulus on composites was investigated. Result indicates the microcapsule's Young's modulus has little effect on the unit cell's carrying capacity. It was found that during the crack propagation process, its direction is attracted toward the microcapsules, which makes it helpful for the microcapsules to be ruptured by the propagating crack fronts resulting in release of the healing agent into the cracks by capillary action.

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.

Geomagnetic Navigation of Autonomous Underwater Vehicle Based on Multi-objective Evolutionary Algorithm.

PubMed

Li, Hong; Liu, Mingyong; Zhang, Feihu

2017-01-01

This paper presents a multi-objective evolutionary algorithm of bio-inspired geomagnetic navigation for Autonomous Underwater Vehicle (AUV). Inspired by the biological navigation behavior, the solution was proposed without using a priori information, simply by magnetotaxis searching. However, the existence of the geomagnetic anomalies has significant influence on the geomagnetic navigation system, which often disrupts the distribution of the geomagnetic field. An extreme value region may easily appear in abnormal regions, which makes AUV lost in the navigation phase. This paper proposes an improved bio-inspired algorithm with behavior constraints, for sake of making AUV escape from the abnormal region. First, the navigation problem is considered as the optimization problem. Second, the environmental monitoring operator is introduced, to determine whether the algorithm falls into the geomagnetic anomaly region. Then, the behavior constraint operator is employed to get out of the abnormal region. Finally, the termination condition is triggered. Compared to the state-of- the-art, the proposed approach effectively overcomes the disturbance of the geomagnetic abnormal. The simulation result demonstrates the reliability and feasibility of the proposed approach in complex environments.

Geomagnetic Navigation of Autonomous Underwater Vehicle Based on Multi-objective Evolutionary Algorithm

PubMed Central

Li, Hong; Liu, Mingyong; Zhang, Feihu

2017-01-01

This paper presents a multi-objective evolutionary algorithm of bio-inspired geomagnetic navigation for Autonomous Underwater Vehicle (AUV). Inspired by the biological navigation behavior, the solution was proposed without using a priori information, simply by magnetotaxis searching. However, the existence of the geomagnetic anomalies has significant influence on the geomagnetic navigation system, which often disrupts the distribution of the geomagnetic field. An extreme value region may easily appear in abnormal regions, which makes AUV lost in the navigation phase. This paper proposes an improved bio-inspired algorithm with behavior constraints, for sake of making AUV escape from the abnormal region. First, the navigation problem is considered as the optimization problem. Second, the environmental monitoring operator is introduced, to determine whether the algorithm falls into the geomagnetic anomaly region. Then, the behavior constraint operator is employed to get out of the abnormal region. Finally, the termination condition is triggered. Compared to the state-of- the-art, the proposed approach effectively overcomes the disturbance of the geomagnetic abnormal. The simulation result demonstrates the reliability and feasibility of the proposed approach in complex environments. PMID:28747884

Dipteran wing motor-inspired flapping flight versatility and effectiveness enhancement

PubMed Central

Harne, R. L.; Wang, K. W.

2015-01-01

Insects are a prime source of inspiration towards the development of small-scale, engineered, flapping wing flight systems. To help interpret the possible energy transformation strategies observed in Diptera as inspiration for mechanical flapping flight systems, we revisit the perspective of the dipteran wing motor as a bistable click mechanism and take a new, and more flexible, outlook to the architectural composition previously considered. Using a representative structural model alongside biological insights and cues from nonlinear dynamics, our analyses and experimental results reveal that a flight mechanism able to adjust motor axial support stiffness and compression characteristics may dramatically modulate the amplitude range and type of wing stroke dynamics achievable. This corresponds to significantly more versatile aerodynamic force generation without otherwise changing flapping frequency or driving force amplitude. Whether monostable or bistable, the axial stiffness is key to enhance compressed motor load bearing ability and aerodynamic efficiency, particularly compared with uncompressed linear motors. These findings provide new foundation to guide future development of bioinspired, flapping wing mechanisms for micro air vehicle applications, and may be used to provide insight to the dipteran muscle-to-wing interface. PMID:25608517

Optimized bio-inspired stiffening design for an engine nacelle.

PubMed

Lazo, Neil; Vodenitcharova, Tania; Hoffman, Mark

2015-11-04

Structural efficiency is a common engineering goal in which an ideal solution provides a structure with optimized performance at minimized weight, with consideration of material mechanical properties, structural geometry, and manufacturability. This study aims to address this goal in developing high performance lightweight, stiff mechanical components by creating an optimized design from a biologically-inspired template. The approach is implemented on the optimization of rib stiffeners along an aircraft engine nacelle. The helical and angled arrangements of cellulose fibres in plants were chosen as the bio-inspired template. Optimization of total displacement and weight was carried out using a genetic algorithm (GA) coupled with finite element analysis. Iterations showed a gradual convergence in normalized fitness. Displacement was given higher emphasis in optimization, thus the GA optimization tended towards individual designs with weights near the mass constraint. Dominant features of the resulting designs were helical ribs with rectangular cross-sections having large height-to-width ratio. Displacement reduction was at 73% as compared to an unreinforced nacelle, and is attributed to the geometric features and layout of the stiffeners, while mass is maintained within the constraint.

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

PubMed

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

2017-08-29

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

[Development and Application of Catalytic Tyrosine Modification].

PubMed

Sato, Shinichi; Tsushima, Michihiko; Nakamura, Kosuke; Nakamura, Hiroyuki

2018-01-01

 The chemical labeling of proteins with synthetic probes is a key technique used in chemical biology, protein-based therapy, and material science. Much of the chemical labeling of native proteins, however, depends on the labeling of lysine and cysteine residues. While those methods have significantly contributed to native protein labeling, alternative methods that can modify different amino acid residues are still required. Herein we report the development of a novel methodology of tyrosine labeling, inspired by the luminol chemiluminescence reaction. Tyrosine residues are often exposed on a protein's surface and are thus expected to be good targets for protein functionalization. In our studies so far, we have found that 1) hemin oxidatively activates luminol derivatives as a catalyst, 2) N-methyl luminol derivative specifically forms a covalent bond with a tyrosine residue among the 20 kinds of natural amino acid residues, and 3) the efficiency of tyrosine labeling with N-methyl luminol derivative is markedly improved by using horseradish peroxidase (HRP) as a catalyst. We were able to use molecular oxygen as an oxidant under HRP/NADH conditions. By using these methods, the functionalization of purified proteins was carried out. Because N-methyl luminol derivative is an excellent protein labeling reagent that responds to the activation of peroxidase, this new method is expected to open doors to such biological applications as the signal amplification of HRP-conjugated antibodies and the detection of protein association in combination with peroxidase-tag technology.

Conditioning of Model Identification Task in Immune Inspired Optimizer SILO

NASA Astrophysics Data System (ADS)

Wojdan, K.; Swirski, K.; Warchol, M.; Maciorowski, M.

2009-10-01

Methods which provide good conditioning of model identification task in immune inspired, steady-state controller SILO (Stochastic Immune Layer Optimizer) are presented in this paper. These methods are implemented in a model based optimization algorithm. The first method uses a safe model to assure that gains of the process's model can be estimated. The second method is responsible for elimination of potential linear dependences between columns of observation matrix. Moreover new results from one of SILO implementation in polish power plant are presented. They confirm high efficiency of the presented solution in solving technical problems.

Optimal time points sampling in pathway modelling.

PubMed

Hu, Shiyan

2004-01-01

Modelling cellular dynamics based on experimental data is at the heart of system biology. Considerable progress has been made to dynamic pathway modelling as well as the related parameter estimation. However, few of them gives consideration for the issue of optimal sampling time selection for parameter estimation. Time course experiments in molecular biology rarely produce large and accurate data sets and the experiments involved are usually time consuming and expensive. Therefore, to approximate parameters for models with only few available sampling data is of significant practical value. For signal transduction, the sampling intervals are usually not evenly distributed and are based on heuristics. In the paper, we investigate an approach to guide the process of selecting time points in an optimal way to minimize the variance of parameter estimates. In the method, we first formulate the problem to a nonlinear constrained optimization problem by maximum likelihood estimation. We then modify and apply a quantum-inspired evolutionary algorithm, which combines the advantages of both quantum computing and evolutionary computing, to solve the optimization problem. The new algorithm does not suffer from the morass of selecting good initial values and being stuck into local optimum as usually accompanied with the conventional numerical optimization techniques. The simulation results indicate the soundness of the new method.

Analysis and Purification of Bioactive Natural Products: The AnaPurNa Study

PubMed Central

2012-01-01

Based on a meta-analysis of data mined from almost 2000 publications on bioactive natural products (NPs) from >80 000 pages of 13 different journals published in 1998–1999, 2004–2005, and 2009–2010, the aim of this systematic review is to provide both a survey of the status quo and a perspective for analytical methodology used for isolation and purity assessment of bioactive NPs. The study provides numerical measures of the common means of sourcing NPs, the chromatographic methodology employed for NP purification, and the role of spectroscopy and purity assessment in NP characterization. A link is proposed between the observed use of various analytical methodologies, the challenges posed by the complexity of metabolomes, and the inescapable residual complexity of purified NPs and their biological assessment. The data provide inspiration for the development of innovative methods for NP analysis as a means of advancing the role of naturally occurring compounds as a viable source of biologically active agents with relevance for human health and global benefit. PMID:22620854

Functionalization of 3D scaffolds with protein-releasing biomaterials for intracellular delivery.

PubMed

Seras-Franzoso, Joaquin; Steurer, Christoph; Roldán, Mònica; Vendrell, Meritxell; Vidaurre-Agut, Carla; Tarruella, Anna; Saldaña, Laura; Vilaboa, Nuria; Parera, Marc; Elizondo, Elisa; Ratera, Imma; Ventosa, Nora; Veciana, Jaume; Campillo-Fernández, Alberto J; García-Fruitós, Elena; Vázquez, Esther; Villaverde, Antonio

2013-10-10

Appropriate combinations of mechanical and biological stimuli are required to promote proper colonization of substrate materials in regenerative medicine. In this context, 3D scaffolds formed by compatible and biodegradable materials are under continuous development in an attempt to mimic the extracellular environment of mammalian cells. We have here explored how novel 3D porous scaffolds constructed by polylactic acid, polycaprolactone or chitosan can be decorated with bacterial inclusion bodies, submicron protein particles formed by releasable functional proteins. A simple dipping-based decoration method tested here specifically favors the penetration of the functional particles deeper than 300μm from the materials' surface. The functionalized surfaces support the intracellular delivery of biologically active proteins to up to more than 80% of the colonizing cells, a process that is slightly influenced by the chemical nature of the scaffold. The combination of 3D soft scaffolds and protein-based sustained release systems (Bioscaffolds) offers promise in the fabrication of bio-inspired hybrid matrices for multifactorial control of cell proliferation in tissue engineering under complex architectonic setting-ups. © 2013.

Applying a multiobjective metaheuristic inspired by honey bees to phylogenetic inference.

PubMed

Santander-Jiménez, Sergio; Vega-Rodríguez, Miguel A

2013-10-01

The development of increasingly popular multiobjective metaheuristics has allowed bioinformaticians to deal with optimization problems in computational biology where multiple objective functions must be taken into account. One of the most relevant research topics that can benefit from these techniques is phylogenetic inference. Throughout the years, different researchers have proposed their own view about the reconstruction of ancestral evolutionary relationships among species. As a result, biologists often report different phylogenetic trees from a same dataset when considering distinct optimality principles. In this work, we detail a multiobjective swarm intelligence approach based on the novel Artificial Bee Colony algorithm for inferring phylogenies. The aim of this paper is to propose a complementary view of phylogenetics according to the maximum parsimony and maximum likelihood criteria, in order to generate a set of phylogenetic trees that represent a compromise between these principles. Experimental results on a variety of nucleotide data sets and statistical studies highlight the relevance of the proposal with regard to other multiobjective algorithms and state-of-the-art biological methods. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Copper-catalysed enantioselective stereodivergent synthesis of amino alcohols.

PubMed

Shi, Shi-Liang; Wong, Zackary L; Buchwald, Stephen L

2016-04-21

The chirality, or 'handedness', of a biologically active molecule can alter its physiological properties. Thus it is routine procedure in the drug discovery and development process to prepare and fully characterize all possible stereoisomers of a drug candidate for biological evaluation. Despite many advances in asymmetric synthesis, developing general and practical strategies for obtaining all possible stereoisomers of an organic compound that has multiple contiguous stereocentres remains a challenge. Here, we report a stereodivergent copper-based approach for the expeditious construction of amino alcohols with high levels of chemo-, regio-, diastereo- and enantioselectivity. Specifically, we synthesized these amino-alcohol products using sequential, copper-hydride-catalysed hydrosilylation and hydroamination of readily available enals and enones. This strategy provides a route to all possible stereoisomers of the amino-alcohol products, which contain up to three contiguous stereocentres. We leveraged catalyst control and stereospecificity simultaneously to attain exceptional control of the product stereochemistry. Beyond the immediate utility of this protocol, our strategy could inspire the development of methods that provide complete sets of stereoisomers for other valuable synthetic targets.

Synthetic Biological Approaches to Natural Product Biosynthesis

PubMed Central

Winter, Jaclyn M; Tang, Yi

2012-01-01

Small molecules produced in Nature continue to be an inspiration for the development of new therapeutic agents. These natural products possess exquisite chemical diversity, which gives rise to their wide range of biological activities. In their host organism, natural products are assembled and modified by dedicated biosynthetic pathways that Nature has meticulously developed. Often times, the complex structures or chemical modifications instated by these pathways are difficult to replicate using traditional synthetic methods. An alternative approach for creating or enhancing the structural variation of natural products is through combinatorial biosynthesis. By rationally reprogramming and manipulating the biosynthetic machinery responsible for their production, unnatural metabolites that were otherwise inaccessible can be obtained. Additionally, new chemical structures can be synthesized or derivatized by developing the enzymes that carry out these complicated chemical reactions into biocatalysts. In this review, we will discuss a variety of combinatorial biosynthetic strategies, their technical challenges, and highlight some recent (since 2007) examples of rationally designed unnatural metabolites, as well as platforms that have been established for the production and modification of clinically important pharmaceutical compounds. PMID:22221832

Cell Surface and Membrane Engineering: Emerging Technologies and Applications

PubMed Central

Saeui, Christopher T.; Mathew, Mohit P.; Liu, Lingshui; Urias, Esteban; Yarema, Kevin J.

2015-01-01

Membranes constitute the interface between the basic unit of life—a single cell—and the outside environment and thus in many ways comprise the ultimate “functional biomaterial”. To perform the many and often conflicting functions required in this role, for example to partition intracellular contents from the outside environment while maintaining rapid intake of nutrients and efflux of waste products, biological membranes have evolved tremendous complexity and versatility. This article describes how membranes, mainly in the context of living cells, are increasingly being manipulated for practical purposes with drug discovery, biofuels, and biosensors providing specific, illustrative examples. Attention is also given to biology-inspired, but completely synthetic, membrane-based technologies that are being enabled by emerging methods such as bio-3D printers. The diverse set of applications covered in this article are intended to illustrate how these versatile technologies—as they rapidly mature—hold tremendous promise to benefit human health in numerous ways ranging from the development of new medicines to sensitive and cost-effective environmental monitoring for pathogens and pollutants to replacing hydrocarbon-based fossil fuels. PMID:26096148

Discerning the Chemistry in Individual Organelles with Small-Molecule Fluorescent Probes.

PubMed

Xu, Wang; Zeng, Zebing; Jiang, Jian-Hui; Chang, Young-Tae; Yuan, Lin

2016-10-24

Principle has it that even the most advanced super-resolution microscope would be futile in providing biological insight into subcellular matrices without well-designed fluorescent tags/probes. Developments in biology have increasingly been boosted by advances of chemistry, with one prominent example being small-molecule fluorescent probes that not only allow cellular-level imaging, but also subcellular imaging. A majority, if not all, of the chemical/biological events take place inside cellular organelles, and researchers have been shifting their attention towards these substructures with the help of fluorescence techniques. This Review summarizes the existing fluorescent probes that target chemical/biological events within a single organelle. More importantly, organelle-anchoring strategies are described and emphasized to inspire the design of new generations of fluorescent probes, before concluding with future prospects on the possible further development of chemical biology. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Synergizing Engineering and Biology to Treat and Model Skeletal Muscle Injury and Disease

PubMed Central

Bursac, Nenad; Juhas, Mark; Rando, Thomas A.

2016-01-01

Although skeletal muscle is one of the most regenerative organs in our body, various genetic defects, alterations in extrinsic signaling, or substantial tissue damage can impair muscle function and the capacity for self-repair. The diversity and complexity of muscle disorders have attracted much interest from both cell biologists and, more recently, bioengineers, leading to concentrated efforts to better understand muscle pathology and develop more efficient therapies. This review describes the biological underpinnings of muscle development, repair, and disease, and discusses recent bioengineering efforts to design and control myomimetic environments, both to study muscle biology and function and to aid in the development of new drug, cell, and gene therapies for muscle disorders. The synergy between engineering-aided biological discovery and biology-inspired engineering solutions will be the path forward for translating laboratory results into clinical practice. PMID:26643021

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

PubMed

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

2016-01-01

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

GeneLab for High Schools: Data Mining for the Next Generation

NASA Technical Reports Server (NTRS)

Blaber, Elizabeth A.; Ly, Diana; Sato, Kevin Y.; Taylor, Elizabeth

2016-01-01

Modern biological sciences have become increasingly based on molecular biology and high-throughput molecular techniques, such as genomics, transcriptomics, and proteomics. NASA Scientists and the NASA Space Biology Program have aimed to examine the fundamental building blocks of life (RNA, DNA and protein) in order to understand the response of living organisms to space and aid in fundamental research discoveries on Earth. In an effort to enable NASA funded science to be available to everyone, NASA has collected the data from omics studies and curated them in a data system called GeneLab. Whilst most college-level interns, academics and other scientists have had some interaction with omics data sets and analysis tools, high school students often have not. Therefore, the Space Biology Program is implementing a new Summer Program for high-school students that aims to inspire the next generation of scientists to learn about and get involved in space research using GeneLabs Data System. The program consists of three main components core learning modules, focused on developing students knowledge on the Space Biology Program and Space Biology research, Genelab and the data system, and previous research conducted on model organisms in space; networking and team work, enabling students to interact with guest lecturers from local universities and their fellow peers, and also enabling them to visit local universities and genomics centers around the Bay area; and finally an independent learning project, whereby students will be required to form small groups, analyze a dataset on the Genelab platform, generate a hypothesis and develop a research plan to test their hypothesis. This program will not only help inspire high-school students to become involved in space-based research but will also help them develop key critical thinking and bioinformatics skills required for most college degrees and furthermore, will enable them to establish networks with their peers and connections with university Professors that may help them achieve their educational goals.

SEQUOIA: significance enhanced network querying through context-sensitive random walk and minimization of network conductance.

PubMed

Jeong, Hyundoo; Yoon, Byung-Jun

2017-03-14

Network querying algorithms provide computational means to identify conserved network modules in large-scale biological networks that are similar to known functional modules, such as pathways or molecular complexes. Two main challenges for network querying algorithms are the high computational complexity of detecting potential isomorphism between the query and the target graphs and ensuring the biological significance of the query results. In this paper, we propose SEQUOIA, a novel network querying algorithm that effectively addresses these issues by utilizing a context-sensitive random walk (CSRW) model for network comparison and minimizing the network conductance of potential matches in the target network. The CSRW model, inspired by the pair hidden Markov model (pair-HMM) that has been widely used for sequence comparison and alignment, can accurately assess the node-to-node correspondence between different graphs by accounting for node insertions and deletions. The proposed algorithm identifies high-scoring network regions based on the CSRW scores, which are subsequently extended by maximally reducing the network conductance of the identified subnetworks. Performance assessment based on real PPI networks and known molecular complexes show that SEQUOIA outperforms existing methods and clearly enhances the biological significance of the query results. The source code and datasets can be downloaded from http://www.ece.tamu.edu/~bjyoon/SEQUOIA .

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

Fungus-mediated biological synthesis of gold nanoparticles: potential in detection of liver cancer

PubMed Central

Chauhan, Arun; Zubair, Swaleha; Tufail, Saba; Sherwani, Asif; Sajid, Mohammad; Raman, Suri C; Azam, Amir; Owais, Mohammad

2011-01-01

Background Nanomaterials are considered to be the pre-eminent component of the rapidly advancing field of nanotechnology. However, developments in the biologically inspired synthesis of nanoparticles are still in their infancy and consequently attracting the attention of material scientists throughout the world. Keeping in mind the fact that microorganism-assisted synthesis of nanoparticles is a safe and economically viable prospect, in the current study we report Candida albicans-mediated biological synthesis of gold nanoparticles. Methods and results Transmission electron microscopy, atomic force microscopy, and various spectrophotometric analyses were performed to characterize the gold nanoparticles. The morphology of the synthesized gold particles depended on the abundance of C. albicans cytosolic extract. Transmission electron microscopy, nanophox particle analysis, and atomic force microscopy revealed the size of spherical gold nanoparticles to be in the range of 20–40 nm and nonspherical gold particles were found to be 60–80 nm. We also evaluated the potential of biogenic gold nanoparticles to probe liver cancer cells by conjugating them with liver cancer cell surface-specific antibodies. The antibody-conjugated gold particles were found to bind specifically to the surface antigens of the cancer cells. Conclusion The antibody-conjugated gold particles synthesized in this study could successfully differentiate normal cell populations from cancerous cells. PMID:22072868

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.

Towards enhancement of performance of K-means clustering using nature-inspired optimization algorithms.

PubMed

Fong, Simon; Deb, Suash; Yang, Xin-She; Zhuang, Yan

2014-01-01

Traditional K-means clustering algorithms have the drawback of getting stuck at local optima that depend on the random values of initial centroids. Optimization algorithms have their advantages in guiding iterative computation to search for global optima while avoiding local optima. The algorithms help speed up the clustering process by converging into a global optimum early with multiple search agents in action. Inspired by nature, some contemporary optimization algorithms which include Ant, Bat, Cuckoo, Firefly, and Wolf search algorithms mimic the swarming behavior allowing them to cooperatively steer towards an optimal objective within a reasonable time. It is known that these so-called nature-inspired optimization algorithms have their own characteristics as well as pros and cons in different applications. When these algorithms are combined with K-means clustering mechanism for the sake of enhancing its clustering quality by avoiding local optima and finding global optima, the new hybrids are anticipated to produce unprecedented performance. In this paper, we report the results of our evaluation experiments on the integration of nature-inspired optimization methods into K-means algorithms. In addition to the standard evaluation metrics in evaluating clustering quality, the extended K-means algorithms that are empowered by nature-inspired optimization methods are applied on image segmentation as a case study of application scenario.

Towards Enhancement of Performance of K-Means Clustering Using Nature-Inspired Optimization Algorithms

PubMed Central

Deb, Suash; Yang, Xin-She

2014-01-01

Traditional K-means clustering algorithms have the drawback of getting stuck at local optima that depend on the random values of initial centroids. Optimization algorithms have their advantages in guiding iterative computation to search for global optima while avoiding local optima. The algorithms help speed up the clustering process by converging into a global optimum early with multiple search agents in action. Inspired by nature, some contemporary optimization algorithms which include Ant, Bat, Cuckoo, Firefly, and Wolf search algorithms mimic the swarming behavior allowing them to cooperatively steer towards an optimal objective within a reasonable time. It is known that these so-called nature-inspired optimization algorithms have their own characteristics as well as pros and cons in different applications. When these algorithms are combined with K-means clustering mechanism for the sake of enhancing its clustering quality by avoiding local optima and finding global optima, the new hybrids are anticipated to produce unprecedented performance. In this paper, we report the results of our evaluation experiments on the integration of nature-inspired optimization methods into K-means algorithms. In addition to the standard evaluation metrics in evaluating clustering quality, the extended K-means algorithms that are empowered by nature-inspired optimization methods are applied on image segmentation as a case study of application scenario. PMID:25202730

Systems biology and mechanics of growth.

PubMed

Eskandari, Mona; Kuhl, Ellen

2015-01-01

In contrast to inert systems, living biological systems have the advantage to adapt to their environment through growth and evolution. This transfiguration is evident during embryonic development, when the predisposed need to grow allows form to follow function. Alterations in the equilibrium state of biological systems breed disease and mutation in response to environmental triggers. The need to characterize the growth of biological systems to better understand these phenomena has motivated the continuum theory of growth and stimulated the development of computational tools in systems biology. Biological growth in development and disease is increasingly studied using the framework of morphoelasticity. Here, we demonstrate the potential for morphoelastic simulations through examples of volume, area, and length growth, inspired by tumor expansion, chronic bronchitis, brain development, intestine formation, plant shape, and myopia. We review the systems biology of living systems in light of biochemical and optical stimuli and classify different types of growth to facilitate the design of growth models for various biological systems within this generic framework. Exploring the systems biology of growth introduces a new venue to control and manipulate embryonic development, disease progression, and clinical intervention. © 2015 Wiley Periodicals, Inc.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Obstacle traversal and self-righting of bio-inspired robots reveal the physics of multi-modal locomotion

NASA Astrophysics Data System (ADS)

Li, Chen; Fearing, Ronald; Full, Robert

Most animals move in nature in a variety of locomotor modes. For example, to traverse obstacles like dense vegetation, cockroaches can climb over, push across, reorient their bodies to maneuver through slits, or even transition among these modes forming diverse locomotor pathways; if flipped over, they can also self-right using wings or legs to generate body pitch or roll. By contrast, most locomotion studies have focused on a single mode such as running, walking, or jumping, and robots are still far from capable of life-like, robust, multi-modal locomotion in the real world. Here, we present two recent studies using bio-inspired robots, together with new locomotion energy landscapes derived from locomotor-environment interaction physics, to begin to understand the physics of multi-modal locomotion. (1) Our experiment of a cockroach-inspired legged robot traversing grass-like beam obstacles reveals that, with a terradynamically ``streamlined'' rounded body like that of the insect, robot traversal becomes more probable by accessing locomotor pathways that overcome lower potential energy barriers. (2) Our experiment of a cockroach-inspired self-righting robot further suggests that body vibrations are crucial for exploring locomotion energy landscapes and reaching lower barrier pathways. Finally, we posit that our new framework of locomotion energy landscapes holds promise to better understand and predict multi-modal biological and robotic movement.

A sensor network based virtual beam-like structure method for fault diagnosis and monitoring of complex structures with Improved Bacterial Optimization

NASA Astrophysics Data System (ADS)

Wang, H.; Jing, X. J.

2017-02-01

This paper proposes a novel method for the fault diagnosis of complex structures based on an optimized virtual beam-like structure approach. A complex structure can be regarded as a combination of numerous virtual beam-like structures considering the vibration transmission path from vibration sources to each sensor. The structural 'virtual beam' consists of a sensor chain automatically obtained by an Improved Bacterial Optimization Algorithm (IBOA). The biologically inspired optimization method (i.e. IBOA) is proposed for solving the discrete optimization problem associated with the selection of the optimal virtual beam for fault diagnosis. This novel virtual beam-like-structure approach needs less or little prior knowledge. Neither does it require stationary response data, nor is it confined to a specific structure design. It is easy to implement within a sensor network attached to the monitored structure. The proposed fault diagnosis method has been tested on the detection of loosening screws located at varying positions in a real satellite-like model. Compared with empirical methods, the proposed virtual beam-like structure method has proved to be very effective and more reliable for fault localization.

Respiratory mechanics by least squares fitting in mechanically ventilated patients: application on flow-limited COPD patients.

PubMed

Volta, Carlo A; Marangoni, Elisabetta; Alvisi, Valentina; Capuzzo, Maurizia; Ragazzi, Riccardo; Pavanelli, Lina; Alvisi, Raffaele

2002-01-01

Although computerized methods of analyzing respiratory system mechanics such as the least squares fitting method have been used in various patient populations, no conclusive data are available in patients with chronic obstructive pulmonary disease (COPD), probably because they may develop expiratory flow limitation (EFL). This suggests that respiratory mechanics be determined only during inspiration. Eight-bed multidisciplinary ICU of a teaching hospital. Eight non-flow-limited postvascular surgery patients and eight flow-limited COPD patients. Patients were sedated, paralyzed for diagnostic purposes, and ventilated in volume control ventilation with constant inspiratory flow rate. Data on resistance, compliance, and dynamic intrinsic positive end-expiratory pressure (PEEPi,dyn) obtained by applying the least squares fitting method during inspiration, expiration, and the overall breathing cycle were compared with those obtained by the traditional method (constant flow, end-inspiratory occlusion method). Our results indicate that (a) the presence of EFL markedly decreases the precision of resistance and compliance values measured by the LSF method, (b) the determination of respiratory variables during inspiration allows the calculation of respiratory mechanics in flow limited COPD patients, and (c) the LSF method is able to detect the presence of PEEPi,dyn if only inspiratory data are used.

A mechanical analysis of woodpecker drumming and its application to shock-absorbing systems.

PubMed

Yoon, Sang-Hee; Park, Sungmin

2011-03-01

A woodpecker is known to drum the hard woody surface of a tree at a rate of 18 to 22 times per second with a deceleration of 1200 g, yet with no sign of blackout or brain damage. As a model in nature, a woodpecker is studied to find clues to develop a shock-absorbing system for micromachined devices. Its advanced shock-absorbing mechanism, which cannot be explained merely by allometric scaling, is analyzed in terms of endoskeletal structures. In this analysis, the head structures (beak, hyoid, spongy bone, and skull bone with cerebrospinal fluid) of the golden-fronted woodpecker, Melanerpes aurifrons, are explored with x-ray computed tomography images, and their shock-absorbing mechanism is analyzed with a mechanical vibration model and an empirical method. Based on these analyses, a new shock-absorbing system is designed to protect commercial micromachined devices from unwanted high-g and high-frequency mechanical excitations. The new shock-absorbing system consists of close-packed microglasses within two metal enclosures and a viscoelastic layer fastened by steel bolts, which are biologically inspired from a spongy bone contained within a skull bone encompassed with the hyoid of a woodpecker. In the experimental characterizations using a 60 mm smoothbore air-gun, this bio-inspired shock-absorbing system shows a failure rate of 0.7% for the commercial micromachined devices at 60 000 g, whereas a conventional hard-resin method yields a failure rate of 26.4%, thus verifying remarkable improvement in the g-force tolerance of the commercial micromachined devices.

Bio-inspired hybrid microelectrodes: a hybrid solution to improve long-term performance of chronic intracortical implants.

PubMed

De Faveri, Sara; Maggiolini, Emma; Miele, Ermanno; De Angelis, Francesco; Cesca, Fabrizia; Benfenati, Fabio; Fadiga, Luciano

2014-01-01

The use of implants that allow chronic electrical stimulation and recording in the brain of human patients is currently limited by a series of events that cause the deterioration over time of both the electrode surface and the surrounding tissue. The main reason of failure is the tissue inflammatory reaction that eventually causes neuronal loss and glial encapsulation, resulting in a progressive increase of the electrode-electrolyte impedance. Here, we describe a new method to create bio-inspired electrodes to mimic the mechanical properties and biological composition of the host tissue. This combination has a great potential to increase the implant lifetime by reducing tissue reaction and improving electrical coupling. Our method implies coating the electrode with reprogrammed neural or glial cells encapsulated within a hydrogel layer. We chose fibrin as a hydrogel and primary hippocampal neurons or astrocytes from rat brain as cellular layer. We demonstrate that fibrin coating is highly biocompatible, forms uniform coatings of controllable thickness, does not alter the electrochemical properties of the microelectrode and allows good quality recordings. Moreover, it reduces the amount of host reactive astrocytes - over time - compared to a bare wire and is fully reabsorbed by the surrounding tissue within 7 days after implantation, avoiding the common problem of hydrogels swelling. Both astrocytes and neurons could be successfully grown onto the electrode surface within the fibrin hydrogel without altering the electrochemical properties of the microelectrode. This bio-hybrid device has therefore a good potential to improve the electrical integration at the neuron-electrode interface and support the long-term success of neural prostheses.

Reconstruction of gene regulatory modules from RNA silencing of IFN-α modulators: experimental set-up and inference method.

PubMed

Grassi, Angela; Di Camillo, Barbara; Ciccarese, Francesco; Agnusdei, Valentina; Zanovello, Paola; Amadori, Alberto; Finesso, Lorenzo; Indraccolo, Stefano; Toffolo, Gianna Maria

2016-03-12

Inference of gene regulation from expression data may help to unravel regulatory mechanisms involved in complex diseases or in the action of specific drugs. A challenging task for many researchers working in the field of systems biology is to build up an experiment with a limited budget and produce a dataset suitable to reconstruct putative regulatory modules worth of biological validation. Here, we focus on small-scale gene expression screens and we introduce a novel experimental set-up and a customized method of analysis to make inference on regulatory modules starting from genetic perturbation data, e.g. knockdown and overexpression data. To illustrate the utility of our strategy, it was applied to produce and analyze a dataset of quantitative real-time RT-PCR data, in which interferon-α (IFN-α) transcriptional response in endothelial cells is investigated by RNA silencing of two candidate IFN-α modulators, STAT1 and IFIH1. A putative regulatory module was reconstructed by our method, revealing an intriguing feed-forward loop, in which STAT1 regulates IFIH1 and they both negatively regulate IFNAR1. STAT1 regulation on IFNAR1 was object of experimental validation at the protein level. Detailed description of the experimental set-up and of the analysis procedure is reported, with the intent to be of inspiration for other scientists who want to realize similar experiments to reconstruct gene regulatory modules starting from perturbations of possible regulators. Application of our approach to the study of IFN-α transcriptional response modulators in endothelial cells has led to many interesting novel findings and new biological hypotheses worth of validation.

Check-Up of Planet Earth at the Turn of the Millennium: Anticipated New Phase in Earth Sciences

NASA Technical Reports Server (NTRS)

Kaufman, Y. J.; Ramanathan, V.

1998-01-01

Langley's remarkable solar and lunar spectra collected from Mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. In 1999, NASA's Earth Observing AM Satellite (EOS-AM) will repeat Langley's experiment, but for the entire planet, thus pioneering calibrated spectral observations from space. Conceived in response to real environmental problems, EOS-AM, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution of few kilometers on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-AM can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment.

Protein-based underwater adhesives and the prospects for their biotechnological production.

PubMed

Stewart, Russell J

2011-01-01

Biotechnological approaches to practical production of biological protein-based adhesives have had limited success over the last several decades. Broader efforts to produce recombinant adhesive proteins may have been limited by early disappointments. More recent synthetic polymer approaches have successfully replicated some aspects of natural underwater adhesives. For example, synthetic polymers, inspired by mussels, containing the catecholic functional group of 3,4-L-dihydroxyphenylalanine adhere strongly to wet metal oxide surfaces. Synthetic complex coacervates inspired by the Sandcastle worm are water-borne adhesives that can be delivered underwater without dispersing. Synthetic approaches offer several advantages, including versatile chemistries and scalable production. In the future, more sophisticated mimetic adhesives may combine synthetic copolymers with recombinant or agriculture-derived proteins to better replicate the structural and functional organization of natural adhesives.

Protein-based underwater adhesives and the prospects for their biotechnological production

PubMed Central

Stewart, Russell J.

2011-01-01

Biotechnological approaches to practical production of biological protein-based adhesives have had limited success over the last several decades. Broader efforts to produce recombinant adhesive proteins may have been limited by early disappointments. More recent synthetic polymer approaches have successfully replicated some aspects of natural underwater adhesives. For example, synthetic polymers, inspired by mussels, containing the catecholic functional group of 3,4-L-dihydroxyphenylalanine adhere strongly to wet metal oxide surfaces. Synthetic complex coacervates inspired by the Sandcastle worm are water-borne adhesives that can be delivered underwater without dispersing. Synthetic approaches offer several advantages, including versatile chemistries and scalable production. In the future, more sophisticated mimetic adhesives may combine synthetic copolymers with recombinant or agriculture-derived proteins to better replicate the structural and functional organization of natural adhesives. PMID:20890598

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

PubMed

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

2014-04-01

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

Water repellent/wetting characteristics of various bio-inspired morphologies and fluid drag reduction testing research.

PubMed

Luo, Yuehao; Song, Wen; Wang, Xudong

2016-03-01

It is well-known that the bio-inspired sharkskin covering the original pattern has the apparent drag reduction function in the turbulent flowing stations, which can be regarded as "sharkskin effect", and it has progressively been put application into the fluid engineering with obtaining great profits. In this paper, the anisotropic wetting phenomena on sharkskin are discovered, the contact angles and rolling angles on different orientations are not the same. In addition, the hydrodynamic experiments on different sharkskin surfaces are conducted, and the experimental results illustrate that the super-hydrophobic and drag-reducing properties on deformed biological surfaces are improved to some extent compared to the original morphology, which has important significance to expand its practical applications. Copyright © 2015 Elsevier Ltd. All rights reserved.

Unexpected amino acid composition of modern Reptilia and its implications in molecular mechanisms of dinosaur extinction.

PubMed

Wang, Guang-Zhong; Ma, Bin-Guang; Yang, Yan; Zhang, Hong-Yu

2005-08-12

Dinosaur extinction is a great challenge to evolutionary biology. Although accumulating evidence suggests that an abrupt change of environment, such as a long period of low temperature induced by asteroid hit or other disasters, may be responsible for dinosaur extinction, little is known about the underlying molecular mechanisms. By analyzing the amino acid compositions of 13 biological classes, we found that the charged amino acid content of modern Reptilia, the sibling of dinosaur, is strikingly different from those of other classes, which inspires us to propose a possible molecular mechanism for dinosaur extinction.

Engineering Ultimate Self-Protection in Autonomic Agents for Space Exploration Missions

NASA Technical Reports Server (NTRS)

Sterritt, Roy; Hinchey, Mike

2005-01-01

NASA's Exploration Initiative (EI) will push space exploration missions to the limit. Future missions will be required to be self-managing as well as self-directed, in order to meet the challenges of human and robotic space exploration. We discuss security and self protection in autonomic agent based-systems, and propose the ultimate self-protection mechanism for such systems-self-destruction. Like other metaphors in Autonomic Computing, this is inspired by biological systems, and is the analog of biological apoptosis. Finally, we discus the role it might play in future NASA space exploration missions.

Artificial Muscle Kits for the Classroom

NASA Technical Reports Server (NTRS)

2004-01-01

Commonly referred to as "artificial muscles," electroactive polymer (EAP) materials are lightweight strips of highly flexible plastic that bend or stretch when subjected to electric voltage. EAP materials may prove to be a substitution for conventional actuation components such as motors and gears. Since the materials behave similarly to biological muscles, this emerging technology has the potential to develop improved prosthetics and biologically-inspired robots, and may even one day replace damaged human muscles. The practical application of artificial muscles provides a challenge, however, since the material requires improved effectiveness and durability before it can fulfill its potential.

A functional approach to emotion in autonomous systems.

PubMed

Sanz, Ricardo; Hernández, Carlos; Gómez, Jaime; Hernando, Adolfo

2010-01-01

The construction of fully effective systems seems to pass through the proper exploitation of goal-centric self-evaluative capabilities that let the system teleologically self-manage. Emotions seem to provide this kind of functionality to biological systems and hence the interest in emotion for function sustainment in artificial systems performing in changing and uncertain environments; far beyond the media hullabaloo of displaying human-like emotion-laden faces in robots. This chapter provides a brief analysis of the scientific theories of emotion and presents an engineering approach for developing technology for robust autonomy by implementing functionality inspired in that of biological emotions.

Protein-centric N-glycoproteomics analysis of membrane and plasma membrane proteins.

PubMed

Sun, Bingyun; Hood, Leroy

2014-06-06

The advent of proteomics technology has transformed our understanding of biological membranes. The challenges for studying membrane proteins have inspired the development of many analytical and bioanalytical tools, and the techniques of glycoproteomics have emerged as an effective means to enrich and characterize membrane and plasma-membrane proteomes. This Review summarizes the development of various glycoproteomics techniques to overcome the hurdles formed by the unique structures and behaviors of membrane proteins with a focus on N-glycoproteomics. Example contributions of N-glycoproteomics to the understanding of membrane biology are provided, and the areas that require future technical breakthroughs are discussed.

Diversification and enrichment of clinical biomaterials inspired by Darwinian evolution.

PubMed

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

2016-09-15

Regenerative medicine and biomaterials design are driven by biomimicry. There is the essential requirement to emulate human cell, tissue, organ and physiological complexity to ensure long-lasting clinical success. Biomimicry projects for biomaterials innovation can be re-invigorated with evolutionary insights and perspectives, since Darwinian evolution is the original dynamic process for biological organisation and complexity. Many existing human inspired regenerative biomaterials (defined as a nature generated, nature derived and nature mimicking structure, produced within a biological system, which can deputise for, or replace human tissues for which it closely matches) are without important elements of biological complexity such as, hierarchy and autonomous actions. It is possible to engineer these essential elements into clinical biomaterials via bioinspired implementation of concepts, processes and mechanisms played out during Darwinian evolution; mechanisms such as, directed, computational, accelerated evolutions and artificial selection contrived in the laboratory. These dynamos for innovation can be used during biomaterials fabrication, but also to choose optimal designs in the regeneration process. Further evolutionary information can help at the design stage; gleaned from the historical evolution of material adaptations compared across phylogenies to changes in their environment and habitats. Taken together, harnessing evolutionary mechanisms and evolutionary pathways, leading to ideal adaptations, will eventually provide a new class of Darwinian and evolutionary biomaterials. This will provide bioengineers with a more diversified and more efficient innovation tool for biomaterial design, synthesis and function than currently achieved with synthetic materials chemistry programmes and rational based materials design approach, which require reasoned logic. It will also inject further creativity, diversity and richness into the biomedical technologies that we make. All of which are based on biological principles. Such evolution-inspired biomaterials have the potential to generate innovative solutions, which match with existing bioengineering problems, in vital areas of clinical materials translation that include tissue engineering, gene delivery, drug delivery, immunity modulation, and scar-less wound healing. Evolution by natural selection is a powerful generator of innovations in molecular, materials and structures. Man has influenced evolution for thousands of years, to create new breeds of farm animals and crop plants, but now molecular and materials can be molded in the same way. Biological molecules and simple structures can be evolved, literally in the laboratory. Furthermore, they are re-designed via lessons learnt from evolutionary history. Through a 3-step process to (1) create variants in material building blocks, (2) screen the variants with beneficial traits/properties and (3) select and support their self-assembly into usable materials, improvements in design and performance can emerge. By introducing biological molecules and small organisms into this process, it is possible to make increasingly diversified, sophisticated and clinically relevant materials for multiple roles in biomedicine. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

A Biologically-Inspired Neural Network Architecture for Image Processing

DTIC Science & Technology

1990-12-01

was organized into twelve groups of 8-by-8 node arrays. Weights were con- strained for each group of nodes, with each node "viewing" a 5-by-5 pixel...single wIndow * smk 0; for(J-0; j< 6 4 ; J++)( sum -sum +t %borfi][J]*rfarray[j]; ) /* Finished calculating ore block, one j:,,sition (first layer

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

DTIC Science & Technology

2011-03-24

4.13. The green circle denotes a ‘ self identification’ of a reference point. This allows a user to place the cursor over what he/she thought was a...deflection’. Figure 4.27 extrap- olates the point residual values (in %) associated with the points that are resposible for providing this thesis

From Informational Technology in Biology Teaching to Inspirational Technology: Where Have We Come from and Where Are We Going?

ERIC Educational Resources Information Center

Peat, Mary; Taylor, Charlotte; Fernandez, Anne

Today university students are demanding a greater say in their tertiary education. In particular they are demanding a greater flexibility in the way they receive their instruction, and it is imperative that course delivery strategies that fulfil these expectations are investigated. On-line delivery of learning materials offers teacher and students…

Advanced Nanostructures for Two-Phase Fluid and Thermal Transport

DTIC Science & Technology

2014-08-07

commercial applications. Pumped phase-change based microfluidic systems promise compact solutions with high heat removal capability. However...materials for liquid transport in microfluidics , cell manipulation in biological systems, and light tuning in optical applications via their...and 3c) with precise control for real- time fluid and optical manipulation. Inspired by hair and motile cilia on animal skin and plant leaves for

Biologically-Inspired Flight for Micro Air Vehicles

DTIC Science & Technology

2012-09-01

dense  vegetation   to   find   fruit,   and   the  nectarivorous  G.s.  must  hover  over   flowers   to   take   nectar...openings   in   two  nets   to   get   a   food   reward   ( banana ,   see   inset).     A:   average   flight   speed

Biological Inspiration for Agile Autonomous Air Vehicles

DTIC Science & Technology

2007-11-01

rhythmically contract the thorax; the hind wings have become specialized as small body rotation sensors (halteres). Butterflies and moths have two pairs of...orthogonal pairs of power muscles that produce alternating dorso-ventral and longitudinal flexure of the thorax from rhythmic contractions similar to...other physical sciences lend themselves to somewhat reductionist approaches for both analysis and synthesis. Complex engineered systems are built from

Use of Novel Surfaces to Reduce Bioadhesion on Infrastructure

DTIC Science & Technology

2010-06-01

Research and Development Center Model species selection • Terrestrial gastropod  Danger to crops  Intermediate host to pathogens  Nocturnal...TBT  Non-target species, legacy contamination  Laborious • Bio-inspiration: leverage biological surfaces that have adapted unique properties... Adapted over 1000s of years • Hypothesis: microstructured pattern tessellations, hydrophobicity, surface properties or hybridizations will reduce

The Use of the Dialogue Concepts from the Arsenal of the Norwegian Dialogue Pedagogy in the Time of Postmodernism

ERIC Educational Resources Information Center

Gradovski, Mikhail

2012-01-01

Inspired by the views by the American educationalist Henry Giroux on the role teachers and educationalists should be playing in the time of postmodernism and by Abraham Maslow's concept of biological idiosyncrasy, the author discusses how the concepts of the dialogues created by the representatives of Norwegian Dialogue Pedagogy, Hans Skjervheim,…

Pro-Apoptotic Breast Cancer Nanotherapeutics

DTIC Science & Technology

2013-07-01

Examples of nonspherical cell-penetrating particles existing in nature include the fila- mentous viruses such as the tobaccomosaic virus and the potato... virus X.4 Inspired by these examples from biology, Discher et al. have shown that cylindrical micelles have longer circulation times relative to...intended to create a protective corona around the assembled nanostructure, which would limit nonspecific adsorption of proteins and reduce proteolysis

From Informational Technology in Biology Teaching to Inspirational Technology: Where Have We Come from and Where Are We Going?

ERIC Educational Resources Information Center

Peat, Mary; Taylor, Charlotte; Fernandez, Anne

2002-01-01

Discusses undergraduate students' demand for a greater flexibility in the way that they receive their instruction, and introduces instructional changes from a teacher-centered focus to a student-centered focus at the University of Sydney. Uses a virtual learning environment (VLE) to encourage independence and increased flexibility of access.…

Obstacle Avoidance and Target Acquisition for Robot Navigation Using a Mixed Signal Analog/Digital Neuromorphic Processing System

PubMed Central

Milde, Moritz B.; Blum, Hermann; Dietmüller, Alexander; Sumislawska, Dora; Conradt, Jörg; Indiveri, Giacomo; Sandamirskaya, Yulia

2017-01-01

Neuromorphic hardware emulates dynamics of biological neural networks in electronic circuits offering an alternative to the von Neumann computing architecture that is low-power, inherently parallel, and event-driven. This hardware allows to implement neural-network based robotic controllers in an energy-efficient way with low latency, but requires solving the problem of device variability, characteristic for analog electronic circuits. In this work, we interfaced a mixed-signal analog-digital neuromorphic processor ROLLS to a neuromorphic dynamic vision sensor (DVS) mounted on a robotic vehicle and developed an autonomous neuromorphic agent that is able to perform neurally inspired obstacle-avoidance and target acquisition. We developed a neural network architecture that can cope with device variability and verified its robustness in different environmental situations, e.g., moving obstacles, moving target, clutter, and poor light conditions. We demonstrate how this network, combined with the properties of the DVS, allows the robot to avoid obstacles using a simple biologically-inspired dynamics. We also show how a Dynamic Neural Field for target acquisition can be implemented in spiking neuromorphic hardware. This work demonstrates an implementation of working obstacle avoidance and target acquisition using mixed signal analog/digital neuromorphic hardware. PMID:28747883

Biotemplated synthesis of inorganic materials: An emerging paradigm for nanomaterial synthesis inspired by nature

DOE PAGES

Krajina, Brad A.; Proctor, Amy C.; Schoen, Alia P.; ...

2017-08-08

Biomineralization, the process by which biological systems direct the synthesis of inorganic structures from organic templates, is an exquisite example of nanomaterial self-assembly in nature. Its products include the shells of mollusks and the bones and teeth of vertebrates. By comparison, conventional inorganic synthesis techniques provide limited control over inorganic nanomaterial architecture. Inspired by biomineralization in nature, over the last two decades, the field of biotemplating has emerged as a new paradigm for inorganic nanomaterial assembly, wherein researchers seek to design novel nano-structures in which inorganic nanomaterial synthesis is directed from an underlying biomolecular template. Here, we review the motivation,more » mechanistic understanding, progress, and challenges for the field of biotemplating. We highlight the interdisciplinary nature of this field, and survey a broad range of examples of bio-templated engineering: ranging from strategies that exploit the inherent capabilities of proteins in nature, to genetically-engineered systems that unlock new capabilities for self-assembly with biomolecules. Here, we illustrate that the use of biological materials as templates for inorganic self-assembly holds tremendous potential for nanomaterial engineering, with applications that range from electronics and energy to medicine.« less

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks

PubMed Central

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-01-01

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains. PMID:26972968

Biologically inspired EM image alignment and neural reconstruction.

PubMed

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

2011-08-15

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

Bacillus spores as building blocks for stimuli-responsive materials and nanogenerators

NASA Astrophysics Data System (ADS)

Sahin, Ozgur; Chen, Xi

2014-03-01

Materials that mechanically respond to external chemical stimuli have applications in a wide range of fields. Inspired by biological systems, stimuli-responsive materials that can oscillate, transport fluid, mimic homeostasis, and undergo complex changes in shape have been previously demonstrated. However, the effectiveness of synthetic stimuli-responsive materials in generating work is limited when compared to mechanical actuators. During studies of bacterial sporulation, we have found that the mechanical response of Bacillus spores to water gradients exhibits an energy density of more than 10 MJ/m3, which is two orders of magnitude higher than synthetic water-responsive materials. We also identified mutations that can approximately double the energy density of the spores, and found that spores can self-assemble into dense, submicron-thick monolayers on substrates such as silicon microcantilevers and elastomer sheets, creating self-assembled actuators that can remotely generate electrical power from an evaporating body of water. The energy conversion mechanism of Bacillus spores may facilitate synthetic stimuli-responsive materials with significantly higher energy densities. We acknowledge support from the U.S. Dept. of Energy Early Career Research Program, the Wyss Institute for Biologically Inspired Engineering, and the Rowland Institute at Harvard.

Design of a dynamic sensor inspired by bat ears

NASA Astrophysics Data System (ADS)

Müller, Rolf; Pannala, Mittu; Reddy, O. Praveen K.; Meymand, Sajjad Z.

2012-09-01

In bats, the outer ear shapes act as beamforming baffles that create a spatial sensitivity pattern for the reception of the biosonar signals. Whereas technical receivers for wave-based signals usually have rigid geometries, the outer ears of some bat species, such as horseshoe bats, can undergo non-rigid deformations as a result of muscular actuation. It is hypothesized that these deformations provide the animals with a mechanism to adapt their spatial hearing sensitivity on short, sub-second time scales. This biological approach could be of interest to engineering as an inspiration for the design of beamforming devices that combine flexibility with parsimonious implementation. To explore this possibility, a biomimetic dynamic baffle was designed based on a simple shape overall geometry based on an average bat ear. This shape was augmented with three different biomimetic local shape features, a ridge on its exposed surface as well as a flap and an incision along its rim. Dynamic non-rigid deformations of the shape were accomplished through a simple actuation mechanism based on linear actuation inserted at a single point. Despite its simplicity, the prototype device was able to reproduce the dynamic functional characteristics that have been predicted for its biological paragon in a qualitative fashion.

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks.

PubMed

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-03-14

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.

An electric-eel-inspired soft power source from stacked hydrogels.

PubMed

Schroeder, Thomas B H; Guha, Anirvan; Lamoureux, Aaron; VanRenterghem, Gloria; Sept, David; Shtein, Max; Yang, Jerry; Mayer, Michael

2017-12-13

Progress towards the integration of technology into living organisms requires electrical power sources that are biocompatible, mechanically flexible, and able to harness the chemical energy available inside biological systems. Conventional batteries were not designed with these criteria in mind. The electric organ of the knifefish Electrophorus electricus (commonly known as the electric eel) is, however, an example of an electrical power source that operates within biological constraints while featuring power characteristics that include peak potential differences of 600 volts and currents of 1 ampere. Here we introduce an electric-eel-inspired power concept that uses gradients of ions between miniature polyacrylamide hydrogel compartments bounded by a repeating sequence of cation- and anion-selective hydrogel membranes. The system uses a scalable stacking or folding geometry that generates 110 volts at open circuit or 27 milliwatts per square metre per gel cell upon simultaneous, self-registered mechanical contact activation of thousands of gel compartments in series while circumventing power dissipation before contact. Unlike typical batteries, these systems are soft, flexible, transparent, and potentially biocompatible. These characteristics suggest that artificial electric organs could be used to power next-generation implant materials such as pacemakers, implantable sensors, or prosthetic devices in hybrids of living and non-living systems.

Magnesium-aspartate-based crystallization switch inspired from shell molt of crustacean

PubMed Central

Tao, Jinhui; Zhou, Dongming; Zhang, Zhisen; Xu, Xurong; Tang, Ruikang

2009-01-01

Many animals such as crustacean periodically undergo cyclic molt of the exoskeleton. During this process, amorphous calcium mineral phases are biologically stabilized by magnesium and are reserved for the subsequent rapid formation of new shell tissue. However, it is a mystery how living organisms can regulate the transition of the precursor phases precisely. We reveal that the shell mineralization from the magnesium stabilized precursors is associated with the presence of Asp-rich proteins. It is suggested that a cooperative effect of magnesium and Asp-rich compound can result into a crystallization switch in biomineralization. Our in vitro experiments confirm that magnesium increases the lifetime of amorphous calcium carbonate and calcium phosphate in solution so that the crystallization can be temporarily switched off. Although Asp monomer alone inhibits the crystallization of pure amorphous calcium minerals, it actually reduces the stability of the magnesium-stabilized precursors to switch on the transformation from the amorphous to crystallized phases. These modification effects on crystallization kinetics can be understood by an Asp-enhanced magnesium desolvation model. The interesting magnesium-Asp-based switch is a biologically inspired lesson from nature, which can be developed into an advanced strategy to control material fabrications. PMID:20007788

Magnesium-aspartate-based crystallization switch inspired from shell molt of crustacean.

PubMed

Tao, Jinhui; Zhou, Dongming; Zhang, Zhisen; Xu, Xurong; Tang, Ruikang

2009-12-29

Many animals such as crustacean periodically undergo cyclic molt of the exoskeleton. During this process, amorphous calcium mineral phases are biologically stabilized by magnesium and are reserved for the subsequent rapid formation of new shell tissue. However, it is a mystery how living organisms can regulate the transition of the precursor phases precisely. We reveal that the shell mineralization from the magnesium stabilized precursors is associated with the presence of Asp-rich proteins. It is suggested that a cooperative effect of magnesium and Asp-rich compound can result into a crystallization switch in biomineralization. Our in vitro experiments confirm that magnesium increases the lifetime of amorphous calcium carbonate and calcium phosphate in solution so that the crystallization can be temporarily switched off. Although Asp monomer alone inhibits the crystallization of pure amorphous calcium minerals, it actually reduces the stability of the magnesium-stabilized precursors to switch on the transformation from the amorphous to crystallized phases. These modification effects on crystallization kinetics can be understood by an Asp-enhanced magnesium desolvation model. The interesting magnesium-Asp-based switch is a biologically inspired lesson from nature, which can be developed into an advanced strategy to control material fabrications.

Obstacle Avoidance and Target Acquisition for Robot Navigation Using a Mixed Signal Analog/Digital Neuromorphic Processing System.

PubMed

Milde, Moritz B; Blum, Hermann; Dietmüller, Alexander; Sumislawska, Dora; Conradt, Jörg; Indiveri, Giacomo; Sandamirskaya, Yulia

2017-01-01

Neuromorphic hardware emulates dynamics of biological neural networks in electronic circuits offering an alternative to the von Neumann computing architecture that is low-power, inherently parallel, and event-driven. This hardware allows to implement neural-network based robotic controllers in an energy-efficient way with low latency, but requires solving the problem of device variability, characteristic for analog electronic circuits. In this work, we interfaced a mixed-signal analog-digital neuromorphic processor ROLLS to a neuromorphic dynamic vision sensor (DVS) mounted on a robotic vehicle and developed an autonomous neuromorphic agent that is able to perform neurally inspired obstacle-avoidance and target acquisition. We developed a neural network architecture that can cope with device variability and verified its robustness in different environmental situations, e.g., moving obstacles, moving target, clutter, and poor light conditions. We demonstrate how this network, combined with the properties of the DVS, allows the robot to avoid obstacles using a simple biologically-inspired dynamics. We also show how a Dynamic Neural Field for target acquisition can be implemented in spiking neuromorphic hardware. This work demonstrates an implementation of working obstacle avoidance and target acquisition using mixed signal analog/digital neuromorphic hardware.

Biomimetics in the design of a robotic exoskeleton for upper limb therapy

NASA Astrophysics Data System (ADS)

Baniqued, Paul Dominick E.; Dungao, Jade R.; Manguerra, Michael V.; Baldovino, Renann G.; Abad, Alexander C.; Bugtai, Nilo T.

2018-02-01

Current methodologies in designing robotic exoskeletons for upper limb therapy simplify the complex requirements of the human anatomy. As a result, such devices tend to compromise safety and biocompatibility with the intended user. However, a new design methodology uses biological analogues as inspiration to address these technical issues. This approach follows that of biomimetics, a design principle that uses the extraction and transfer of useful information from natural morphologies and processes to solve technical design issues. In this study, a biomimetic approach in the design of a 5-degree-of-freedom robotic exoskeleton for upper limb therapy was performed. A review of biomimetics was first discussed along with its current contribution to the design of rehabilitation robots. With a proposed methodological framework, the design for an upper limb robotic exoskeleton was generated using CATIA software. The design was inspired by the morphology of the bones and the muscle force transmission of the upper limbs. Finally, a full design assembly presented had integrated features extracted from the biological analogue. The successful execution of a biomimetic design methodology made a case in providing safer and more biocompatible robots for rehabilitation.

An electric-eel-inspired soft power source from stacked hydrogels

NASA Astrophysics Data System (ADS)

Schroeder, Thomas B. H.; Guha, Anirvan; Lamoureux, Aaron; Vanrenterghem, Gloria; Sept, David; Shtein, Max; Yang, Jerry; Mayer, Michael

2017-12-01

Progress towards the integration of technology into living organisms requires electrical power sources that are biocompatible, mechanically flexible, and able to harness the chemical energy available inside biological systems. Conventional batteries were not designed with these criteria in mind. The electric organ of the knifefish Electrophorus electricus (commonly known as the electric eel) is, however, an example of an electrical power source that operates within biological constraints while featuring power characteristics that include peak potential differences of 600 volts and currents of 1 ampere. Here we introduce an electric-eel-inspired power concept that uses gradients of ions between miniature polyacrylamide hydrogel compartments bounded by a repeating sequence of cation- and anion-selective hydrogel membranes. The system uses a scalable stacking or folding geometry that generates 110 volts at open circuit or 27 milliwatts per square metre per gel cell upon simultaneous, self-registered mechanical contact activation of thousands of gel compartments in series while circumventing power dissipation before contact. Unlike typical batteries, these systems are soft, flexible, transparent, and potentially biocompatible. These characteristics suggest that artificial electric organs could be used to power next-generation implant materials such as pacemakers, implantable sensors, or prosthetic devices in hybrids of living and non-living systems.

Boundary layer drag reduction research hypotheses derived from bio-inspired surface and recent advanced applications.

PubMed

Luo, Yuehao; Yuan, Lu; Li, Jianhua; Wang, Jianshe

2015-12-01

Nature has supplied the inexhaustible resources for mankind, and at the same time, it has also progressively developed into the school for scientists and engineers. Through more than four billions years of rigorous and stringent evolution, different creatures in nature gradually exhibit their own special and fascinating biological functional surfaces. For example, sharkskin has the potential drag-reducing effect in turbulence, lotus leaf possesses the self-cleaning and anti-foiling function, gecko feet have the controllable super-adhesion surfaces, the flexible skin of dolphin can accelerate its swimming velocity. Great profits of applying biological functional surfaces in daily life, industry, transportation and agriculture have been achieved so far, and much attention from all over the world has been attracted and focused on this field. In this overview, the bio-inspired drag-reducing mechanism derived from sharkskin is explained and explored comprehensively from different aspects, and then the main applications in different fluid engineering are demonstrated in brief. This overview will inevitably improve the comprehension of the drag reduction mechanism of sharkskin surface and better understand the recent applications in fluid engineering. Copyright © 2015 Elsevier Ltd. All rights reserved.

Automated cross-modal mapping in robotic eye/hand systems using plastic radial basis function networks

NASA Astrophysics Data System (ADS)

Meng, Qinggang; Lee, M. H.

2007-03-01

Advanced autonomous artificial systems will need incremental learning and adaptive abilities similar to those seen in humans. Knowledge from biology, psychology and neuroscience is now inspiring new approaches for systems that have sensory-motor capabilities and operate in complex environments. Eye/hand coordination is an important cross-modal cognitive function, and is also typical of many of the other coordinations that must be involved in the control and operation of embodied intelligent systems. This paper examines a biologically inspired approach for incrementally constructing compact mapping networks for eye/hand coordination. We present a simplified node-decoupled extended Kalman filter for radial basis function networks, and compare this with other learning algorithms. An experimental system consisting of a robot arm and a pan-and-tilt head with a colour camera is used to produce results and test the algorithms in this paper. We also present three approaches for adapting to structural changes during eye/hand coordination tasks, and the robustness of the algorithms under noise are investigated. The learning and adaptation approaches in this paper have similarities with current ideas about neural growth in the brains of humans and animals during tool-use, and infants during early cognitive development.

Biotemplated synthesis of inorganic materials: An emerging paradigm for nanomaterial synthesis inspired by nature

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

Krajina, Brad A.; Proctor, Amy C.; Schoen, Alia P.

Biomineralization, the process by which biological systems direct the synthesis of inorganic structures from organic templates, is an exquisite example of nanomaterial self-assembly in nature. Its products include the shells of mollusks and the bones and teeth of vertebrates. By comparison, conventional inorganic synthesis techniques provide limited control over inorganic nanomaterial architecture. Inspired by biomineralization in nature, over the last two decades, the field of biotemplating has emerged as a new paradigm for inorganic nanomaterial assembly, wherein researchers seek to design novel nano-structures in which inorganic nanomaterial synthesis is directed from an underlying biomolecular template. Here, we review the motivation,more » mechanistic understanding, progress, and challenges for the field of biotemplating. We highlight the interdisciplinary nature of this field, and survey a broad range of examples of bio-templated engineering: ranging from strategies that exploit the inherent capabilities of proteins in nature, to genetically-engineered systems that unlock new capabilities for self-assembly with biomolecules. Here, we illustrate that the use of biological materials as templates for inorganic self-assembly holds tremendous potential for nanomaterial engineering, with applications that range from electronics and energy to medicine.« less

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.

Bioinspired spring origami

NASA Astrophysics Data System (ADS)

Faber, Jakob A.; Arrieta, Andres F.; Studart, André R.

2018-03-01

Origami enables folding of objects into a variety of shapes in arts, engineering, and biological systems. In contrast to well-known paper-folded objects, the wing of the earwig has an exquisite natural folding system that cannot be sufficiently described by current origami models. Such an unusual biological system displays incompatible folding patterns, remains open by a bistable locking mechanism during flight, and self-folds rapidly without muscular actuation. We show that these notable functionalities arise from the protein-rich joints of the earwig wing, which work as extensional and rotational springs between facets. Inspired by this biological wing, we establish a spring origami model that broadens the folding design space of traditional origami and allows for the fabrication of precisely tunable, four-dimensional–printed objects with programmable bioinspired morphing functionalities.

Review: bioprinting: a beginning.

PubMed

Mironov, Vladimir; Reis, Nuno; Derby, Brian

2006-04-01

An increasing demand for directed assembly of biologically relevant materials, with prescribed three-dimensional hierarchical organizations, is stimulating technology developments with the ultimate goal of re-creating multicellular tissues and organs de novo. Existing techniques, mostly adapted from other applications or fields of research, are capable of independently meeting partial requirements for engineering biological or biomimetic structures, but their integration toward organ engineering is proving difficult. Inspired by recent developments in material transfer processes operating at all relevant length scales--from nano to macro--which are amenable to biological elements, a new research field of bioprinting and biopatterning has emerged. Here we present a short review regarding the framework, state of the art, and perspectives of this new field, based on the findings presented at a recent international workshop.

Biologically inspired adaptive walking of a quadruped robot.

PubMed

Kimura, Hiroshi; Fukuoka, Yasuhiro; Cohen, Avis H

2007-01-15

We describe here the efforts to induce a quadruped robot to walk with medium-walking speed on irregular terrain based on biological concepts. We propose the necessary conditions for stable dynamic walking on irregular terrain in general, and we design the mechanical and the neural systems by comparing biological concepts with those necessary conditions described in physical terms. PD-controller at joints constructs the virtual spring-damper system as the viscoelasticity model of a muscle. The neural system model consists of a central pattern generator (CPG), reflexes and responses. We validate the effectiveness of the proposed neural system model control using the quadruped robots called 'Tekken1&2'. MPEG footage of experiments can be seen at http://www.kimura.is.uec.ac.jp.

Elucidating the ensemble of functionally-relevant transitions in protein systems with a robotics-inspired method.

PubMed

Molloy, Kevin; Shehu, Amarda

2013-01-01

Many proteins tune their biological function by transitioning between different functional states, effectively acting as dynamic molecular machines. Detailed structural characterization of transition trajectories is central to understanding the relationship between protein dynamics and function. Computational approaches that build on the Molecular Dynamics framework are in principle able to model transition trajectories at great detail but also at considerable computational cost. Methods that delay consideration of dynamics and focus instead on elucidating energetically-credible conformational paths connecting two functionally-relevant structures provide a complementary approach. Effective sampling-based path planning methods originating in robotics have been recently proposed to produce conformational paths. These methods largely model short peptides or address large proteins by simplifying conformational space. We propose a robotics-inspired method that connects two given structures of a protein by sampling conformational paths. The method focuses on small- to medium-size proteins, efficiently modeling structural deformations through the use of the molecular fragment replacement technique. In particular, the method grows a tree in conformational space rooted at the start structure, steering the tree to a goal region defined around the goal structure. We investigate various bias schemes over a progress coordinate for balance between coverage of conformational space and progress towards the goal. A geometric projection layer promotes path diversity. A reactive temperature scheme allows sampling of rare paths that cross energy barriers. Experiments are conducted on small- to medium-size proteins of length up to 214 amino acids and with multiple known functionally-relevant states, some of which are more than 13Å apart of each-other. Analysis reveals that the method effectively obtains conformational paths connecting structural states that are significantly different. A detailed analysis on the depth and breadth of the tree suggests that a soft global bias over the progress coordinate enhances sampling and results in higher path diversity. The explicit geometric projection layer that biases the exploration away from over-sampled regions further increases coverage, often improving proximity to the goal by forcing the exploration to find new paths. The reactive temperature scheme is shown effective in increasing path diversity, particularly in difficult structural transitions with known high-energy barriers.