Vehicle routing problem with time windows using natural inspired algorithms

NASA Astrophysics Data System (ADS)

Pratiwi, A. B.; Pratama, A.; Sa’diyah, I.; Suprajitno, H.

2018-03-01

Process of distribution of goods needs a strategy to make the total cost spent for operational activities minimized. But there are several constrains have to be satisfied which are the capacity of the vehicles and the service time of the customers. This Vehicle Routing Problem with Time Windows (VRPTW) gives complex constrains problem. This paper proposes natural inspired algorithms for dealing with constrains of VRPTW which involves Bat Algorithm and Cat Swarm Optimization. Bat Algorithm is being hybrid with Simulated Annealing, the worst solution of Bat Algorithm is replaced by the solution from Simulated Annealing. Algorithm which is based on behavior of cats, Cat Swarm Optimization, is improved using Crow Search Algorithm to make simplier and faster convergence. From the computational result, these algorithms give good performances in finding the minimized total distance. Higher number of population causes better computational performance. The improved Cat Swarm Optimization with Crow Search gives better performance than the hybridization of Bat Algorithm and Simulated Annealing in dealing with big 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.

ACOustic: A Nature-Inspired Exploration Indicator for Ant Colony Optimization.

PubMed

Sagban, Rafid; Ku-Mahamud, Ku Ruhana; Abu Bakar, Muhamad Shahbani

2015-01-01

A statistical machine learning indicator, ACOustic, is proposed to evaluate the exploration behavior in the iterations of ant colony optimization algorithms. This idea is inspired by the behavior of some parasites in their mimicry to the queens' acoustics of their ant hosts. The parasites' reaction results from their ability to indicate the state of penetration. The proposed indicator solves the problem of robustness that results from the difference of magnitudes in the distance's matrix, especially when combinatorial optimization problems with rugged fitness landscape are applied. The performance of the proposed indicator is evaluated against the existing indicators in six variants of ant colony optimization algorithms. Instances for travelling salesman problem and quadratic assignment problem are used in the experimental evaluation. The analytical results showed that the proposed indicator is more informative and more robust.

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

How Can Bee Colony Algorithm Serve Medicine?

PubMed Central

Salehahmadi, Zeinab; Manafi, Amir

2014-01-01

Healthcare professionals usually should make complex decisions with far reaching consequences and associated risks in health care fields. As it was demonstrated in other industries, the ability to drill down into pertinent data to explore knowledge behind the data can greatly facilitate superior, informed decisions to ensue the facts. Nature has always inspired researchers to develop models of solving the problems. Bee colony algorithm (BCA), based on the self-organized behavior of social insects is one of the most popular member of the family of population oriented, nature inspired meta-heuristic swarm intelligence method which has been proved its superiority over some other nature inspired algorithms. The objective of this model was to identify valid novel, potentially useful, and understandable correlations and patterns in existing data. This review employs a thematic analysis of online series of academic papers to outline BCA in medical hive, reducing the response and computational time and optimizing the problems. To illustrate the benefits of this model, the cases of disease diagnose system are presented. PMID:25489530

How can bee colony algorithm serve medicine?

PubMed

Salehahmadi, Zeinab; Manafi, Amir

2014-07-01

Healthcare professionals usually should make complex decisions with far reaching consequences and associated risks in health care fields. As it was demonstrated in other industries, the ability to drill down into pertinent data to explore knowledge behind the data can greatly facilitate superior, informed decisions to ensue the facts. Nature has always inspired researchers to develop models of solving the problems. Bee colony algorithm (BCA), based on the self-organized behavior of social insects is one of the most popular member of the family of population oriented, nature inspired meta-heuristic swarm intelligence method which has been proved its superiority over some other nature inspired algorithms. The objective of this model was to identify valid novel, potentially useful, and understandable correlations and patterns in existing data. This review employs a thematic analysis of online series of academic papers to outline BCA in medical hive, reducing the response and computational time and optimizing the problems. To illustrate the benefits of this model, the cases of disease diagnose system are presented.

Firefly Algorithm, Lévy Flights and Global Optimization

NASA Astrophysics Data System (ADS)

Yang, Xin-She

Nature-inspired algorithms such as Particle Swarm Optimization and Firefly Algorithm are among the most powerful algorithms for optimization. In this paper, we intend to formulate a new metaheuristic algorithm by combining Lévy flights with the search strategy via the Firefly Algorithm. Numerical studies and results suggest that the proposed Lévy-flight firefly algorithm is superior to existing metaheuristic algorithms. Finally implications for further research and wider applications will be discussed.

Large Scale Multi-area Static/Dynamic Economic Dispatch using Nature Inspired Optimization

NASA Astrophysics Data System (ADS)

Pandit, Manjaree; Jain, Kalpana; Dubey, Hari Mohan; Singh, Rameshwar

2017-04-01

Economic dispatch (ED) ensures that the generation allocation to the power units is carried out such that the total fuel cost is minimized and all the operating equality/inequality constraints are satisfied. Classical ED does not take transmission constraints into consideration, but in the present restructured power systems the tie-line limits play a very important role in deciding operational policies. ED is a dynamic problem which is performed on-line in the central load dispatch centre with changing load scenarios. The dynamic multi-area ED (MAED) problem is more complex due to the additional tie-line, ramp-rate and area-wise power balance constraints. Nature inspired (NI) heuristic optimization methods are gaining popularity over the traditional methods for complex problems. This work presents the modified particle swarm optimization (PSO) based techniques where parameter automation is effectively used for improving the search efficiency by avoiding stagnation to a sub-optimal result. This work validates the performance of the PSO variants with traditional solver GAMS for single as well as multi-area economic dispatch (MAED) on three test cases of a large 140-unit standard test system having complex constraints.

Robust design of multiple trailing edge flaps for helicopter vibration reduction: A multi-objective bat algorithm approach

NASA Astrophysics Data System (ADS)

Mallick, Rajnish; Ganguli, Ranjan; Seetharama Bhat, M.

2015-09-01

The objective of this study is to determine an optimal trailing edge flap configuration and flap location to achieve minimum hub vibration levels and flap actuation power simultaneously. An aeroelastic analysis of a soft in-plane four-bladed rotor is performed in conjunction with optimal control. A second-order polynomial response surface based on an orthogonal array (OA) with 3-level design describes both the objectives adequately. Two new orthogonal arrays called MGB2P-OA and MGB4P-OA are proposed to generate nonlinear response surfaces with all interaction terms for two and four parameters, respectively. A multi-objective bat algorithm (MOBA) approach is used to obtain the optimal design point for the mutually conflicting objectives. MOBA is a recently developed nature-inspired metaheuristic optimization algorithm that is based on the echolocation behaviour of bats. It is found that MOBA inspired Pareto optimal trailing edge flap design reduces vibration levels by 73% and flap actuation power by 27% in comparison with the baseline design.

a New Hybrid Yin-Yang Swarm Optimization Algorithm for Uncapacitated Warehouse Location Problems

NASA Astrophysics Data System (ADS)

Heidari, A. A.; Kazemizade, O.; Hakimpour, F.

2017-09-01

Yin-Yang-pair optimization (YYPO) is one of the latest metaheuristic algorithms (MA) proposed in 2015 that tries to inspire the philosophy of balance between conflicting concepts. Particle swarm optimizer (PSO) is one of the first population-based MA inspired by social behaviors of birds. In spite of PSO, the YYPO is not a nature inspired optimizer. It has a low complexity and starts with only two initial positions and can produce more points with regard to the dimension of target problem. Due to unique advantages of these methodologies and to mitigate the immature convergence and local optima (LO) stagnation problems in PSO, in this work, a continuous hybrid strategy based on the behaviors of PSO and YYPO is proposed to attain the suboptimal solutions of uncapacitated warehouse location (UWL) problems. This efficient hierarchical PSO-based optimizer (PSOYPO) can improve the effectiveness of PSO on spatial optimization tasks such as the family of UWL problems. The performance of the proposed PSOYPO is verified according to some UWL benchmark cases. These test cases have been used in several works to evaluate the efficacy of different MA. Then, the PSOYPO is compared to the standard PSO, genetic algorithm (GA), harmony search (HS), modified HS (OBCHS), and evolutionary simulated annealing (ESA). The experimental results demonstrate that the PSOYPO can reveal a better or competitive efficacy compared to the PSO and other MA.

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.

Multi Dimensional Honey Bee Foraging Algorithm Based on Optimal Energy Consumption

NASA Astrophysics Data System (ADS)

Saritha, R.; Vinod Chandra, S. S.

2017-10-01

In this paper a new nature inspired algorithm is proposed based on natural foraging behavior of multi-dimensional honey bee colonies. This method handles issues that arise when food is shared from multiple sources by multiple swarms at multiple destinations. The self organizing nature of natural honey bee swarms in multiple colonies is based on the principle of energy consumption. Swarms of multiple colonies select a food source to optimally fulfill the requirements of its colonies. This is based on the energy requirement for transporting food between a source and destination. Minimum use of energy leads to maximizing profit in each colony. The mathematical model proposed here is based on this principle. This has been successfully evaluated by applying it on multi-objective transportation problem for optimizing cost and time. The algorithm optimizes the needs at each destination in linear time.

Optimal Golomb Ruler Sequences Generation for Optical WDM Systems: A Novel Parallel Hybrid Multi-objective Bat Algorithm

NASA Astrophysics Data System (ADS)

Bansal, Shonak; Singh, Arun Kumar; Gupta, Neena

2017-02-01

In real-life, multi-objective engineering design problems are very tough and time consuming optimization problems due to their high degree of nonlinearities, complexities and inhomogeneity. Nature-inspired based multi-objective optimization algorithms are now becoming popular for solving multi-objective engineering design problems. This paper proposes original multi-objective Bat algorithm (MOBA) and its extended form, namely, novel parallel hybrid multi-objective Bat algorithm (PHMOBA) to generate shortest length Golomb ruler called optimal Golomb ruler (OGR) sequences at a reasonable computation time. The OGRs found their application in optical wavelength division multiplexing (WDM) systems as channel-allocation algorithm to reduce the four-wave mixing (FWM) crosstalk. The performances of both the proposed algorithms to generate OGRs as optical WDM channel-allocation is compared with other existing classical computing and nature-inspired algorithms, including extended quadratic congruence (EQC), search algorithm (SA), genetic algorithms (GAs), biogeography based optimization (BBO) and big bang-big crunch (BB-BC) optimization algorithms. Simulations conclude that the proposed parallel hybrid multi-objective Bat algorithm works efficiently as compared to original multi-objective Bat algorithm and other existing algorithms to generate OGRs for optical WDM systems. The algorithm PHMOBA to generate OGRs, has higher convergence and success rate than original MOBA. The efficiency improvement of proposed PHMOBA to generate OGRs up to 20-marks, in terms of ruler length and total optical channel bandwidth (TBW) is 100 %, whereas for original MOBA is 85 %. Finally the implications for further research are also discussed.

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

Application of firefly algorithm to the dynamic model updating problem

NASA Astrophysics Data System (ADS)

Shabbir, Faisal; Omenzetter, Piotr

2015-04-01

Model updating can be considered as a branch of optimization problems in which calibration of the finite element (FE) model is undertaken by comparing the modal properties of the actual structure with these of the FE predictions. The attainment of a global solution in a multi dimensional search space is a challenging problem. The nature-inspired algorithms have gained increasing attention in the previous decade for solving such complex optimization problems. This study applies the novel Firefly Algorithm (FA), a global optimization search technique, to a dynamic model updating problem. This is to the authors' best knowledge the first time FA is applied to model updating. The working of FA is inspired by the flashing characteristics of fireflies. Each firefly represents a randomly generated solution which is assigned brightness according to the value of the objective function. The physical structure under consideration is a full scale cable stayed pedestrian bridge with composite bridge deck. Data from dynamic testing of the bridge was used to correlate and update the initial model by using FA. The algorithm aimed at minimizing the difference between the natural frequencies and mode shapes of the structure. The performance of the algorithm is analyzed in finding the optimal solution in a multi dimensional search space. The paper concludes with an investigation of the efficacy of the algorithm in obtaining a reference finite element model which correctly represents the as-built original structure.

Computational Intelligence-Assisted Understanding of Nature-Inspired Superhydrophobic Behavior.

PubMed

Zhang, Xia; Ding, Bei; Cheng, Ran; Dixon, Sebastian C; Lu, Yao

2018-01-01

In recent years, state-of-the-art computational modeling of physical and chemical systems has shown itself to be an invaluable resource in the prediction of the properties and behavior of functional materials. However, construction of a useful computational model for novel systems in both academic and industrial contexts often requires a great depth of physicochemical theory and/or a wealth of empirical data, and a shortage in the availability of either frustrates the modeling process. In this work, computational intelligence is instead used, including artificial neural networks and evolutionary computation, to enhance our understanding of nature-inspired superhydrophobic behavior. The relationships between experimental parameters (water droplet volume, weight percentage of nanoparticles used in the synthesis of the polymer composite, and distance separating the superhydrophobic surface and the pendant water droplet in adhesive force measurements) and multiple objectives (water droplet contact angle, sliding angle, and adhesive force) are built and weighted. The obtained optimal parameters are consistent with the experimental observations. This new approach to materials modeling has great potential to be applied more generally to aid design, fabrication, and optimization for myriad functional materials.

Biologically-Inspired Anisotropic Flexible Wing for Optimal Flapping Flight

DTIC Science & Technology

2013-07-01

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

A hybrid artificial bee colony algorithm for numerical function optimization

NASA Astrophysics Data System (ADS)

Alqattan, Zakaria N.; Abdullah, Rosni

2015-02-01

Artificial Bee Colony (ABC) algorithm is one of the swarm intelligence algorithms; it has been introduced by Karaboga in 2005. It is a meta-heuristic optimization search algorithm inspired from the intelligent foraging behavior of the honey bees in nature. Its unique search process made it as one of the most competitive algorithm with some other search algorithms in the area of optimization, such as Genetic algorithm (GA) and Particle Swarm Optimization (PSO). However, the ABC performance of the local search process and the bee movement or the solution improvement equation still has some weaknesses. The ABC is good in avoiding trapping at the local optimum but it spends its time searching around unpromising random selected solutions. Inspired by the PSO, we propose a Hybrid Particle-movement ABC algorithm called HPABC, which adapts the particle movement process to improve the exploration of the original ABC algorithm. Numerical benchmark functions were used in order to experimentally test the HPABC algorithm. The results illustrate that the HPABC algorithm can outperform the ABC algorithm in most of the experiments (75% better in accuracy and over 3 times faster).

Cyclical parthenogenesis algorithm for layout optimization of truss structures with frequency constraints

NASA Astrophysics Data System (ADS)

Kaveh, A.; Zolghadr, A.

2017-08-01

Structural optimization with frequency constraints is seen as a challenging problem because it is associated with highly nonlinear, discontinuous and non-convex search spaces consisting of several local optima. Therefore, competent optimization algorithms are essential for addressing these problems. In this article, a newly developed metaheuristic method called the cyclical parthenogenesis algorithm (CPA) is used for layout optimization of truss structures subjected to frequency constraints. CPA is a nature-inspired, population-based metaheuristic algorithm, which imitates the reproductive and social behaviour of some animal species such as aphids, which alternate between sexual and asexual reproduction. The efficiency of the CPA is validated using four numerical examples.

Nature-Inspired Design of Artificial Solar-to-Fuel Conversion Systems based on Copper Phosphate Microflowers.

PubMed

Wang, Jing; Zhu, Ting; Ho, Ghim Wei

2016-07-07

Phosphates play significant roles in plant photosynthesis by mediating electron transportation and furnishing energy for CO2 reduction. Motivated by this, we demonstrate herein an artificial solar-to-fuel conversion system, involving versatile copper phosphate microflowers as template and titanium dioxide nanoparticles as host photocatalyst. The elaborate flowerlike architectures, coupled with a unique proton-reduction cycle from interchangeability of different species of orthophosphate ions, not only offer a 2D nanosheet platform for an optimal heterostructure interface but also effectively augment charge-carrier transfer, thereby contributing to enhanced photoactivity and hydrogen generation. These nature-inspired, phosphate-derived nanocomposites advance the synthesis of a large variety of functional materials, which holds great potential for photochemical, photoelectric and catalytic applications. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Humidification on Ventilated Patients: Heated Humidifications or Heat and Moisture Exchangers?

PubMed Central

Cerpa, F; Cáceres, D; Romero-Dapueto, C; Giugliano-Jaramillo, C; Pérez, R; Budini, H; Hidalgo, V; Gutiérrez, T; Molina, J; Keymer, J

2015-01-01

The normal physiology of conditioning of inspired gases is altered when the patient requires an artificial airway access and an invasive mechanical ventilation (IMV). The endotracheal tube (ETT) removes the natural mechanisms of filtration, humidification and warming of inspired air. Despite the noninvasive ventilation (NIMV) in the upper airways, humidification of inspired gas may not be optimal mainly due to the high flow that is being created by the leakage compensation, among other aspects. Any moisture and heating deficit is compensated by the large airways of the tracheobronchial tree, these are poorly suited for this task, which alters mucociliary function, quality of secretions, and homeostasis gas exchange system. To avoid the occurrence of these events, external devices that provide humidification, heating and filtration have been developed, with different degrees of evidence that support their use. PMID:26312102

Humidification on Ventilated Patients: Heated Humidifications or Heat and Moisture Exchangers?

PubMed

Cerpa, F; Cáceres, D; Romero-Dapueto, C; Giugliano-Jaramillo, C; Pérez, R; Budini, H; Hidalgo, V; Gutiérrez, T; Molina, J; Keymer, J

2015-01-01

The normal physiology of conditioning of inspired gases is altered when the patient requires an artificial airway access and an invasive mechanical ventilation (IMV). The endotracheal tube (ETT) removes the natural mechanisms of filtration, humidification and warming of inspired air. Despite the noninvasive ventilation (NIMV) in the upper airways, humidification of inspired gas may not be optimal mainly due to the high flow that is being created by the leakage compensation, among other aspects. Any moisture and heating deficit is compensated by the large airways of the tracheobronchial tree, these are poorly suited for this task, which alters mucociliary function, quality of secretions, and homeostasis gas exchange system. To avoid the occurrence of these events, external devices that provide humidification, heating and filtration have been developed, with different degrees of evidence that support their use.

Three-Dimensional Path Planning for Uninhabited Combat Aerial Vehicle Based on Predator-Prey Pigeon-Inspired Optimization in Dynamic Environment.

PubMed

Zhang, Bo; Duan, Haibin

2017-01-01

Three-dimension path planning of uninhabited combat aerial vehicle (UCAV) is a complicated optimal problem, which mainly focused on optimizing the flight route considering the different types of constrains under complex combating environment. A novel predator-prey pigeon-inspired optimization (PPPIO) is proposed to solve the UCAV three-dimension path planning problem in dynamic environment. Pigeon-inspired optimization (PIO) is a new bio-inspired optimization algorithm. In this algorithm, map and compass operator model and landmark operator model are used to search the best result of a function. The prey-predator concept is adopted to improve global best properties and enhance the convergence speed. The characteristics of the optimal path are presented in the form of a cost function. The comparative simulation results show that our proposed PPPIO algorithm is more efficient than the basic PIO, particle swarm optimization (PSO), and different evolution (DE) in solving UCAV three-dimensional path planning problems.

Methodology for Designing and Developing a New Ultra-Wideband Antenna Based on Bio-Inspired Optimization Techniques

DTIC Science & Technology

2017-11-01

ARL-TR-8225 ● NOV 2017 US Army Research Laboratory Methodology for Designing and Developing a New Ultra-Wideband Antenna Based...Research Laboratory Methodology for Designing and Developing a New Ultra-Wideband Antenna Based on Bio-Inspired Optimization Techniques by...SUBTITLE Methodology for Designing and Developing a New Ultra-Wideband Antenna Based on Bio-Inspired Optimization Techniques 5a. CONTRACT NUMBER

Optimal Siting and Sizing of Multiple DG Units for the Enhancement of Voltage Profile and Loss Minimization in Transmission Systems Using Nature Inspired Algorithms

PubMed Central

Ramamoorthy, Ambika; Ramachandran, Rajeswari

2016-01-01

Power grid becomes smarter nowadays along with technological development. The benefits of smart grid can be enhanced through the integration of renewable energy sources. In this paper, several studies have been made to reconfigure a conventional network into a smart grid. Amongst all the renewable sources, solar power takes the prominent position due to its availability in abundance. Proposed methodology presented in this paper is aimed at minimizing network power losses and at improving the voltage stability within the frame work of system operation and security constraints in a transmission system. Locations and capacities of DGs have a significant impact on the system losses in a transmission system. In this paper, combined nature inspired algorithms are presented for optimal location and sizing of DGs. This paper proposes a two-step optimization technique in order to integrate DG. In a first step, the best size of DG is determined through PSO metaheuristics and the results obtained through PSO is tested for reverse power flow by negative load approach to find possible bus locations. Then, optimal location is found by Loss Sensitivity Factor (LSF) and weak (WK) bus methods and the results are compared. In a second step, optimal sizing of DGs is determined by PSO, GSA, and hybrid PSOGSA algorithms. Apart from optimal sizing and siting of DGs, different scenarios with number of DGs (3, 4, and 5) and PQ capacities of DGs (P alone, Q alone, and  P and Q both) are also analyzed and the results are analyzed in this paper. A detailed performance analysis is carried out on IEEE 30-bus system to demonstrate the effectiveness of the proposed methodology. PMID:27057557

Optimal Siting and Sizing of Multiple DG Units for the Enhancement of Voltage Profile and Loss Minimization in Transmission Systems Using Nature Inspired Algorithms.

PubMed

Ramamoorthy, Ambika; Ramachandran, Rajeswari

2016-01-01

Power grid becomes smarter nowadays along with technological development. The benefits of smart grid can be enhanced through the integration of renewable energy sources. In this paper, several studies have been made to reconfigure a conventional network into a smart grid. Amongst all the renewable sources, solar power takes the prominent position due to its availability in abundance. Proposed methodology presented in this paper is aimed at minimizing network power losses and at improving the voltage stability within the frame work of system operation and security constraints in a transmission system. Locations and capacities of DGs have a significant impact on the system losses in a transmission system. In this paper, combined nature inspired algorithms are presented for optimal location and sizing of DGs. This paper proposes a two-step optimization technique in order to integrate DG. In a first step, the best size of DG is determined through PSO metaheuristics and the results obtained through PSO is tested for reverse power flow by negative load approach to find possible bus locations. Then, optimal location is found by Loss Sensitivity Factor (LSF) and weak (WK) bus methods and the results are compared. In a second step, optimal sizing of DGs is determined by PSO, GSA, and hybrid PSOGSA algorithms. Apart from optimal sizing and siting of DGs, different scenarios with number of DGs (3, 4, and 5) and PQ capacities of DGs (P alone, Q alone, and P and Q both) are also analyzed and the results are analyzed in this paper. A detailed performance analysis is carried out on IEEE 30-bus system to demonstrate the effectiveness of the proposed methodology.

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.

Spontaneous water filtration of bio-inspired membrane

NASA Astrophysics Data System (ADS)

Kim, Kiwoong; Kim, Hyejeong; Lee, Sang Joon

2016-11-01

Water is one of the most important elements for plants, because it is essential for various metabolic activities. Thus, water management systems of vascular plants, such as water collection and water filtration have been optimized through a long history. In this view point, bio-inspired technologies can be developed by mimicking the nature's strategies for the survival of the fittest. However, most of the underlying biophysical features of the optimized water management systems remain unsolved In this study, the biophysical characteristics of water filtration phenomena in the roots of mangrove are experimentally investigated. To understand water-filtration features of the mangrove, the morphological structures of its roots are analyzed. The electrokinetic properties of the root surface are also examined. Based on the quantitatively analyzed information, filtration of sodium ions in the roots are visualized. Motivated by this mechanism, spontaneous desalination mechanism in the root of mangrove is proposed by combining the electrokinetics and hydrodynamic transportation of ions. This study would be helpful for understanding the water-filtration mechanism of the roots of mangrove and developing a new bio-inspired desalination technology. This research was financially supported by the National Research Foundation (NRF) of Korea (Contract Grant Number: 2008-0061991).

Morphogenesis and mechanostabilization of complex natural and 3D printed shapes

PubMed Central

Tiwary, Chandra Sekhar; Kishore, Sharan; Sarkar, Suman; Mahapatra, Debiprosad Roy; Ajayan, Pulickel M.; Chattopadhyay, Kamanio

2015-01-01

The natural selection and the evolutionary optimization of complex shapes in nature are closely related to their functions. Mechanostabilization of shape of biological structure via morphogenesis has several beautiful examples. With the help of simple mechanics-based modeling and experiments, we show an important causality between natural shape selection as evolutionary outcome and the mechanostabilization of seashells. The effect of biological growth on the mechanostabilization process is identified with examples of two natural shapes of seashells, one having a diametrically converging localization of stresses and the other having a helicoidally concentric localization of stresses. We demonstrate how the evolved shape enables predictable protection of soft body parts of the species. The effect of bioavailability of natural material is found to be a secondary factor compared to shape selectivity, where material microstructure only acts as a constraint to evolutionary optimization. This is confirmed by comparing the mechanostabilization behavior of three-dimensionally printed synthetic polymer structural shapes with that of natural seashells consisting of ceramic and protein. This study also highlights interesting possibilities in achieving a new design of structures made of ordinary materials which have bio-inspired optimization objectives. PMID:26601170

Investigation of earthquake factor for optimum tuned mass dampers

NASA Astrophysics Data System (ADS)

Nigdeli, Sinan Melih; Bekdaş, Gebrail

2012-09-01

In this study the optimum parameters of tuned mass dampers (TMD) are investigated under earthquake excitations. An optimization strategy was carried out by using the Harmony Search (HS) algorithm. HS is a metaheuristic method which is inspired from the nature of musical performances. In addition to the HS algorithm, the results of the optimization objective are compared with the results of the other documented method and the corresponding results are eliminated. In that case, the best optimum results are obtained. During the optimization, the optimum TMD parameters were searched for single degree of freedom (SDOF) structure models with different periods. The optimization was done for different earthquakes separately and the results were compared.

FOCuS: a metaheuristic algorithm for computing knockouts from genome-scale models for strain optimization.

PubMed

Mutturi, Sarma

2017-06-27

Although handful tools are available for constraint-based flux analysis to generate knockout strains, most of these are either based on bilevel-MIP or its modifications. However, metaheuristic approaches that are known for their flexibility and scalability have been less studied. Moreover, in the existing tools, sectioning of search space to find optimal knocks has not been considered. Herein, a novel computational procedure, termed as FOCuS (Flower-pOllination coupled Clonal Selection algorithm), was developed to find the optimal reaction knockouts from a metabolic network to maximize the production of specific metabolites. FOCuS derives its benefits from nature-inspired flower pollination algorithm and artificial immune system-inspired clonal selection algorithm to converge to an optimal solution. To evaluate the performance of FOCuS, reported results obtained from both MIP and other metaheuristic-based tools were compared in selected case studies. The results demonstrated the robustness of FOCuS irrespective of the size of metabolic network and number of knockouts. Moreover, sectioning of search space coupled with pooling of priority reactions based on their contribution to objective function for generating smaller search space significantly reduced the computational time.

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.

Bio-inspired Murray materials for mass transfer and activity

NASA Astrophysics Data System (ADS)

Zheng, Xianfeng; Shen, Guofang; Wang, Chao; Li, Yu; Dunphy, Darren; Hasan, Tawfique; Brinker, C. Jeffrey; Su, Bao-Lian

2017-04-01

Both plants and animals possess analogous tissues containing hierarchical networks of pores, with pore size ratios that have evolved to maximize mass transport and rates of reactions. The underlying physical principles of this optimized hierarchical design are embodied in Murray's law. However, we are yet to realize the benefit of mimicking nature's Murray networks in synthetic materials due to the challenges in fabricating vascularized structures. Here we emulate optimum natural systems following Murray's law using a bottom-up approach. Such bio-inspired materials, whose pore sizes decrease across multiple scales and finally terminate in size-invariant units like plant stems, leaf veins and vascular and respiratory systems provide hierarchical branching and precise diameter ratios for connecting multi-scale pores from macro to micro levels. Our Murray material mimics enable highly enhanced mass exchange and transfer in liquid-solid, gas-solid and electrochemical reactions and exhibit enhanced performance in photocatalysis, gas sensing and as Li-ion battery electrodes.

An efficient swarm intelligence approach to feature selection based on invasive weed optimization: Application to multivariate calibration and classification using spectroscopic data

NASA Astrophysics Data System (ADS)

Sheykhizadeh, Saheleh; Naseri, Abdolhossein

2018-04-01

Variable selection plays a key role in classification and multivariate calibration. Variable selection methods are aimed at choosing a set of variables, from a large pool of available predictors, relevant to the analyte concentrations estimation, or to achieve better classification results. Many variable selection techniques have now been introduced among which, those which are based on the methodologies of swarm intelligence optimization have been more respected during a few last decades since they are mainly inspired by nature. In this work, a simple and new variable selection algorithm is proposed according to the invasive weed optimization (IWO) concept. IWO is considered a bio-inspired metaheuristic mimicking the weeds ecological behavior in colonizing as well as finding an appropriate place for growth and reproduction; it has been shown to be very adaptive and powerful to environmental changes. In this paper, the first application of IWO, as a very simple and powerful method, to variable selection is reported using different experimental datasets including FTIR and NIR data, so as to undertake classification and multivariate calibration tasks. Accordingly, invasive weed optimization - linear discrimination analysis (IWO-LDA) and invasive weed optimization- partial least squares (IWO-PLS) are introduced for multivariate classification and calibration, respectively.

An efficient swarm intelligence approach to feature selection based on invasive weed optimization: Application to multivariate calibration and classification using spectroscopic data.

PubMed

Sheykhizadeh, Saheleh; Naseri, Abdolhossein

2018-04-05

Variable selection plays a key role in classification and multivariate calibration. Variable selection methods are aimed at choosing a set of variables, from a large pool of available predictors, relevant to the analyte concentrations estimation, or to achieve better classification results. Many variable selection techniques have now been introduced among which, those which are based on the methodologies of swarm intelligence optimization have been more respected during a few last decades since they are mainly inspired by nature. In this work, a simple and new variable selection algorithm is proposed according to the invasive weed optimization (IWO) concept. IWO is considered a bio-inspired metaheuristic mimicking the weeds ecological behavior in colonizing as well as finding an appropriate place for growth and reproduction; it has been shown to be very adaptive and powerful to environmental changes. In this paper, the first application of IWO, as a very simple and powerful method, to variable selection is reported using different experimental datasets including FTIR and NIR data, so as to undertake classification and multivariate calibration tasks. Accordingly, invasive weed optimization - linear discrimination analysis (IWO-LDA) and invasive weed optimization- partial least squares (IWO-PLS) are introduced for multivariate classification and calibration, respectively. Copyright © 2018 Elsevier B.V. All rights reserved.

Chaotic Teaching-Learning-Based Optimization with Lévy Flight for Global Numerical Optimization.

PubMed

He, Xiangzhu; Huang, Jida; Rao, Yunqing; Gao, Liang

2016-01-01

Recently, teaching-learning-based optimization (TLBO), as one of the emerging nature-inspired heuristic algorithms, has attracted increasing attention. In order to enhance its convergence rate and prevent it from getting stuck in local optima, a novel metaheuristic has been developed in this paper, where particular characteristics of the chaos mechanism and Lévy flight are introduced to the basic framework of TLBO. The new algorithm is tested on several large-scale nonlinear benchmark functions with different characteristics and compared with other methods. Experimental results show that the proposed algorithm outperforms other algorithms and achieves a satisfactory improvement over TLBO.

Performance comparison of some evolutionary algorithms on job shop scheduling problems

NASA Astrophysics Data System (ADS)

Mishra, S. K.; Rao, C. S. P.

2016-09-01

Job Shop Scheduling as a state space search problem belonging to NP-hard category due to its complexity and combinational explosion of states. Several naturally inspire evolutionary methods have been developed to solve Job Shop Scheduling Problems. In this paper the evolutionary methods namely Particles Swarm Optimization, Artificial Intelligence, Invasive Weed Optimization, Bacterial Foraging Optimization, Music Based Harmony Search Algorithms are applied and find tuned to model and solve Job Shop Scheduling Problems. To compare about 250 Bench Mark instances have been used to evaluate the performance of these algorithms. The capabilities of each these algorithms in solving Job Shop Scheduling Problems are outlined.

Artificial evolution by viability rather than competition.

PubMed

Maesani, Andrea; Fernando, Pradeep Ruben; Floreano, Dario

2014-01-01

Evolutionary algorithms are widespread heuristic methods inspired by natural evolution to solve difficult problems for which analytical approaches are not suitable. In many domains experimenters are not only interested in discovering optimal solutions, but also in finding the largest number of different solutions satisfying minimal requirements. However, the formulation of an effective performance measure describing these requirements, also known as fitness function, represents a major challenge. The difficulty of combining and weighting multiple problem objectives and constraints of possibly varying nature and scale into a single fitness function often leads to unsatisfactory solutions. Furthermore, selective reproduction of the fittest solutions, which is inspired by competition-based selection in nature, leads to loss of diversity within the evolving population and premature convergence of the algorithm, hindering the discovery of many different solutions. Here we present an alternative abstraction of artificial evolution, which does not require the formulation of a composite fitness function. Inspired from viability theory in dynamical systems, natural evolution and ethology, the proposed method puts emphasis on the elimination of individuals that do not meet a set of changing criteria, which are defined on the problem objectives and constraints. Experimental results show that the proposed method maintains higher diversity in the evolving population and generates more unique solutions when compared to classical competition-based evolutionary algorithms. Our findings suggest that incorporating viability principles into evolutionary algorithms can significantly improve the applicability and effectiveness of evolutionary methods to numerous complex problems of science and engineering, ranging from protein structure prediction to aircraft wing design.

Modern meta-heuristics based on nonlinear physics processes: A review of models and design procedures

NASA Astrophysics Data System (ADS)

Salcedo-Sanz, S.

2016-10-01

Meta-heuristic algorithms are problem-solving methods which try to find good-enough solutions to very hard optimization problems, at a reasonable computation time, where classical approaches fail, or cannot even been applied. Many existing meta-heuristics approaches are nature-inspired techniques, which work by simulating or modeling different natural processes in a computer. Historically, many of the most successful meta-heuristic approaches have had a biological inspiration, such as evolutionary computation or swarm intelligence paradigms, but in the last few years new approaches based on nonlinear physics processes modeling have been proposed and applied with success. Non-linear physics processes, modeled as optimization algorithms, are able to produce completely new search procedures, with extremely effective exploration capabilities in many cases, which are able to outperform existing optimization approaches. In this paper we review the most important optimization algorithms based on nonlinear physics, how they have been constructed from specific modeling of a real phenomena, and also their novelty in terms of comparison with alternative existing algorithms for optimization. We first review important concepts on optimization problems, search spaces and problems' difficulty. Then, the usefulness of heuristics and meta-heuristics approaches to face hard optimization problems is introduced, and some of the main existing classical versions of these algorithms are reviewed. The mathematical framework of different nonlinear physics processes is then introduced as a preparatory step to review in detail the most important meta-heuristics based on them. A discussion on the novelty of these approaches, their main computational implementation and design issues, and the evaluation of a novel meta-heuristic based on Strange Attractors mutation will be carried out to complete the review of these techniques. We also describe some of the most important application areas, in broad sense, of meta-heuristics, and describe free-accessible software frameworks which can be used to make easier the implementation of these algorithms.

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.

The Homogeneity of Optimal Sensor Placement Across Multiple Winged Insect Species

NASA Astrophysics Data System (ADS)

Jenkins, Abigail L.

Taking inspiration from biology, control algorithms can be implemented to imitate the naturally occurring control systems present in nature. This research is primarily concerned with insect flight and optimal wing sensor placement. Many winged insects with halteres are equipped with mechanoreceptors termed campaniform sensilla. Although the exact information these receptors provide to the insect's nervous system is unknown, it is thought to have the capability of measuring inertial rotation forces. During flight, when the wing bends, the information measured by the campaniform sensilla is received by the central nervous system, and provides the insect necessary data to control flight. This research compares three insect species - the hawkmoth Manduca sexta, the honeybee Apis mellifera, and the fruit fly Drosophila melanogaster. Using an observability-based sensor placement algorithm, the optimal sensor placement for these three species is determined. Simulations resolve if this optimal sensor placement corresponds to the insect's campaniform sensilla, as well as if placement is homogeneous across species.

Biologically Inspired Technology Using Electroactive Polymers (EAP)

NASA Technical Reports Server (NTRS)

Bar-Cohen, Yoseph

2006-01-01

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

Synthesis of concentric circular antenna arrays using dragonfly algorithm

NASA Astrophysics Data System (ADS)

Babayigit, B.

2018-05-01

Due to the strong non-linear relationship between the array factor and the array elements, concentric circular antenna array (CCAA) synthesis problem is challenging. Nature-inspired optimisation techniques have been playing an important role in solving array synthesis problems. Dragonfly algorithm (DA) is a novel nature-inspired optimisation technique which is based on the static and dynamic swarming behaviours of dragonflies in nature. This paper presents the design of CCAAs to get low sidelobes using DA. The effectiveness of the proposed DA is investigated in two different (with and without centre element) cases of two three-ring (having 4-, 6-, 8-element or 8-, 10-, 12-element) CCAA design. The radiation pattern of each design cases is obtained by finding optimal excitation weights of the array elements using DA. Simulation results show that the proposed algorithm outperforms the other state-of-the-art techniques (symbiotic organisms search, biogeography-based optimisation, sequential quadratic programming, opposition-based gravitational search algorithm, cat swarm optimisation, firefly algorithm, evolutionary programming) for all design cases. DA can be a promising technique for electromagnetic problems.

Two hybrid compaction algorithms for the layout optimization problem.

PubMed

Xiao, Ren-Bin; Xu, Yi-Chun; Amos, Martyn

2007-01-01

In this paper we present two new algorithms for the layout optimization problem: this concerns the placement of circular, weighted objects inside a circular container, the two objectives being to minimize imbalance of mass and to minimize the radius of the container. This problem carries real practical significance in industrial applications (such as the design of satellites), as well as being of significant theoretical interest. We present two nature-inspired algorithms for this problem, the first based on simulated annealing, and the second on particle swarm optimization. We compare our algorithms with the existing best-known algorithm, and show that our approaches out-perform it in terms of both solution quality and execution time.

Three-input majority function as the unique optimal function for the bias amplification using nonlocal boxes

NASA Astrophysics Data System (ADS)

Mori, Ryuhei

2016-11-01

Brassard et al. [Phys. Rev. Lett. 96, 250401 (2006), 10.1103/PhysRevLett.96.250401] showed that shared nonlocal boxes with a CHSH (Clauser, Horne, Shimony, and Holt) probability greater than 3/+√{6 } 6 yield trivial communication complexity. There still exists a gap with the maximum CHSH probability 2/+√{2 } 4 achievable by quantum mechanics. It is an interesting open question to determine the exact threshold for the trivial communication complexity. Brassard et al.'s idea is based on recursive bias amplification by the three-input majority function. It was not obvious if another choice of function exhibits stronger bias amplification. We show that the three-input majority function is the unique optimal function, so that one cannot improve the threshold 3/+√{6 } 6 by Brassard et al.'s bias amplification. In this work, protocols for computing the function used for the bias amplification are restricted to be nonadaptive protocols or a particular adaptive protocol inspired by Pawłowski et al.'s protocol for information causality [Nature (London) 461, 1101 (2009), 10.1038/nature08400]. We first show an adaptive protocol inspired by Pawłowski et al.'s protocol, and then show that the adaptive protocol improves upon nonadaptive protocols. Finally, we show that the three-input majority function is the unique optimal function for the bias amplification if we apply the adaptive protocol to each step of the bias amplification.

Molecular descriptor subset selection in theoretical peptide quantitative structure-retention relationship model development using nature-inspired optimization algorithms.

PubMed

Žuvela, Petar; Liu, J Jay; Macur, Katarzyna; Bączek, Tomasz

2015-10-06

In this work, performance of five nature-inspired optimization algorithms, genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), firefly algorithm (FA), and flower pollination algorithm (FPA), was compared in molecular descriptor selection for development of quantitative structure-retention relationship (QSRR) models for 83 peptides that originate from eight model proteins. The matrix with 423 descriptors was used as input, and QSRR models based on selected descriptors were built using partial least squares (PLS), whereas root mean square error of prediction (RMSEP) was used as a fitness function for their selection. Three performance criteria, prediction accuracy, computational cost, and the number of selected descriptors, were used to evaluate the developed QSRR models. The results show that all five variable selection methods outperform interval PLS (iPLS), sparse PLS (sPLS), and the full PLS model, whereas GA is superior because of its lowest computational cost and higher accuracy (RMSEP of 5.534%) with a smaller number of variables (nine descriptors). The GA-QSRR model was validated initially through Y-randomization. In addition, it was successfully validated with an external testing set out of 102 peptides originating from Bacillus subtilis proteomes (RMSEP of 22.030%). Its applicability domain was defined, from which it was evident that the developed GA-QSRR exhibited strong robustness. All the sources of the model's error were identified, thus allowing for further application of the developed methodology in proteomics.

Stability of hard plates on soft substrates and application to the design of bioinspired segmented armor

NASA Astrophysics Data System (ADS)

Martini, R.; Barthelat, F.

2016-07-01

Flexible natural armors from fish, alligators or armadillo are attracting an increasing amount of attention from their unique and attractive combinations of hardness, flexibility and light weight. In particular, the extreme contrast of stiffness between hard plates and surrounding soft tissues give rise to unusual and attractive mechanisms, which now serve as model for the design of bio-inspired armors. Despite a growing interest in bio-inspired flexible protection, there is little guidelines as to the choice of materials, optimum thickness, size, shape and arrangement for the protective plates. In this work, we focus on a failure mode we recently observed on natural and bio-inspired scaled armors: the unstable tilting of individual scales subjected to off-centered point forces. We first present a series of experiments on this system, followed by a model based on contact mechanics and friction. We condense the result into a single stability diagram which capture the key parameters that govern the onset of plate tilting from a localized force. We found that the stability of individual plates is governed by the location of the point force on the plate, by the friction at the surface of the plate, by the size of the plate and by the stiffness of the substrate. We finally discuss how some of these parameters can be optimized at the design stage to produce bio-inspired protective systems with desired combination of surface hardness, stability and flexural compliance.

A Bioinspired Alginate-Gum Arabic Hydrogel with Micro-/Nanoscale Structures for Controlled Drug Release in Chronic Wound Healing.

PubMed

Li, Mi; Li, Haichang; Li, Xiangguang; Zhu, Hua; Xu, Zihui; Liu, Lianqing; Ma, Jianjie; Zhang, Mingjun

2017-07-12

Biopolymeric hydrogels have drawn increasing research interest in biomaterials due to their tunable physical and chemical properties for both creating bioactive cellular microenvironment and serving as sustainable therapeutic reagents. Inspired by a naturally occurring hydrogel secreted from the carnivorous Sundew plant for trapping insects, here we have developed a bioinspired hydrogel to deliver mitsugumin 53 (MG53), an important protein in cell membrane repair, for chronic wound healing. Both chemical compositions and micro-/nanomorphological properties inherent from the natural Sundew hydrogel were mimicked using sodium alginate and gum arabic with calcium ion-mediated cross-linking. On the basis of atomic force microscopy (AFM) force measurements, an optimal sticky hydrogel scaffold was obtained through orthogonal experimental design. Imaging and mechanical analysis showed the distinct correlation between structural morphology, adhesion characteristics, and mechanical properties of the Sundew-inspired hydrogel. Combined characterization and biochemistry techniques were utilized to uncover the underlying molecular composition involved in the interactions between hydrogel and protein. In vitro drug release experiments confirmed that the Sundew-inspired hydrogel had a biphasic-kinetics release, which can facilitate both fast delivery of MG53 for improving the reepithelization process of the wounds and sustained release of the protein for treating chronic wounds. In vivo experiments showed that the Sundew-inspired hydrogel encapsulating with rhMG53 could facilitate dermal wound healing in mouse model. Together, these studies confirmed that the Sundew-inspired hydrogel has both tunable micro-/nanostructures and physicochemical properties, which enable it as a delivery vehicle for chronic wounding healing. The research may provide a new way to develop biocompatible and tunable biomaterials for sustainable drug release to meet the needs of biological activities.

Nature speaks - an exploratory study of nature as inspiration

Treesearch

Will LaPage

2001-01-01

Artists, composers, writers, and photographers who have been inspired by Acadia National Park and Baxter State Park, share their thoughts about the importance of nature to creativity, their feelings about park landscapes, their need for personal expression and the importance of sharing the inspirational experience. Implications for a better understanding of the park...

Topology Optimization of Lightweight Lattice Structural Composites Inspired by Cuttlefish Bone

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Bio-inspired Murray materials for mass transfer and activity

PubMed Central

Zheng, Xianfeng; Shen, Guofang; Wang, Chao; Li, Yu; Dunphy, Darren; Hasan, Tawfique; Brinker, C. Jeffrey; Su, Bao-Lian

2017-01-01

Both plants and animals possess analogous tissues containing hierarchical networks of pores, with pore size ratios that have evolved to maximize mass transport and rates of reactions. The underlying physical principles of this optimized hierarchical design are embodied in Murray's law. However, we are yet to realize the benefit of mimicking nature's Murray networks in synthetic materials due to the challenges in fabricating vascularized structures. Here we emulate optimum natural systems following Murray's law using a bottom-up approach. Such bio-inspired materials, whose pore sizes decrease across multiple scales and finally terminate in size-invariant units like plant stems, leaf veins and vascular and respiratory systems provide hierarchical branching and precise diameter ratios for connecting multi-scale pores from macro to micro levels. Our Murray material mimics enable highly enhanced mass exchange and transfer in liquid–solid, gas–solid and electrochemical reactions and exhibit enhanced performance in photocatalysis, gas sensing and as Li-ion battery electrodes. PMID:28382972

Silk-microfluidics for advanced biotechnological applications: A progressive review.

PubMed

Konwarh, Rocktotpal; Gupta, Prerak; Mandal, Biman B

2016-01-01

Silk based biomaterials have not only carved a unique niche in the domain of regenerative medicine but new avenues are also being explored for lab-on-a-chip applications. It is pertinent to note that biospinning of silk represents nature's signature microfluidic-maneuver. Elucidation of non-Newtonian flow of silk in the glands of spiders and silkworms has inspired researchers to fabricate devices for continuous extrusion and concentration of silk. Microfluidic channel networks within porous silk scaffolds ensure optimal nutrient and oxygen supply apart from serving as precursors for vascularization in tissue engineering applications. On the other hand, unique topographical features and surface wettability of natural silk fibers have inspired development of a number of simple and cost-effective devices for applications like blood typing and chemical sensing. This review mirrors the recent progress and challenges in the domain of silk-microfluidics for prospective avant-garde applications in the realm of biotechnology. Copyright © 2016 Elsevier Inc. All rights reserved.

Perspective: Stochastic magnetic devices for cognitive computing

NASA Astrophysics Data System (ADS)

Roy, Kaushik; Sengupta, Abhronil; Shim, Yong

2018-06-01

Stochastic switching of nanomagnets can potentially enable probabilistic cognitive hardware consisting of noisy neural and synaptic components. Furthermore, computational paradigms inspired from the Ising computing model require stochasticity for achieving near-optimality in solutions to various types of combinatorial optimization problems such as the Graph Coloring Problem or the Travelling Salesman Problem. Achieving optimal solutions in such problems are computationally exhaustive and requires natural annealing to arrive at the near-optimal solutions. Stochastic switching of devices also finds use in applications involving Deep Belief Networks and Bayesian Inference. In this article, we provide a multi-disciplinary perspective across the stack of devices, circuits, and algorithms to illustrate how the stochastic switching dynamics of spintronic devices in the presence of thermal noise can provide a direct mapping to the computational units of such probabilistic intelligent systems.

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

Case study: Optimizing fault model input parameters using bio-inspired algorithms

NASA Astrophysics Data System (ADS)

Plucar, Jan; Grunt, Onřej; Zelinka, Ivan

2017-07-01

We present a case study that demonstrates a bio-inspired approach in the process of finding optimal parameters for GSM fault model. This model is constructed using Petri Nets approach it represents dynamic model of GSM network environment in the suburban areas of Ostrava city (Czech Republic). We have been faced with a task of finding optimal parameters for an application that requires high amount of data transfers between the application itself and secure servers located in datacenter. In order to find the optimal set of parameters we employ bio-inspired algorithms such as Differential Evolution (DE) or Self Organizing Migrating Algorithm (SOMA). In this paper we present use of these algorithms, compare results and judge their performance in fault probability mitigation.

A genetic algorithm solution to the unit commitment problem

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

Kazarlis, S.A.; Bakirtzis, A.G.; Petridis, V.

1996-02-01

This paper presents a Genetic Algorithm (GA) solution to the Unit Commitment problem. GAs are general purpose optimization techniques based on principles inspired from the biological evolution using metaphors of mechanisms such as natural selection, genetic recombination and survival of the fittest. A simple Ga algorithm implementation using the standard crossover and mutation operators could locate near optimal solutions but in most cases failed to converge to the optimal solution. However, using the Varying Quality Function technique and adding problem specific operators, satisfactory solutions to the Unit Commitment problem were obtained. Test results for systems of up to 100 unitsmore » and comparisons with results obtained using Lagrangian Relaxation and Dynamic Programming are also reported.« less

Functional surfaces for tribological applications: inspiration and design

NASA Astrophysics Data System (ADS)

Abdel-Aal, Hisham A.

2016-12-01

Surface texturing has been recognized as a method for enhancing the tribological properties of surfaces for many years. Adding a controlled texture to one of two faces in relative motion can have many positive effects, such as reduction of friction and wear and increase in load capacity. To date, the true potential of texturing has not been realized not because of the lack of enabling texturing technologies but because of the severe lack of detailed information about the mechanistic functional details of texturing in a tribological situation. Experimental as well as theoretical analysis of textured surfaces define important metrics for performance evaluation. These metrics represent the interaction between geometry of the texturing element and surface topology. To date, there is no agreement on the optimal values that should be implemented given a particular surface. More importantly, a well-defined methodology for the generation of deterministic textures of optimized designs virtually does not exist. Nature, on the other hand, offers many examples of efficient texturing strategies (geometries and topologies) specifically applied to mitigate frictional effects in a variety of situations. Studying these examples may advance the technology of surface engineering. This paper therefore, provides a comparative review of surface texturing that manifest viable synergy between tribology and biology. We attempt to provide successful emerging examples where borrowing from nature has inspired viable surface solutions that address difficult tribological problems both in dry and lubricated contact situations.

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.

An efficient algorithm for function optimization: modified stem cells algorithm

NASA Astrophysics Data System (ADS)

Taherdangkoo, Mohammad; Paziresh, Mahsa; Yazdi, Mehran; Bagheri, Mohammad Hadi

2013-03-01

In this paper, we propose an optimization algorithm based on the intelligent behavior of stem cell swarms in reproduction and self-organization. Optimization algorithms, such as the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm and Artificial Bee Colony (ABC) algorithm, can give solutions to linear and non-linear problems near to the optimum for many applications; however, in some case, they can suffer from becoming trapped in local optima. The Stem Cells Algorithm (SCA) is an optimization algorithm inspired by the natural behavior of stem cells in evolving themselves into new and improved cells. The SCA avoids the local optima problem successfully. In this paper, we have made small changes in the implementation of this algorithm to obtain improved performance over previous versions. Using a series of benchmark functions, we assess the performance of the proposed algorithm and compare it with that of the other aforementioned optimization algorithms. The obtained results prove the superiority of the Modified Stem Cells Algorithm (MSCA).

Metaheuristic Optimization and its Applications in Earth Sciences

NASA Astrophysics Data System (ADS)

Yang, Xin-She

2010-05-01

A common but challenging task in modelling geophysical and geological processes is to handle massive data and to minimize certain objectives. This can essentially be considered as an optimization problem, and thus many new efficient metaheuristic optimization algorithms can be used. In this paper, we will introduce some modern metaheuristic optimization algorithms such as genetic algorithms, harmony search, firefly algorithm, particle swarm optimization and simulated annealing. We will also discuss how these algorithms can be applied to various applications in earth sciences, including nonlinear least-squares, support vector machine, Kriging, inverse finite element analysis, and data-mining. We will present a few examples to show how different problems can be reformulated as optimization. Finally, we will make some recommendations for choosing various algorithms to suit various problems. References 1) D. H. Wolpert and W. G. Macready, No free lunch theorems for optimization, IEEE Trans. Evolutionary Computation, Vol. 1, 67-82 (1997). 2) X. S. Yang, Nature-Inspired Metaheuristic Algorithms, Luniver Press, (2008). 3) X. S. Yang, Mathematical Modelling for Earth Sciences, Dunedin Academic Press, (2008).

Synthesis and bio-inspired optimization of drimenal: Discovery of chiral drimane fused oxazinones as promising antifungal and antibacterial candidates.

PubMed

Li, Dangdang; Zhang, Shasha; Song, Zehua; Li, Wei; Zhu, Feng; Zhang, Jiwen; Li, Shengkun

2018-01-01

The synthesis of antifungal natural product drimenal was accomplished. Bio-inspired optimization protruded chiral 8-(R)-drimane fused oxazinone D as a lead, considering favorable physicochemical profiles for novel pesticides. The improved scalable synthesis of scaffold D was implemented by Hofmann rearrangment under mild conditions. Detailed structural optimization was discussed for both antifungal and antibacterial exploration. Substituted groups (SGs) with C 3 ∼C 5 hydrocarbon chain are recommended for exploration of antifungal agents, while substituents with C 4 ∼C 6 carbon length are preferred for antibacterial ingredients. The chiral drimane fused oxazinone D8 was selected as a promising antifungal candidate against Botrytis cirerea, with an EC 50 value of 1.18 mg/L, with the enhancement of up to >25 folds and >80 folds than the mother compound D, and acyclic counterpart AB5, respectively. The in vivo bioassay confirmed much better preservative effect of D8 than that of Carbendazim. The chiral oxazinone variant D10 possessed prominent antibacterial activity, with MIC values of 8 mg/L against both Bacillus subtilis and Ralstonia solanacearum, showing advantages over the positive control streptomycin sulfate. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Interactive Learning Environment for Bio-Inspired Optimization Algorithms for UAV Path Planning

ERIC Educational Resources Information Center

Duan, Haibin; Li, Pei; Shi, Yuhui; Zhang, Xiangyin; Sun, Changhao

2015-01-01

This paper describes the development of BOLE, a MATLAB-based interactive learning environment, that facilitates the process of learning bio-inspired optimization algorithms, and that is dedicated exclusively to unmanned aerial vehicle path planning. As a complement to conventional teaching methods, BOLE is designed to help students consolidate the…

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

NASA Astrophysics Data System (ADS)

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

2010-10-01

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

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

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.

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.

Pathway Design, Engineering, and Optimization.

PubMed

Garcia-Ruiz, Eva; HamediRad, Mohammad; Zhao, Huimin

The microbial metabolic versatility found in nature has inspired scientists to create microorganisms capable of producing value-added compounds. Many endeavors have been made to transfer and/or combine pathways, existing or even engineered enzymes with new function to tractable microorganisms to generate new metabolic routes for drug, biofuel, and specialty chemical production. However, the success of these pathways can be impeded by different complications from an inherent failure of the pathway to cell perturbations. Pursuing ways to overcome these shortcomings, a wide variety of strategies have been developed. This chapter will review the computational algorithms and experimental tools used to design efficient metabolic routes, and construct and optimize biochemical pathways to produce chemicals of high interest.

Design and development of bio-inspired framework for reservoir operation optimization

NASA Astrophysics Data System (ADS)

Asvini, M. Sakthi; Amudha, T.

2017-12-01

Frameworks for optimal reservoir operation play an important role in the management of water resources and delivery of economic benefits. Effective utilization and conservation of water from reservoirs helps to manage water deficit periods. The main challenge in reservoir optimization is to design operating rules that can be used to inform real-time decisions on reservoir release. We develop a bio-inspired framework for the optimization of reservoir release to satisfy the diverse needs of various stakeholders. In this work, single-objective optimization and multiobjective optimization problems are formulated using an algorithm known as "strawberry optimization" and tested with actual reservoir data. Results indicate that well planned reservoir operations lead to efficient deployment of the reservoir water with the help of optimal release patterns.

Towards Biological Inspiration in the Development of Complex Systems

NASA Technical Reports Server (NTRS)

Hinchey, Michael G.; Sterritt, Roy

2006-01-01

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

Swarm size and iteration number effects to the performance of PSO algorithm in RFID tag coverage optimization

NASA Astrophysics Data System (ADS)

Prathabrao, M.; Nawawi, Azli; Sidek, Noor Azizah

2017-04-01

Radio Frequency Identification (RFID) system has multiple benefits which can improve the operational efficiency of the organization. The advantages are the ability to record data systematically and quickly, reducing human errors and system errors, update the database automatically and efficiently. It is often more readers (reader) is needed for the installation purposes in RFID system. Thus, it makes the system more complex. As a result, RFID network planning process is needed to ensure the RFID system works perfectly. The planning process is also considered as an optimization process and power adjustment because the coordinates of each RFID reader to be determined. Therefore, algorithms inspired by the environment (Algorithm Inspired by Nature) is often used. In the study, PSO algorithm is used because it has few number of parameters, the simulation time is fast, easy to use and also very practical. However, PSO parameters must be adjusted correctly, for robust and efficient usage of PSO. Failure to do so may result in disruption of performance and results of PSO optimization of the system will be less good. To ensure the efficiency of PSO, this study will examine the effects of two parameters on the performance of PSO Algorithm in RFID tag coverage optimization. The parameters to be studied are the swarm size and iteration number. In addition to that, the study will also recommend the most optimal adjustment for both parameters that is, 200 for the no. iterations and 800 for the no. of swarms. Finally, the results of this study will enable PSO to operate more efficiently in order to optimize RFID network planning system.

Curious Play: Children's Exploration of Nature

ERIC Educational Resources Information Center

Gurholt, Kirsti Pedersen; Sanderud, Jostein Rønning

2016-01-01

This article explores the concept of "curious play" as a theoretical framework to understand and communicate children's experiences of free play in nature. The concept emerged interactively from three sources of inspiration: an ethnographically inspired study of children playing in nature; as a critique of the concept of "risky…

Smell Detection Agent Based Optimization Algorithm

NASA Astrophysics Data System (ADS)

Vinod Chandra, S. S.

2016-09-01

In this paper, a novel nature-inspired optimization algorithm has been employed and the trained behaviour of dogs in detecting smell trails is adapted into computational agents for problem solving. The algorithm involves creation of a surface with smell trails and subsequent iteration of the agents in resolving a path. This algorithm can be applied in different computational constraints that incorporate path-based problems. Implementation of the algorithm can be treated as a shortest path problem for a variety of datasets. The simulated agents have been used to evolve the shortest path between two nodes in a graph. This algorithm is useful to solve NP-hard problems that are related to path discovery. This algorithm is also useful to solve many practical optimization problems. The extensive derivation of the algorithm can be enabled to solve shortest path problems.

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

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.

A review of compliant transmission mechanisms for bio-inspired flapping-wing micro air vehicles.

PubMed

Zhang, C; Rossi, C

2017-02-15

Flapping-wing micro air vehicles (FWMAVs) are a class of unmanned aircraft that imitate flight characteristics of natural organisms such as birds, bats, and insects, in order to achieve maximum flight efficiency and manoeuvrability. Designing proper mechanisms for flapping transmission is an extremely important aspect for FWMAVs. Compliant transmission mechanisms have been considered as an alternative to rigid transmission systems due to their lower the number of parts, thereby reducing the total weight, lower energy loss thanks to little or practically no friction among parts, and at the same time, being able to store and release mechanical power during the flapping cycle. In this paper, the state-of-the-art research in this field is dealt upon, highlighting open challenges and research topics. An optimization method for designing compliant transmission mechanisms inspired by the thoraxes of insects is also introduced.

Development of optimization model for sputtering process parameter based on gravitational search algorithm

NASA Astrophysics Data System (ADS)

Norlina, M. S.; Diyana, M. S. Nor; Mazidah, P.; Rusop, M.

2016-07-01

In the RF magnetron sputtering process, the desirable layer properties are largely influenced by the process parameters and conditions. If the quality of the thin film has not reached up to its intended level, the experiments have to be repeated until the desirable quality has been met. This research is proposing Gravitational Search Algorithm (GSA) as the optimization model to reduce the time and cost to be spent in the thin film fabrication. The optimization model's engine has been developed using Java. The model is developed based on GSA concept, which is inspired by the Newtonian laws of gravity and motion. In this research, the model is expected to optimize four deposition parameters which are RF power, deposition time, oxygen flow rate and substrate temperature. The results have turned out to be promising and it could be concluded that the performance of the model is satisfying in this parameter optimization problem. Future work could compare GSA with other nature based algorithms and test them with various set of data.

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.

Understanding Natural Sciences Education in a Reggio Emilia-Inspired Preschool

ERIC Educational Resources Information Center

Inan, Hatice Zeynep; Trundle, Kathy Cabe; Kantor, Rebecca

2010-01-01

This ethnographic study explored aspects of how the natural sciences were represented in a Reggio Emilia-inspired laboratory preschool. The natural sciences as a discipline--a latecomer to preschool curricula--and the internationally known approach, Reggio Emilia, interested educators and researchers, but there was little research about science in…

Designing nacre-like materials for simultaneous stiffness, strength and toughness: Optimum materials, composition, microstructure and size

NASA Astrophysics Data System (ADS)

Barthelat, Francois

2014-12-01

Nacre, bone and spider silk are staggered composites where inclusions of high aspect ratio reinforce a softer matrix. Such staggered composites have emerged through natural selection as the best configuration to produce stiffness, strength and toughness simultaneously. As a result, these remarkable materials are increasingly serving as model for synthetic composites with unusual and attractive performance. While several models have been developed to predict basic properties for biological and bio-inspired staggered composites, the designer is still left to struggle with finding optimum parameters. Unresolved issues include choosing optimum properties for inclusions and matrix, and resolving the contradictory effects of certain design variables. Here we overcome these difficulties with a multi-objective optimization for simultaneous high stiffness, strength and energy absorption in staggered composites. Our optimization scheme includes material properties for inclusions and matrix as design variables. This process reveals new guidelines, for example the staggered microstructure is only advantageous if the tablets are at least five times stronger than the interfaces, and only if high volume concentrations of tablets are used. We finally compile the results into a step-by-step optimization procedure which can be applied for the design of any type of high-performance staggered composite and at any length scale. The procedure produces optimum designs which are consistent with the materials and microstructure of natural nacre, confirming that this natural material is indeed optimized for mechanical performance.

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.

Bio-inspired optimization algorithms for optical parameter extraction of dielectric materials: A comparative study

NASA Astrophysics Data System (ADS)

Ghulam Saber, Md; Arif Shahriar, Kh; Ahmed, Ashik; Hasan Sagor, Rakibul

2016-10-01

Particle swarm optimization (PSO) and invasive weed optimization (IWO) algorithms are used for extracting the modeling parameters of materials useful for optics and photonics research community. These two bio-inspired algorithms are used here for the first time in this particular field to the best of our knowledge. The algorithms are used for modeling graphene oxide and the performances of the two are compared. Two objective functions are used for different boundary values. Root mean square (RMS) deviation is determined and compared.

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.

Biomimicry in Product Design through Materials Selection and Computer Aided Engineering

NASA Astrophysics Data System (ADS)

Alexandridis, G.; Tzetzis, D.; Kyratsis, P.

2016-11-01

The aim of this study is to demonstrate a 7-step methodology that describes the way nature can act as a source of inspiration for the design and the development of a product. Furthermore, it suggests special computerized tools and methods for the product optimization regarding its environmental impact i.e. material selection, production methods. For validation purposes, a garden chaise lounge that imitates the form of a scorpion was developed as a result for the case study and the presentation of the current methodology.

Nature Foil Reliefs

ERIC Educational Resources Information Center

Lane, Shaw J.

2012-01-01

Nature has always been a source of inspiration for artists across the centuries. Artists such as Leonardo da Vinci, Georgia O'Keeffe, Ansel Adams, and Andy Goldsworthy all drew inspiration for their work from nature. Seeds come from the dried pods, which when planted and cared for, bear fruit. In this article, the author describes how her…

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.

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.

Model-based setting of inspiratory pressure and respiratory rate in pressure-controlled ventilation.

PubMed

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

2014-03-01

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

Swarm intelligence-based approach for optimal design of CMOS differential amplifier and comparator circuit using a hybrid salp swarm algorithm

NASA Astrophysics Data System (ADS)

Asaithambi, Sasikumar; Rajappa, Muthaiah

2018-05-01

In this paper, an automatic design method based on a swarm intelligence approach for CMOS analog integrated circuit (IC) design is presented. The hybrid meta-heuristics optimization technique, namely, the salp swarm algorithm (SSA), is applied to the optimal sizing of a CMOS differential amplifier and the comparator circuit. SSA is a nature-inspired optimization algorithm which mimics the navigating and hunting behavior of salp. The hybrid SSA is applied to optimize the circuit design parameters and to minimize the MOS transistor sizes. The proposed swarm intelligence approach was successfully implemented for an automatic design and optimization of CMOS analog ICs using Generic Process Design Kit (GPDK) 180 nm technology. The circuit design parameters and design specifications are validated through a simulation program for integrated circuit emphasis simulator. To investigate the efficiency of the proposed approach, comparisons have been carried out with other simulation-based circuit design methods. The performances of hybrid SSA based CMOS analog IC designs are better than the previously reported studies.

Swarm intelligence-based approach for optimal design of CMOS differential amplifier and comparator circuit using a hybrid salp swarm algorithm.

PubMed

Asaithambi, Sasikumar; Rajappa, Muthaiah

2018-05-01

In this paper, an automatic design method based on a swarm intelligence approach for CMOS analog integrated circuit (IC) design is presented. The hybrid meta-heuristics optimization technique, namely, the salp swarm algorithm (SSA), is applied to the optimal sizing of a CMOS differential amplifier and the comparator circuit. SSA is a nature-inspired optimization algorithm which mimics the navigating and hunting behavior of salp. The hybrid SSA is applied to optimize the circuit design parameters and to minimize the MOS transistor sizes. The proposed swarm intelligence approach was successfully implemented for an automatic design and optimization of CMOS analog ICs using Generic Process Design Kit (GPDK) 180 nm technology. The circuit design parameters and design specifications are validated through a simulation program for integrated circuit emphasis simulator. To investigate the efficiency of the proposed approach, comparisons have been carried out with other simulation-based circuit design methods. The performances of hybrid SSA based CMOS analog IC designs are better than the previously reported studies.

INSPIRE

NASA Technical Reports Server (NTRS)

Taylor, Bill; Pine, Bill

2003-01-01

INSPIRE (Interactive NASA Space Physics Ionosphere Radio Experiment - http://image.gsfc.nasa.gov/poetry/inspire) is a non-profit scientific, educational organization whose objective is to bring the excitement of observing natural and manmade radio waves in the audio region to high school students and others. The project consists of building an audio frequency radio receiver kit, making observations of natural and manmade radio waves and analyzing the data. Students also learn about NASA and our natural environment through the study of lightning, the source of many of the audio frequency waves, the atmosphere, the ionosphere, and the magnetosphere where the waves travel.

Optimal path planning for a mobile robot using cuckoo search algorithm

NASA Astrophysics Data System (ADS)

Mohanty, Prases K.; Parhi, Dayal R.

2016-03-01

The shortest/optimal path planning is essential for efficient operation of autonomous vehicles. In this article, a new nature-inspired meta-heuristic algorithm has been applied for mobile robot path planning in an unknown or partially known environment populated by a variety of static obstacles. This meta-heuristic algorithm is based on the levy flight behaviour and brood parasitic behaviour of cuckoos. A new objective function has been formulated between the robots and the target and obstacles, which satisfied the conditions of obstacle avoidance and target-seeking behaviour of robots present in the terrain. Depending upon the objective function value of each nest (cuckoo) in the swarm, the robot avoids obstacles and proceeds towards the target. The smooth optimal trajectory is framed with this algorithm when the robot reaches its goal. Some simulation and experimental results are presented at the end of the paper to show the effectiveness of the proposed navigational controller.

Relationship between the humidity and temperature of inspired gas and the function of the airway mucosa.

PubMed

Williams, R; Rankin, N; Smith, T; Galler, D; Seakins, P

1996-11-01

To review the available literature on the relationship between the humidity and temperature of inspired gas and airway mucosal function. International computerized databases and published indices, experts in the field, conference proceedings, bibliographies. Two hundred articles/texts on respiratory tract physiology and humidification were reviewed. Seventeen articles were selected from 40 articles for inclusion in the published data verification of the model. Selection was by independent reviewers. Extraction was by consensus, and was based on finding sufficient data. A relationship exists between inspired gas humidity and temperature, exposure time to a given humidity level, and mucosal function. This relationship can be modeled and represented as an inspired humidity magnitude vs. exposure time map. The model is predictive of mucosal function and can be partially verified by the available literature. It predicts that if inspired humidity deviates from an optimal level, a progressive mucosal dysfunction begins. The greater the humidity deviation, the faster the mucosal dysfunction progresses. A model for the relationship between airway mucosal dysfunction and the combination of the humidity of inspired gas and the duration over which the airway mucosa is exposed to that humidity is proposed. This model suggests that there is an optimal temperature and humidity above which, and below which, there is impaired mucosal function. This optimal level of temperature and humidity is core temperature and 100% relative humidity. However, existing data are only sufficient to test this model for gas conditions below core temperature and 100% relative humidity. These data concur with the model in that region. No studies have yet looked at this relationship beyond 24 hrs. Longer exposure times to any given level of inspired humidity and inspired gas temperatures and humidities above core temperature and 100% relative humidity need to be studied to fully verify the proposed model.

Feature selection with harmony search.

PubMed

Diao, Ren; Shen, Qiang

2012-12-01

Many search strategies have been exploited for the task of feature selection (FS), in an effort to identify more compact and better quality subsets. Such work typically involves the use of greedy hill climbing (HC), or nature-inspired heuristics, in order to discover the optimal solution without going through exhaustive search. In this paper, a novel FS approach based on harmony search (HS) is presented. It is a general approach that can be used in conjunction with many subset evaluation techniques. The simplicity of HS is exploited to reduce the overall complexity of the search process. The proposed approach is able to escape from local solutions and identify multiple solutions owing to the stochastic nature of HS. Additional parameter control schemes are introduced to reduce the effort and impact of parameter configuration. These can be further combined with the iterative refinement strategy, tailored to enforce the discovery of quality subsets. The resulting approach is compared with those that rely on HC, genetic algorithms, and particle swarm optimization, accompanied by in-depth studies of the suggested improvements.

Rotational 3D printing of damage-tolerant composites with programmable mechanics

PubMed Central

Raney, Jordan R.; Compton, Brett G.; Ober, Thomas J.; Shea, Kristina; Lewis, Jennifer A.

2018-01-01

Natural composites exhibit exceptional mechanical performance that often arises from complex fiber arrangements within continuous matrices. Inspired by these natural systems, we developed a rotational 3D printing method that enables spatially controlled orientation of short fibers in polymer matrices solely by varying the nozzle rotation speed relative to the printing speed. Using this method, we fabricated carbon fiber–epoxy composites composed of volume elements (voxels) with programmably defined fiber arrangements, including adjacent regions with orthogonally and helically oriented fibers that lead to nonuniform strain and failure as well as those with purely helical fiber orientations akin to natural composites that exhibit enhanced damage tolerance. Our approach broadens the design, microstructural complexity, and performance space for fiber-reinforced composites through site-specific optimization of their fiber orientation, strain, failure, and damage tolerance. PMID:29348206

Performance evaluation of firefly algorithm with variation in sorting for non-linear benchmark problems

NASA Astrophysics Data System (ADS)

Umbarkar, A. J.; Balande, U. T.; Seth, P. D.

2017-06-01

The field of nature inspired computing and optimization techniques have evolved to solve difficult optimization problems in diverse fields of engineering, science and technology. The firefly attraction process is mimicked in the algorithm for solving optimization problems. In Firefly Algorithm (FA) sorting of fireflies is done by using sorting algorithm. The original FA is proposed with bubble sort for ranking the fireflies. In this paper, the quick sort replaces bubble sort to decrease the time complexity of FA. The dataset used is unconstrained benchmark functions from CEC 2005 [22]. The comparison of FA using bubble sort and FA using quick sort is performed with respect to best, worst, mean, standard deviation, number of comparisons and execution time. The experimental result shows that FA using quick sort requires less number of comparisons but requires more execution time. The increased number of fireflies helps to converge into optimal solution whereas by varying dimension for algorithm performed better at a lower dimension than higher dimension.

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.

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

PubMed Central

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

2016-01-01

There are a great variety of joint types used in nature which can inspire engineering joints. In order to design such biomimetic joints, it is at first important to understand how biological joints work. A comprehensive literature review, considering natural joints from a mechanical point of view, was undertaken. This was used to develop a taxonomy based on the different methods/functions that nature successfully uses to attach dissimilar tissues. One of the key methods that nature uses to join dissimilar materials is a transitional zone of stiffness at the insertion site. This method was used to propose bio-inspired solutions with a transitional zone of stiffness at the joint site for several glass fibre reinforced plastic (GFRP) to steel adhesively bonded joint configurations. The transition zone was used to reduce the material stiffness mismatch of the joint parts. A numerical finite element model was used to identify the optimum variation in material stiffness that minimises potential failure of the joint. The best bio-inspired joints showed a 118% increase of joint strength compared to the standard joints. PMID:28773688

Natural Inspired Intelligent Visual Computing and Its Application to Viticulture.

PubMed

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

2017-05-23

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

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.

Metabolic Engineering for the Production of Natural Products

PubMed Central

Pickens, Lauren B.; Tang, Yi; Chooi, Yit-Heng

2014-01-01

Natural products and natural product derived compounds play an important role in modern healthcare as frontline treatments for many diseases and as inspiration for chemically synthesized therapeutics. With advances in sequencing and recombinant DNA technology, many of the biosynthetic pathways responsible for the production of these chemically complex and pharmaceutically valuable compounds have been elucidated. With an ever expanding toolkit of biosynthetic components, metabolic engineering is an increasingly powerful method to improve natural product titers and generate novel compounds. Heterologous production platforms have enabled access to pathways from difficult to culture strains; systems biology and metabolic modeling tools have resulted in increasing predictive and analytic capabilities; advances in expression systems and regulation have enabled the fine-tuning of pathways for increased efficiency, and characterization of individual pathway components has facilitated the construction of hybrid pathways for the production of new compounds. These advances in the many aspects of metabolic engineering have not only yielded fascinating scientific discoveries but also make it an increasingly viable approach for the optimization of natural product biosynthesis. PMID:22432617

Physics-based Morphology Analysis and Adjoint Optimization of Flexible Flapping Wings

DTIC Science & Technology

2016-08-30

understand the underlying physics of flexible wings in flying insects and birds towards the bio -inspired wing designs with superior aerodynamic...flapping flights have been developed to understand the underlying physics of flexible wings in flying insects and birds towards the bio -inspired wing...been developed to understand the underlying physics of flexible wings in flying insects and birds towards the bio -inspired wing designs with superior

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

Biogelx: Cell Culture on Self-Assembling Peptide Gels.

PubMed

Harper, Mhairi M; Connolly, Michael L; Goldie, Laura; Irvine, Eleanore J; Shaw, Joshua E; Jayawarna, Vineetha; Richardson, Stephen M; Dalby, Matthew J; Lightbody, David; Ulijn, Rein V

2018-01-01

Aromatic peptide amphiphiles can form self-supporting nanostructured hydrogels with tunable mechanical properties and chemical compositions. These hydrogels are increasingly applied in two-dimensional (2D) and three-dimensional (3D) cell culture, where there is a rapidly growing need to store, grow, proliferate, and manipulate naturally derived cells within a hydrated, 3D matrix. Biogelx Limited is a biomaterials company, created to commercialize these bio-inspired hydrogels to cell biologists for a range of cell culture applications. This chapter describes methods of various characterization and cell culture techniques specifically optimized for compatibility with Biogelx products.

A new class of hybrid anticancer agents inspired by the synergistic effects of curcumin and genistein: Design, synthesis, and anti-proliferative evaluation.

PubMed

Chen, Qiao-Hong; Yu, Kevin; Zhang, Xiaojie; Chen, Guanglin; Hoover, Andrew; Leon, Francisco; Wang, Rubing; Subrahmanyam, Nithya; Addo Mekuria, Ermias; Harinantenaina Rakotondraibe, Liva

2015-10-15

Inspired by the synergistic effects of dietary natural products with different scaffolds on the inhibition of cancer cell proliferation, incorporation of central (1E,4E)-1,4-penta-dien-3-one linker (an optimal substitute for the central metabolically unstable diketone linker of curcumin), 1-alkyl-1H-imidazol-2-yl (a promising bioisostere of terminal aryl group in curcumin), and chromone (the common pharmacophore in genistein and quercetin) into one chemical entity resulted in ten new hybrid molecules, 3-((1E,4E)-5-(1-alkyl-1H-imidazol-2-yl)-3-oxopenta-1,4-dien-1-yl)-4H-chromen-4-ones. They were synthesized through a three-step transformation using acid-catalyzed aldol condensation as key step. The WST-1 cell proliferation assay showed that they have greater anti-proliferative potency than curcumin, quercetin, and genistein on both androgen-dependent and androgen-independent human prostate cancer cells. Published by Elsevier Ltd.

MGA trajectory planning with an ACO-inspired algorithm

NASA Astrophysics Data System (ADS)

Ceriotti, Matteo; Vasile, Massimiliano

2010-11-01

Given a set of celestial bodies, the problem of finding an optimal sequence of swing-bys, deep space manoeuvres (DSM) and transfer arcs connecting the elements of the set is combinatorial in nature. The number of possible paths grows exponentially with the number of celestial bodies. Therefore, the design of an optimal multiple gravity assist (MGA) trajectory is a NP-hard mixed combinatorial-continuous problem. Its automated solution would greatly improve the design of future space missions, allowing the assessment of a large number of alternative mission options in a short time. This work proposes to formulate the complete automated design of a multiple gravity assist trajectory as an autonomous planning and scheduling problem. The resulting scheduled plan will provide the optimal planetary sequence and a good estimation of the set of associated optimal trajectories. The trajectory model consists of a sequence of celestial bodies connected by two-dimensional transfer arcs containing one DSM. For each transfer arc, the position of the planet and the spacecraft, at the time of arrival, are matched by varying the pericentre of the preceding swing-by, or the magnitude of the launch excess velocity, for the first arc. For each departure date, this model generates a full tree of possible transfers from the departure to the destination planet. Each leaf of the tree represents a planetary encounter and a possible way to reach that planet. An algorithm inspired by ant colony optimization (ACO) is devised to explore the space of possible plans. The ants explore the tree from departure to destination adding one node at the time: every time an ant is at a node, a probability function is used to select a feasible direction. This approach to automatic trajectory planning is applied to the design of optimal transfers to Saturn and among the Galilean moons of Jupiter. Solutions are compared to those found through more traditional genetic-algorithm techniques.

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.

2016 Summer Series - Vytas SunSpiral - SUPERBall: A Biologically Inspired Robot for Planetary Exploration

NASA Image and Video Library

2016-06-14

Nature is a major source of inspiration for robotics and aerospace engineering, giving rise to biologically inspired structures. Tensegrity robots mimic a structure similar to muscles and bones to produce a robust three-dimensional skeletal structure that is able to adapt. Vytas SunSpiral will present his work on biologically inspired robotics for advancing NASA space exploration missions.

Dynamic Resource Allocation in Disaster Response: Tradeoffs in Wildfire Suppression

PubMed Central

Petrovic, Nada; Alderson, David L.; Carlson, Jean M.

2012-01-01

Challenges associated with the allocation of limited resources to mitigate the impact of natural disasters inspire fundamentally new theoretical questions for dynamic decision making in coupled human and natural systems. Wildfires are one of several types of disaster phenomena, including oil spills and disease epidemics, where (1) the disaster evolves on the same timescale as the response effort, and (2) delays in response can lead to increased disaster severity and thus greater demand for resources. We introduce a minimal stochastic process to represent wildfire progression that nonetheless accurately captures the heavy tailed statistical distribution of fire sizes observed in nature. We then couple this model for fire spread to a series of response models that isolate fundamental tradeoffs both in the strength and timing of response and also in division of limited resources across multiple competing suppression efforts. Using this framework, we compute optimal strategies for decision making scenarios that arise in fire response policy. PMID:22514605

Rotational 3D printing of damage-tolerant composites with programmable mechanics.

PubMed

Raney, Jordan R; Compton, Brett G; Mueller, Jochen; Ober, Thomas J; Shea, Kristina; Lewis, Jennifer A

2018-02-06

Natural composites exhibit exceptional mechanical performance that often arises from complex fiber arrangements within continuous matrices. Inspired by these natural systems, we developed a rotational 3D printing method that enables spatially controlled orientation of short fibers in polymer matrices solely by varying the nozzle rotation speed relative to the printing speed. Using this method, we fabricated carbon fiber-epoxy composites composed of volume elements (voxels) with programmably defined fiber arrangements, including adjacent regions with orthogonally and helically oriented fibers that lead to nonuniform strain and failure as well as those with purely helical fiber orientations akin to natural composites that exhibit enhanced damage tolerance. Our approach broadens the design, microstructural complexity, and performance space for fiber-reinforced composites through site-specific optimization of their fiber orientation, strain, failure, and damage tolerance. Copyright © 2018 the Author(s). Published by PNAS.

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.

Nature as Inspiration

ERIC Educational Resources Information Center

Tank, Kristina; Moore, Tamara; Strnat, Meg

2015-01-01

This article describes the final lesson within a seven-day STEM and literacy unit that is part of the Picture STEM curriculum (pictureSTEM. org) and uses engineering to integrate science and mathematics learning in a meaningful way (Tank and Moore 2013). For this engineering challenge, students used nature as a source of inspiration for designs to…

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.

Music and the Nature: Input of the Czech Composers

NASA Astrophysics Data System (ADS)

Nemec, Vaclav; Nemcova, Lidmila

2014-05-01

Extraordinary occasions for art of any kind - music, creative graphic and plastic arts, literature (classic, modern incl. science fiction), theatre, cinema, etc. - exist to harmonise individual personal interests with those of the humanity well-being and of the Nature and also to cultivate individual spirituality and the appropriate values. Arts can be applied as irreplaceable means for making any human being better, for improving his sense for solidarity and for increasing his ethical sensibility. An interest for the art should be cultivated already since the childhood. - How much of inspiration for numerous composers all over the world has been given by the Nature, how much of inspiration for people who by listening to such a music are increasing nobility of their behaviour as well as their friendly approach to the Nature. - Many classical music works have been written with a strong inspiration by the Nature itself from the past until today. The actual Year of the Czech Music gives the possibility to present the most famous Czech composers inspired by the Nature (selected examples only): Bedřich Smetana (1824 - 1884): At the sea shore - a concert etude for piano inspired by his stay in Göteborg (Sweden); Vltava (Moldau) - a symphonic poem from the cycle "My country" inspired by the river crossing Bohemia from the South to Prague; From the Bohemian woods and meadows - another symphonic poem from the same cycle. Antonín Dvořák (1841 - 1904): V přírodě (In the Nature) - a work for orchestra Leoš Janáček (1854 - 1928): Příhody li\\vsky Bystrou\\vsky (The Cunning Little Vixen) - an opera situated mostly in a forest. Josef Bohuslav Foerster (1859-1951): Velké širé rodné lány (Big large native fields) - a choir for men singers inspired by the nature in the region where the composer as a boy from Prague was visiting his grand-father. Vítězslav Novák (1870 - 1949): In Tatra mountains - a symphonic poem expressing the author's passion for the famous Slovak mountains. Josef Suk (1874 - 1935): Pohádka léta (A Summer's Tale) - a work for orchestra remembering a relax and consolation in beauties of the Nature. Bohuslav Martinů (1890 - 1959): Otvírání studánek (The Opening of the Springs) - cantata for soli, female chorus and instrumental accompaniment remembering old local customs of purifying water in the wells when spring comes.

Visually guided gait modifications for stepping over an obstacle: a bio-inspired approach.

PubMed

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

2014-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Genetic algorithm optimized triply compensated pulses in NMR spectroscopy

NASA Astrophysics Data System (ADS)

Manu, V. S.; Veglia, Gianluigi

2015-11-01

Sensitivity and resolution in NMR experiments are affected by magnetic field inhomogeneities (of both external and RF), errors in pulse calibration, and offset effects due to finite length of RF pulses. To remedy these problems, built-in compensation mechanisms for these experimental imperfections are often necessary. Here, we propose a new family of phase-modulated constant-amplitude broadband pulses with high compensation for RF inhomogeneity and heteronuclear coupling evolution. These pulses were optimized using a genetic algorithm (GA), which consists in a global optimization method inspired by Nature's evolutionary processes. The newly designed π and π / 2 pulses belong to the 'type A' (or general rotors) symmetric composite pulses. These GA-optimized pulses are relatively short compared to other general rotors and can be used for excitation and inversion, as well as refocusing pulses in spin-echo experiments. The performance of the GA-optimized pulses was assessed in Magic Angle Spinning (MAS) solid-state NMR experiments using a crystalline U-13C, 15N NAVL peptide as well as U-13C, 15N microcrystalline ubiquitin. GA optimization of NMR pulse sequences opens a window for improving current experiments and designing new robust pulse sequences.

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.

Bio-Optics and Bio-Inspired Optical Materials.

PubMed

Tadepalli, Sirimuvva; Slocik, Joseph M; Gupta, Maneesh K; Naik, Rajesh R; Singamaneni, Srikanth

2017-10-25

Through the use of the limited materials palette, optimally designed micro- and nanostructures, and tightly regulated processes, nature demonstrates exquisite control of light-matter interactions at various length scales. In fact, control of light-matter interactions is an important element in the evolutionary arms race and has led to highly engineered optical materials and systems. In this review, we present a detailed summary of various optical effects found in nature with a particular emphasis on the materials and optical design aspects responsible for their optical functionality. Using several representative examples, we discuss various optical phenomena, including absorption and transparency, diffraction, interference, reflection and antireflection, scattering, light harvesting, wave guiding and lensing, camouflage, and bioluminescence, that are responsible for the unique optical properties of materials and structures found in nature and biology. Great strides in understanding the design principles adapted by nature have led to a tremendous progress in realizing biomimetic and bioinspired optical materials and photonic devices. We discuss the various micro- and nanofabrication techniques that have been employed for realizing advanced biomimetic optical structures.

Intrinsic hierarchical structural imperfections in a natural ceramic of bivalve shell with distinctly graded properties

PubMed Central

Jiao, Da; Liu, Zengqian; Zhang, Zhenjun; Zhang, Zhefeng

2015-01-01

Despite the extensive investigation on the structure of natural biological materials, insufficient attention has been paid to the structural imperfections by which the mechanical properties of synthetic materials are dominated. In this study, the structure of bivalve Saxidomus purpuratus shell has been systematically characterized quantitatively on multiple length scales from millimeter to sub-nanometer. It is revealed that hierarchical imperfections are intrinsically involved in the crossed-lamellar structure of the shell despite its periodically packed platelets. In particular, various favorable characters which are always pursued in synthetic materials, e.g. nanotwins and low-angle misorientations, have been incorporated herein. The possible contributions of these imperfections to mechanical properties are further discussed. It is suggested that the imperfections may serve as structural adaptations, rather than detrimental defects in the real sense, to help improve the mechanical properties of natural biological materials. This study may aid in understanding the optimizing strategies of structure and properties designed by nature, and accordingly, provide inspiration for the design of synthetic materials. PMID:26198844

Intrinsic hierarchical structural imperfections in a natural ceramic of bivalve shell with distinctly graded properties.

PubMed

Jiao, Da; Liu, Zengqian; Zhang, Zhenjun; Zhang, Zhefeng

2015-07-22

Despite the extensive investigation on the structure of natural biological materials, insufficient attention has been paid to the structural imperfections by which the mechanical properties of synthetic materials are dominated. In this study, the structure of bivalve Saxidomus purpuratus shell has been systematically characterized quantitatively on multiple length scales from millimeter to sub-nanometer. It is revealed that hierarchical imperfections are intrinsically involved in the crossed-lamellar structure of the shell despite its periodically packed platelets. In particular, various favorable characters which are always pursued in synthetic materials, e.g. nanotwins and low-angle misorientations, have been incorporated herein. The possible contributions of these imperfections to mechanical properties are further discussed. It is suggested that the imperfections may serve as structural adaptations, rather than detrimental defects in the real sense, to help improve the mechanical properties of natural biological materials. This study may aid in understanding the optimizing strategies of structure and properties designed by nature, and accordingly, provide inspiration for the design of synthetic materials.

An improved harmony search algorithm for emergency inspection scheduling

NASA Astrophysics Data System (ADS)

Kallioras, Nikos A.; Lagaros, Nikos D.; Karlaftis, Matthew G.

2014-11-01

The ability of nature-inspired search algorithms to efficiently handle combinatorial problems, and their successful implementation in many fields of engineering and applied sciences, have led to the development of new, improved algorithms. In this work, an improved harmony search (IHS) algorithm is presented, while a holistic approach for solving the problem of post-disaster infrastructure management is also proposed. The efficiency of IHS is compared with that of the algorithms of particle swarm optimization, differential evolution, basic harmony search and the pure random search procedure, when solving the districting problem that is the first part of post-disaster infrastructure management. The ant colony optimization algorithm is employed for solving the associated routing problem that constitutes the second part. The comparison is based on the quality of the results obtained, the computational demands and the sensitivity on the algorithmic parameters.

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.

A Heuristic Bioinspired for 8-Piece Puzzle

NASA Astrophysics Data System (ADS)

Machado, M. O.; Fabres, P. A.; Melo, J. C. L.

2017-10-01

This paper investigates a mathematical model inspired by nature, and presents a Meta-Heuristic that is efficient in improving the performance of an informed search, when using strategy A * using a General Search Tree as data structure. The work hypothesis suggests that the investigated meta-heuristic is optimal in nature and may be promising in minimizing the computational resources required by an objective-based agent in solving high computational complexity problems (n-part puzzle) as well as In the optimization of objective functions for local search agents. The objective of this work is to describe qualitatively the characteristics and properties of the mathematical model investigated, correlating the main concepts of the A * function with the significant variables of the metaheuristic used. The article shows that the amount of memory required to perform this search when using the metaheuristic is less than using the A * function to evaluate the nodes of a general search tree for the eight-piece puzzle. It is concluded that the meta-heuristic must be parameterized according to the chosen heuristic and the level of the tree that contains the possible solutions to the chosen problem.

INSPIRE: A VLF Radio Project for High School Students

ERIC Educational Resources Information Center

Marshall, Jill A.; Pine, Bill; Taylor, William W. L.

2007-01-01

Since 1988 the Interactive NASA Space Physics Ionospheric Radio Experiment, or INSPIRE, has given students the opportunity to build research-quality VLF radio receivers and make observations of both natural and stimulated radio waves in the atmosphere. Any high school science class is eligible to join the INSPIRE volunteer observing network and…

Experimental Investigation and Optimization of TIG Welding Parameters on Aluminum 6061 Alloy Using Firefly Algorithm

NASA Astrophysics Data System (ADS)

Kumar, Rishi; Mevada, N. Ramesh; Rathore, Santosh; Agarwal, Nitin; Rajput, Vinod; Sinh Barad, AjayPal

2017-08-01

To improve Welding quality of aluminum (Al) plate, the TIG Welding system has been prepared, by which Welding current, Shielding gas flow rate and Current polarity can be controlled during Welding process. In the present work, an attempt has been made to study the effect of Welding current, current polarity, and shielding gas flow rate on the tensile strength of the weld joint. Based on the number of parameters and their levels, the Response Surface Methodology technique has been selected as the Design of Experiment. For understanding the influence of input parameters on Ultimate tensile strength of weldment, ANOVA analysis has been carried out. Also to describe and optimize TIG Welding using a new metaheuristic Nature - inspired algorithm which is called as Firefly algorithm which was developed by Dr. Xin-She Yang at Cambridge University in 2007. A general formulation of firefly algorithm is presented together with an analytical, mathematical modeling to optimize the TIG Welding process by a single equivalent objective function.

Performance improvement of an active vibration absorber subsystem for an aircraft model using a bees algorithm based on multi-objective intelligent optimization

NASA Astrophysics Data System (ADS)

Zarchi, Milad; Attaran, Behrooz

2017-11-01

This study develops a mathematical model to investigate the behaviour of adaptable shock absorber dynamics for the six-degree-of-freedom aircraft model in the taxiing phase. The purpose of this research is to design a proportional-integral-derivative technique for control of an active vibration absorber system using a hydraulic nonlinear actuator based on the bees algorithm. This optimization algorithm is inspired by the natural intelligent foraging behaviour of honey bees. The neighbourhood search strategy is used to find better solutions around the previous one. The parameters of the controller are adjusted by minimizing the aircraft's acceleration and impact force as the multi-objective function. The major advantages of this algorithm over other optimization algorithms are its simplicity, flexibility and robustness. The results of the numerical simulation indicate that the active suspension increases the comfort of the ride for passengers and the fatigue life of the structure. This is achieved by decreasing the impact force, displacement and acceleration significantly.

Ultimate explanations and suboptimal choice.

PubMed

Vasconcelos, Marco; Machado, Armando; Pandeirada, Josefa N S

2018-07-01

Researchers have unraveled multiple cases in which behavior deviates from rationality principles. We propose that such deviations are valuable tools to understand the adaptive significance of the underpinning mechanisms. To illustrate, we discuss in detail an experimental protocol in which animals systematically incur substantial foraging losses by preferring a lean but informative option over a rich but non-informative one. To understand how adaptive mechanisms may fail to maximize food intake, we review a model inspired by optimal foraging principles that reconciles sub-optimal choice with the view that current behavioral mechanisms were pruned by the optimizing action of natural selection. To move beyond retrospective speculation, we then review critical tests of the model, regarding both its assumptions and its (sometimes counterintuitive) predictions, all of which have been upheld. The overall contention is that (a) known mechanisms can be used to develop better ultimate accounts and that (b) to understand why mechanisms that generate suboptimal behavior evolved, we need to consider their adaptive value in the animal's characteristic ecology. Copyright © 2018 Elsevier B.V. All rights reserved.

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

PubMed Central

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

2016-01-01

Bi-objective Traveling Salesman Problem (bTSP) is an important field in the operations research, its solutions can be widely applied in the real world. Many researches of Multi-objective Ant Colony Optimization (MOACOs) have been proposed to solve bTSPs. However, most of MOACOs suffer premature convergence. This paper proposes an optimization strategy for MOACOs by optimizing the initialization of pheromone matrix with the prior knowledge of Physarum-inspired Mathematical Model (PMM). PMM can find the shortest route between two nodes based on the positive feedback mechanism. The optimized algorithms, named as iPM-MOACOs, can enhance the pheromone in the short paths and promote the search ability of ants. A series of experiments are conducted and experimental results show that the proposed strategy can achieve a better compromise solution than the original MOACOs for solving bTSPs. PMID:26751562

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

PubMed

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

2016-01-01

Bi-objective Traveling Salesman Problem (bTSP) is an important field in the operations research, its solutions can be widely applied in the real world. Many researches of Multi-objective Ant Colony Optimization (MOACOs) have been proposed to solve bTSPs. However, most of MOACOs suffer premature convergence. This paper proposes an optimization strategy for MOACOs by optimizing the initialization of pheromone matrix with the prior knowledge of Physarum-inspired Mathematical Model (PMM). PMM can find the shortest route between two nodes based on the positive feedback mechanism. The optimized algorithms, named as iPM-MOACOs, can enhance the pheromone in the short paths and promote the search ability of ants. A series of experiments are conducted and experimental results show that the proposed strategy can achieve a better compromise solution than the original MOACOs for solving bTSPs.

MDTri: robust and efficient global mixed integer search of spaces of multiple ternary alloys: A DIRECT-inspired optimization algorithm for experimentally accessible computational material design

DOE PAGES

Graf, Peter A.; Billups, Stephen

2017-07-24

Computational materials design has suffered from a lack of algorithms formulated in terms of experimentally accessible variables. Here we formulate the problem of (ternary) alloy optimization at the level of choice of atoms and their composition that is normal for synthesists. Mathematically, this is a mixed integer problem where a candidate solution consists of a choice of three elements, and how much of each of them to use. This space has the natural structure of a set of equilateral triangles. We solve this problem by introducing a novel version of the DIRECT algorithm that (1) operates on equilateral triangles insteadmore » of rectangles and (2) works across multiple triangles. We demonstrate on a test case that the algorithm is both robust and efficient. Lastly, we offer an explanation of the efficacy of DIRECT -- specifically, its balance of global and local search -- by showing that 'potentially optimal rectangles' of the original algorithm are akin to the Pareto front of the 'multi-component optimization' of global and local search.« less

MDTri: robust and efficient global mixed integer search of spaces of multiple ternary alloys: A DIRECT-inspired optimization algorithm for experimentally accessible computational material design

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

Graf, Peter A.; Billups, Stephen

Computational materials design has suffered from a lack of algorithms formulated in terms of experimentally accessible variables. Here we formulate the problem of (ternary) alloy optimization at the level of choice of atoms and their composition that is normal for synthesists. Mathematically, this is a mixed integer problem where a candidate solution consists of a choice of three elements, and how much of each of them to use. This space has the natural structure of a set of equilateral triangles. We solve this problem by introducing a novel version of the DIRECT algorithm that (1) operates on equilateral triangles insteadmore » of rectangles and (2) works across multiple triangles. We demonstrate on a test case that the algorithm is both robust and efficient. Lastly, we offer an explanation of the efficacy of DIRECT -- specifically, its balance of global and local search -- by showing that 'potentially optimal rectangles' of the original algorithm are akin to the Pareto front of the 'multi-component optimization' of global and local search.« less

Compact and Thermosensitive Nature-inspired Micropump

PubMed Central

Kim, Hyejeong; Kim, Kiwoong; Lee, Sang Joon

2016-01-01

Liquid transportation without employing a bulky power source, often observed in nature, has been an essential prerequisite for smart applications of microfluidic devices. In this report, a leaf-inspired micropump (LIM) which is composed of thermo-responsive stomata-inspired membrane (SIM) and mesophyll-inspired agarose cryogel (MAC) is proposed. The LIM provides a durable flow rate of 30 μl/h · cm2 for more than 30 h at room temperature without external mechanical power source. By adapting a thermo-responsive polymer, the LIM can smartly adjust the delivery rate of a therapeutic liquid in response to temperature changes. In addition, as the LIM is compact, portable, and easily integrated into any liquid, it might be utilized as an essential component in advanced hand-held drug delivery devices. PMID:27796357

Nature-Inspired Structural Materials for Flexible Electronic Devices.

PubMed

Liu, Yaqing; He, Ke; Chen, Geng; Leow, Wan Ru; Chen, Xiaodong

2017-10-25

Exciting advancements have been made in the field of flexible electronic devices in the last two decades and will certainly lead to a revolution in peoples' lives in the future. However, because of the poor sustainability of the active materials in complex stress environments, new requirements have been adopted for the construction of flexible devices. Thus, hierarchical architectures in natural materials, which have developed various environment-adapted structures and materials through natural selection, can serve as guides to solve the limitations of materials and engineering techniques. This review covers the smart designs of structural materials inspired by natural materials and their utility in the construction of flexible devices. First, we summarize structural materials that accommodate mechanical deformations, which is the fundamental requirement for flexible devices to work properly in complex environments. Second, we discuss the functionalities of flexible devices induced by nature-inspired structural materials, including mechanical sensing, energy harvesting, physically interacting, and so on. Finally, we provide a perspective on newly developed structural materials and their potential applications in future flexible devices, as well as frontier strategies for biomimetic functions. These analyses and summaries are valuable for a systematic understanding of structural materials in electronic devices and will serve as inspirations for smart designs in flexible electronics.

OPTIMIZING THROUGH CO-EVOLUTIONARY AVALANCHES

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

S. BOETTCHER; A. PERCUS

2000-08-01

We explore a new general-purpose heuristic for finding high-quality solutions to hard optimization problems. The method, called extremal optimization, is inspired by ''self-organized critically,'' a concept introduced to describe emergent complexity in many physical systems. In contrast to Genetic Algorithms which operate on an entire ''gene-pool'' of possible solutions, extremal optimization successively replaces extremely undesirable elements of a sub-optimal solution with new, random ones. Large fluctuations, called ''avalanches,'' ensue that efficiently explore many local optima. Drawing upon models used to simulate far-from-equilibrium dynamics, extremal optimization complements approximation methods inspired by equilibrium statistical physics, such as simulated annealing. With only onemore » adjustable parameter, its performance has proved competitive with more elaborate methods, especially near phase transitions. Those phase transitions are found in the parameter space of most optimization problems, and have recently been conjectured to be the origin of some of the hardest instances in computational complexity. We will demonstrate how extremal optimization can be implemented for a variety of combinatorial optimization problems. We believe that extremal optimization will be a useful tool in the investigation of phase transitions in combinatorial optimization problems, hence valuable in elucidating the origin of computational complexity.« less

Intelligent Systems For Aerospace Engineering: An Overview

NASA Technical Reports Server (NTRS)

KrishnaKumar, K.

2003-01-01

Intelligent systems are nature-inspired, mathematically sound, computationally intensive problem solving tools and methodologies that have become extremely important for advancing the current trends in information technology. Artificially intelligent systems currently utilize computers to emulate various faculties of human intelligence and biological metaphors. They use a combination of symbolic and sub-symbolic systems capable of evolving human cognitive skills and intelligence, not just systems capable of doing things humans do not do well. Intelligent systems are ideally suited for tasks such as search and optimization, pattern recognition and matching, planning, uncertainty management, control, and adaptation. In this paper, the intelligent system technologies and their application potential are highlighted via several examples.

Bioinspired Composite Materials: Applications in Diagnostics and Therapeutics

NASA Astrophysics Data System (ADS)

Prasad, Alisha; Mahato, Kuldeep; Chandra, Pranjal; Srivastava, Ananya; Joshi, Shrikrishna N.; Maurya, Pawan Kumar

2016-08-01

Evolution-optimized specimens from nature with inimitable properties, and unique structure-function relationships have long served as a source of inspiration for researchers all over the world. For instance, the micro/nanostructured patterns of lotus-leaf and gecko feet helps in self-cleaning, and adhesion, respectively. Such unique properties shown by creatures are results of billions of years of adaptive transformation, that have been mimicked by applying both science and engineering concepts to design bioinspired materials. Various bioinspired composite materials have been developed based on biomimetic principles. This review presents the latest developments in bioinspired materials under various categories with emphasis on diagnostic and therapeutic applications.

Intelligent Systems for Aerospace Engineering: An Overview

NASA Technical Reports Server (NTRS)

Krishnakumar, Kalmanje

2002-01-01

Intelligent systems are nature-inspired, mathematically sound, computationally intensive problem solving tools and methodologies that have become extremely important for advancing the current trends in information technology. Artificially intelligent systems currently utilize computers to emulate various faculties of human intelligence and biological metaphors. They use a combination of symbolic and sub-symbolic systems capable of evolving human cognitive skills and intelligence, not just systems capable of doing things humans do not do well. Intelligent systems are ideally suited for tasks such as search and optimization, pattern recognition and matching, planning, uncertainty management, control, and adaptation. In this paper, the intelligent system technologies and their application potential are highlighted via several examples.

Application of ant colony optimization to optimal foragaing theory: comparison of simulation and field results

USDA-ARS?s Scientific Manuscript database

Ant Colony Optimization (ACO) refers to the family of algorithms inspired by the behavior of real ants and used to solve combinatorial problems such as the Traveling Salesman Problem (TSP).Optimal Foraging Theory (OFT) is an evolutionary principle wherein foraging organisms or insect parasites seek ...

The role of inspiration in scientific scholarship and discovery: views of theistic scientists.

PubMed

O'Grady, Kari A; Richards, P Scott

2011-01-01

This qualitative research study examined the ways those who identify themselves as theistic scientists and scholars experience inspiration, as defined as divine guidance or influence, in their scientific scholarship and discovery. It also explored participants' beliefs about how scientists and scholars can seek and prepare to receive inspiration in their work. Open-ended surveys of 450 participants from the behavioral and natural sciences and from a variety of religious backgrounds were analyzed for content themes in the areas of experiences with inspiration, preparing to receive inspiration, and further thoughts on inspiration in science. The themes extracted indicated that these scientists and scholars have experienced inspiration throughout all stages of the research process. They also believe that certain practices and virtues, such as openness to inspiration and nurturing a relationship with God, can help scientists and scholars be more prepared to receive inspiration in their work. Copyright © 2011 Elsevier Inc. All rights reserved.

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.

Cultural Contrasts and Commonalities in Inspiring Language Teaching

ERIC Educational Resources Information Center

Lamb, Martin; Wedell, Martin

2015-01-01

Inspiring teaching is the kind of pedagogy that motivates pupils to study autonomously, in their own time, of their own volition beyond the classroom, and may be particularly important for long-term endeavours such as learning a second language. This study aimed to find out the prevalence and nature of inspiring English language teaching in the…

Universal optimal working cycles of molecular motors.

PubMed

Efremov, Artem; Wang, Zhisong

2011-04-07

Molecular motors capable of directional track-walking or rotation are abundant in living cells, and inspire the emerging field of artificial nanomotors. Some biomotors can convert 90% of free energy from chemical fuels into usable mechanical work, and the same motors still maintain a speed sufficient for cellular functions. This study exposed a new regime of universal optimization that amounts to a thermodynamically best working regime for molecular motors but is unfamiliar in macroscopic engines. For the ideal case of zero energy dissipation, the universally optimized working cycle for molecular motors is infinitely slow like Carnot cycle for heat engines. But when a small amount of energy dissipation reduces energy efficiency linearly from 100%, the speed is recovered exponentially due to Boltzmann's law. Experimental data on a major biomotor (kinesin) suggest that the regime of universal optimization has been largely approached in living cells, underpinning the extreme efficiency-speed trade-off in biomotors. The universal optimization and its practical approachability are unique thermodynamic advantages of molecular systems over macroscopic engines in facilitating motor functions. The findings have important implications for the natural evolution of biomotors as well as the development of artificial counterparts.

Unraveling Quantum Annealers using Classical Hardness

PubMed Central

Martin-Mayor, Victor; Hen, Itay

2015-01-01

Recent advances in quantum technology have led to the development and manufacturing of experimental programmable quantum annealing optimizers that contain hundreds of quantum bits. These optimizers, commonly referred to as ‘D-Wave’ chips, promise to solve practical optimization problems potentially faster than conventional ‘classical’ computers. Attempts to quantify the quantum nature of these chips have been met with both excitement and skepticism but have also brought up numerous fundamental questions pertaining to the distinguishability of experimental quantum annealers from their classical thermal counterparts. Inspired by recent results in spin-glass theory that recognize ‘temperature chaos’ as the underlying mechanism responsible for the computational intractability of hard optimization problems, we devise a general method to quantify the performance of quantum annealers on optimization problems suffering from varying degrees of temperature chaos: A superior performance of quantum annealers over classical algorithms on these may allude to the role that quantum effects play in providing speedup. We utilize our method to experimentally study the D-Wave Two chip on different temperature-chaotic problems and find, surprisingly, that its performance scales unfavorably as compared to several analogous classical algorithms. We detect, quantify and discuss several purely classical effects that possibly mask the quantum behavior of the chip. PMID:26483257

Biomimicry of symbiotic multi-species coevolution for discrete and continuous optimization in RFID networks.

PubMed

Lin, Na; Chen, Hanning; Jing, Shikai; Liu, Fang; Liang, Xiaodan

2017-03-01

In recent years, symbiosis as a rich source of potential engineering applications and computational model has attracted more and more attentions in the adaptive complex systems and evolution computing domains. Inspired by different symbiotic coevolution forms in nature, this paper proposed a series of multi-swarm particle swarm optimizers called PS 2 Os, which extend the single population particle swarm optimization (PSO) algorithm to interacting multi-swarms model by constructing hierarchical interaction topologies and enhanced dynamical update equations. According to different symbiotic interrelationships, four versions of PS 2 O are initiated to mimic mutualism, commensalism, predation, and competition mechanism, respectively. In the experiments, with five benchmark problems, the proposed algorithms are proved to have considerable potential for solving complex optimization problems. The coevolutionary dynamics of symbiotic species in each PS 2 O version are also studied respectively to demonstrate the heterogeneity of different symbiotic interrelationships that effect on the algorithm's performance. Then PS 2 O is used for solving the radio frequency identification (RFID) network planning (RNP) problem with a mixture of discrete and continuous variables. Simulation results show that the proposed algorithm outperforms the reference algorithms for planning RFID networks, in terms of optimization accuracy and computation robustness.

Golden spiral photonic crystal fiber: polarization and dispersion properties.

PubMed

Agrawal, Arti; Kejalakshmy, N; Chen, J; Rahman, B M A; Grattan, K T V

2008-11-15

A golden spiral photonic crystal fiber (GS-PCF) design is presented in which air holes are arranged in a spiral pattern governed by the golden ratio, where the design has been inspired by the optimal arrangement of seeds found in nature. The birefringence and polarization properties of this fiber are analyzed using a vectorial finite-element method. The fiber that is investigated shows a large modal birefringence peak value of 0.016 at an operating wavelength of 1.55 microm and exhibits highly tuneable dispersion with multiple zero dispersion wavelengths and also large normal dispersion. The GS-PCF design has identical circular air holes that potentially simplify fabrication. In light of its properties, the GS-PCF could have application as a highly birefringent fiber and in nonlinear optics, and moreover the 2D chiral nature of the pattern could yield exotic properties.

Natural photonics for industrial inspiration.

PubMed

Parker, Andrew R

2009-05-13

There are two considerations for optical biomimetics: the diversity of submicrometre architectures found in the natural world, and the industrial manufacture of these. A review exists on the latter subject, where current engineering methods are considered along with those of the natural cells. Here, on the other hand, I will provide a modern review of the different categories of reflectors and antireflectors found in animals, including their optical characterization. The purpose of this is to inspire designers within the $2 billion annual optics industry.

A fault-tolerant addressable spin qubit in a natural silicon quantum dot

PubMed Central

Takeda, Kenta; Kamioka, Jun; Otsuka, Tomohiro; Yoneda, Jun; Nakajima, Takashi; Delbecq, Matthieu R.; Amaha, Shinichi; Allison, Giles; Kodera, Tetsuo; Oda, Shunri; Tarucha, Seigo

2016-01-01

Fault-tolerant quantum computing requires high-fidelity qubits. This has been achieved in various solid-state systems, including isotopically purified silicon, but is yet to be accomplished in industry-standard natural (unpurified) silicon, mainly as a result of the dephasing caused by residual nuclear spins. This high fidelity can be achieved by speeding up the qubit operation and/or prolonging the dephasing time, that is, increasing the Rabi oscillation quality factor Q (the Rabi oscillation decay time divided by the π rotation time). In isotopically purified silicon quantum dots, only the second approach has been used, leaving the qubit operation slow. We apply the first approach to demonstrate an addressable fault-tolerant qubit using a natural silicon double quantum dot with a micromagnet that is optimally designed for fast spin control. This optimized design allows access to Rabi frequencies up to 35 MHz, which is two orders of magnitude greater than that achieved in previous studies. We find the optimum Q = 140 in such high-frequency range at a Rabi frequency of 10 MHz. This leads to a qubit fidelity of 99.6% measured via randomized benchmarking, which is the highest reported for natural silicon qubits and comparable to that obtained in isotopically purified silicon quantum dot–based qubits. This result can inspire contributions to quantum computing from industrial communities. PMID:27536725

A fault-tolerant addressable spin qubit in a natural silicon quantum dot.

PubMed

Takeda, Kenta; Kamioka, Jun; Otsuka, Tomohiro; Yoneda, Jun; Nakajima, Takashi; Delbecq, Matthieu R; Amaha, Shinichi; Allison, Giles; Kodera, Tetsuo; Oda, Shunri; Tarucha, Seigo

2016-08-01

Fault-tolerant quantum computing requires high-fidelity qubits. This has been achieved in various solid-state systems, including isotopically purified silicon, but is yet to be accomplished in industry-standard natural (unpurified) silicon, mainly as a result of the dephasing caused by residual nuclear spins. This high fidelity can be achieved by speeding up the qubit operation and/or prolonging the dephasing time, that is, increasing the Rabi oscillation quality factor Q (the Rabi oscillation decay time divided by the π rotation time). In isotopically purified silicon quantum dots, only the second approach has been used, leaving the qubit operation slow. We apply the first approach to demonstrate an addressable fault-tolerant qubit using a natural silicon double quantum dot with a micromagnet that is optimally designed for fast spin control. This optimized design allows access to Rabi frequencies up to 35 MHz, which is two orders of magnitude greater than that achieved in previous studies. We find the optimum Q = 140 in such high-frequency range at a Rabi frequency of 10 MHz. This leads to a qubit fidelity of 99.6% measured via randomized benchmarking, which is the highest reported for natural silicon qubits and comparable to that obtained in isotopically purified silicon quantum dot-based qubits. This result can inspire contributions to quantum computing from industrial communities.

Model Specification Searches Using Ant Colony Optimization Algorithms

ERIC Educational Resources Information Center

Marcoulides, George A.; Drezner, Zvi

2003-01-01

Ant colony optimization is a recently proposed heuristic procedure inspired by the behavior of real ants. This article applies the procedure to model specification searches in structural equation modeling and reports the results. The results demonstrate the capabilities of ant colony optimization algorithms for conducting automated searches.

Amoeba-Inspired Heuristic Search Dynamics for Exploring Chemical Reaction Paths.

PubMed

Aono, Masashi; Wakabayashi, Masamitsu

2015-09-01

We propose a nature-inspired model for simulating chemical reactions in a computationally resource-saving manner. The model was developed by extending our previously proposed heuristic search algorithm, called "AmoebaSAT [Aono et al. 2013]," which was inspired by the spatiotemporal dynamics of a single-celled amoeboid organism that exhibits sophisticated computing capabilities in adapting to its environment efficiently [Zhu et al. 2013]. AmoebaSAT is used for solving an NP-complete combinatorial optimization problem [Garey and Johnson 1979], "the satisfiability problem," and finds a constraint-satisfying solution at a speed that is dramatically faster than one of the conventionally known fastest stochastic local search methods [Iwama and Tamaki 2004] for a class of randomly generated problem instances [ http://www.cs.ubc.ca/~hoos/5/benchm.html ]. In cases where the problem has more than one solution, AmoebaSAT exhibits dynamic transition behavior among a variety of the solutions. Inheriting these features of AmoebaSAT, we formulate "AmoebaChem," which explores a variety of metastable molecules in which several constraints determined by input atoms are satisfied and generates dynamic transition processes among the metastable molecules. AmoebaChem and its developed forms will be applied to the study of the origins of life, to discover reaction paths for which expected or unexpected organic compounds may be formed via unknown unstable intermediates and to estimate the likelihood of each of the discovered paths.

Mechanical properties of nanostructure of biological materials

NASA Astrophysics Data System (ADS)

Ji, Baohua; Gao, Huajian

2004-09-01

Natural biological materials such as bone, teeth and nacre are nanocomposites of protein and mineral with superior strength. It is quite a marvel that nature produces hard and tough materials out of protein as soft as human skin and mineral as brittle as classroom chalk. What are the secrets of nature? Can we learn from this to produce bio-inspired materials in the laboratory? These questions have motivated us to investigate the mechanics of protein-mineral nanocomposite structure. Large aspect ratios and a staggered alignment of mineral platelets are found to be the key factors contributing to the large stiffness of biomaterials. A tension-shear chain (TSC) model of biological nanostructure reveals that the strength of biomaterials hinges upon optimizing the tensile strength of the mineral crystals. As the size of the mineral crystals is reduced to nanoscale, they become insensitive to flaws with strength approaching the theoretical strength of atomic bonds. The optimized tensile strength of mineral crystals thus allows a large amount of fracture energy to be dissipated in protein via shear deformation and consequently enhances the fracture toughness of biocomposites. We derive viscoelastic properties of the protein-mineral nanostructure and show that the toughness of biocomposite can be further enhanced by the viscoelastic properties of protein.

Unequal-area, fixed-shape facility layout problems using the firefly algorithm

NASA Astrophysics Data System (ADS)

Ingole, Supriya; Singh, Dinesh

2017-07-01

In manufacturing industries, the facility layout design is a very important task, as it is concerned with the overall manufacturing cost and profit of the industry. The facility layout problem (FLP) is solved by arranging the departments or facilities of known dimensions on the available floor space. The objective of this article is to implement the firefly algorithm (FA) for solving unequal-area, fixed-shape FLPs and optimizing the costs of total material handling and transportation between the facilities. The FA is a nature-inspired algorithm and can be used for combinatorial optimization problems. Benchmark problems from the previous literature are solved using the FA. To check its effectiveness, it is implemented to solve large-sized FLPs. Computational results obtained using the FA show that the algorithm is less time consuming and the total layout costs for FLPs are better than the best results achieved so far.

An Adjoint-Based Approach to Study a Flexible Flapping Wing in Pitching-Rolling Motion

NASA Astrophysics Data System (ADS)

Jia, Kun; Wei, Mingjun; Xu, Min; Li, Chengyu; Dong, Haibo

2017-11-01

Flapping-wing aerodynamics, with advantages in agility, efficiency, and hovering capability, has been the choice of many flyers in nature. However, the study of bio-inspired flapping-wing propulsion is often hindered by the problem's large control space with different wing kinematics and deformation. The adjoint-based approach reduces largely the computational cost to a feasible level by solving an inverse problem. Facing the complication from moving boundaries, non-cylindrical calculus provides an easy extension of traditional adjoint-based approach to handle the optimization involving moving boundaries. The improved adjoint method with non-cylindrical calculus for boundary treatment is first applied on a rigid pitching-rolling plate, then extended to a flexible one with active deformation to further increase its propulsion efficiency. The comparison of flow dynamics with the initial and optimal kinematics and deformation provides a unique opportunity to understand the flapping-wing mechanism. Supported by AFOSR and ARL.

Towards a cross-domain interoperable framework for natural hazards and disaster risk reduction information

NASA Astrophysics Data System (ADS)

Tomas, Robert; Harrison, Matthew; Barredo, José I.; Thomas, Florian; Llorente Isidro, Miguel; Cerba, Otakar; Pfeiffer, Manuela

2014-05-01

The vast amount of information and data necessary for comprehensive hazard and risk assessment presents many challenges regarding the lack of accessibility, comparability, quality, organisation and dissemination of natural hazards spatial data. In order to mitigate these limitations an interoperable framework has been developed in the framework of the development of legally binding Implementing rules of the EU INSPIRE Directive1* aiming at the establishment of the European Spatial Data Infrastructure. The interoperability framework is described in the Data Specification on Natural risk zones - Technical Guidelines (DS) document2* that was finalized and published on 10.12. 2013. This framework provides means for facilitating access, integration, harmonisation and dissemination of natural hazard data from different domains and sources. The objective of this paper is twofold. Firstly, the paper demonstrates the applicability of the interoperable framework developed in the DS and highlights the key aspects of the interoperability to the various natural hazards communities. Secondly, the paper "translates" into common language the main features and potentiality of the interoperable framework of the DS for a wider audience of scientists and practitioners in the natural hazards domain. Further in this paper the main five aspects of the interoperable framework will be presented. First, the issue of a common terminology for the natural hazards domain will be addressed. A common data model to facilitate cross domain data integration will follow secondly. Thirdly, the common methodology developed to provide qualitative or quantitative assessments of natural hazards will be presented. Fourthly, the extensible classification schema for natural hazards developed from a literature review and key reference documents from the contributing community of practice will be shown. Finally, the applicability of the interoperable framework for the various stakeholder groups will be also presented. This paper closes discussing open issues and next steps regarding the sustainability and evolution of the interoperable framework and missing aspects such as multi-hazard and multi-risk. --------------- 1*INSPIRE - Infrastructure for spatial information in Europe, http://inspire.ec.europa.eu 2*http://inspire.jrc.ec.europa.eu/documents/Data_Specifications/INSPIRE_DataSpecification_NZ_v3.0.pdf

Evaluation of a hepatitis C clinical care coordination programme's effect on treatment initiation and cure: A surveillance-based propensity score matching approach.

PubMed

Deming, R; Ford, M M; Moore, M S; Lim, S; Perumalswami, P; Weiss, J; Wyatt, B; Shukla, S; Litwin, A; Reynoso, S; Laraque, F

2018-05-14

Hepatitis C (HCV) is a viral infection that if left untreated can severely damage the liver. Project INSPIRE was a 3 year HCV care coordination programme in New York City (NYC) that aimed to address barriers to treatment initiation and cure by providing patients with supportive services and health promotion. We examined whether enrolment in Project INSPIRE was associated with differences in HCV treatment and cure compared with a demographically similar group not enrolled in the programme. INSPIRE participants in 2015 were matched with a cohort of HCV-infected persons identified in the NYC surveillance registry, using full optimal matching on propensity scores and stratified by INSPIRE enrolment status. Conditional logistic regression was used to assess group differences in the two treatment outcomes. Two follow-up sensitivity analyses using individual pair-matched sets and the full unadjusted cohort were also conducted. Treatment was initiated by 72% (790/1130) of INSPIRE participants and 36% (11 960/32 819) of study-eligible controls. Among initiators, 65% (514/790) of INSPIRE participants compared with 47% (5641/11 960) of controls achieved cure. In the matched analysis, enrolment in INSPIRE increased the odds of treatment initiation (OR: 5.25, 95% CI: 4.47-6.17) and cure (OR: 2.52, 95% CI: 2.00-3.16). Results from the sensitivity analyses showed agreement with the results from the full optimal match. Participation in the HCV care coordination programme significantly increased the probability of treatment initiation and cure, demonstrating that care coordination for HCV-infected individuals improves treatment outcomes. © 2018 John Wiley & Sons Ltd.

Expression, Purification, and Characterization of a Carbohydrate-Active Enzyme: A Research-Inspired Methods Optimization Experiment for the Biochemistry Laboratory

ERIC Educational Resources Information Center

Willbur, Jaime F.; Vail, Justin D.; Mitchell, Lindsey N.; Jakeman, David L.; Timmons, Shannon C.

2016-01-01

The development and implementation of research-inspired, discovery-based experiences into science laboratory curricula is a proven strategy for increasing student engagement and ownership of experiments. In the novel laboratory module described herein, students learn to express, purify, and characterize a carbohydrate-active enzyme using modern…

Combining local search with co-evolution in a remarkably simple way

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

Boettcher, S.; Percus, A.

2000-05-01

The authors explore a new general-purpose heuristic for finding high-quality solutions to hard optimization problem. The method, called extremal optimization, is inspired by self-organized criticality, a concept introduced to describe emergent complexity in physical systems. In contrast to genetic algorithms, which operate on an entire gene-pool of possible solutions, extremal optimization successively replaces extremely undesirable elements of a single sub-optimal solution with new, random ones. Large fluctuations, or avalanches, ensue that efficiently explore many local optima. Drawing upon models used to simulate far-from-equilibrium dynamics, extremal optimization complements heuristics inspired by equilibrium statistical physics, such as simulated annealing. With only onemore » adjustable parameter, its performance has proved competitive with more elaborate methods, especially near phase transitions. Phase transitions are found in many combinatorial optimization problems, and have been conjectured to occur in the region of parameter space containing the hardest instances. We demonstrate how extremal optimization can be implemented for a variety of hard optimization problems. We believe that this will be a useful tool in the investigation of phase transitions in combinatorial optimization, thereby helping to elucidate the origin of computational complexity.« less

The application of artificial intelligence in the optimal design of mechanical systems

NASA Astrophysics Data System (ADS)

Poteralski, A.; Szczepanik, M.

2016-11-01

The paper is devoted to new computational techniques in mechanical optimization where one tries to study, model, analyze and optimize very complex phenomena, for which more precise scientific tools of the past were incapable of giving low cost and complete solution. Soft computing methods differ from conventional (hard) computing in that, unlike hard computing, they are tolerant of imprecision, uncertainty, partial truth and approximation. The paper deals with an application of the bio-inspired methods, like the evolutionary algorithms (EA), the artificial immune systems (AIS) and the particle swarm optimizers (PSO) to optimization problems. Structures considered in this work are analyzed by the finite element method (FEM), the boundary element method (BEM) and by the method of fundamental solutions (MFS). The bio-inspired methods are applied to optimize shape, topology and material properties of 2D, 3D and coupled 2D/3D structures, to optimize the termomechanical structures, to optimize parameters of composites structures modeled by the FEM, to optimize the elastic vibrating systems to identify the material constants for piezoelectric materials modeled by the BEM and to identify parameters in acoustics problem modeled by the MFS.

Designing Industrial Networks Using Ecological Food Web Metrics.

PubMed

Layton, Astrid; Bras, Bert; Weissburg, Marc

2016-10-18

Biologically Inspired Design (biomimicry) and Industrial Ecology both look to natural systems to enhance the sustainability and performance of engineered products, systems and industries. Bioinspired design (BID) traditionally has focused on a unit operation and single product level. In contrast, this paper describes how principles of network organization derived from analysis of ecosystem properties can be applied to industrial system networks. Specifically, this paper examines the applicability of particular food web matrix properties as design rules for economically and biologically sustainable industrial networks, using an optimization model developed for a carpet recycling network. Carpet recycling network designs based on traditional cost and emissions based optimization are compared to designs obtained using optimizations based solely on ecological food web metrics. The analysis suggests that networks optimized using food web metrics also were superior from a traditional cost and emissions perspective; correlations between optimization using ecological metrics and traditional optimization ranged generally from 0.70 to 0.96, with flow-based metrics being superior to structural parameters. Four structural food parameters provided correlations nearly the same as that obtained using all structural parameters, but individual structural parameters provided much less satisfactory correlations. The analysis indicates that bioinspired design principles from ecosystems can lead to both environmentally and economically sustainable industrial resource networks, and represent guidelines for designing sustainable industry networks.

Particle swarm optimization and gravitational wave data analysis: Performance on a binary inspiral testbed

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

Wang Yan; Mohanty, Soumya D.; Center for Gravitational Wave Astronomy, Department of Physics and Astronomy, University of Texas at Brownsville, 80 Fort Brown, Brownsville, Texas 78520

2010-03-15

The detection and estimation of gravitational wave signals belonging to a parameterized family of waveforms requires, in general, the numerical maximization of a data-dependent function of the signal parameters. Because of noise in the data, the function to be maximized is often highly multimodal with numerous local maxima. Searching for the global maximum then becomes computationally expensive, which in turn can limit the scientific scope of the search. Stochastic optimization is one possible approach to reducing computational costs in such applications. We report results from a first investigation of the particle swarm optimization method in this context. The method ismore » applied to a test bed motivated by the problem of detection and estimation of a binary inspiral signal. Our results show that particle swarm optimization works well in the presence of high multimodality, making it a viable candidate method for further applications in gravitational wave data analysis.« less

Different methodologies for sustainability of optimization techniques used in submerged and solid state fermentation.

PubMed

Ashok, Anup; Kumar, Devarai Santhosh

2017-10-01

Optimization techniques are considered as a part of nature's way of adjusting to the changes happening around it. There are different factors that establish the optimum working condition or the production of any value-added product. A model is accepted for a particular process after its sustainability has been verified on a statistical and analytical level. Optimization techniques can be divided into categories as statistical, nature inspired and artificial neural network each with its own benefits and usage in particular cases. A brief introduction about subcategories of different techniques that are available and their computational effectivity will be discussed. The main focus of the study revolves around the applicability of these techniques to any particular operation such as submerged fermentation (SmF) and solid state fermentation (SSF), their ability to produce secondary metabolites and the usefulness in the laboratory and industrial level. Primary studies to determine the enzyme activity of different microorganisms such as bacteria, fungi and yeast will also be discussed. l-Asparaginase, the most commonly used drugs in the treatment of acute lymphoblastic leukemia (ALL) shall be considered as an example, a short discussion on models used in the production by the processes of SmF and SSF will be discussed to understand the optimization techniques that are being dealt. It is expected that this discussion would help in determining the proper technique that can be used in running any optimization process for different purposes, and would help in making these processes less time-consuming with better output.

Genetic learning in rule-based and neural systems

NASA Technical Reports Server (NTRS)

Smith, Robert E.

1993-01-01

The design of neural networks and fuzzy systems can involve complex, nonlinear, and ill-conditioned optimization problems. Often, traditional optimization schemes are inadequate or inapplicable for such tasks. Genetic Algorithms (GA's) are a class of optimization procedures whose mechanics are based on those of natural genetics. Mathematical arguments show how GAs bring substantial computational leverage to search problems, without requiring the mathematical characteristics often necessary for traditional optimization schemes (e.g., modality, continuity, availability of derivative information, etc.). GA's have proven effective in a variety of search tasks that arise in neural networks and fuzzy systems. This presentation begins by introducing the mechanism and theoretical underpinnings of GA's. GA's are then related to a class of rule-based machine learning systems called learning classifier systems (LCS's). An LCS implements a low-level production-system that uses a GA as its primary rule discovery mechanism. This presentation illustrates how, despite its rule-based framework, an LCS can be thought of as a competitive neural network. Neural network simulator code for an LCS is presented. In this context, the GA is doing more than optimizing and objective function. It is searching for an ecology of hidden nodes with limited connectivity. The GA attempts to evolve this ecology such that effective neural network performance results. The GA is particularly well adapted to this task, given its naturally-inspired basis. The LCS/neural network analogy extends itself to other, more traditional neural networks. Conclusions to the presentation discuss the implications of using GA's in ecological search problems that arise in neural and fuzzy systems.

A Review on Development and Applications of Bio-Inspired Superhydrophobic Textiles

PubMed Central

Ahmad, Ishaq; Kan, Chi-wai

2016-01-01

Bio-inspired engineering has been envisioned in a wide array of applications. All living bodies on Earth, including animals and plants, have well organized functional systems developed by nature. These naturally designed functional systems inspire scientists and engineers worldwide to mimic the system for practical applications by human beings. Researchers in the academic world and industries have been trying, for hundreds of years, to demonstrate how these natural phenomena could be translated into the real world to save lives, money and time. One of the most fascinating natural phenomena is the resistance of living bodies to contamination by dust and other pollutants, thus termed as self-cleaning phenomenon. This phenomenon has been observed in many plants, animals and insects and is termed as the Lotus Effect. With advancement in research and technology, attention has been given to the exploration of the underlying mechanisms of water repellency and self-cleaning. As a result, various concepts have been developed including Young’s equation, and Wenzel and Cassie–Baxter theories. The more we unravel this process, the more we get access to its implications and applications. A similar pursuit is emphasized in this review to explain the fundamental principles, mechanisms, past experimental approaches and ongoing research in the development of bio-inspired superhydrophobic textiles. PMID:28774012

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.

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

Sum-of-squares-based fuzzy controller design using quantum-inspired evolutionary algorithm

NASA Astrophysics Data System (ADS)

Yu, Gwo-Ruey; Huang, Yu-Chia; Cheng, Chih-Yung

2016-07-01

In the field of fuzzy control, control gains are obtained by solving stabilisation conditions in linear-matrix-inequality-based Takagi-Sugeno fuzzy control method and sum-of-squares-based polynomial fuzzy control method. However, the optimal performance requirements are not considered under those stabilisation conditions. In order to handle specific performance problems, this paper proposes a novel design procedure with regard to polynomial fuzzy controllers using quantum-inspired evolutionary algorithms. The first contribution of this paper is a combination of polynomial fuzzy control and quantum-inspired evolutionary algorithms to undertake an optimal performance controller design. The second contribution is the proposed stability condition derived from the polynomial Lyapunov function. The proposed design approach is dissimilar to the traditional approach, in which control gains are obtained by solving the stabilisation conditions. The first step of the controller design uses the quantum-inspired evolutionary algorithms to determine the control gains with the best performance. Then, the stability of the closed-loop system is analysed under the proposed stability conditions. To illustrate effectiveness and validity, the problem of balancing and the up-swing of an inverted pendulum on a cart is used.

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

Martino, Mikaël M.; Briquez, Priscilla S.; Maruyama, Kenta

Growth factors are very promising molecules to enhance bone regeneration. However, their translation to clinical use has been seriously limited, facing issues related to safety and cost-effectiveness. These problems derive from the vastly supra-physiological doses of growth factor used without optimized delivery systems. Therefore, these issues have motivated the development of new delivery systems allowing better control of the spatio-temporal release and signaling of growth factors. Because the extracellular matrix (ECM) naturally plays a fundamental role in coordinating growth factor activity in vivo, a number of novel delivery systems have been inspired by the growth factor regulatory function of themore » ECM. After introducing the role of growth factors during the bone regeneration process, this review exposes different issues that growth factor-based therapies have encountered in the clinic and highlights recent delivery approaches based on the natural interaction between growth factor and the ECM.« less

Differential Cloud Particles Evolution Algorithm Based on Data-Driven Mechanism for Applications of ANN

PubMed Central

2017-01-01

Computational scientists have designed many useful algorithms by exploring a biological process or imitating natural evolution. These algorithms can be used to solve engineering optimization problems. Inspired by the change of matter state, we proposed a novel optimization algorithm called differential cloud particles evolution algorithm based on data-driven mechanism (CPDD). In the proposed algorithm, the optimization process is divided into two stages, namely, fluid stage and solid stage. The algorithm carries out the strategy of integrating global exploration with local exploitation in fluid stage. Furthermore, local exploitation is carried out mainly in solid stage. The quality of the solution and the efficiency of the search are influenced greatly by the control parameters. Therefore, the data-driven mechanism is designed for obtaining better control parameters to ensure good performance on numerical benchmark problems. In order to verify the effectiveness of CPDD, numerical experiments are carried out on all the CEC2014 contest benchmark functions. Finally, two application problems of artificial neural network are examined. The experimental results show that CPDD is competitive with respect to other eight state-of-the-art intelligent optimization algorithms. PMID:28761438

An Efficient Optimization Method for Solving Unsupervised Data Classification Problems.

PubMed

Shabanzadeh, Parvaneh; Yusof, Rubiyah

2015-01-01

Unsupervised data classification (or clustering) analysis is one of the most useful tools and a descriptive task in data mining that seeks to classify homogeneous groups of objects based on similarity and is used in many medical disciplines and various applications. In general, there is no single algorithm that is suitable for all types of data, conditions, and applications. Each algorithm has its own advantages, limitations, and deficiencies. Hence, research for novel and effective approaches for unsupervised data classification is still active. In this paper a heuristic algorithm, Biogeography-Based Optimization (BBO) algorithm, was adapted for data clustering problems by modifying the main operators of BBO algorithm, which is inspired from the natural biogeography distribution of different species. Similar to other population-based algorithms, BBO algorithm starts with an initial population of candidate solutions to an optimization problem and an objective function that is calculated for them. To evaluate the performance of the proposed algorithm assessment was carried on six medical and real life datasets and was compared with eight well known and recent unsupervised data classification algorithms. Numerical results demonstrate that the proposed evolutionary optimization algorithm is efficient for unsupervised data classification.

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.

Symbiosis-Based Alternative Learning Multi-Swarm Particle Swarm Optimization.

PubMed

Niu, Ben; Huang, Huali; Tan, Lijing; Duan, Qiqi

2017-01-01

Inspired by the ideas from the mutual cooperation of symbiosis in natural ecosystem, this paper proposes a new variant of PSO, named Symbiosis-based Alternative Learning Multi-swarm Particle Swarm Optimization (SALMPSO). A learning probability to select one exemplar out of the center positions, the local best position, and the historical best position including the experience of internal and external multiple swarms, is used to keep the diversity of the population. Two different levels of social interaction within and between multiple swarms are proposed. In the search process, particles not only exchange social experience with others that are from their own sub-swarms, but also are influenced by the experience of particles from other fellow sub-swarms. According to the different exemplars and learning strategy, this model is instantiated as four variants of SALMPSO and a set of 15 test functions are conducted to compare with some variants of PSO including 10, 30 and 50 dimensions, respectively. Experimental results demonstrate that the alternative learning strategy in each SALMPSO version can exhibit better performance in terms of the convergence speed and optimal values on most multimodal functions in our simulation.

Harmony search algorithm: application to the redundancy optimization problem

NASA Astrophysics Data System (ADS)

Nahas, Nabil; Thien-My, Dao

2010-09-01

The redundancy optimization problem is a well known NP-hard problem which involves the selection of elements and redundancy levels to maximize system performance, given different system-level constraints. This article presents an efficient algorithm based on the harmony search algorithm (HSA) to solve this optimization problem. The HSA is a new nature-inspired algorithm which mimics the improvization process of music players. Two kinds of problems are considered in testing the proposed algorithm, with the first limited to the binary series-parallel system, where the problem consists of a selection of elements and redundancy levels used to maximize the system reliability given various system-level constraints; the second problem for its part concerns the multi-state series-parallel systems with performance levels ranging from perfect operation to complete failure, and in which identical redundant elements are included in order to achieve a desirable level of availability. Numerical results for test problems from previous research are reported and compared. The results of HSA showed that this algorithm could provide very good solutions when compared to those obtained through other approaches.

Lifting scheme-based method for joint coding 3D stereo digital cinema with luminace correction and optimized prediction

NASA Astrophysics Data System (ADS)

Darazi, R.; Gouze, A.; Macq, B.

2009-01-01

Reproducing a natural and real scene as we see in the real world everyday is becoming more and more popular. Stereoscopic and multi-view techniques are used for this end. However due to the fact that more information are displayed requires supporting technologies such as digital compression to ensure the storage and transmission of the sequences. In this paper, a new scheme for stereo image coding is proposed. The original left and right images are jointly coded. The main idea is to optimally exploit the existing correlation between the two images. This is done by the design of an efficient transform that reduces the existing redundancy in the stereo image pair. This approach was inspired by Lifting Scheme (LS). The novelty in our work is that the prediction step is been replaced by an hybrid step that consists in disparity compensation followed by luminance correction and an optimized prediction step. The proposed scheme can be used for lossless and for lossy coding. Experimental results show improvement in terms of performance and complexity compared to recently proposed methods.

An improved marriage in honey bees optimization algorithm for single objective unconstrained optimization.

PubMed

Celik, Yuksel; Ulker, Erkan

2013-01-01

Marriage in honey bees optimization (MBO) is a metaheuristic optimization algorithm developed by inspiration of the mating and fertilization process of honey bees and is a kind of swarm intelligence optimizations. In this study we propose improved marriage in honey bees optimization (IMBO) by adding Levy flight algorithm for queen mating flight and neighboring for worker drone improving. The IMBO algorithm's performance and its success are tested on the well-known six unconstrained test functions and compared with other metaheuristic optimization algorithms.

Optimal design of a smart post-buckled beam actuator using bat algorithm: simulations and experiments

NASA Astrophysics Data System (ADS)

Mallick, Rajnish; Ganguli, Ranjan; Kumar, Ravi

2017-05-01

The optimized design of a smart post-buckled beam actuator (PBA) is performed in this study. A smart material based piezoceramic stack actuator is used as a prime-mover to drive the buckled beam actuator. Piezoceramic actuators are high force, small displacement devices; they possess high energy density and have high bandwidth. In this study, bench top experiments are conducted to investigate the angular tip deflections due to the PBA. A new design of a linear-to-linear motion amplification device (LX-4) is developed to circumvent the small displacement handicap of piezoceramic stack actuators. LX-4 enhances the piezoceramic actuator mechanical leverage by a factor of four. The PBA model is based on dynamic elastic stability and is analyzed using the Mathieu-Hill equation. A formal optimization is carried out using a newly developed meta-heuristic nature inspired algorithm, named as the bat algorithm (BA). The BA utilizes the echolocation capability of bats. An optimized PBA in conjunction with LX-4 generates end rotations of the order of 15° at the output end. The optimized PBA design incurs less weight and induces large end rotations, which will be useful in development of various mechanical and aerospace devices, such as helicopter trailing edge flaps, micro and nano aerial vehicles and other robotic systems.

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.).

Solving mixed integer nonlinear programming problems using spiral dynamics optimization algorithm

NASA Astrophysics Data System (ADS)

Kania, Adhe; Sidarto, Kuntjoro Adji

2016-02-01

Many engineering and practical problem can be modeled by mixed integer nonlinear programming. This paper proposes to solve the problem with modified spiral dynamics inspired optimization method of Tamura and Yasuda. Four test cases have been examined, including problem in engineering and sport. This method succeeds in obtaining the optimal result in all test cases.

Biomimetic microstructures for photonic and fluidic synergies

NASA Astrophysics Data System (ADS)

Vasileiou, Maria; Mpatzaka, Theodora; Alexandropoulos, Dimitris; Vainos, Nikolaos A.

2017-08-01

Nature-inspired micro- and nano-structures offer a unique platform for the development of novel synergetic systems combining photonic and microfluidic functionalities. In this context, we examine the paradigm of butterfly Vanessa cardui and develop artificial diffractive microstructures inspired by its natural designs. Softlithographic and nanoimprint protocols are developed to replicate surfaces of natural specimens. Further to their optical behavior, interphases tailored by such microstructures exhibit enhanced hydrophobic properties, as compared to their planar counterparts made of the same materials. Such synergies exploited by new design approaches pave the way to prospective optofluidic, lab-on-chip and sensing applications.

Using natural products for drug discovery: the impact of the genomics era.

PubMed

Zhang, Mingzi M; Qiao, Yuan; Ang, Ee Lui; Zhao, Huimin

2017-05-01

Evolutionarily selected over billions of years for their interactions with biomolecules, natural products have been and continue to be a major source of pharmaceuticals. In the 1990s, pharmaceutical companies scaled down their natural product discovery programs in favor of synthetic chemical libraries due to major challenges such as high rediscovery rates, challenging isolation, and low production titers. Propelled by advances in DNA sequencing and synthetic biology technologies, insights into microbial secondary metabolism provided have inspired a number of strategies to address these challenges. Areas covered: This review highlights the importance of genomics and metagenomics in natural product discovery, and provides an overview of the technical and conceptual advances that offer unprecedented access to molecules encoded by biosynthetic gene clusters. Expert opinion: Genomics and metagenomics revealed nature's remarkable biosynthetic potential and her vast chemical inventory that we can now prioritize and systematically mine for novel chemical scaffolds with desirable bioactivities. Coupled with synthetic biology and genome engineering technologies, significant progress has been made in identifying and predicting the chemical output of biosynthetic gene clusters, as well as in optimizing cluster expression in native and heterologous host systems for the production of pharmaceutically relevant metabolites and their derivatives.

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.

Nature inspires sensors to do more with less.

PubMed

Mulvaney, Shawn P; Sheehan, Paul E

2014-10-28

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

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

PubMed

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

2014-09-01

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

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.

Optimal Control of Inspired Perfluorocarbon Temperature for Ultrafast Hypothermia Induction by Total Liquid Ventilation in an Adult Patient Model.

PubMed

Nadeau, Mathieu; Sage, Michael; Kohlhauer, Matthias; Mousseau, Julien; Vandamme, Jonathan; Fortin-Pellerin, Etienne; Praud, Jean-Paul; Tissier, Renaud; Walti, Herve; Micheau, Philippe

2017-12-01

Recent preclinical studies have shown that therapeutic hypothermia induced in less than 30 min by total liquid ventilation (TLV) strongly improves the survival rate after cardiac arrest. When the lung is ventilated with a breathable perfluorocarbon liquid, the inspired perfluorocarbon allows us to control efficiently the cooling process of the organs. While TLV can rapidly cool animals, the cooling speed in humans remains unknown. The objective is to predict the efficiency and safety of ultrafast cooling by TLV in adult humans. It is based on a previously published thermal model of ovines in TLV and the design of a direct optimal controller to compute the inspired perfluorocarbon temperature profile. The experimental results in an adult sheep are presented. The thermal model of sheep is subsequently projected to a human model to simulate the optimal hypothermia induction and its sensitivity to physiological parameter uncertainties. The results in the sheep showed that the computed inspired perfluorocarbon temperature command can avoid arterial temperature undershoot. The projection to humans revealed that mild hypothermia should be ultrafast (reached in fewer than 3 min (-72 °C/h) for the brain and 20 min (-10 °C/h) for the entire body). The projection to human model allows concluding that therapeutic hypothermia induction by TLV can be ultrafast and safe. This study is the first to simulate ultrafast cooling by TLV in a human model and is a strong motivation to translate TLV to humans to improve the quality of life of postcardiac arrest patients.

Modified Backtracking Search Optimization Algorithm Inspired by Simulated Annealing for Constrained Engineering Optimization Problems

PubMed Central

Wang, Hailong; Sun, Yuqiu; Su, Qinghua; Xia, Xuewen

2018-01-01

The backtracking search optimization algorithm (BSA) is a population-based evolutionary algorithm for numerical optimization problems. BSA has a powerful global exploration capacity while its local exploitation capability is relatively poor. This affects the convergence speed of the algorithm. In this paper, we propose a modified BSA inspired by simulated annealing (BSAISA) to overcome the deficiency of BSA. In the BSAISA, the amplitude control factor (F) is modified based on the Metropolis criterion in simulated annealing. The redesigned F could be adaptively decreased as the number of iterations increases and it does not introduce extra parameters. A self-adaptive ε-constrained method is used to handle the strict constraints. We compared the performance of the proposed BSAISA with BSA and other well-known algorithms when solving thirteen constrained benchmarks and five engineering design problems. The simulation results demonstrated that BSAISA is more effective than BSA and more competitive with other well-known algorithms in terms of convergence speed. PMID:29666635

The effects of uncinectomy and natural ostial dilatation on maxillary sinus ventilation: a clinical experimental study.

PubMed

Kutluhan, Ahmet; Şalvız, Mehti; Bozdemir, Kazım; Kanbak, Orhan; Ulu, Mustafa; Yalçıner, Gökhan; Bilgen, Akif Sinan

2011-04-01

The purpose of this study was to determine the effect of uncinectomy without sinusotomy and natural ostial dilatation on maxillary sinus ventilation in chronic rhinosinusitis. Twenty patients with chronic rhinosinusitis were included in this study. The patients were randomly divided into two groups. Group 1 consisted of patients with uncinectomy (n = 10), while group 2 was made up of patients treated with natural ostial dilatation (n = 10). The CO(2) tension and pressure levels of the maxillary sinus during inspiration and expiration phases were obtained and compared before and after the procedures within and between the groups. The mean CO(2) tension levels in both groups were significantly decreased after the procedures. The mean maxillary sinus pressure during inspiration was significantly decreased to a negative value after uncinectomy; however, no significant change was observed during expiration. There were no significant changes in maxillary sinus pressures after natural ostial dilatation procedure. Both uncinectomy and natural ostial dilatation seem to be equally effective in decreasing maxillary sinus pCO(2) levels. The effects of decreased maxillary sinus pressure during inspiration after uncinectomy on mucociliary clearance and development mechanisms of chronic rhinosinusitis seem to be worth investigating.

Innovation Inspired by Nature: Capabilities, Potentials and Challenges

NASA Technical Reports Server (NTRS)

Bar-Cohen, Yoseph

2012-01-01

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

Holarchical Systems and Emotional Holons : Biologically-Inspired System Designs for Control of Autonomous Aerial Vehicles

NASA Technical Reports Server (NTRS)

Ippolito, Corey; Plice, Laura; Pisanich, Greg

2003-01-01

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

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.

Characterization of anthocyanin based dye-sensitized organic solar cells (DSSC) and modifications based on bio-inspired ion mobility improvements

NASA Astrophysics Data System (ADS)

Mawyin, Jose Amador

The worldwide electrical energy consumption will increase from currently 10 terawatts to 30 terawatts by 2050. To decrease the current atmospheric CO2 would require our civilization to develop a 20 terawatts non-greenhouse emitting (renewable) electrical power generation capability. Solar photovoltaic electric power generation is thought to be a major component of proposed renewable energy-based economy. One approach to less costly, easily manufactured solar cells is the Dye-sensitized solar cells (DSSC) introduced by Greatzel and others. This dissertation describes the work focused on improving the performance of DSSC type solar cells. In particular parameters affecting dye-sensitized solar cells (DSSC) based on anthocyanin pigments extracted from California blackberries (Rubus ursinus) and bio-inspired modifications were analyzed and solar cell designs optimized. Using off-the-shelf materials DSSC were constructed and tested using a custom made solar spectrum simulator and photoelectric property characterization. This equipment facilitated the taking of automated I-V curve plots and the experimental determination of parameters such as open circuit voltage (V OC), short circuit current (JSC), fill factor (FF), etc. This equipment was used to probe the effect of various modifications such as changes in the annealing time and composition of the of the electrode counter-electrode. Solar cell optimization schemes included novel schemes such as solar spectrum manipulation to increase the percentage of the solar spectrum capable of generating power in the DSSC. Solar manipulation included light scattering and photon upconversion. Techniques examined here focused on affordable materials such as silica nanoparticles embedded inside a TiO2 matrix. Such materials were examined for controlled scattering of visible light and optimize light trapping within the matrix as well as a means to achieve photon up-energy-conversion using the Raman effect in silica nano-particles (due to a strong Raman anti-Stoke scattering probability). Finally, solutions to the mobility problem of organic photovoltaics were explored. The solutions examined here were based on the bio-inspired neural ionic conduction were nature has overcome the poor ionic mobility in solutions (D ˜ 10-5cm2/ s) to achieve amazingly fast ionic conduction using non-electric field energy gradients. Electric-permeability-graded layers with possibility to create an energy gradient that helps the diffusion DSSC electrolyte diffusion were explored in this work.

Surfacing Authentic Leadership: Inspiration from "After Life"

ERIC Educational Resources Information Center

Billsberry, Jon; North-Samardzic, Andrea

2016-01-01

This paper advocates an innovative approach to help leadership students analyze, capture, and remember the nature of their authentic leadership. This developmental activity was inspired by the Japanese film, "Wandâfuru raifu" ("After Life") (Kore-Eda, Sato, & Shigenobu, 1998), in which the recently deceased are asked to…

Biophysical analysis of water filtration phenomenon in the roots of halophytes

NASA Astrophysics Data System (ADS)

Kim, Kiwoong; Lee, Sang Joon

2015-11-01

The water management systems of plants, such as water collection and water filtration have been optimized through a long history. In this point of view, new bio-inspired technologies can be developed by mimicking the nature's strategies for the survival of the fittest. In this study, the biophysical characteristics of water filtration process in the roots of halophytes are experimentally investigated in the plant hydrodynamic point of view. To understand the functional features of the halophytes 3D morphological structure of their roots are analyzed using advanced bioimaging techniques. The surface properties of the roots of halophytes are also examined Based on the quantitatively analyzed information, water filtration phenomenon in the roots is examined. Sodium treated mangroves are soaked in sodium acting fluorescent dye solution to trace sodium ions in the roots. In addition, in vitroexperiment is carried out by using the roots. As a result, the outermost layer of the roots filters out continuously most of sodium ions. This study on developing halophytes would be helpful for understanding the water filtration mechanism of the roots of halophytes and developing a new bio inspired desalination system. This research was financially supported by the National Research Foundation (NRF) of Korea (Contract grant number: 2008-0061991).

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

NASA Astrophysics Data System (ADS)

Giorgio-Serchi, Francesco; Weymouth, Gabriel

2017-11-01

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

An Improved Marriage in Honey Bees Optimization Algorithm for Single Objective Unconstrained Optimization

PubMed Central

Celik, Yuksel; Ulker, Erkan

2013-01-01

Marriage in honey bees optimization (MBO) is a metaheuristic optimization algorithm developed by inspiration of the mating and fertilization process of honey bees and is a kind of swarm intelligence optimizations. In this study we propose improved marriage in honey bees optimization (IMBO) by adding Levy flight algorithm for queen mating flight and neighboring for worker drone improving. The IMBO algorithm's performance and its success are tested on the well-known six unconstrained test functions and compared with other metaheuristic optimization algorithms. PMID:23935416

Network Community Detection based on the Physarum-inspired Computational Framework.

PubMed

Gao, Chao; Liang, Mingxin; Li, Xianghua; Zhang, Zili; Wang, Zhen; Zhou, Zhili

2016-12-13

Community detection is a crucial and essential problem in the structure analytics of complex networks, which can help us understand and predict the characteristics and functions of complex networks. Many methods, ranging from the optimization-based algorithms to the heuristic-based algorithms, have been proposed for solving such a problem. Due to the inherent complexity of identifying network structure, how to design an effective algorithm with a higher accuracy and a lower computational cost still remains an open problem. Inspired by the computational capability and positive feedback mechanism in the wake of foraging process of Physarum, which is a large amoeba-like cell consisting of a dendritic network of tube-like pseudopodia, a general Physarum-based computational framework for community detection is proposed in this paper. Based on the proposed framework, the inter-community edges can be identified from the intra-community edges in a network and the positive feedback of solving process in an algorithm can be further enhanced, which are used to improve the efficiency of original optimization-based and heuristic-based community detection algorithms, respectively. Some typical algorithms (e.g., genetic algorithm, ant colony optimization algorithm, and Markov clustering algorithm) and real-world datasets have been used to estimate the efficiency of our proposed computational framework. Experiments show that the algorithms optimized by Physarum-inspired computational framework perform better than the original ones, in terms of accuracy and computational cost. Moreover, a computational complexity analysis verifies the scalability of our framework.

ABCluster: the artificial bee colony algorithm for cluster global optimization.

PubMed

Zhang, Jun; Dolg, Michael

2015-10-07

Global optimization of cluster geometries is of fundamental importance in chemistry and an interesting problem in applied mathematics. In this work, we introduce a relatively new swarm intelligence algorithm, i.e. the artificial bee colony (ABC) algorithm proposed in 2005, to this field. It is inspired by the foraging behavior of a bee colony, and only three parameters are needed to control it. We applied it to several potential functions of quite different nature, i.e., the Coulomb-Born-Mayer, Lennard-Jones, Morse, Z and Gupta potentials. The benchmarks reveal that for long-ranged potentials the ABC algorithm is very efficient in locating the global minimum, while for short-ranged ones it is sometimes trapped into a local minimum funnel on a potential energy surface of large clusters. We have released an efficient, user-friendly, and free program "ABCluster" to realize the ABC algorithm. It is a black-box program for non-experts as well as experts and might become a useful tool for chemists to study clusters.

Global Optimization of Interplanetary Trajectories in the Presence of Realistic Mission Constraints

NASA Technical Reports Server (NTRS)

Hinckley, David; Englander, Jacob; Hitt, Darren

2015-01-01

Single trial evaluations Trial creation by Phase-wise GA-style or DE-inspired recombination Bin repository structure requires an initialization period Non-exclusionary Kill Distance Population collapse mechanic Main loop Creation Probabilistic switch between GA and DE creation types Locally optimize Submit to repository Repeat.

Structure and mechanical properties of naturally occurring lightweight foam-filled cylinder--the peacock's tail coverts shaft and its components.

PubMed

Liu, Z Q; Jiao, D; Meyers, M A; Zhang, Z F

2015-04-01

Feather shaft, which is primarily featured by a cylinder filled with foam, possesses a unique combination of mechanical robustness and flexibility with a low density through natural evolution and selection. Here the hierarchical structures of peacock's tail coverts shaft and its components are systematically characterized from millimeter to nanometer length scales. The variations in constituent and geometry along the length are examined. The mechanical properties under both dry and wet conditions are investigated. The deformation and failure behaviors and involved strengthening, stiffening and toughening mechanisms are analyzed qualitatively and quantitatively and correlated to the structures. It is revealed that the properties of feather shaft and its components have been optimized through various structural adaptations. Synergetic strengthening and stiffening effects can be achieved in overall rachis owing to increased failure resistance. This study is expected to aid in deeper understandings on the ingenious structure-property design strategies developed by nature, and accordingly, provide useful inspiration for the development of high-performance synthetic foams and foam-filled materials. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Biologically Inspired, Anisoptropic Flexible Wing for Optimal Flapping Flight

DTIC Science & Technology

2013-01-31

Anisotropic Flexible Wing for Optimal Flapping Flight FA9550-07-1-0547 Sb. GRANT NUMBER Sc. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Sd. PROJECT NUMBER...anisotropic structural flexibility ; c) Conducted coordinated experimental and computational modeling to determine the roles of aerodynamic loading, wing inertia...and structural flexibility and elasticity; and d) Developed surrogate tools for flapping wing MA V design and optimization. Detailed research

Using natural products for drug discovery: the impact of the genomics era

PubMed Central

Zhang, Mingzi M; Qiao, Yuan; Ang, Ee Lui; Zhao, Huimin

2017-01-01

Introduction Evolutionarily selected over billions of years for their interactions with biomolecules, natural products have been and continue to be a major source of pharmaceuticals. In the 1990s, pharmaceutical companies scaled down their natural product discovery programs in favor of synthetic chemical libraries due to major challenges such as high rediscovery rates, challenging isolation, and low production titers. Propelled by advances in DNA sequencing and synthetic biology technologies, insights into microbial secondary metabolism provided have inspired a number of strategies to address these challenges. Areas covered This review highlights the importance of genomics and metagenomics in natural product discovery, and provides an overview of the technical and conceptual advances that offer unprecedented access to molecules encoded by biosynthetic gene clusters. Expert opinion Genomics and metagenomics revealed nature’s remarkable biosynthetic potential and her vast chemical inventory that we can now prioritize and systematically mine for novel chemical scaffolds with desirable bioactivities. Coupled with synthetic biology and genome engineering technologies, significant progress has been made in identifying and predicting the chemical output of biosynthetic gene clusters, as well as in optimizing cluster expression in native and heterologous host systems for the production of pharmaceutically relevant metabolites and their derivatives. PMID:28277838

Bioinspired Photonic Pigments from Colloidal Self-Assembly.

PubMed

Goerlitzer, Eric S A; Klupp Taylor, Robin N; Vogel, Nicolas

2018-05-07

The natural world is a colorful environment. Stunning displays of coloration have evolved throughout nature to optimize camouflage, warning, and communication. The resulting flamboyant visual effects and remarkable dynamic properties, often caused by an intricate structural design at the nano- and microscale, continue to inspire scientists to unravel the underlying physics and to recreate the observed effects. Here, the methodologies to create bioinspired photonic pigments using colloidal self-assembly approaches are considered. The physics governing the interaction of light with structural features and natural examples of structural coloration are briefly introduced. It is then outlined how the self-assembly of colloidal particles, acting as wavelength-scale building blocks, can be particularly useful to replicate coloration from nature. Different coloration effects that result from the defined structure of the self-assembled colloids are introduced and it is highlighted how these optical properties can be translated into photonic pigments by modifications of the assembly processes. The importance of absorbing elements, as well as the role of surface chemistry and wettability to control structural coloration is discussed. Finally, approaches to integrate dynamic control of coloration into such self-assembled photonic pigments are outlined. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Non-linear Multidimensional Optimization for use in Wire Scanner Fitting

NASA Astrophysics Data System (ADS)

Henderson, Alyssa; Terzic, Balsa; Hofler, Alicia; Center Advanced Studies of Accelerators Collaboration

2014-03-01

To ensure experiment efficiency and quality from the Continuous Electron Beam Accelerator at Jefferson Lab, beam energy, size, and position must be measured. Wire scanners are devices inserted into the beamline to produce measurements which are used to obtain beam properties. Extracting physical information from the wire scanner measurements begins by fitting Gaussian curves to the data. This study focuses on optimizing and automating this curve-fitting procedure. We use a hybrid approach combining the efficiency of Newton Conjugate Gradient (NCG) method with the global convergence of three nature-inspired (NI) optimization approaches: genetic algorithm, differential evolution, and particle-swarm. In this Python-implemented approach, augmenting the locally-convergent NCG with one of the globally-convergent methods ensures the quality, robustness, and automation of curve-fitting. After comparing the methods, we establish that given an initial data-derived guess, each finds a solution with the same chi-square- a measurement of the agreement of the fit to the data. NCG is the fastest method, so it is the first to attempt data-fitting. The curve-fitting procedure escalates to one of the globally-convergent NI methods only if NCG fails, thereby ensuring a successful fit. This method allows for the most optimal signal fit and can be easily applied to similar problems.

Modelling and Optimization Studies on a Novel Lipase Production by Staphylococcus arlettae through Submerged Fermentation

PubMed Central

Chauhan, Mamta; Chauhan, Rajinder Singh; Garlapati, Vijay Kumar

2013-01-01

Microbial enzymes from extremophilic regions such as hot spring serve as an important source of various stable and valuable industrial enzymes. The present paper encompasses the modeling and optimization approach for production of halophilic, solvent, tolerant, and alkaline lipase from Staphylococcus arlettae through response surface methodology integrated nature inspired genetic algorithm. Response surface model based on central composite design has been developed by considering the individual and interaction effects of fermentation conditions on lipase production through submerged fermentation. The validated input space of response surface model (with R 2 value of 96.6%) has been utilized for optimization through genetic algorithm. An optimum lipase yield of 6.5 U/mL has been obtained using binary coded genetic algorithm predicted conditions of 9.39% inoculum with the oil concentration of 10.285% in 2.99 hrs using pH of 7.32 at 38.8°C. This outcome could contribute to introducing this extremophilic lipase (halophilic, solvent, and tolerant) to industrial biotechnology sector and will be a probable choice for different food, detergent, chemical, and pharmaceutical industries. The present work also demonstrated the feasibility of statistical design tools integration with computational tools for optimization of fermentation conditions for maximum lipase production. PMID:24455210

'Extremotaxis': computing with a bacterial-inspired algorithm.

PubMed

Nicolau, Dan V; Burrage, Kevin; Nicolau, Dan V; Maini, Philip K

2008-01-01

We present a general-purpose optimization algorithm inspired by "run-and-tumble", the biased random walk chemotactic swimming strategy used by the bacterium Escherichia coli to locate regions of high nutrient concentration The method uses particles (corresponding to bacteria) that swim through the variable space (corresponding to the attractant concentration profile). By constantly performing temporal comparisons, the particles drift towards the minimum or maximum of the function of interest. We illustrate the use of our method with four examples. We also present a discrete version of the algorithm. The new algorithm is expected to be useful in combinatorial optimization problems involving many variables, where the functional landscape is apparently stochastic and has local minima, but preserves some derivative structure at intermediate scales.

Bioinspired Functional Surfaces for Technological Applications

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

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

Experimental optimization of wing shape for a hummingbird-like flapping wing micro air vehicle.

PubMed

Nan, Yanghai; Karásek, Matěj; Lalami, Mohamed Esseghir; Preumont, André

2017-03-06

Flapping wing micro air vehicles (MAVs) take inspiration from natural fliers, such as insects and hummingbirds. Existing designs manage to mimic the wing motion of natural fliers to a certain extent; nevertheless, differences will always exist due to completely different building blocks of biological and man-made systems. The same holds true for the design of the wings themselves, as biological and engineering materials differ significantly. This paper presents results of experimental optimization of wing shape of a flexible wing for a hummingbird-sized flapping wing MAV. During the experiments we varied the wing 'slackness' (defined by a camber angle), the wing shape (determined by the aspect and taper ratios) and the surface area. Apart from the generated lift, we also evaluated the overall power efficiency of the flapping wing MAV achieved with the various wing design. The results indicate that especially the camber angle and aspect ratio have a critical impact on the force production and efficiency. The best performance was obtained with a wing of trapezoidal shape with a straight leading edge and an aspect ratio of 9.3, both parameters being very similar to a typical hummingbird wing. Finally, the wing performance was demonstrated by a lift-off of a 17.2 g flapping wing robot.

Optimization of power utilization in multimobile robot foraging behavior inspired by honeybees system.

PubMed

Ahmad, Faisul Arif; Ramli, Abd Rahman; Samsudin, Khairulmizam; Hashim, Shaiful Jahari

2014-01-01

Deploying large numbers of mobile robots which can interact with each other produces swarm intelligent behavior. However, mobile robots are normally running with finite energy resource, supplied from finite battery. The limitation of energy resource required human intervention for recharging the batteries. The sharing information among the mobile robots would be one of the potentials to overcome the limitation on previously recharging system. A new approach is proposed based on integrated intelligent system inspired by foraging of honeybees applied to multimobile robot scenario. This integrated approach caters for both working and foraging stages for known/unknown power station locations. Swarm mobile robot inspired by honeybee is simulated to explore and identify the power station for battery recharging. The mobile robots will share the location information of the power station with each other. The result showed that mobile robots consume less energy and less time when they are cooperating with each other for foraging process. The optimizing of foraging behavior would result in the mobile robots spending more time to do real work.

Optimization of Power Utilization in Multimobile Robot Foraging Behavior Inspired by Honeybees System

PubMed Central

Ahmad, Faisul Arif; Ramli, Abd Rahman; Samsudin, Khairulmizam; Hashim, Shaiful Jahari

2014-01-01

Deploying large numbers of mobile robots which can interact with each other produces swarm intelligent behavior. However, mobile robots are normally running with finite energy resource, supplied from finite battery. The limitation of energy resource required human intervention for recharging the batteries. The sharing information among the mobile robots would be one of the potentials to overcome the limitation on previously recharging system. A new approach is proposed based on integrated intelligent system inspired by foraging of honeybees applied to multimobile robot scenario. This integrated approach caters for both working and foraging stages for known/unknown power station locations. Swarm mobile robot inspired by honeybee is simulated to explore and identify the power station for battery recharging. The mobile robots will share the location information of the power station with each other. The result showed that mobile robots consume less energy and less time when they are cooperating with each other for foraging process. The optimizing of foraging behavior would result in the mobile robots spending more time to do real work. PMID:24949491

Synthesis and characterization of inorganic materials precipitated into polymeric and novel liquid crystalline systems

NASA Astrophysics Data System (ADS)

Lubeck, Christopher Ryan

The use of nanostructured, hybrid materials possesses great future potential. Many examples of nanostructured materials exist within nature, such as animal bone, animal teeth, and seashells. This research, inspired by nature, strove to mimic salient properties of natural materials, utilizing methods observed within nature to produce materials. Further, this research increased the functionality of the templates from "mere" template to functional participant. Different chemical methods to produce hybrid materials were employed within this research to achieve these goals. First, electro-osmosis was utilized to drive ions into a polymeric matrix to form hybrid inorganic polymer material, creating a material inspired by naturally occurring bone or seashell in which the inorganic component provides strength and the polymeric material decreases the brittleness of the combined hybrid material. Second, self-assembled amphiphiles, forming higher ordered structures, acted as a template for inorganic cadmium sulfide. Electronically active molecules based on ethylene oxide and aniline segments were synthesized to create interaction between the templating material and the resulting inorganic cadmium sulfide. The templating process utilized self-assembly to create the inorganic structure through the interaction of the amphiphiles with water. The use of self-assembly is itself inspired by nature. Self-assembled structures are observed within living cells as cell walls and cell membranes are created through hydrophilic and hydrophobic interactions. Finally, the mesostructured inorganic cadmium sulfide was itself utilized as a template to form mesostructured copper sulfide.

Winter Birch Trees

ERIC Educational Resources Information Center

Sweeney, Debra; Rounds, Judy

2011-01-01

Trees are great inspiration for artists. Many art teachers find themselves inspired and maybe somewhat obsessed with the natural beauty and elegance of the lofty tree, and how it changes through the seasons. One such tree that grows in several regions and always looks magnificent, regardless of the time of year, is the birch. In this article, the…

The Inspir=Ed Project: A Holistic Early Childhood Program for Enhancing Parent-Child Well-Being

ERIC Educational Resources Information Center

Hanckel, Jane; Segal, Leonie

2016-01-01

All Indigenous communities have a time-tested child-rearing knowledge base that reflects and honors their cultural beliefs and historical experiences. Many of these communities emphasize group harmony and collaboration and respect for the natural environment--competencies that are increasingly important on our crowded and depleted planet.…

Park It!

ERIC Educational Resources Information Center

Sartorius, Tara Cady

2010-01-01

Many artists visit national parks to draw, paint and take photographs of some of the most amazing scenery on earth. Raw nature is one of the greatest inspirations to an artist, and artists can be credited for helping inspire the government to create the National Park System. This article features Thomas Moran (1837-1926), one of the artists who…

Nasal and Oral Inspiration during Natural Speech Breathing

ERIC Educational Resources Information Center

Lester, Rosemary A.; Hoit, Jeannette D.

2014-01-01

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…

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.

White blood cell segmentation by circle detection using electromagnetism-like optimization.

PubMed

Cuevas, Erik; Oliva, Diego; Díaz, Margarita; Zaldivar, Daniel; Pérez-Cisneros, Marco; Pajares, Gonzalo

2013-01-01

Medical imaging is a relevant field of application of image processing algorithms. In particular, the analysis of white blood cell (WBC) images has engaged researchers from fields of medicine and computer vision alike. Since WBCs can be approximated by a quasicircular form, a circular detector algorithm may be successfully applied. This paper presents an algorithm for the automatic detection of white blood cells embedded into complicated and cluttered smear images that considers the complete process as a circle detection problem. The approach is based on a nature-inspired technique called the electromagnetism-like optimization (EMO) algorithm which is a heuristic method that follows electromagnetism principles for solving complex optimization problems. The proposed approach uses an objective function which measures the resemblance of a candidate circle to an actual WBC. Guided by the values of such objective function, the set of encoded candidate circles are evolved by using EMO, so that they can fit into the actual blood cells contained in the edge map of the image. Experimental results from blood cell images with a varying range of complexity are included to validate the efficiency of the proposed technique regarding detection, robustness, and stability.

White Blood Cell Segmentation by Circle Detection Using Electromagnetism-Like Optimization

PubMed Central

Oliva, Diego; Díaz, Margarita; Zaldivar, Daniel; Pérez-Cisneros, Marco; Pajares, Gonzalo

2013-01-01

Medical imaging is a relevant field of application of image processing algorithms. In particular, the analysis of white blood cell (WBC) images has engaged researchers from fields of medicine and computer vision alike. Since WBCs can be approximated by a quasicircular form, a circular detector algorithm may be successfully applied. This paper presents an algorithm for the automatic detection of white blood cells embedded into complicated and cluttered smear images that considers the complete process as a circle detection problem. The approach is based on a nature-inspired technique called the electromagnetism-like optimization (EMO) algorithm which is a heuristic method that follows electromagnetism principles for solving complex optimization problems. The proposed approach uses an objective function which measures the resemblance of a candidate circle to an actual WBC. Guided by the values of such objective function, the set of encoded candidate circles are evolved by using EMO, so that they can fit into the actual blood cells contained in the edge map of the image. Experimental results from blood cell images with a varying range of complexity are included to validate the efficiency of the proposed technique regarding detection, robustness, and stability. PMID:23476713

Neuro Inspired Adaptive Perception and Control for Agile Mobility of Autonomous Vehicles in Uncertain and Hostile Environments

DTIC Science & Technology

2017-02-08

Georgia Tech Research Corporation 505 Tenth Street NW Atlanta, GA 30332 -0420 ABSTRACT Final Report: MURI: Neuro-Inspired Adaptive Perception and...Conquer Strategy for Optimal Trajectory Planning via Mixed-Integer Programming, IEEE Transactions on Robotics, (12 2015): 0. doi: 10.1109/TRO...Learning Day, Microsoft Corporation , Cambridge, MA, May 18, 2015. (c) Presentations 09/06/2015 09/08/2015 125 131 Ali Borji, Dicky N. Sihite, Laurent Itti

Filtering Data Based on Human-Inspired Forgetting.

PubMed

Freedman, S T; Adams, J A

2011-12-01

Robots are frequently presented with vast arrays of diverse data. Unfortunately, perfect memory and recall provides a mixed blessing. While flawless recollection of episodic data allows increased reasoning, photographic memory can hinder a robot's ability to operate in real-time dynamic environments. Human-inspired forgetting methods may enable robotic systems to rid themselves of out-dated, irrelevant, and erroneous data. This paper presents the use of human-inspired forgetting to act as a filter, removing unnecessary, erroneous, and out-of-date information. The novel ActSimple forgetting algorithm has been developed specifically to provide effective forgetting capabilities to robotic systems. This paper presents the ActSimple algorithm and how it was optimized and tested in a WiFi signal strength estimation task. The results generated by real-world testing suggest that human-inspired forgetting is an effective means of improving the ability of mobile robots to move and operate within complex and dynamic environments.

Analyzing nature's protective design: The glyptodont body armor.

PubMed

du Plessis, Anton; Broeckhoven, Chris; Yadroitsev, Igor; Yadroitsava, Ina; le Roux, Stephan Gerhard

2018-06-01

Many animal species evolved some form of body armor, such as scales of fish and bony plates or osteoderms of reptiles. Although a protective function is often taken for granted, recent studies show that body armor might comprise multiple functionalities and is shaped by trade-offs among these functionalities. Hence, despite the fact that natural body armor might serve as bio-inspiration for the development of artificial protective materials, focussing on model systems in which body armor serves a solely protective function might be pivotal. In this study, we investigate the osteoderms of Glyptotherium arizonae, an extinct armadillo-like mammal in which body armor evolved as protection against predators and/or tail club blows of conspecifics. By using a combination of micro-computed tomography, reverse-engineering, stress simulations and mechanical testing of 3D printed models, we show that the combination of dense compact layers and porous lattice core might provide an optimized combination of strength and high energy absorption. Copyright © 2018 Elsevier Ltd. All rights reserved.

Geology and Design: Formal and Rational Connections

NASA Astrophysics Data System (ADS)

Eriksson, S. C.; Brewer, J.

2016-12-01

Geological forms and the manmade environment have always been inextricably linked. From the time that Upper Paleolithic man created drawings in the Lascaux Caves in the southwest of France, geology has provided a critical and dramatic spoil for human creativity. This inspiration has manifested itself in many different ways, and the history of architecture is rife with examples of geologically derived buildings. During the early 20th Century, German Expressionist art and architecture was heavily influenced by the natural and often translucent quality of minerals. Architects like Bruno Taut drew and built crystalline forms that would go on to inspire the more restrained Bauhaus movement. Even within the context of Contemporary architecture, geology has been a fertile source for inspiration. Architectural practices across the globe leverage the rationality and grounding found in geology to inform a process that is otherwise dominated by computer-driven parametric design. The connection between advanced design technology and the beautifully realized geo natural forms insures that geology will be a relevant source of architectural inspiration well into the 21st century. The sometimes hidden relationship of geology to the various sub-disciplines of Design such as Architecture, Interiors, Landscape Architecture, and Historic Preservation is explored in relation to curriculum and the practice of design. Topics such as materials, form, history, the cultural and physical landscape, natural hazards, and global design enrich and inform curriculum across the college. Commonly, these help define place-based education.

Foraging on the potential energy surface: a swarm intelligence-based optimizer for molecular geometry.

PubMed

Wehmeyer, Christoph; Falk von Rudorff, Guido; Wolf, Sebastian; Kabbe, Gabriel; Schärf, Daniel; Kühne, Thomas D; Sebastiani, Daniel

2012-11-21

We present a stochastic, swarm intelligence-based optimization algorithm for the prediction of global minima on potential energy surfaces of molecular cluster structures. Our optimization approach is a modification of the artificial bee colony (ABC) algorithm which is inspired by the foraging behavior of honey bees. We apply our modified ABC algorithm to the problem of global geometry optimization of molecular cluster structures and show its performance for clusters with 2-57 particles and different interatomic interaction potentials.

Foraging on the potential energy surface: A swarm intelligence-based optimizer for molecular geometry

NASA Astrophysics Data System (ADS)

Wehmeyer, Christoph; Falk von Rudorff, Guido; Wolf, Sebastian; Kabbe, Gabriel; Schärf, Daniel; Kühne, Thomas D.; Sebastiani, Daniel

2012-11-01

We present a stochastic, swarm intelligence-based optimization algorithm for the prediction of global minima on potential energy surfaces of molecular cluster structures. Our optimization approach is a modification of the artificial bee colony (ABC) algorithm which is inspired by the foraging behavior of honey bees. We apply our modified ABC algorithm to the problem of global geometry optimization of molecular cluster structures and show its performance for clusters with 2-57 particles and different interatomic interaction potentials.

Wood as inspiration for new stimuli-responsive structures and materials

Treesearch

Joseph E. Jakes; Nayomi Plaza-Rodriguez; Samuel L. Zelinka; Donald S. Stone; Sophie-Charlotte Gleber; Stefan Vogt

2014-01-01

Nature has often provided inspiration for new smart structures and materials. Recently, we showed a bundle of a few wood cells are moisture-activated torsional actuators that can reversibly twist multiple revolutions per centimeter of length. The bundles produce specific torque higher than that produced by electric motors and possess shape memory twist capabilities....

Inspirations in medical genetics.

PubMed

Asadollahi, Reza

2016-02-01

There are abundant instances in the history of genetics and medical genetics to illustrate how curiosity, charisma of mentors, nature, art, the saving of lives and many other matters have inspired great discoveries. These achievements from deciphering genetic concepts to characterizing genetic disorders have been crucial for management of the patients. There remains, however, a long pathway ahead. © The Author(s) 2014.

Printmaking with Geometric and Nature-Inspired Forms

ERIC Educational Resources Information Center

Burtner, Erin

2012-01-01

What excites the author the most is finding something new and turning it into a lesson her students will enjoy and learn from. Lately, she has been most inspired by the work she finds on one website. The lesson began with a brief PowerPoint based on an artist's website. This particular artist--Jennifer Schmitt--does reduction prints using several…

Inspiration from Nature: Creative Outdoor Writing Activities.

ERIC Educational Resources Information Center

Cardno, Anthony R.

1998-01-01

When campers notice the natural world around them, they can identify with nature and build an emotional connection with the environment. Creative-writing activities tied to nature are presented that can help campers enhance their descriptive and communication skills, and also learn something about themselves in the process. (TD)

Machining Parameters Optimization using Hybrid Firefly Algorithm and Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Farahlina Johari, Nur; Zain, Azlan Mohd; Haszlinna Mustaffa, Noorfa; Udin, Amirmudin

2017-09-01

Firefly Algorithm (FA) is a metaheuristic algorithm that is inspired by the flashing behavior of fireflies and the phenomenon of bioluminescent communication and the algorithm is used to optimize the machining parameters (feed rate, depth of cut, and spindle speed) in this research. The algorithm is hybridized with Particle Swarm Optimization (PSO) to discover better solution in exploring the search space. Objective function of previous research is used to optimize the machining parameters in turning operation. The optimal machining cutting parameters estimated by FA that lead to a minimum surface roughness are validated using ANOVA test.

Neuromorphic Data Microscope

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

Naegle, John H.; Suppona, Roger A.; Aimone, James Bradley

In 2016, Lewis Rhodes Labs, (LRL), shipped the first commercially viable Neuromorphic Processing Unit, (NPU), branded as a Neuromorphic Data Microscope (NDM). This product leverages architectural mechanisms derived from the sensory cortex of the human brain to efficiently implement pattern matching. LRL and Sandia National Labs have optimized this product for streaming analytics, and demonstrated a 1,000x power per operation reduction in an FPGA format. When reduced to an ASIC, the efficiency will improve to 1,000,000x. Additionally, the neuromorphic nature of the device gives it powerful computational attributes that are counterintuitive to those schooled in traditional von Neumann architectures. Themore » Neuromorphic Data Microscope is the first of a broad class of brain-inspired, time domain processors that will profoundly alter the functionality and economics of data processing.« less

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.

Human body motion tracking based on quantum-inspired immune cloning algorithm

NASA Astrophysics Data System (ADS)

Han, Hong; Yue, Lichuan; Jiao, Licheng; Wu, Xing

2009-10-01

In a static monocular camera system, to gain a perfect 3D human body posture is a great challenge for Computer Vision technology now. This paper presented human postures recognition from video sequences using the Quantum-Inspired Immune Cloning Algorithm (QICA). The algorithm included three parts. Firstly, prior knowledge of human beings was used, the key joint points of human could be detected automatically from the human contours and skeletons which could be thinning from the contours; And due to the complexity of human movement, a forecasting mechanism of occlusion joint points was addressed to get optimum 2D key joint points of human body; And then pose estimation recovered by optimizing between the 2D projection of 3D human key joint points and 2D detection key joint points using QICA, which recovered the movement of human body perfectly, because this algorithm could acquire not only the global optimal solution, but the local optimal solution.

Nature's Four Seasons as Inspiration.

ERIC Educational Resources Information Center

Bain, Christina; Padgelek, Mary

1999-01-01

Presents an instructional resource examining artwork by Charles Burchfield, Utagawa Hiroshige, Childe Hassam, and Georgia O'Keeffe that focuses on nature's four seasons. Offers activities to encourage students' observational skills and guide them to depict their personal views of nature in their own artwork (CMK)

Naturally Inspired Firefly Controller For Stabilization Of Double Inverted Pendulum

NASA Astrophysics Data System (ADS)

Srikanth, Kavirayani; Nagesh, Gundavarapu

2015-12-01

A double inverted pendulum plant as an established model that is analyzed as part of this work was tested under the influence of time delay, where the controller was fine tuned using a firefly algorithm taking into considering the fitness function of variation of the cart position and to minimize the cart position displacement and still stabilize it effectively. The naturally inspired algorithm which imitates the fireflies definitely is an energy efficient method owing to the inherent logic of the way the fireflies respond collectively and has shown that critical time delays makes the system healthy.

A global optimization algorithm inspired in the behavior of selfish herds.

PubMed

Fausto, Fernando; Cuevas, Erik; Valdivia, Arturo; González, Adrián

2017-10-01

In this paper, a novel swarm optimization algorithm called the Selfish Herd Optimizer (SHO) is proposed for solving global optimization problems. SHO is based on the simulation of the widely observed selfish herd behavior manifested by individuals within a herd of animals subjected to some form of predation risk. In SHO, individuals emulate the predatory interactions between groups of prey and predators by two types of search agents: the members of a selfish herd (the prey) and a pack of hungry predators. Depending on their classification as either a prey or a predator, each individual is conducted by a set of unique evolutionary operators inspired by such prey-predator relationship. These unique traits allow SHO to improve the balance between exploration and exploitation without altering the population size. To illustrate the proficiency and robustness of the proposed method, it is compared to other well-known evolutionary optimization approaches such as Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Firefly Algorithm (FA), Differential Evolution (DE), Genetic Algorithms (GA), Crow Search Algorithm (CSA), Dragonfly Algorithm (DA), Moth-flame Optimization Algorithm (MOA) and Sine Cosine Algorithm (SCA). The comparison examines several standard benchmark functions, commonly considered within the literature of evolutionary algorithms. The experimental results show the remarkable performance of our proposed approach against those of the other compared methods, and as such SHO is proven to be an excellent alternative to solve global optimization problems. Copyright © 2017 Elsevier B.V. All rights reserved.

Biomimetics for next generation materials.

PubMed

Barthelat, Francois

2007-12-15

Billions of years of evolution have produced extremely efficient natural materials, which are increasingly becoming a source of inspiration for engineers. Biomimetics-the science of imitating nature-is a growing multidisciplinary field which is now leading to the fabrication of novel materials with remarkable mechanical properties. This article discusses the mechanics of hard biological materials, and more specifically of nacre and bone. These high-performance natural composites are made up of relatively weak components (brittle minerals and soft proteins) arranged in intricate ways to achieve specific combinations of stiffness, strength and toughness (resistance to cracking). Determining which features control the performance of these materials is the first step in biomimetics. These 'key features' can then be implemented into artificial bio-inspired synthetic materials, using innovative techniques such as layer-by-layer assembly or ice-templated crystallization. The most promising approaches, however, are self-assembly and biomineralization because they will enable tight control of structures at the nanoscale. In this 'bottom-up' fabrication, also inspired from nature, molecular structures and crystals are assembled with a little or no external intervention. The resulting materials will offer new combinations of low weight, stiffness and toughness, with added functionalities such as self-healing. Only tight collaborations between engineers, chemists, materials scientists and biologists will make these 'next-generation' materials a reality.

Tracks in the Sand: Hooke's Pendulum "Cum Grano Salis"

ERIC Educational Resources Information Center

Babovic, Vukota; Babovic, Miloš

2014-01-01

The history of science remembers more than just formal facts about scientific discoveries. These side stories are often inspiring. One of them, the story of an unfulfilled death wish of Jacob Bernoulli regarding spirals, inspired us to look around ourselves. And we saw natural spirals around us, which led to the creation of a Hooke's…

Design of gecko-inspired fibrillar surfaces with strong attachment and easy-removal properties: a numerical analysis of peel-zone

PubMed Central

Zhou, Ming; Pesika, Noshir; Zeng, Hongbo; Wan, Jin; Zhang, Xiangjun; Meng, Yonggang; Wen, Shizhu; Tian, Yu

2012-01-01

Despite successful fabrication of gecko-inspired fibrillar surfaces with strong adhesion forces, how to achieve an easy-removal property becomes a major concern that may restrict the wide applications of these bio-inspired surfaces. Research on how geckos detach rapidly has inspired the design of novel adhesive surfaces with strong and reversible adhesion capabilities, which relies on further fundamental understanding of the peeling mechanisms. Recent studies showed that the peel-zone plays an important role in the peeling off of adhesive tapes or fibrillar surfaces. In this study, a numerical method was developed to evaluate peel-zone deformation and the resulting mechanical behaviour due to the deformations of fibrillar surfaces detaching from a smooth rigid substrate. The effect of the geometrical parameters of pillars and the stiffness of backing layer on the peel-zone and peel strength, and the strong attachment and easy-removal properties have been analysed to establish a design map for bio-inspired fibrillar surfaces, which shows that the optimized strong attachment and easy-removal properties can vary by over three orders of magnitude. The adhesion and peeling design map established provides new insights into the design and development of novel gecko-inspired fibrillar surfaces. PMID:22572030

Bio-inspired multistructured conical copper wires for highly efficient liquid manipulation.

PubMed

Wang, Qianbin; Meng, Qingan; Chen, Ming; Liu, Huan; Jiang, Lei

2014-09-23

Animal hairs are typical structured conical fibers ubiquitous in natural system that enable the manipulation of low viscosity liquid in a well-controlled manner, which serves as the fundamental structure in Chinese brush for ink delivery in a controllable manner. Here, drawing inspiration from these structure, we developed a dynamic electrochemical method that enables fabricating the anisotropic multiscale structured conical copper wire (SCCW) with controllable conicity and surface morphology. The as-prepared SCCW exhibits a unique ability for manipulating liquid with significantly high efficiency, and over 428 times greater than its own volume of liquid could be therefore operated. We propose that the boundary condition of the dynamic liquid balance behavior on conical fibers, namely, steady holding of liquid droplet at the tip region of the SCCW, makes it an excellent fibrous medium to manipulate liquid. Moreover, we demonstrate that the titling angle of the SCCW can also affect its efficiency of liquid manipulation by virtue of its mechanical rigidity, which is hardly realized by flexible natural hairs. We envision that the bio-inspired SCCW could give inspiration in designing materials and devices to manipulate liquid in a more controllable way and with high efficiency.

Biologically inspired dynamic material systems.

PubMed

Studart, André R

2015-03-09

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

Evaluating Moving Target Defense with PLADD

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

Jones, Stephen T.; Outkin, Alexander V.; Gearhart, Jared Lee

This project evaluates the effectiveness of moving target defense (MTD) techniques using a new game we have designed, called PLADD, inspired by the game FlipIt [28]. PLADD extends FlipIt by incorporating what we believe are key MTD concepts. We have analyzed PLADD and proven the existence of a defender strategy that pushes a rational attacker out of the game, demonstrated how limited the strategies available to an attacker are in PLADD, and derived analytic expressions for the expected utility of the game’s players in multiple game variants. We have created an algorithm for finding a defender’s optimal PLADD strategy. Wemore » show that in the special case of achieving deterrence in PLADD, MTD is not always cost effective and that its optimal deployment may shift abruptly from not using MTD at all to using it as aggressively as possible. We believe our effort provides basic, fundamental insights into the use of MTD, but conclude that a truly practical analysis requires model selection and calibration based on real scenarios and empirical data. We propose several avenues for further inquiry, including (1) agents with adaptive capabilities more reflective of real world adversaries, (2) the presence of multiple, heterogeneous adversaries, (3) computational game theory-based approaches such as coevolution to allow scaling to the real world beyond the limitations of analytical analysis and classical game theory, (4) mapping the game to real-world scenarios, (5) taking player risk into account when designing a strategy (in addition to expected payoff), (6) improving our understanding of the dynamic nature of MTD-inspired games by using a martingale representation, defensive forecasting, and techniques from signal processing, and (7) using adversarial games to develop inherently resilient cyber systems.« less

Biomimicry of quorum sensing using bacterial lifecycle model.

PubMed

Niu, Ben; Wang, Hong; Duan, Qiqi; Li, Li

2013-01-01

Recent microbiologic studies have shown that quorum sensing mechanisms, which serve as one of the fundamental requirements for bacterial survival, exist widely in bacterial intra- and inter-species cell-cell communication. Many simulation models, inspired by the social behavior of natural organisms, are presented to provide new approaches for solving realistic optimization problems. Most of these simulation models follow population-based modelling approaches, where all the individuals are updated according to the same rules. Therefore, it is difficult to maintain the diversity of the population. In this paper, we present a computational model termed LCM-QS, which simulates the bacterial quorum-sensing (QS) mechanism using an individual-based modelling approach under the framework of Agent-Environment-Rule (AER) scheme, i.e. bacterial lifecycle model (LCM). LCM-QS model can be classified into three main sub-models: chemotaxis with QS sub-model, reproduction and elimination sub-model and migration sub-model. The proposed model is used to not only imitate the bacterial evolution process at the single-cell level, but also concentrate on the study of bacterial macroscopic behaviour. Comparative experiments under four different scenarios have been conducted in an artificial 3-D environment with nutrients and noxious distribution. Detailed study on bacterial chemotatic processes with quorum sensing and without quorum sensing are compared. By using quorum sensing mechanisms, artificial bacteria working together can find the nutrient concentration (or global optimum) quickly in the artificial environment. Biomimicry of quorum sensing mechanisms using the lifecycle model allows the artificial bacteria endowed with the communication abilities, which are essential to obtain more valuable information to guide their search cooperatively towards the preferred nutrient concentrations. It can also provide an inspiration for designing new swarm intelligence optimization algorithms, which can be used for solving the real-world problems.

Biomimicry of quorum sensing using bacterial lifecycle model

PubMed Central

2013-01-01

Background Recent microbiologic studies have shown that quorum sensing mechanisms, which serve as one of the fundamental requirements for bacterial survival, exist widely in bacterial intra- and inter-species cell-cell communication. Many simulation models, inspired by the social behavior of natural organisms, are presented to provide new approaches for solving realistic optimization problems. Most of these simulation models follow population-based modelling approaches, where all the individuals are updated according to the same rules. Therefore, it is difficult to maintain the diversity of the population. Results In this paper, we present a computational model termed LCM-QS, which simulates the bacterial quorum-sensing (QS) mechanism using an individual-based modelling approach under the framework of Agent-Environment-Rule (AER) scheme, i.e. bacterial lifecycle model (LCM). LCM-QS model can be classified into three main sub-models: chemotaxis with QS sub-model, reproduction and elimination sub-model and migration sub-model. The proposed model is used to not only imitate the bacterial evolution process at the single-cell level, but also concentrate on the study of bacterial macroscopic behaviour. Comparative experiments under four different scenarios have been conducted in an artificial 3-D environment with nutrients and noxious distribution. Detailed study on bacterial chemotatic processes with quorum sensing and without quorum sensing are compared. By using quorum sensing mechanisms, artificial bacteria working together can find the nutrient concentration (or global optimum) quickly in the artificial environment. Conclusions Biomimicry of quorum sensing mechanisms using the lifecycle model allows the artificial bacteria endowed with the communication abilities, which are essential to obtain more valuable information to guide their search cooperatively towards the preferred nutrient concentrations. It can also provide an inspiration for designing new swarm intelligence optimization algorithms, which can be used for solving the real-world problems. PMID:23815296

Dosimetric Considerations in Respiratory-Gated Deep Inspiration Breath-Hold for Left Breast Irradiation.

PubMed

Walston, Steve; Quick, Allison M; Kuhn, Karla; Rong, Yi

2017-02-01

To present our clinical workflow of incorporating AlignRT for left breast deep inspiration breath-hold treatments and the dosimetric considerations with the deep inspiration breath-hold protocol. Patients with stage I to III left-sided breast cancer who underwent lumpectomy or mastectomy were considered candidates for deep inspiration breath-hold technique for their external beam radiation therapy. Treatment plans were created on both free-breathing and deep inspiration breath-hold computed tomography for each patient to determine whether deep inspiration breath-hold was beneficial based on dosimetric comparison. The AlignRT system was used for patient setup and monitoring. Dosimetric measurements and their correlation with chest wall excursion and increase in left lung volume were studied for free-breathing and deep inspiration breath-hold plans. Deep inspiration breath-hold plans had significantly increased chest wall excursion when compared with free breathing. This change in geometry resulted in reduced mean and maximum heart dose but did not impact lung V 20 or mean dose. The correlation between chest wall excursion and absolute reduction in heart or lung dose was found to be nonsignificant, but correlation between left lung volume and heart dose showed a linear association. It was also identified that higher levels of chest wall excursion may paradoxically increase heart or lung dose. Reduction in heart dose can be achieved for many left-sided breast and chest wall patients using deep inspiration breath-hold. Chest wall excursion as well as left lung volume did not correlate with reduction in heart dose, and it remains to be determined what metric will provide the most optimal and reliable dosimetric advantage.

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

2-D Ultrasound Sparse Arrays Multidepth Radiation Optimization Using Simulated Annealing and Spiral-Array Inspired Energy Functions.

PubMed

Roux, Emmanuel; Ramalli, Alessandro; Tortoli, Piero; Cachard, Christian; Robini, Marc C; Liebgott, Herve

2016-12-01

Full matrix arrays are excellent tools for 3-D ultrasound imaging, but the required number of active elements is too high to be individually controlled by an equal number of scanner channels. The number of active elements is significantly reduced by the sparse array techniques, but the position of the remaining elements must be carefully optimized. This issue is faced here by introducing novel energy functions in the simulated annealing (SA) algorithm. At each iteration step of the optimization process, one element is freely translated and the associated radiated pattern is simulated. To control the pressure field behavior at multiple depths, three energy functions inspired by the pressure field radiated by a Blackman-tapered spiral array are introduced. Such energy functions aim at limiting the main lobe width while lowering the side lobe and grating lobe levels at multiple depths. Numerical optimization results illustrate the influence of the number of iterations, pressure measurement points, and depths, as well as the influence of the energy function definition on the optimized layout. It is also shown that performance close to or even better than the one provided by a spiral array, here assumed as reference, may be obtained. The finite-time convergence properties of SA allow the duration of the optimization process to be set in advance.

The Applications of Genetic Algorithms in Medicine.

PubMed

Ghaheri, Ali; Shoar, Saeed; Naderan, Mohammad; Hoseini, Sayed Shahabuddin

2015-11-01

A great wealth of information is hidden amid medical research data that in some cases cannot be easily analyzed, if at all, using classical statistical methods. Inspired by nature, metaheuristic algorithms have been developed to offer optimal or near-optimal solutions to complex data analysis and decision-making tasks in a reasonable time. Due to their powerful features, metaheuristic algorithms have frequently been used in other fields of sciences. In medicine, however, the use of these algorithms are not known by physicians who may well benefit by applying them to solve complex medical problems. Therefore, in this paper, we introduce the genetic algorithm and its applications in medicine. The use of the genetic algorithm has promising implications in various medical specialties including radiology, radiotherapy, oncology, pediatrics, cardiology, endocrinology, surgery, obstetrics and gynecology, pulmonology, infectious diseases, orthopedics, rehabilitation medicine, neurology, pharmacotherapy, and health care management. This review introduces the applications of the genetic algorithm in disease screening, diagnosis, treatment planning, pharmacovigilance, prognosis, and health care management, and enables physicians to envision possible applications of this metaheuristic method in their medical career.].

The Applications of Genetic Algorithms in Medicine

PubMed Central

Ghaheri, Ali; Shoar, Saeed; Naderan, Mohammad; Hoseini, Sayed Shahabuddin

2015-01-01

A great wealth of information is hidden amid medical research data that in some cases cannot be easily analyzed, if at all, using classical statistical methods. Inspired by nature, metaheuristic algorithms have been developed to offer optimal or near-optimal solutions to complex data analysis and decision-making tasks in a reasonable time. Due to their powerful features, metaheuristic algorithms have frequently been used in other fields of sciences. In medicine, however, the use of these algorithms are not known by physicians who may well benefit by applying them to solve complex medical problems. Therefore, in this paper, we introduce the genetic algorithm and its applications in medicine. The use of the genetic algorithm has promising implications in various medical specialties including radiology, radiotherapy, oncology, pediatrics, cardiology, endocrinology, surgery, obstetrics and gynecology, pulmonology, infectious diseases, orthopedics, rehabilitation medicine, neurology, pharmacotherapy, and health care management. This review introduces the applications of the genetic algorithm in disease screening, diagnosis, treatment planning, pharmacovigilance, prognosis, and health care management, and enables physicians to envision possible applications of this metaheuristic method in their medical career.] PMID:26676060

Accelerated Self-Replication under Non-Equilibrium, Periodic Energy Delivery

NASA Astrophysics Data System (ADS)

Zhang, Rui; Olvera de La Cruz, Monica

2014-03-01

Self-replication is a remarkable phenomenon in nature that has fascinated scientists for decades. In a self-replicating system, the original units are attracted to a template, which induce their binding. In equilibrium, the energy required to disassemble the newly assembled copy from the mother template is supplied by thermal energy. The possibility of optimizing self-replication is explored by controlling the frequency at which energy is supplied to the system. A model system inspired by a class of light switchable colloids is considered where light is used to control the interactions. Conditions under which self-replication can be significantly more effective under non-equilibrium, cyclic energy delivery than under equilibrium constant energy conditions are identified. Optimal self-replication does not require constant energy expenditure. Instead, the proper timing at which energy is delivered to the system is an essential controllable parameter to induce high replication rates. This work was supported by the Non-Equilibrium Energy Research Center (NERC), which is an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Award Number DE-SC0000989.

Evaluation of the selection methods used in the exIWO algorithm based on the optimization of multidimensional functions

NASA Astrophysics Data System (ADS)

Kostrzewa, Daniel; Josiński, Henryk

2016-06-01

The expanded Invasive Weed Optimization algorithm (exIWO) is an optimization metaheuristic modelled on the original IWO version inspired by dynamic growth of weeds colony. The authors of the present paper have modified the exIWO algorithm introducing a set of both deterministic and non-deterministic strategies of individuals' selection. The goal of the project was to evaluate the modified exIWO by testing its usefulness for multidimensional numerical functions optimization. The optimized functions: Griewank, Rastrigin, and Rosenbrock are frequently used as benchmarks because of their characteristics.

Analysis of point-to-point lung motion with full inspiration and expiration CT data using non-linear optimization method: optimal geometric assumption model for the effective registration algorithm

NASA Astrophysics Data System (ADS)

Kim, Namkug; Seo, Joon Beom; Heo, Jeong Nam; Kang, Suk-Ho

2007-03-01

The study was conducted to develop a simple model for more robust lung registration of volumetric CT data, which is essential for various clinical lung analysis applications, including the lung nodule matching in follow up CT studies, semi-quantitative assessment of lung perfusion, and etc. The purpose of this study is to find the most effective reference point and geometric model based on the lung motion analysis from the CT data sets obtained in full inspiration (In.) and expiration (Ex.). Ten pairs of CT data sets in normal subjects obtained in full In. and Ex. were used in this study. Two radiologists were requested to draw 20 points representing the subpleural point of the central axis in each segment. The apex, hilar point, and center of inertia (COI) of each unilateral lung were proposed as the reference point. To evaluate optimal expansion point, non-linear optimization without constraints was employed. The objective function is sum of distances from the line, consist of the corresponding points between In. and Ex. to the optimal point x. By using the nonlinear optimization, the optimal points was evaluated and compared between reference points. The average distance between the optimal point and each line segment revealed that the balloon model was more suitable to explain the lung expansion model. This lung motion analysis based on vector analysis and non-linear optimization shows that balloon model centered on the center of inertia of lung is most effective geometric model to explain lung expansion by breathing.

Non-linear Multidimensional Optimization for use in Wire Scanner Fitting

NASA Astrophysics Data System (ADS)

Henderson, Alyssa; Terzic, Balsa; Hofler, Alicia; CASA and Accelerator Ops Collaboration

2013-10-01

To ensure experiment efficiency and quality from the Continuous Electron Beam Accelerator at Jefferson Lab, beam energy, size, and position must be measured. Wire scanners are devices inserted into the beamline to produce measurements which are used to obtain beam properties. Extracting physical information from the wire scanner measurements begins by fitting Gaussian curves to the data. This study focuses on optimizing and automating this curve-fitting procedure. We use a hybrid approach combining the efficiency of Newton Conjugate Gradient (NCG) method with the global convergence of three nature-inspired (NI) optimization approaches: genetic algorithm, differential evolution, and particle-swarm. In this Python-implemented approach, augmenting the locally-convergent NCG with one of the globally-convergent methods ensures the quality, robustness, and automation of curve-fitting. After comparing the methods, we establish that given an initial data-derived guess, each finds a solution with the same chi-square- a measurement of the agreement of the fit to the data. NCG is the fastest method, so it is the first to attempt data-fitting. The curve-fitting procedure escalates to one of the globally-convergent NI methods only if NCG fails, thereby ensuring a successful fit. This method allows for the most optimal signal fit and can be easily applied to similar problems. Financial support from DoE, NSF, ODU, DoD, and Jefferson Lab.

Cuckoo Search with Lévy Flights for Weighted Bayesian Energy Functional Optimization in Global-Support Curve Data Fitting

PubMed Central

Gálvez, Akemi; Iglesias, Andrés; Cabellos, Luis

2014-01-01

The problem of data fitting is very important in many theoretical and applied fields. In this paper, we consider the problem of optimizing a weighted Bayesian energy functional for data fitting by using global-support approximating curves. By global-support curves we mean curves expressed as a linear combination of basis functions whose support is the whole domain of the problem, as opposed to other common approaches in CAD/CAM and computer graphics driven by piecewise functions (such as B-splines and NURBS) that provide local control of the shape of the curve. Our method applies a powerful nature-inspired metaheuristic algorithm called cuckoo search, introduced recently to solve optimization problems. A major advantage of this method is its simplicity: cuckoo search requires only two parameters, many fewer than other metaheuristic approaches, so the parameter tuning becomes a very simple task. The paper shows that this new approach can be successfully used to solve our optimization problem. To check the performance of our approach, it has been applied to five illustrative examples of different types, including open and closed 2D and 3D curves that exhibit challenging features, such as cusps and self-intersections. Our results show that the method performs pretty well, being able to solve our minimization problem in an astonishingly straightforward way. PMID:24977175

Cuckoo search with Lévy flights for weighted Bayesian energy functional optimization in global-support curve data fitting.

PubMed

Gálvez, Akemi; Iglesias, Andrés; Cabellos, Luis

2014-01-01

The problem of data fitting is very important in many theoretical and applied fields. In this paper, we consider the problem of optimizing a weighted Bayesian energy functional for data fitting by using global-support approximating curves. By global-support curves we mean curves expressed as a linear combination of basis functions whose support is the whole domain of the problem, as opposed to other common approaches in CAD/CAM and computer graphics driven by piecewise functions (such as B-splines and NURBS) that provide local control of the shape of the curve. Our method applies a powerful nature-inspired metaheuristic algorithm called cuckoo search, introduced recently to solve optimization problems. A major advantage of this method is its simplicity: cuckoo search requires only two parameters, many fewer than other metaheuristic approaches, so the parameter tuning becomes a very simple task. The paper shows that this new approach can be successfully used to solve our optimization problem. To check the performance of our approach, it has been applied to five illustrative examples of different types, including open and closed 2D and 3D curves that exhibit challenging features, such as cusps and self-intersections. Our results show that the method performs pretty well, being able to solve our minimization problem in an astonishingly straightforward way.

Evaluation of force generation mechanisms in natural, passive hydraulic actuators

NASA Astrophysics Data System (ADS)

Le Duigou, A.; Castro, M.

2016-01-01

Pine cones are well known natural actuators that can move their scales upon humidity gradient. The mechanism manifests itself through a displacement easily observable by the naked eye, but coupled with stress generation. In ancient Egypt, wooden wedges were used to break soft blocks of stone by the generated swelling stress. The purpose of the present study is to evaluate the ability of pine cone scales to generate forces while being wetted. In our experiments, a blocking force of around 3N is measured depending on the position on the pine cone where the scales are extracted. A fairly good agreement is obtained when theoretical results based on bimetallic strip systems are compared with experimental data, even if overestimation is observed arising from the input data considered for dry tissues. Inspired by a simplified pine cone microstructure, a biocomposite analogue is manufactured and tested. Although an adequate blocking force can be generated, it has a lower value compared to natural pine cones which benefit from optimized swelling tissue content and interfacial bond strength between them. This study provides new insights to understand the generation of force by pine cones as well as to develop novel biocomposite functionalities.

A plant-inspired robot with soft differential bending capabilities.

PubMed

Sadeghi, A; Mondini, A; Del Dottore, E; Mattoli, V; Beccai, L; Taccola, S; Lucarotti, C; Totaro, M; Mazzolai, B

2016-12-20

We present the design and development of a plant-inspired robot, named Plantoid, with sensorized robotic roots. Natural roots have a multi-sensing capability and show a soft bending behaviour to follow or escape from various environmental parameters (i.e., tropisms). Analogously, we implement soft bending capabilities in our robotic roots by designing and integrating soft spring-based actuation (SSBA) systems using helical springs to transmit the motor power in a compliant manner. Each robotic tip integrates four different sensors, including customised flexible touch and innovative humidity sensors together with commercial gravity and temperature sensors. We show how the embedded sensing capabilities together with a root-inspired control algorithm lead to the implementation of tropic behaviours. Future applications for such plant-inspired technologies include soil monitoring and exploration, useful for agriculture and environmental fields.

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

PubMed Central

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

2017-01-01

Data acquisition is the foundation of soft sensor and data fusion. Distributed data acquisition and its synchronization are the important technologies to ensure the accuracy of soft sensors. As a research topic in bionic science, the firefly-inspired algorithm has attracted widespread attention as a new synchronization method. Aiming at reducing the design difficulty of firefly-inspired synchronization algorithms for Wireless Sensor Networks (WSNs) with complex topologies, this paper presents a firefly-inspired synchronization algorithm based on a multiscale discrete phase model that can optimize the performance tradeoff between the network scalability and synchronization capability in a complex wireless sensor network. The synchronization process can be regarded as a Markov state transition, which ensures the stability of this algorithm. Compared with the Miroll and Steven model and Reachback Firefly Algorithm, the proposed algorithm obtains better stability and performance. Finally, its practicality has been experimentally confirmed using 30 nodes in a real multi-hop topology with low quality links. PMID:28282899

Biomimetic Sniffing Improves the Detection Performance of a 3D Printed Nose of a Dog and a Commercial Trace Vapor Detector

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Biomimetic Sniffing Improves the Detection Performance of a 3D Printed Nose of a Dog and a Commercial Trace Vapor Detector

PubMed Central

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

2016-01-01

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

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

PubMed

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

2017-03-08

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

Armours for soft bodies: how far can bioinspiration take us?

PubMed

White, Zachary W; Vernerey, Franck J

2018-05-15

The development of armour is as old as the dawn of civilization. Early man looked to natural structures to harvest or replicate for protection, leaning on millennia of evolutionary developments in natural protection. Since the advent of more modern weaponry, Armor development has seemingly been driven more by materials research than bio-inspiration. However, parallels can still be drawn between modern bullet-protective armours and natural defensive structures. Soft armour for handgun and fragmentation threats can be likened to mammalian skin, and similarly, hard armour can be compared with exoskeletons and turtle shells. Via bio-inspiration, it may be possible to develop structures previously un-researched for ballistic protection. This review will cover current modern ballistic protective structures focusing on energy dissipation and absorption methods, and their natural analogues. As all armour is a compromise between weight, flexibility and protection, the imbricated structure of scaled skin will be presented as a better balance between these factors.

Bio-inspired UAV routing, source localization, and acoustic signature classification for persistent surveillance

NASA Astrophysics Data System (ADS)

Burman, Jerry; Hespanha, Joao; Madhow, Upamanyu; Pham, Tien

2011-06-01

A team consisting of Teledyne Scientific Company, the University of California at Santa Barbara and the Army Research Laboratory* is developing technologies in support of automated data exfiltration from heterogeneous battlefield sensor networks to enhance situational awareness for dismounts and command echelons. Unmanned aerial vehicles (UAV) provide an effective means to autonomously collect data from a sparse network of unattended ground sensors (UGSs) that cannot communicate with each other. UAVs are used to reduce the system reaction time by generating autonomous collection routes that are data-driven. Bio-inspired techniques for search provide a novel strategy to detect, capture and fuse data. A fast and accurate method has been developed to localize an event by fusing data from a sparse number of UGSs. This technique uses a bio-inspired algorithm based on chemotaxis or the motion of bacteria seeking nutrients in their environment. A unique acoustic event classification algorithm was also developed based on using swarm optimization. Additional studies addressed the problem of routing multiple UAVs, optimally placing sensors in the field and locating the source of gunfire at helicopters. A field test was conducted in November of 2009 at Camp Roberts, CA. The field test results showed that a system controlled by bio-inspired software algorithms can autonomously detect and locate the source of an acoustic event with very high accuracy and visually verify the event. In nine independent test runs of a UAV, the system autonomously located the position of an explosion nine times with an average accuracy of 3 meters. The time required to perform source localization using the UAV was on the order of a few minutes based on UAV flight times. In June 2011, additional field tests of the system will be performed and will include multiple acoustic events, optimal sensor placement based on acoustic phenomenology and the use of the International Technology Alliance (ITA) Sensor Network Fabric (IBM).

"Friluftsliv": Traditional Norwegian Outdoor Life.

ERIC Educational Resources Information Center

Tellnes, Atle

1992-01-01

Nature and outdoor life are part of Norway's national identity, as exemplified by a long history of nature-inspired art and literature, the formation of outdoor organizations since the turn of the century, and the development of skiing. Norwegian traditional outdoor life is characterized as travelling with respectful use of nature, to achieve a…

A Sustaining Environment for Environmental Art

ERIC Educational Resources Information Center

Malamud, Randy

2008-01-01

Environmental art (aka land art, green art, earthworks) aims to interpret nature and to inspire audiences to re-envision people's relationship with nature. Some artists see their work as a springboard for reclaiming and remediating damaged environments. Art began keenly grounded in nature--think of cave paintings of animals, in charcoal and…

Biomimetic photonic materials with tunable structural colors.

PubMed

Xu, Jun; Guo, Zhiguang

2013-09-15

Nature is a huge gallery of art involving nearly perfect structures and forms over the millions of years developing. Inspiration from natural structures exhibiting structural colors is first discussed. We give some examples of natural one-, two-, and three-dimensional photonic structures. This review article presents a brief summary of recent progress on bio-inspired photonic materials with variable structural colors, including the different facile and efficient routes to construct the nano-architectures, and the development of the artificial variable structural color photonic materials. Besides the superior optical properties, the excellent functions such as robust mechanical strength, good wettability are also mentioned, as well as the technical importance in various applications. This review will provide significant insight into the fabrication, design and application of the structural color materials. Copyright © 2013 Elsevier Inc. All rights reserved.

Estimating Origin-Destination Matrices Using AN Efficient Moth Flame-Based Spatial Clustering Approach

NASA Astrophysics Data System (ADS)

Heidari, A. A.; Moayedi, A.; Abbaspour, R. Ali

2017-09-01

Automated fare collection (AFC) systems are regarded as valuable resources for public transport planners. In this paper, the AFC data are utilized to analysis and extract mobility patterns in a public transportation system. For this purpose, the smart card data are inserted into a proposed metaheuristic-based aggregation model and then converted to O-D matrix between stops, since the size of O-D matrices makes it difficult to reproduce the measured passenger flows precisely. The proposed strategy is applied to a case study from Haaglanden, Netherlands. In this research, moth-flame optimizer (MFO) is utilized and evaluated for the first time as a new metaheuristic algorithm (MA) in estimating transit origin-destination matrices. The MFO is a novel, efficient swarm-based MA inspired from the celestial navigation of moth insects in nature. To investigate the capabilities of the proposed MFO-based approach, it is compared to methods that utilize the K-means algorithm, gray wolf optimization algorithm (GWO) and genetic algorithm (GA). The sum of the intra-cluster distances and computational time of operations are considered as the evaluation criteria to assess the efficacy of the optimizers. The optimality of solutions of different algorithms is measured in detail. The traveler's behavior is analyzed to achieve to a smooth and optimized transport system. The results reveal that the proposed MFO-based aggregation strategy can outperform other evaluated approaches in terms of convergence tendency and optimality of the results. The results show that it can be utilized as an efficient approach to estimating the transit O-D matrices.

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.

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.

Performance Analysis of the Enhanced Bio-Inspired Planning Algorithm for Rapid Situation Awareness Response

DTIC Science & Technology

2013-10-18

low cost robot testbed. 15. SUBJECT TERMS Bio-inspired trajectory generation, in-situ obstacle avoidance, low-cost LEGO robots, vision- based...will not affect the solution optimality and thus will be regarded as zero. Following the LP motion strategy Eq. (1), the position vector of the Lego ...Lobatto (LGL) method [14], the position of Lego robot can be further represented as ’ 1 ,( )j p jD   ζ ζ (6) in which ,0 ,,..., T j j j

Robust extrema features for time-series data analysis.

PubMed

Vemulapalli, Pramod K; Monga, Vishal; Brennan, Sean N

2013-06-01

The extraction of robust features for comparing and analyzing time series is a fundamentally important problem. Research efforts in this area encompass dimensionality reduction using popular signal analysis tools such as the discrete Fourier and wavelet transforms, various distance metrics, and the extraction of interest points from time series. Recently, extrema features for analysis of time-series data have assumed increasing significance because of their natural robustness under a variety of practical distortions, their economy of representation, and their computational benefits. Invariably, the process of encoding extrema features is preceded by filtering of the time series with an intuitively motivated filter (e.g., for smoothing), and subsequent thresholding to identify robust extrema. We define the properties of robustness, uniqueness, and cardinality as a means to identify the design choices available in each step of the feature generation process. Unlike existing methods, which utilize filters "inspired" from either domain knowledge or intuition, we explicitly optimize the filter based on training time series to optimize robustness of the extracted extrema features. We demonstrate further that the underlying filter optimization problem reduces to an eigenvalue problem and has a tractable solution. An encoding technique that enhances control over cardinality and uniqueness is also presented. Experimental results obtained for the problem of time series subsequence matching establish the merits of the proposed algorithm.

Cat swarm optimization based evolutionary framework for multi document summarization

NASA Astrophysics Data System (ADS)

Rautray, Rasmita; Balabantaray, Rakesh Chandra

2017-07-01

Today, World Wide Web has brought us enormous quantity of on-line information. As a result, extracting relevant information from massive data has become a challenging issue. In recent past text summarization is recognized as one of the solution to extract useful information from vast amount documents. Based on number of documents considered for summarization, it is categorized as single document or multi document summarization. Rather than single document, multi document summarization is more challenging for the researchers to find accurate summary from multiple documents. Hence in this study, a novel Cat Swarm Optimization (CSO) based multi document summarizer is proposed to address the problem of multi document summarization. The proposed CSO based model is also compared with two other nature inspired based summarizer such as Harmony Search (HS) based summarizer and Particle Swarm Optimization (PSO) based summarizer. With respect to the benchmark Document Understanding Conference (DUC) datasets, the performance of all algorithms are compared in terms of different evaluation metrics such as ROUGE score, F score, sensitivity, positive predicate value, summary accuracy, inter sentence similarity and readability metric to validate non-redundancy, cohesiveness and readability of the summary respectively. The experimental analysis clearly reveals that the proposed approach outperforms the other summarizers included in the study.

Robotics-inspired biology.

PubMed

Gravish, Nick; Lauder, George V

2018-03-29

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

Power law-based local search in spider monkey optimisation for lower order system modelling

NASA Astrophysics Data System (ADS)

Sharma, Ajay; Sharma, Harish; Bhargava, Annapurna; Sharma, Nirmala

2017-01-01

The nature-inspired algorithms (NIAs) have shown efficiency to solve many complex real-world optimisation problems. The efficiency of NIAs is measured by their ability to find adequate results within a reasonable amount of time, rather than an ability to guarantee the optimal solution. This paper presents a solution for lower order system modelling using spider monkey optimisation (SMO) algorithm to obtain a better approximation for lower order systems and reflects almost original higher order system's characteristics. Further, a local search strategy, namely, power law-based local search is incorporated with SMO. The proposed strategy is named as power law-based local search in SMO (PLSMO). The efficiency, accuracy and reliability of the proposed algorithm is tested over 20 well-known benchmark functions. Then, the PLSMO algorithm is applied to solve the lower order system modelling problem.

Borehole Tool for the Comprehensive Characterization of Hydrate-bearing Sediments

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

Dai, Sheng; Santamarina, J. Carlos

Reservoir characterization and simulation require reliable parameters to anticipate hydrate deposits responses and production rates. The acquisition of the required fundamental properties currently relies on wireline logging, pressure core testing, and/or laboratory observations of synthesized specimens, which are challenged by testing capabilities and innate sampling disturbances. The project reviews hydrate-bearing sediments, properties, and inherent sampling effects, albeit lessen with the developments in pressure core technology, in order to develop robust correlations with index parameters. The resulting information is incorporated into a tool for optimal field characterization and parameter selection with uncertainty analyses. Ultimately, the project develops a borehole tool formore » the comprehensive characterization of hydrate-bearing sediments at in situ, with the design recognizing past developments and characterization experience and benefited from the inspiration of nature and sensor miniaturization.« less

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.

Humanlike Robots - Synthetically Mimicking Humans

NASA Technical Reports Server (NTRS)

Bar-Cohen, Yoseph

2012-01-01

Nature inspired many inventions and the field of technology that is based on the mimicking or inspiration of nature is widely known as Biomimetics and it is increasingly leading to many new capabilities. There are numerous examples of biomimetic successes including the copying of fins for swimming, and the inspiration of the insects and birds flight. More and more commercial implementations of biomimetics are appearing and behaving lifelike and applications are emerging that are important to our daily life. Making humanlike robots is the ultimate challenge to biomimetics and, for many years, it was considered science fiction, but such robots are becoming an engineering reality. Advances in producing such robot are allowing them to perform impressive functions and tasks. The development of such robots involves addressing many challenges and is raising concerns that are related to fear of their application implications and potential ethical issues. In this paper, the state-of-the-art of humanlike robots, potential applications and challenges will be reviewed.

Inspiring Collaboration: The Legacy of Theo Colborn's Transdisciplinary Research on Fracking.

PubMed

Wylie, Sara; Schultz, Kim; Thomas, Deborah; Kassotis, Chris; Nagel, Susan

2016-09-13

This article describes Dr Theo Colborn's legacy of inspiring complementary and synergistic environmental health research and advocacy. Colborn, a founder of endocrine disruption research, also stimulated study of hydraulic fracturing (fracking). In 2014, the United States led the world in oil and gas production, with fifteen million Americans living within one mile of an oil or gas well. Colborn pioneered efforts to understand and control the impacts of this sea change in energy production. In 2005, her research organization The Endocrine Disruption Exchange (TEDX) developed a database of chemicals used in natural gas extraction and their health effects. This database stimulated novel scientific and social scientific research and informed advocacy by (1) connecting communities' diverse health impacts to chemicals used in natural gas development, (2) inspiring social science research on open-source software and hardware for citizen science, and (3) posing new scientific questions about the endocrine-disrupting properties of fracking chemicals. © The Author(s) 2016.

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.

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.

Multivariable bio-inspired photonic sensors for non-condensable gases

NASA Astrophysics Data System (ADS)

Potyrailo, Radislav A.; Karker, Nicholas; Carpenter, Michael A.; Minnick, Andrew

2018-02-01

Existing gas sensors often lose their measurement accuracy in practical field applications. To mitigate this significant problem, here, we report a demonstration of fabricated multivariable photonic sensors inspired by a known nanostructure of Morpho butterfly scales for detection of exemplary non-condensable gases such as H2, CO, and CO2. We fabricated bio-inspired nanostructures using conventional photolithography and chemical etching and detected individual gases that were difficult or unrealistic to detect using natural Morpho nanostructures. Such bio-inspired gas sensors are the critical step in the development of new sensors with improved accuracy for diverse operational scenarios. While this report is our initial demonstration of responses of fabricated multivariable sensors to individual gases in pristine laboratory conditions, it is a significant milestone in understanding the next steps toward field tests and practical applications of these sensors.

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.

Plants as model in biomimetics and biorobotics: new perspectives.

PubMed

Mazzolai, Barbara; Beccai, Lucia; Mattoli, Virgilio

2014-01-01

Especially in robotics, rarely plants have been considered as a model of inspiration for designing and developing new technology. This is probably due to their radically different operational principles compared to animals and the difficulty to study their movements and features. Owing to the sessile nature of their lifestyle, plants have evolved the capability to respond to a wide range of signals and efficiently adapt to changing environmental conditions. Plants in fact are able to show considerable plasticity in their morphology and physiology in response to variability within their environment. This results in movements that are characterized by energy efficiency and high density. Plant materials are optimized to reduce energy consumption during motion and these capabilities offer a plethora of solutions in the artificial world, exploiting approaches that are muscle-free and thus not necessarily animal-like. Plant roots then are excellent natural diggers, and their characteristics such as adaptive growth, low energy consumption movements, and the capability of penetrating soil at any angle are interesting from an engineering perspective. A few examples are described to lay the perspectives of plants in the artificial world.

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.

Modified harmony search

NASA Astrophysics Data System (ADS)

Mohamed, Najihah; Lutfi Amri Ramli, Ahmad; Majid, Ahmad Abd; Piah, Abd Rahni Mt

2017-09-01

A metaheuristic algorithm, called Harmony Search is quite highly applied in optimizing parameters in many areas. HS is a derivative-free real parameter optimization algorithm, and draws an inspiration from the musical improvisation process of searching for a perfect state of harmony. Propose in this paper Modified Harmony Search for solving optimization problems, which employs a concept from genetic algorithm method and particle swarm optimization for generating new solution vectors that enhances the performance of HS algorithm. The performances of MHS and HS are investigated on ten benchmark optimization problems in order to make a comparison to reflect the efficiency of the MHS in terms of final accuracy, convergence speed and robustness.

Thinking outside the Four Walls of the Classroom: A Canadian Nature Kindergarten

ERIC Educational Resources Information Center

Elliot, Enid; Krusekopf, Frances

2017-01-01

The authors share a narrative of planning and implementing a Nature Kindergarten in the public school system in British Columbia, Canada. Inspired by similar programs in Northern Europe, the Nature Kindergarten became the first program of its kind in Western Canada. The importance of developing pedagogical principles, understanding local context…

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

Artificially Engineered Protein Polymers.

PubMed

Yang, Yun Jung; Holmberg, Angela L; Olsen, Bradley D

2017-06-07

Modern polymer science increasingly requires precise control over macromolecular structure and properties for engineering advanced materials and biomedical systems. The application of biological processes to design and synthesize artificial protein polymers offers a means for furthering macromolecular tunability, enabling polymers with dispersities of ∼1.0 and monomer-level sequence control. Taking inspiration from materials evolved in nature, scientists have created modular building blocks with simplified monomer sequences that replicate the function of natural systems. The corresponding protein engineering toolbox has enabled the systematic development of complex functional polymeric materials across areas as diverse as adhesives, responsive polymers, and medical materials. This review discusses the natural proteins that have inspired the development of key building blocks for protein polymer engineering and the function of these elements in material design. The prospects and progress for scalable commercialization of protein polymers are reviewed, discussing both technology needs and opportunities.

Solid oxide fuel cell anode image segmentation based on a novel quantum-inspired fuzzy clustering

NASA Astrophysics Data System (ADS)

Fu, Xiaowei; Xiang, Yuhan; Chen, Li; Xu, Xin; Li, Xi

2015-12-01

High quality microstructure modeling can optimize the design of fuel cells. For three-phase accurate identification of Solid Oxide Fuel Cell (SOFC) microstructure, this paper proposes a novel image segmentation method on YSZ/Ni anode Optical Microscopic (OM) images. According to Quantum Signal Processing (QSP), the proposed approach exploits a quantum-inspired adaptive fuzziness factor to adaptively estimate the energy function in the fuzzy system based on Markov Random Filed (MRF). Before defuzzification, a quantum-inspired probability distribution based on distance and gray correction is proposed, which can adaptively adjust the inaccurate probability estimation of uncertain points caused by noises and edge points. In this study, the proposed method improves accuracy and effectiveness of three-phase identification on the micro-investigation. It provides firm foundation to investigate the microstructural evolution and its related properties.

High-performance mussel-inspired adhesives of reduced complexity.

PubMed

Ahn, B Kollbe; Das, Saurabh; Linstadt, Roscoe; Kaufman, Yair; Martinez-Rodriguez, Nadine R; Mirshafian, Razieh; Kesselman, Ellina; Talmon, Yeshayahu; Lipshutz, Bruce H; Israelachvili, Jacob N; Waite, J Herbert

2015-10-19

Despite the recent progress in and demand for wet adhesives, practical underwater adhesion remains limited or non-existent for diverse applications. Translation of mussel-inspired wet adhesion typically entails catechol functionalization of polymers and/or polyelectrolytes, and solution processing of many complex components and steps that require optimization and stabilization. Here we reduced the complexity of a wet adhesive primer to synthetic low-molecular-weight catecholic zwitterionic surfactants that show very strong adhesion (∼50 mJ m(-2)) and retain the ability to coacervate. This catecholic zwitterion adheres to diverse surfaces and self-assembles into a molecularly smooth, thin (<4 nm) and strong glue layer. The catecholic zwitterion holds particular promise as an adhesive for nanofabrication. This study significantly simplifies bio-inspired themes for wet adhesion by combining catechol with hydrophobic and electrostatic functional groups in a small molecule.

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.

Real-time immune-inspired optimum state-of-charge trajectory estimation using upcoming route information preview and neural networks for plug-in hybrid electric vehicles fuel economy

NASA Astrophysics Data System (ADS)

Mozaffari, Ahmad; Vajedi, Mahyar; Azad, Nasser L.

2015-06-01

The main proposition of the current investigation is to develop a computational intelligence-based framework which can be used for the real-time estimation of optimum battery state-of-charge (SOC) trajectory in plug-in hybrid electric vehicles (PHEVs). The estimated SOC trajectory can be then employed for an intelligent power management to significantly improve the fuel economy of the vehicle. The devised intelligent SOC trajectory builder takes advantage of the upcoming route information preview to achieve the lowest possible total cost of electricity and fossil fuel. To reduce the complexity of real-time optimization, the authors propose an immune system-based clustering approach which allows categorizing the route information into a predefined number of segments. The intelligent real-time optimizer is also inspired on the basis of interactions in biological immune systems, and is called artificial immune algorithm (AIA). The objective function of the optimizer is derived from a computationally efficient artificial neural network (ANN) which is trained by a database obtained from a high-fidelity model of the vehicle built in the Autonomie software. The simulation results demonstrate that the integration of immune inspired clustering tool, AIA and ANN, will result in a powerful framework which can generate a near global optimum SOC trajectory for the baseline vehicle, that is, the Toyota Prius PHEV. The outcomes of the current investigation prove that by taking advantage of intelligent approaches, it is possible to design a computationally efficient and powerful SOC trajectory builder for the intelligent power management of PHEVs.

INTO THE LAIR: GRAVITATIONAL-WAVE SIGNATURES OF DARK MATTER

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

Macedo, Caio F. B.; Cardoso, Vitor; Crispino, Luis C. B.

The nature and properties of dark matter (DM) are both outstanding issues in physics. Besides clustering in halos, the universal character of gravity implies that self-gravitating compact DM configurations-predicted by various models-might be spread throughout the universe. Their astrophysical signature can be used to probe fundamental particle physics, or to test alternative descriptions of compact objects in active galactic nuclei. Here, we discuss the most promising dissection tool of such configurations: the inspiral of a compact stellar-size object and consequent gravitational-wave (GW) emission. The inward motion of this ''test probe'' encodes unique information about the nature of the supermassive configuration.more » When the probe travels through some compact region we show, within a Newtonian approximation, that the quasi-adiabatic inspiral is mainly driven by DM accretion and by dynamical friction, rather than by radiation reaction. When accretion dominates, the frequency and amplitude of the GW signal produced during the latest stages of the inspiral are nearly constant. In the exterior region we study a model in which the inspiral is driven by GW and scalar-wave emission, described at a fully relativistic level. Resonances in the energy flux appear whenever the orbital frequency matches the effective mass of the DM particle, corresponding to the excitation of the central object's quasinormal frequencies. Unexpectedly, these resonances can lead to large dephasing with respect to standard inspiral templates, to such an extent as to prevent detection with matched filtering techniques. We discuss some observational consequences of these effects for GW detection.« less

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.

Bio-inspired photon detection using chromophore/nanotube hybrids (Conference Presentation)

NASA Astrophysics Data System (ADS)

Léonard, François

2017-05-01

The human eye is an exquisite optical system with the ability to detect individual photons at room temperature. However, the complexity of this system, optimized over millions of years, has been difficult to reproduce using synthetic techniques. Here we discuss a bio-inspired approach for photon detection based on chromophore/nanotube hybrids, where the chromophore plays a similar role to the retinal molecule in the human eye, and the signal transduction is provided by electronic transport in the carbon nanotube. In this presentation, I will present the concept and discuss our progress in realizing this type of photodetection mechanism.

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

Les nanostructures pour créer de la couleur, un art inspiré par la nature

NASA Astrophysics Data System (ADS)

Ball, Philip

2018-02-01

Les reflets changeants des plumes de la queue du paon ont captivé plus d'un esprit curieux. Le scientifique anglais Robert Hooke les qualifiait en 1665 de « surnaturelles » en constatant que, mouillées, elles perdaient leurs couleurs. À l'aide du microscope inventé depuis peu, il observa ces plumes, et découvrit qu'elles étaient couvertes de stries - qu'il suspecta d'être à l'origine des couleurs. Aujourd'hui, la recherche tente de s'inspirer de ces phénomènes : des applications « bio-inspirées » sont en voie de concrétisation. ARRAY(0x29ad218)

Fly-ear inspired acoustic sensors for gunshot localization

NASA Astrophysics Data System (ADS)

Liu, Haijun; Currano, Luke; Gee, Danny; Yang, Benjamin; Yu, Miao

2009-05-01

The supersensitive ears of the parasitoid fly Ormia ochracea have inspired researchers to develop bio-inspired directional microphone for sound localization. Although the fly ear is optimized for localizing the narrow-band calling song of crickets at 5 kHz, experiments and simulation have shown that it can amplify directional cues for a wide frequency range. In this article, a theoretical investigation is presented to study the use of fly-ear inspired directional microphones for gunshot localization. Using an equivalent 2-DOF model of the fly ear, the time responses of the fly ear structure to a typical shock wave are obtained and the associated time delay is estimated by using cross-correlation. Both near-field and far-field scenarios are considered. The simulation shows that the fly ear can greatly amplify the time delay by ~20 times, which indicates that with an interaural distance of only 1.2 mm the fly ear is able to generate a time delay comparable to that obtained by a conventional microphone pair with a separation as large as 24 mm. Since the parameters of the fly ear structure can also be tuned for muzzle blast and other impulse stimulus, fly-ear inspired acoustic sensors offers great potential for developing portable gunshot localization systems.

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

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.

Fire Process Research Natural Areas: Managing research and restoration of dynamic ecosystem processes

Treesearch

Timothy Ingalsbee

2001-01-01

Since 1992 a collaborative group of fire scientists, forest conservationists, and Federal resource specialists have been developing proposals for a Research Natural Area (RNA) in the Warner Creek Fire area on the Willamette National Forest in Oregon. Inspired by these proposals, the Oregon Natural Heritage Plan created the new category of "Fire Process RNAs"...

Bio-inspired ``jigsaw''-like interlocking sutures: Modeling, optimization, 3D printing and testing

NASA Astrophysics Data System (ADS)

Malik, I. A.; Mirkhalaf, M.; Barthelat, F.

2017-05-01

Structural biological materials such as bone, teeth or mollusk shells draw their remarkable performance from a sophisticated interplay of architectures and weak interfaces. Pushed to the extreme, this concept leads to sutured materials, which contain thin lines with complex geometries. Sutured materials are prominent in nature, and have recently served as bioinspiration for toughened ceramics and glasses. Sutures can generate large deformations, toughness and damping in otherwise all brittle systems and materials. In this study we examine the design and optimization of sutures with a jigsaw puzzle-like geometry, focusing on the non-linear traction behavior generated by the frictional pullout of the jigsaw tabs. We present analytical models which accurately predict the entire pullout response. Pullout strength and energy absorption increase with higher interlocking angles and for higher coefficients of friction, but the associated high stresses in the solid may fracture the tabs. Systematic optimization reveals a counter-intuitive result: the best pullout performance is achieved with interfaces with low coefficient of friction and high interlocking angle. We finally use 3D printing and mechanical testing to verify the accuracy of the models and of the optimization. The models and guidelines we present here can be extended to other types of geometries and sutured materials subjected to other loading/boundary conditions. The nonlinear responses of sutures are particularly attractive to augment the properties and functionalities of inherently brittle materials such as ceramics and glasses.

Astronomy Adventures.

ERIC Educational Resources Information Center

Braus, Judy, Ed.

1986-01-01

Ranger Rick's NatureScope is a creative education series dedicated to inspiring in children an understanding and appreciation of the natural world while developing the skills they will need to make responsible decisions about the environment. The topic of this issue is "Astronomy Adventures." Contents are organized into the following…

Amazing Mammals Part II.

ERIC Educational Resources Information Center

Braus, Judy, Ed.

1989-01-01

Ranger Rick's NatureScope is a creative education series dedicated to inspiring in children an understanding and appreciation of the natural world while developing the skills they will need to make responsible decisions about the environment. Contents are organized into the following sections: (1) "The Primates," including information…

Rangeland Ecosystem Services: Nature's Supply and Humans' Demand

USDA-ARS?s Scientific Manuscript database

Ecosystem services are the benefits that society receives from nature and they include the regulation of climate, the pollination of crops, the provisioning of intellectual inspiration and recreational environment, as well as many essential goods such as food, fiber, and wood. Rangeland ecosystem se...

Insights from nature for cybersecurity.

PubMed

Rzeszutko, Elżbieta; Mazurczyk, Wojciech

2015-01-01

The alarming rise in the quantity of malware in the past few years poses a serious challenge to the security community and requires urgent response. However, current countermeasures seem no longer to be effective. Thus, it is our belief that it is now time for researchers and security experts to turn to nature in the search for novel inspiration for defense systems. Nature has provided species with a whole range of offensive and defensive techniques, which have been developing and improving over the course of billions of years of evolution. Extremely diverse living conditions have promoted a large variation in the devised biosecurity solutions. In this article we introduce a novel Protection framework in which common denominators of the encountered offensive and defensive means are proposed and presented. The bio-inspired solutions are discussed in the context of cybersecurity, where some principles have already been adopted. The deployment of the whole nature-based framework should aid in the design and improvement of modern cyberdefense systems.

Ringed Seal Search for Global Optimization via a Sensitive Search Model.

PubMed

Saadi, Younes; Yanto, Iwan Tri Riyadi; Herawan, Tutut; Balakrishnan, Vimala; Chiroma, Haruna; Risnumawan, Anhar

2016-01-01

The efficiency of a metaheuristic algorithm for global optimization is based on its ability to search and find the global optimum. However, a good search often requires to be balanced between exploration and exploitation of the search space. In this paper, a new metaheuristic algorithm called Ringed Seal Search (RSS) is introduced. It is inspired by the natural behavior of the seal pup. This algorithm mimics the seal pup movement behavior and its ability to search and choose the best lair to escape predators. The scenario starts once the seal mother gives birth to a new pup in a birthing lair that is constructed for this purpose. The seal pup strategy consists of searching and selecting the best lair by performing a random walk to find a new lair. Affected by the sensitive nature of seals against external noise emitted by predators, the random walk of the seal pup takes two different search states, normal state and urgent state. In the normal state, the pup performs an intensive search between closely adjacent lairs; this movement is modeled via a Brownian walk. In an urgent state, the pup leaves the proximity area and performs an extensive search to find a new lair from sparse targets; this movement is modeled via a Levy walk. The switch between these two states is realized by the random noise emitted by predators. The algorithm keeps switching between normal and urgent states until the global optimum is reached. Tests and validations were performed using fifteen benchmark test functions to compare the performance of RSS with other baseline algorithms. The results show that RSS is more efficient than Genetic Algorithm, Particles Swarm Optimization and Cuckoo Search in terms of convergence rate to the global optimum. The RSS shows an improvement in terms of balance between exploration (extensive) and exploitation (intensive) of the search space. The RSS can efficiently mimic seal pups behavior to find best lair and provide a new algorithm to be used in global optimization problems.

Extended non-local games and monogamy-of-entanglement games.

PubMed

Johnston, Nathaniel; Mittal, Rajat; Russo, Vincent; Watrous, John

2016-05-01

We study a generalization of non-local games-which we call extended non-local games -in which the players, Alice and Bob, initially share a tripartite quantum state with the referee. In such games, the winning conditions for Alice and Bob may depend on the outcomes of measurements made by the referee, on its part of the shared quantum state, in addition to Alice and Bob's answers to randomly selected questions. Our study of this class of games was inspired by the monogamy-of-entanglement games introduced by Tomamichel, Fehr, Kaniewski and Wehner, which they also generalize. We prove that a natural extension of the Navascués-Pironio-Acín hierarchy of semidefinite programmes converges to the optimal commuting measurement value of extended non-local games, and we prove two extensions of results of Tomamichel et al.  concerning monogamy-of-entanglement games.

On flaw tolerance of nacre: a theoretical study

PubMed Central

Shao, Yue; Zhao, Hong-Ping; Feng, Xi-Qiao

2014-01-01

As a natural composite, nacre has an elegant staggered ‘brick-and-mortar’ microstructure consisting of mineral platelets glued by organic macromolecules, which endows the material with superior mechanical properties to achieve its biological functions. In this paper, a microstructure-based crack-bridging model is employed to investigate how the strength of nacre is affected by pre-existing structural defects. Our analysis demonstrates that owing to its special microstructure and the toughening effect of platelets, nacre has a superior flaw-tolerance feature. The maximal crack size that does not evidently reduce the tensile strength of nacre is up to tens of micrometres, about three orders higher than that of pure aragonite. Through dimensional analysis, a non-dimensional parameter is proposed to quantify the flaw-tolerance ability of nacreous materials in a wide range of structural parameters. This study provides us some inspirations for optimal design of advanced biomimetic composites. PMID:24402917

Prevention and schizophrenia--the role of dietary factors.

PubMed

McGrath, John; Brown, Alan; St Clair, David

2011-03-01

Adequate prenatal nutrition is essential for optimal brain development. There is a growing body of evidence from epidemiology linking exposure to nutritional deprivation and increased risk of schizophrenia. Based on studies from the Netherlands and China, those exposed to macronutrient deficiencies during famine have an increased risk of schizophrenia. With respect to micronutrients, we focus on 3 candidates where there is biological plausibility for a role in this disorder and at least 1 study of an association with schizophrenia. These nutrients include vitamin D, folic acid, and iron. While the current evidence is incomplete, we discuss the potential implications of these findings for the prevention of schizophrenia. We argue that schizophrenia can draw inspiration from public health interventions related to prenatal nutrition and other outcomes and speculate on relevant factors that bear on the nature, risks, impact, and logistics of various nutritional strategies that may be employed to prevent this disorder.

Air flow optimization for energy efficient blower of biosafety cabinet class II A2

NASA Astrophysics Data System (ADS)

Ibrahim, M. D.; Mohtar, M. Z.; Alias, A. A.; Wong, L. K.; Yunos, Y. S.; Rahman, M. R. A.; Zulkharnain, A.; Tan, C. S.; Thayan, R.

2017-04-01

An energy efficient Biosafety Cabinet (BSC) has become a big challenge for manufacturers to develop BSC with the highest level of protection. The objective of research is to increase air flow velocity discharge from centrifugal blower. An aerodynamic duct shape inspired by the shape of Peregrine Falcon’s wing during diving flight is added to the end of the centrifugal blower. Investigation of air movement is determined by computational fluid dynamics (CFD) simulation. The results showed that air velocity can be increased by double compared to typical manufactured BSC and no air recirculation. As conclusion, a novel design of aerodynamic duct shape successfully developed and proved that air velocity can be increase naturally with same impeller speed. It can contribute in increasing energy efficiency of the centrifugal blower. It is vital to BSC manufacturer and can be apply to Heating, Air Ventilation and Air Conditioning (HVAC) industries.

A simplified genetic design for mammalian enamel

PubMed Central

Snead, ML; Zhu, D; Lei, YP; Luo, W; Bringas, P.; Sucov, H.; Rauth, RJ; Paine, ML; White, SN

2011-01-01

A biomimetic replacement for tooth enamel is urgently needed because dental caries is the most prevalent infectious disease to affect man. Here, design specifications for an enamel replacement material inspired by Nature are deployed for testing in an animal model. Using genetic engineering we created a simplified enamel protein matrix precursor where only one, rather than dozens of amelogenin isoforms, contributed to enamel formation. Enamel function and architecture were unaltered, but the balance between the competing materials properties of hardness and toughness was modulated. While the other amelogenin isoforms make a modest contribution to optimal biomechanical design, the enamel made with only one amelogenin isoform served as a functional substitute. Where enamel has been lost to caries or trauma a suitable biomimetic replacement material could be fabricated using only one amelogenin isoform, thereby simplifying the protein matrix parameters by one order of magnitude. PMID:21295848

Extended non-local games and monogamy-of-entanglement games

PubMed Central

Johnston, Nathaniel; Mittal, Rajat; Watrous, John

2016-01-01

We study a generalization of non-local games—which we call extended non-local games—in which the players, Alice and Bob, initially share a tripartite quantum state with the referee. In such games, the winning conditions for Alice and Bob may depend on the outcomes of measurements made by the referee, on its part of the shared quantum state, in addition to Alice and Bob's answers to randomly selected questions. Our study of this class of games was inspired by the monogamy-of-entanglement games introduced by Tomamichel, Fehr, Kaniewski and Wehner, which they also generalize. We prove that a natural extension of the Navascués–Pironio–Acín hierarchy of semidefinite programmes converges to the optimal commuting measurement value of extended non-local games, and we prove two extensions of results of Tomamichel et al. concerning monogamy-of-entanglement games. PMID:27279771

Selective binding of choline by a phosphate-coordination-based triple helicate featuring an aromatic box

DOE PAGES

Jia, Chuandong; Zuo, Wei; Yang, Dong; ...

2017-10-16

In nature, proteins have evolved sophisticated cavities tailored for capturing target guests selectively among competitors of similar size, shape, and charge. The fundamental principles guiding the molecular recognition, such as self-assembly and complementarity, have inspired the development of biomimetic receptors. In the current work, we report a self-assembled triple anion helicate (host 2) featuring a cavity resembling that of the choline-binding protein ChoX, as revealed by crystal and density functional theory (DFT)-optimized structures, which binds choline in a unique dual-site-binding mode. Here, this similarity in structure leads to a similarly high selectivity of host 2 for choline over its derivatives,more » as demonstrated by the NMR and fluorescence competition experiments. Furthermore, host 2 is able to act as a fluorescence displacement sensor for discriminating choline, acetylcholine, l-carnitine, and glycine betaine effectively.« less

Polarization and dispersion properties of elliptical hole golden spiral photonic crystal fiber

NASA Astrophysics Data System (ADS)

Agrawal, A.; Kejalakshmy, N.; Rahman, B. M. A.; Grattan, K. T. V.

2010-06-01

An elliptical air-hole golden spiral photonic crystal fiber (EGS-PCF) is analyzed with the full-vectorial finite element method. The air-holes in the EGS-PCF are arranged in a spiral pattern governed by the Golden Ratio, where the design has been inspired by the optimal arrangement of seeds found in nature. The EGS-PCF exhibits extremely high birefringence (˜0.022 at operating wavelength 1550 nm) which is particularly useful for generating a polarization stable supercontinuum (SC). The fiber can also be designed to have a Zero Dispersion Wavelength (ZDW) at a suitable wavelength for only one polarization and large negative dispersion for the other, leading to a single-polarization SC. In addition, the fiber dispersion can be designed to obtain ZDWs at 800 nm and 1064 nm simultaneously, which can facilitate broadband supercontinuum generation (SCG) through multi-wavelength pumping.

Porphyrins at interfaces

NASA Astrophysics Data System (ADS)

Auwärter, Willi; Écija, David; Klappenberger, Florian; Barth, Johannes V.

2015-02-01

Porphyrins and other tetrapyrrole macrocycles possess an impressive variety of functional properties that have been exploited in natural and artificial systems. Different metal centres incorporated within the tetradentate ligand are key for achieving and regulating vital processes, including reversible axial ligation of adducts, electron transfer, light-harvesting and catalytic transformations. Tailored substituents optimize their performance, dictating their arrangement in specific environments and mediating the assembly of molecular nanoarchitectures. Here we review the current understanding of these species at well-defined interfaces, disclosing exquisite insights into their structural and chemical properties, and also discussing methods by which to manipulate their intramolecular and organizational features. The distinct characteristics arising from the interfacial confinement offer intriguing prospects for molecular science and advanced materials. We assess the role of surface interactions with respect to electronic and physicochemical characteristics, and describe in situ metallation pathways, molecular magnetism, rotation and switching. The engineering of nanostructures, organized layers, interfacial hybrid and bio-inspired systems is also addressed.

Harnessing out-of-plane deformation to design 3D architected lattice metamaterials with tunable Poisson's ratio.

PubMed

Li, Tiantian; Hu, Xiaoyi; Chen, Yanyu; Wang, Lifeng

2017-08-21

Auxetic materials exhibiting a negative Poisson's ratio are of great research interest due to their unusual mechanical responses and a wide range of potential deployment. Efforts have been devoted to exploring novel 2D and 3D auxetic structures through rational design, optimization, and taking inspiration from nature. Here we report a 3D architected lattice system showing a negative Poisson's ratio over a wide range of applied uniaxial stretch. 3D printing, experimental tests, numerical simulation, and analytical modeling are implemented to quantify the evolution of the Poisson's ratio and reveal the underlying mechanisms responsible for this unusual behavior. We further show that the auxetic behavior can be controlled by tailoring the geometric features of the ligaments. The findings reported here provide a new routine to design architected metamaterial systems exhibiting unusual properties and having a wide range of potential applications.

A synthetic redox biofilm made from metalloprotein-prion domain chimera nanowires

NASA Astrophysics Data System (ADS)

Altamura, Lucie; Horvath, Christophe; Rengaraj, Saravanan; Rongier, Anaëlle; Elouarzaki, Kamal; Gondran, Chantal; Maçon, Anthony L. B.; Vendrely, Charlotte; Bouchiat, Vincent; Fontecave, Marc; Mariolle, Denis; Rannou, Patrice; Le Goff, Alan; Duraffourg, Nicolas; Holzinger, Michael; Forge, Vincent

2017-02-01

Engineering bioelectronic components and set-ups that mimic natural systems is extremely challenging. Here we report the design of a protein-only redox film inspired by the architecture of bacterial electroactive biofilms. The nanowire scaffold is formed using a chimeric protein that results from the attachment of a prion domain to a rubredoxin (Rd) that acts as an electron carrier. The prion domain self-assembles into stable fibres and provides a suitable arrangement of redox metal centres in Rd to permit electron transport. This results in highly organized films, able to transport electrons over several micrometres through a network of bionanowires. We demonstrate that our bionanowires can be used as electron-transfer mediators to build a bioelectrode for the electrocatalytic oxygen reduction by laccase. This approach opens opportunities for the engineering of protein-only electron mediators (with tunable redox potentials and optimized interactions with enzymes) and applications in the field of protein-only bioelectrodes.

Cellulose-Based Biomimetics and Their Applications.

PubMed

Almeida, Ana P C; Canejo, João P; Fernandes, Susete N; Echeverria, Coro; Almeida, Pedro L; Godinho, Maria H

2018-05-01

Nature has been producing cellulose since long before man walked the surface of the earth. Millions of years of natural design and testing have resulted in cellulose-based structures that are an inspiration for the production of synthetic materials based on cellulose with properties that can mimic natural designs, functions, and properties. Here, five sections describe cellulose-based materials with characteristics that are inspired by gratings that exist on the petals of the plants, structurally colored materials, helical filaments produced by plants, water-responsive materials in plants, and environmental stimuli-responsive tissues found in insects and plants. The synthetic cellulose-based materials described herein are in the form of fibers and films. Fascinating multifunctional materials are prepared from cellulose-based liquid crystals and from composite cellulosic materials that combine functionality with structural performance. Future and recent applications are outlined. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Bridging the gap: basic metabolomics methods for natural product chemistry.

PubMed

Jones, Oliver A H; Hügel, Helmut M

2013-01-01

Natural products and their derivatives often have potent physiological activities and therefore play important roles as both frontline treatments for many diseases and as the inspiration for chemically synthesized therapeutics. However, the detection and synthesis of new therapeutic compounds derived from, or inspired by natural compounds has declined in recent years due to the increased difficulty of identifying and isolating novel active compounds. A new strategy is therefore necessary to jumpstart this field of research. Metabolomics, including both targeted and global metabolite profiling strategies, has the potential to be instrumental in this effort since it allows a systematic study of complex mixtures (such as plant extracts) without the need for prior isolation of active ingredients (or mixtures thereof). Here we describe the basic steps for conducting metabolomics experiments and analyzing the results using some of the more commonly used analytical and statistical methodologies.

Interior search algorithm (ISA): a novel approach for global optimization.

PubMed

Gandomi, Amir H

2014-07-01

This paper presents the interior search algorithm (ISA) as a novel method for solving optimization tasks. The proposed ISA is inspired by interior design and decoration. The algorithm is different from other metaheuristic algorithms and provides new insight for global optimization. The proposed method is verified using some benchmark mathematical and engineering problems commonly used in the area of optimization. ISA results are further compared with well-known optimization algorithms. The results show that the ISA is efficiently capable of solving optimization problems. The proposed algorithm can outperform the other well-known algorithms. Further, the proposed algorithm is very simple and it only has one parameter to tune. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Geo-hazard harmonised data a driven process to environmental analysis system

NASA Astrophysics Data System (ADS)

Cipolloni, Carlo; Iadanza, Carla; Pantaloni, Marco; Trigila, Alessandro

2015-04-01

In the last decade an increase of damage caused by natural disasters has been recorded in Italy. To support environmental safety and human protection, by reducing vulnerability of exposed elements as well as improving the resilience of the involved communities, it need to give access to harmonized and customized data that is one of several steps towards delivering adequate support to risk assessment, reduction and management. In this contest has been developed SEIS and Copernicus-GEMES as infrastructure based on web services for environmental analysis, to integrates in its own system specifications and results from INSPIRE. The two landslide risk scenarios developed in different European projects driven the harmonization process of data that represents the basic element to have interoperable web services in environmental analysis system. From two different perspective we have built a common methodology to analyse dataset and transform them into INSPIRE compliant format following the Data Specification on Geology and on Natural Risk Zone given by INSPIRE. To ensure the maximum results and re-usability of data we have also applied to the landslide and geological datasets a wider Data model standard like GeoSciML, that represents the natural extension of INSPIRE data model to provide more information. The aim of this work is to present the first results of two projects concerning the data harmonisation process, where an important role is played by the semantic harmonisation using the ontology service and/or the hierarchy vocabularies available as Link Data or Link Open Data by means of URI directly in the data spatial services. It will be presented how the harmonised web services can provide an add value in a risk scenario analysis system, showing the first results of the landslide environmental analysis developed by the eENVplus and LIFE+IMAGINE projects.

High-performance mussel-inspired adhesives of reduced complexity

PubMed Central

Ahn, B. Kollbe; Das, Saurabh; Linstadt, Roscoe; Kaufman, Yair; Martinez-Rodriguez, Nadine R.; Mirshafian, Razieh; Kesselman, Ellina; Talmon, Yeshayahu; Lipshutz, Bruce H.; Israelachvili, Jacob N.; Waite, J. Herbert

2015-01-01

Despite the recent progress in and demand for wet adhesives, practical underwater adhesion remains limited or non-existent for diverse applications. Translation of mussel-inspired wet adhesion typically entails catechol functionalization of polymers and/or polyelectrolytes, and solution processing of many complex components and steps that require optimization and stabilization. Here we reduced the complexity of a wet adhesive primer to synthetic low-molecular-weight catecholic zwitterionic surfactants that show very strong adhesion (∼50 mJ m−2) and retain the ability to coacervate. This catecholic zwitterion adheres to diverse surfaces and self-assembles into a molecularly smooth, thin (<4 nm) and strong glue layer. The catecholic zwitterion holds particular promise as an adhesive for nanofabrication. This study significantly simplifies bio-inspired themes for wet adhesion by combining catechol with hydrophobic and electrostatic functional groups in a small molecule. PMID:26478273

Training managers for high productivity: Guidelines and a case history

NASA Technical Reports Server (NTRS)

Ranftl, R. M.

1985-01-01

Hughes Aircrafts 13-year productivity study clearly identifies management as the key link in the entire productivity chain. This fact led to the establishment of a long-term series of seminars on personal, managerial, organizational, and operational productivity for all levels and sectors of line and staff management. To inspire the work force to higher levels of productivity and creativity management, itself, must first be inspired. In turn they have to clearly understand the productive and creative processes, fashion an effective productivity improvement plan with sound strategy and implementation, create an optimal environmental chemistry, and provide the outstanding leadership necessary to propel their organizations to achieve full potential. The primary goals of the seminars are to (1) ignite that spark of inspiration, enabling productive action to follow, (2) provide participants a credible roadmap and effective tools for implementation, and (3) develop a dedicated commitment to leadership and productivity throughout the management team.

Quadrupedal galloping control for a wide range of speed via vertical impulse scaling.

PubMed

Park, Hae-Won; Kim, Sangbae

2015-03-25

This paper presents a bio-inspired quadruped controller that allows variable-speed galloping. The controller design is inspired by observations from biological runners. Quadrupedal animals increase the vertical impulse that is generated by ground reaction forces at each stride as running speed increases and the duration of each stance phase reduces, whereas the swing phase stays relatively constant. Inspired by this observation, the presented controller estimates the required vertical impulse at each stride by applying the linear momentum conservation principle in the vertical direction and prescribes the ground reaction forces at each stride. The design process begins with deriving a planar model from the MIT Cheetah 2 robot. A baseline periodic limit cycle is obtained by optimizing ground reaction force profiles and the temporal gait pattern (timing and duration of gait phases). To stabilize the optimized limit cycle, the obtained limit cycle is converted to a state feedback controller by representing the obtained ground reaction force profiles as functions of the state variable, which is monotonically increasing throughout the gait, adding impedance control around the height and pitch trajectories of the obtained limit cycle and introducing a finite state machine and a pattern stabilizer to enforce the optimized gait pattern. The controller that achieves a stable 3 m s(-1) gallop successfully adapts the speed change by scaling the vertical ground reaction force to match the momentum lost by gravity and adding a simple speed controller that controls horizontal speed. Without requiring additional gait optimization processes, the controller achieves galloping at speeds ranging from 3 m s(-1) to 14.9 m s(-1) while respecting the torque limit of the motor used in the MIT Cheetah 2 robot. The robustness of the controller is verified by demonstrating stable running during various disturbances, including 1.49 m step down and 0.18 m step up, as well as random ground height and model parameter variations.

Sustainable Food Processing Inspired by Nature.

PubMed

Sybesma, Wilbert; Blank, Imre; Lee, Yuan-Kun

2017-04-01

Here, we elaborate on the natural origin and use of enzymes and cultures in sustainable food processing. We also illustrate how enzymatically treated or fermented food can contribute to solving challenges involving nutrition and health, such as aging, malnutrition, obesity, and allergy. Copyright © 2017. Published by Elsevier Ltd.

Diving into Oceans.

ERIC Educational Resources Information Center

Braus, Judy, Ed.

1992-01-01

Ranger Rick's NatureScope is a creative education series dedicated to inspiring in children an understanding and appreciation of the natural world while developing the skills they will need to make responsible decisions about the environment. The topic of this issue is "Diving Into Oceans." Contents are organized into the following…

Birds, Birds, Birds!

ERIC Educational Resources Information Center

Braus, Judy, Ed.

1992-01-01

Ranger Rick's Nature Scope is a creative education series dedicated to inspiring in children an understanding and appreciation of the natural world while developing the skills they will need to make responsible decisions about the environment. Contents are organized into the following sections: (1) "What Makes a Bird a Bird?," which…

Geology: The Active Earth.

ERIC Educational Resources Information Center

Braus, Judy, Ed.

1987-01-01

Ranger Rick's NatureScope is a creative education series dedicated to inspiring in children an understanding and appreciation of the natural world while developing the skills they will need to make responsible decisions about the environment. The topic of this issue is "Geology: The Active Earth." Contents are organized into the…

Summer Youth Forestry Institute

ERIC Educational Resources Information Center

Roesch, Gabrielle E.; Neuffer, Tamara; Zobrist, Kevin

2013-01-01

The Summer Youth Forestry Institute (SYFI) was developed to inspire youth through experiential learning opportunities and early work experience in the field of natural resources. Declining enrollments in forestry and other natural resource careers has made it necessary to actively engage youth and provide them with exposure to careers in these…

Rain Forests: Tropical Treasures.

ERIC Educational Resources Information Center

Braus, Judy, Ed.

1989-01-01

Ranger Rick's NatureScope is a creative education series dedicated to inspiring in children an understanding and appreciation of the natural world while developing the skills they will need to make responsible decisions about the environment. The topic of this issue is "Rain Forests: Tropical Treasures." Contents are organized into the…

Trees Are Terrific!

ERIC Educational Resources Information Center

Braus, Judy, Ed.

1992-01-01

Ranger Rick's NatureScope is a creative education series dedicated to inspiring in children an understanding and appreciation of the natural world while developing the skills they will need to make responsible decisions about the environment. Contents are organized into the following sections: (1) "What Makes a Tree a Tree?," including…

Wading into Wetlands.

ERIC Educational Resources Information Center

Braus, Judy, Ed.

1986-01-01

Ranger Rick's NatureScope is a creative education series dedicated to inspiring in children an understanding and appreciation of the natural world while developing the skills they will need to make responsible decisions about the environment. The topic of this issue is "Wading into Wetlands." Contents are organized into the following…

How to dip nectar: optimal time apportionment in natural viscous fluid transport

NASA Astrophysics Data System (ADS)

Wu, Jianing; Shi, Guanya; Zhao, Yiwei; Yan, Shaoze

2018-06-01

The mouthparts of some animals are highly evolved fluid transporters. Most honeybees dip viscous nectar in a cyclic fashion by using protrusible tongues with active hairs that can erect rhythmically. The glossal hairs flatten when the tongue extends into the nectar, and then erect outwards like an umbrella to catch nectar while retracting. This paper examines the potential capability of honeybees in allocating the duration of the tongue protraction and retraction phases for the sake of energy saving. A physical model is established to analyze energy consumption induced by viscous drag, considering tongue kinematics and variation of the surface profile in different phases of tongue movements. The results indicate that the theoretically optimal time apportionment ratio at which the energy consumption is the minimum, is directly related to the square root of the tongue’s diameter ratio between the protraction and retraction phase. Through dipping observations, we validate that the duration for the protraction and retraction phases show high accordance with the theoretical prediction. These findings not only broaden the insights into honeybee’s foraging strategy but inspire the design of high-performance microfluidic pumps with dynamic surfaces to transport viscous fluid.

Firefly Mating Algorithm for Continuous Optimization Problems

PubMed Central

Ritthipakdee, Amarita; Premasathian, Nol; Jitkongchuen, Duangjai

2017-01-01

This paper proposes a swarm intelligence algorithm, called firefly mating algorithm (FMA), for solving continuous optimization problems. FMA uses genetic algorithm as the core of the algorithm. The main feature of the algorithm is a novel mating pair selection method which is inspired by the following 2 mating behaviors of fireflies in nature: (i) the mutual attraction between males and females causes them to mate and (ii) fireflies of both sexes are of the multiple-mating type, mating with multiple opposite sex partners. A female continues mating until her spermatheca becomes full, and, in the same vein, a male can provide sperms for several females until his sperm reservoir is depleted. This new feature enhances the global convergence capability of the algorithm. The performance of FMA was tested with 20 benchmark functions (sixteen 30-dimensional functions and four 2-dimensional ones) against FA, ALC-PSO, COA, MCPSO, LWGSODE, MPSODDS, DFOA, SHPSOS, LSA, MPDPGA, DE, and GABC algorithms. The experimental results showed that the success rates of our proposed algorithm with these functions were higher than those of other algorithms and the proposed algorithm also required fewer numbers of iterations to reach the global optima. PMID:28808442

Firefly Mating Algorithm for Continuous Optimization Problems.

PubMed

Ritthipakdee, Amarita; Thammano, Arit; Premasathian, Nol; Jitkongchuen, Duangjai

2017-01-01

This paper proposes a swarm intelligence algorithm, called firefly mating algorithm (FMA), for solving continuous optimization problems. FMA uses genetic algorithm as the core of the algorithm. The main feature of the algorithm is a novel mating pair selection method which is inspired by the following 2 mating behaviors of fireflies in nature: (i) the mutual attraction between males and females causes them to mate and (ii) fireflies of both sexes are of the multiple-mating type, mating with multiple opposite sex partners. A female continues mating until her spermatheca becomes full, and, in the same vein, a male can provide sperms for several females until his sperm reservoir is depleted. This new feature enhances the global convergence capability of the algorithm. The performance of FMA was tested with 20 benchmark functions (sixteen 30-dimensional functions and four 2-dimensional ones) against FA, ALC-PSO, COA, MCPSO, LWGSODE, MPSODDS, DFOA, SHPSOS, LSA, MPDPGA, DE, and GABC algorithms. The experimental results showed that the success rates of our proposed algorithm with these functions were higher than those of other algorithms and the proposed algorithm also required fewer numbers of iterations to reach the global optima.

Ant algorithms for discrete optimization.

PubMed

Dorigo, M; Di Caro, G; Gambardella, L M

1999-01-01

This article presents an overview of recent work on ant algorithms, that is, algorithms for discrete optimization that took inspiration from the observation of ant colonies' foraging behavior, and introduces the ant colony optimization (ACO) metaheuristic. In the first part of the article the basic biological findings on real ants are reviewed and their artificial counterparts as well as the ACO metaheuristic are defined. In the second part of the article a number of applications of ACO algorithms to combinatorial optimization and routing in communications networks are described. We conclude with a discussion of related work and of some of the most important aspects of the ACO metaheuristic.

Grapple with a Giant Squid at the Natural History Museum's Darwin Centre

ERIC Educational Resources Information Center

Tinkler, Abigail; Collins, Sally

2009-01-01

The Natural History Museum's new Darwin Centre fulfils three main roles. It is a state-of-the-art scientific research and collections facility, but it is also an awe-inspiring new public space that allows visitors to explore the natural world in an exciting and innovative way. With its opening, students can experience the relevance of the science…

Maslow Revisited: Constructing a Road Map of Human Nature

ERIC Educational Resources Information Center

O'Connor, Dennis; Yballe, Leodones

2007-01-01

Given the scope and intent of Maslow's work, the current textbook treatment is wanting. Therefore, an inductive exercise has been created and is offered here to build "the road map of human nature." This age-old, philosophic focus on our true nature has been a way to successfully engage and inspire both our students and our pedagogy. In the spirit…

1-D DC Resistivity Modeling and Interpretation in Anisotropic Media Using Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Pekşen, Ertan; Yas, Türker; Kıyak, Alper

2014-09-01

We examine the one-dimensional direct current method in anisotropic earth formation. We derive an analytic expression of a simple, two-layered anisotropic earth model. Further, we also consider a horizontally layered anisotropic earth response with respect to the digital filter method, which yields a quasi-analytic solution over anisotropic media. These analytic and quasi-analytic solutions are useful tests for numerical codes. A two-dimensional finite difference earth model in anisotropic media is presented in order to generate a synthetic data set for a simple one-dimensional earth. Further, we propose a particle swarm optimization method for estimating the model parameters of a layered anisotropic earth model such as horizontal and vertical resistivities, and thickness. The particle swarm optimization is a naturally inspired meta-heuristic algorithm. The proposed method finds model parameters quite successfully based on synthetic and field data. However, adding 5 % Gaussian noise to the synthetic data increases the ambiguity of the value of the model parameters. For this reason, the results should be controlled by a number of statistical tests. In this study, we use probability density function within 95 % confidence interval, parameter variation of each iteration and frequency distribution of the model parameters to reduce the ambiguity. The result is promising and the proposed method can be used for evaluating one-dimensional direct current data in anisotropic media.

Rayleigh wave dispersion curve inversion by using particle swarm optimization and genetic algorithm

NASA Astrophysics Data System (ADS)

Buyuk, Ersin; Zor, Ekrem; Karaman, Abdullah

2017-04-01

Inversion of surface wave dispersion curves with its highly nonlinear nature has some difficulties using traditional linear inverse methods due to the need and strong dependence to the initial model, possibility of trapping in local minima and evaluation of partial derivatives. There are some modern global optimization methods to overcome of these difficulties in surface wave analysis such as Genetic algorithm (GA) and Particle Swarm Optimization (PSO). GA is based on biologic evolution consisting reproduction, crossover and mutation operations, while PSO algorithm developed after GA is inspired from the social behaviour of birds or fish of swarms. Utility of these methods require plausible convergence rate, acceptable relative error and optimum computation cost that are important for modelling studies. Even though PSO and GA processes are similar in appearence, the cross-over operation in GA is not used in PSO and the mutation operation is a stochastic process for changing the genes within chromosomes in GA. Unlike GA, the particles in PSO algorithm changes their position with logical velocities according to particle's own experience and swarm's experience. In this study, we applied PSO algorithm to estimate S wave velocities and thicknesses of the layered earth model by using Rayleigh wave dispersion curve and also compared these results with GA and we emphasize on the advantage of using PSO algorithm for geophysical modelling studies considering its rapid convergence, low misfit error and computation cost.

Endangered Species: Wild & Rare.

ERIC Educational Resources Information Center

Braus, Judy, Ed.

1987-01-01

Ranger Rick's NatureScope is a creative education series dedicated to inspiring in children an understanding and appreciation of the natural world while developing the skills they will need to make responsible decisions about the environment. The topic of this issue is "Endangered Species: Wild and Rare." Contents are organized into the…

Let's Hear It for Herps!

ERIC Educational Resources Information Center

Braus, Judy, Ed.

1987-01-01

Ranger Rick's NatureScope is a creative education series dedicated to inspiring in children an understanding and appreciation of the natural world while developing the skills they will need to make responsible decisions about the environment. The topic of this issue is "Let's Hear It for the Herps!" Contents are organized into the…

Inside Pasteur's Quadrant: Knowledge Production in a Profession

ERIC Educational Resources Information Center

Tierney, William G.; Holley, Karri A.

2008-01-01

In this paper, we examine the current state of educational research through the framework of "use-inspired" knowledge. Previous discussions regarding the nature of educational research have disproportionately focused on the soft/applied nature of knowledge in the discipline or a need for methodological priority. After acknowledging these…

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.

Empowering Learning through Natural, Human, and Building Ecologies.

ERIC Educational Resources Information Center

Kobet, Robert J.

This article asserts that it is critical to understand the connections between human ecology and building ecology to create humane environments that show inspiration and creativity and that also serve diverse needs. It calls for efforts to: (1) construct an environmental education approach that fuses the three ecologies (natural, human, and…

Teaching through Trade Books: Humans and the Earth

ERIC Educational Resources Information Center

Royce, Christine Anne

2016-01-01

This column includes activities inspired by children's literature. Elementary students are beginning to understand the Earth's natural processes and humans' impact on the Earth. Humans need the natural resources that the Earth produces, use these resources to develop civilizations, and make decisions to offset the damage they cause, as well as…

Bio-inspired, large scale, highly-scattering films for nanoparticle-alternative white surfaces

PubMed Central

Syurik, Julia; Siddique, Radwanul Hasan; Dollmann, Antje; Gomard, Guillaume; Schneider, Marc; Worgull, Matthias; Wiegand, Gabriele; Hölscher, Hendrik

2017-01-01

Inspired by the white beetle of the genus Cyphochilus, we fabricate ultra-thin, porous PMMA films by foaming with CO2 saturation. Optimising pore diameter and fraction in terms of broad-band reflectance results in very thin films with exceptional whiteness. Already films with 60 µm-thick scattering layer feature a whiteness with a reflectance of 90%. Even 9 µm thin scattering layers appear white with a reflectance above 57%. The transport mean free path in the artificial films is between 3.5 µm and 4 µm being close to the evolutionary optimised natural prototype. The bio-inspired white films do not lose their whiteness during further shaping, allowing for various applications. PMID:28429805

Bio-inspired, large scale, highly-scattering films for nanoparticle-alternative white surfaces

NASA Astrophysics Data System (ADS)

Syurik, Julia; Siddique, Radwanul Hasan; Dollmann, Antje; Gomard, Guillaume; Schneider, Marc; Worgull, Matthias; Wiegand, Gabriele; Hölscher, Hendrik

2017-04-01

Inspired by the white beetle of the genus Cyphochilus, we fabricate ultra-thin, porous PMMA films by foaming with CO2 saturation. Optimising pore diameter and fraction in terms of broad-band reflectance results in very thin films with exceptional whiteness. Already films with 60 µm-thick scattering layer feature a whiteness with a reflectance of 90%. Even 9 µm thin scattering layers appear white with a reflectance above 57%. The transport mean free path in the artificial films is between 3.5 µm and 4 µm being close to the evolutionary optimised natural prototype. The bio-inspired white films do not lose their whiteness during further shaping, allowing for various applications.

Metamaterial-inspired silicon nanophotonics

NASA Astrophysics Data System (ADS)

Staude, Isabelle; Schilling, Jörg

2017-04-01

The prospect of creating metamaterials with optical properties greatly exceeding the parameter space accessible with natural materials has been inspiring intense research efforts in nanophotonics for more than a decade. Following an era of plasmonic metamaterials, low-loss dielectric nanostructures have recently moved into the focus of metamaterial-related research. This development was mainly triggered by the experimental observation of electric and magnetic multipolar Mie-type resonances in high-refractive-index dielectric nanoparticles. Silicon in particular has emerged as a popular material choice, due to not only its high refractive index and very low absorption losses in the telecom spectral range, but also its paramount technological relevance. This Review overviews recent progress on metamaterial-inspired silicon nanostructures, including Mie-resonant and off-resonant regimes.

"Kind and Grateful": A Context-Sensitive Smartphone App Utilizing Inspirational Content to Promote Gratitude.

PubMed

Ghandeharioun, Asma; Azaria, Asaph; Taylor, Sara; Picard, Rosalind W

Previous research has shown that gratitude positively influences psychological wellbeing and physical health. Grateful people are reported to feel more optimistic and happy, to better mitigate aversive experiences, and to have stronger interpersonal bonds. Gratitude interventions have been shown to result in improved sleep, more frequent exercise and stronger cardiovascular and immune systems. These findings call for the development of technologies that would inspire gratitude. This paper presents a novel system designed toward this end. We leverage pervasive technologies to naturally embed inspiration to express gratitude in everyday life. Novel to this work, mobile sensor data is utilized to infer optimal moments for stimulating contextually relevant thankfulness and appreciation. Sporadic mood measurements are inventively obtained through the smartphone lock screen, investigating their interplay with grateful expressions. Both momentary thankful emotion and dispositional gratitude are measured. To evaluate our system, we ran two rounds of randomized control trials (RCT), including a pilot study (N = 15, 2 weeks) and a main study (N = 27, 5 weeks). Studies' participants were provided with a newly developed smartphone app through which they were asked to express gratitude; the app displayed inspirational content to only the intervention group, while measuring contextual cues for all users. In both rounds of the RCT, the intervention was associated with improved thankful behavior. Significant increase was observed in multiple facets of practicing gratitude in the intervention groups. The average frequency of practicing thankfulness increased by more than 120 %, comparing the baseline weeks with the intervention weeks of the main study. In contrast, the control group of the same study exhibited a decrease of 90 % in the frequency of thankful expressions. In the course of the study's 5 weeks, increases in dispositional gratitude and in psychological wellbeing were also apparent. Analyzing the relation between mood and gratitude expressions, our data suggest that practicing gratitude increases the probability of going up in terms of emotional valence and down in terms of emotional arousal. The influences of inspirational content and contextual cues on promoting thankful behavior were also analyzed: We present data suggesting that the more successful times for eliciting expressions of gratitude tend to be shortly after a social experience, shortly after location change, and shortly after physical activity. The results support our intervention as an impactful method to promote grateful affect and behavior. Moreover, they provide insights into design and evaluation of general behavioral intervention technologies.

Metal oxide resistive random access memory based synaptic devices for brain-inspired computing

NASA Astrophysics Data System (ADS)

Gao, Bin; Kang, Jinfeng; Zhou, Zheng; Chen, Zhe; Huang, Peng; Liu, Lifeng; Liu, Xiaoyan

2016-04-01

The traditional Boolean computing paradigm based on the von Neumann architecture is facing great challenges for future information technology applications such as big data, the Internet of Things (IoT), and wearable devices, due to the limited processing capability issues such as binary data storage and computing, non-parallel data processing, and the buses requirement between memory units and logic units. The brain-inspired neuromorphic computing paradigm is believed to be one of the promising solutions for realizing more complex functions with a lower cost. To perform such brain-inspired computing with a low cost and low power consumption, novel devices for use as electronic synapses are needed. Metal oxide resistive random access memory (ReRAM) devices have emerged as the leading candidate for electronic synapses. This paper comprehensively addresses the recent work on the design and optimization of metal oxide ReRAM-based synaptic devices. A performance enhancement methodology and optimized operation scheme to achieve analog resistive switching and low-energy training behavior are provided. A three-dimensional vertical synapse network architecture is proposed for high-density integration and low-cost fabrication. The impacts of the ReRAM synaptic device features on the performances of neuromorphic systems are also discussed on the basis of a constructed neuromorphic visual system with a pattern recognition function. Possible solutions to achieve the high recognition accuracy and efficiency of neuromorphic systems are presented.

Mimosa-inspired design of a flexible pressure sensor with touch sensitivity.

PubMed

Su, Bin; Gong, Shu; Ma, Zheng; Yap, Lim Wei; Cheng, Wenlong

2015-04-24

A bio-inspired flexible pressure sensor is generated with high sensitivity (50.17 kPa(-1)), quick responding time (<20 ms), and durable stability (negligible loading-unloading signal changes over 10 000 cycles). Notably, the key resource of surface microstructures upon sensor substrates results from the direct molding of natural mimosa leaves, presenting a simple, environment-friendly and easy scale-up fabrication process for these flexible pressure sensors. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Design of a bio-inspired controller for dynamic soaring in a simulated unmanned aerial vehicle.

PubMed

Barate, Renaud; Doncieux, Stéphane; Meyer, Jean-Arcady

2006-09-01

This paper is inspired by the way birds such as albatrosses are able to exploit wind gradients at the surface of the ocean for staying aloft for very long periods while minimizing their energy expenditure. The corresponding behaviour has been partially reproduced here via a set of Takagi-Sugeno-Kang fuzzy rules controlling a simulated glider. First, the rules were hand-designed. Then, they were optimized with an evolutionary algorithm that improved their efficiency at coping with challenging conditions. Finally, the robustness properties of the controller generated were assessed with a view to its applicability to a real platform.

Datacube Services in Action, Using Open Source and Open Standards

NASA Astrophysics Data System (ADS)

Baumann, P.; Misev, D.

2016-12-01

Array Databases comprise novel, promising technology for massive spatio-temporal datacubes, extending the SQL paradigm of "any query, anytime" to n-D arrays. On server side, such queries can be optimized, parallelized, and distributed based on partitioned array storage. The rasdaman ("raster data manager") system, which has pioneered Array Databases, is available in open source on www.rasdaman.org. Its declarative query language extends SQL with array operators which are optimized and parallelized on server side. The rasdaman engine, which is part of OSGeo Live, is mature and in operational use databases individually holding dozens of Terabytes. Further, the rasdaman concepts have strongly impacted international Big Data standards in the field, including the forthcoming MDA ("Multi-Dimensional Array") extension to ISO SQL, the OGC Web Coverage Service (WCS) and Web Coverage Processing Service (WCPS) standards, and the forthcoming INSPIRE WCS/WCPS; in both OGC and INSPIRE, OGC is WCS Core Reference Implementation. In our talk we present concepts, architecture, operational services, and standardization impact of open-source rasdaman, as well as experiences made.

Statistical-Mechanics-Inspired Optimization of Sensor Field Configuration for Detection of Mobile Targets (PREPRINT)

DTIC Science & Technology

2010-11-01

pected target motion. Along this line, Wettergren [5] analyzed the performance of the track - before - detect schemes for the sensor networks. Furthermore...dressed by Baumgartner and Ferrari [11] for the reorganization of the sensor field to achieve the maximum coverage. The track - before - detect -based optimal...confirming a target. In accordance with the track - before - detect paradigm [4], a moving target is detected if the kd (typically kd = 3 or 4) sensors detect

Swarm Intelligence Optimization and Its Applications

NASA Astrophysics Data System (ADS)

Ding, Caichang; Lu, Lu; Liu, Yuanchao; Peng, Wenxiu

Swarm Intelligence is a computational and behavioral metaphor for solving distributed problems inspired from biological examples provided by social insects such as ants, termites, bees, and wasps and by swarm, herd, flock, and shoal phenomena in vertebrates such as fish shoals and bird flocks. An example of successful research direction in Swarm Intelligence is ant colony optimization (ACO), which focuses on combinatorial optimization problems. Ant algorithms can be viewed as multi-agent systems (ant colony), where agents (individual ants) solve required tasks through cooperation in the same way that ants create complex social behavior from the combined efforts of individuals.

Bio-Inspired Controller on an FPGA Applied to Closed-Loop Diaphragmatic Stimulation

PubMed Central

Zbrzeski, Adeline; Bornat, Yannick; Hillen, Brian; Siu, Ricardo; Abbas, James; Jung, Ranu; Renaud, Sylvie

2016-01-01

Cervical spinal cord injury can disrupt connections between the brain respiratory network and the respiratory muscles which can lead to partial or complete loss of ventilatory control and require ventilatory assistance. Unlike current open-loop technology, a closed-loop diaphragmatic pacing system could overcome the drawbacks of manual titration as well as respond to changing ventilation requirements. We present an original bio-inspired assistive technology for real-time ventilation assistance, implemented in a digital configurable Field Programmable Gate Array (FPGA). The bio-inspired controller, which is a spiking neural network (SNN) inspired by the medullary respiratory network, is as robust as a classic controller while having a flexible, low-power and low-cost hardware design. The system was simulated in MATLAB with FPGA-specific constraints and tested with a computational model of rat breathing; the model reproduced experimentally collected respiratory data in eupneic animals. The open-loop version of the bio-inspired controller was implemented on the FPGA. Electrical test bench characterizations confirmed the system functionality. Open and closed-loop paradigm simulations were simulated to test the FPGA system real-time behavior using the rat computational model. The closed-loop system monitors breathing and changes in respiratory demands to drive diaphragmatic stimulation. The simulated results inform future acute animal experiments and constitute the first step toward the development of a neuromorphic, adaptive, compact, low-power, implantable device. The bio-inspired hardware design optimizes the FPGA resource and time costs while harnessing the computational power of spike-based neuromorphic hardware. Its real-time feature makes it suitable for in vivo applications. PMID:27378844

Quantum-Inspired Maximizer

NASA Technical Reports Server (NTRS)

Zak, Michail

2008-01-01

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

Swarm intelligence inspired shills and the evolution of cooperation.

PubMed

Duan, Haibin; Sun, Changhao

2014-06-09

Many hostile scenarios exist in real-life situations, where cooperation is disfavored and the collective behavior needs intervention for system efficiency improvement. Towards this end, the framework of soft control provides a powerful tool by introducing controllable agents called shills, who are allowed to follow well-designed updating rules for varying missions. Inspired by swarm intelligence emerging from flocks of birds, we explore here the dependence of the evolution of cooperation on soft control by an evolutionary iterated prisoner's dilemma (IPD) game staged on square lattices, where the shills adopt a particle swarm optimization (PSO) mechanism for strategy updating. We demonstrate that not only can cooperation be promoted by shills effectively seeking for potentially better strategies and spreading them to others, but also the frequency of cooperation could be arbitrarily controlled by choosing appropriate parameter settings. Moreover, we show that adding more shills does not contribute to further cooperation promotion, while assigning higher weights to the collective knowledge for strategy updating proves a efficient way to induce cooperative behavior. Our research provides insights into cooperation evolution in the presence of PSO-inspired shills and we hope it will be inspirational for future studies focusing on swarm intelligence based soft control.

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

PubMed

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

2015-06-16

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

Extremal Optimization: Methods Derived from Co-Evolution

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

Boettcher, S.; Percus, A.G.

1999-07-13

We describe a general-purpose method for finding high-quality solutions to hard optimization problems, inspired by self-organized critical models of co-evolution such as the Bak-Sneppen model. The method, called Extremal Optimization, successively eliminates extremely undesirable components of sub-optimal solutions, rather than ''breeding'' better components. In contrast to Genetic Algorithms which operate on an entire ''gene-pool'' of possible solutions, Extremal Optimization improves on a single candidate solution by treating each of its components as species co-evolving according to Darwinian principles. Unlike Simulated Annealing, its non-equilibrium approach effects an algorithm requiring few parameters to tune. With only one adjustable parameter, its performance provesmore » competitive with, and often superior to, more elaborate stochastic optimization procedures. We demonstrate it here on two classic hard optimization problems: graph partitioning and the traveling salesman problem.« less

Human Inspired Self-developmental Model of Neural Network (HIM): Introducing Content/Form Computing

NASA Astrophysics Data System (ADS)

Krajíček, Jiří

This paper presents cross-disciplinary research between medical/psychological evidence on human abilities and informatics needs to update current models in computer science to support alternative methods for computation and communication. In [10] we have already proposed hypothesis introducing concept of human information model (HIM) as cooperative system. Here we continue on HIM design in detail. In our design, first we introduce Content/Form computing system which is new principle of present methods in evolutionary computing (genetic algorithms, genetic programming). Then we apply this system on HIM (type of artificial neural network) model as basic network self-developmental paradigm. Main inspiration of our natural/human design comes from well known concept of artificial neural networks, medical/psychological evidence and Sheldrake theory of "Nature as Alive" [22].

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

Nature vs Nurture: Effects of Learning on Evolution

NASA Astrophysics Data System (ADS)

Nagrani, Nagina

In the field of Evolutionary Robotics, the design, development and application of artificial neural networks as controllers have derived their inspiration from biology. Biologists and artificial intelligence researchers are trying to understand the effects of neural network learning during the lifetime of the individuals on evolution of these individuals by qualitative and quantitative analyses. The conclusion of these analyses can help develop optimized artificial neural networks to perform any given task. The purpose of this thesis is to study the effects of learning on evolution. This has been done by applying Temporal Difference Reinforcement Learning methods to the evolution of Artificial Neural Tissue controller. The controller has been assigned the task to collect resources in a designated area in a simulated environment. The performance of the individuals is measured by the amount of resources collected. A comparison has been made between the results obtained by incorporating learning in evolution and evolution alone. The effects of learning parameters: learning rate, training period, discount rate, and policy on evolution have also been studied. It was observed that learning delays the performance of the evolving individuals over the generations. However, the non zero learning rate throughout the evolution process signifies natural selection preferring individuals possessing plasticity.

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.

Literature and the Land: Reading and Writing for Environmental Literacy, 7-12.

ERIC Educational Resources Information Center

Rous, Emma Wood

Not only inspiring teachers to help students become environmentally literate, this book also provides the tools to make it happen in the literature classroom. Beginning with readings and exercises about perception, it explores a wealth of nature writing activities, the history of people's relationship with nature from mythological times to the…

Joy of Nature, "Friluftsliv" Education and Self: Combining Narrative and Cultural-Ecological Approaches to Environmental Sustainability

ERIC Educational Resources Information Center

Gurholt, Kirsti Pedersen

2014-01-01

Autobiographies of prominent environmentalists describe that their early lives have been rich in personal experiences of nature. The early childhood experiences of philosopher and climber Arne Naess (1912-2009) inspired the development of deep ecology philosophy, which markedly influenced the emergence of Norwegian "friluftsliv"…

Colloidal-based additive manufacturing of bio-inspired composites

NASA Astrophysics Data System (ADS)

Studart, Andre R.

Composite materials in nature exhibit heterogeneous architectures that are tuned to fulfill the functional demands of the surrounding environment. Examples range from the cellulose-based organic structure of plants to highly mineralized collagen-based skeletal parts like bone and teeth. Because they are often utilized to combine opposing properties such as strength and low-density or stiffness and wear resistance, the heterogeneous architecture of natural materials can potentially address several of the technical limitations of artificial homogeneous composites. However, current man-made manufacturing technologies do not allow for the level of composition and fiber orientation control found in natural heterogeneous systems. In this talk, I will present two additive manufacturing technologies recently developed in our group to build composites with exquisite architectures only rivaled by structures made by living organisms in nature. Since the proposed techniques utilize colloidal suspensions as feedstock, understanding the physics underlying the stability, assembly and rheology of the printing inks is key to predict and control the architecture of manufactured parts. Our results will show that additive manufacturing routes offer a new exciting pathway for the fabrication of biologically-inspired composite materials with unprecedented architectures and functionalities.

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

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

Magic Trees in Mammalians Respiration or when Evolution Selected Clever Physical Systems

NASA Astrophysics Data System (ADS)

Sapoval, B.; Filoche, M.

2013-01-01

The respiratory system of mammalians is made of two successive branched structures with different physiological functions. The upper structure, or bronchial tree, is a fluid transportation system made of approximately 15 generations of bifurcations leading to the order of 215 = 30,000 bronchioles with a diameter of order 0.5 mm in the human lung.1 The branching pattern continues up to generation 23 but the structure and function of each of the subsequent structures, called the acini, is different. Each acinus is made of a branched system of ducts surrounded by alveolae and play the role of a diffusion cell where oxygen and carbon dioxide are exchanged with blood across the alveolar membrane.2 We show in this paper that the bronchial tree presents simultaneously several optimal properties of totally different nature. It is first energy efficient;3-6 second, it is space filling;7 and third it is "rapid" as discussed here. It is this multi-optimality that is qualified here as magic. The multi-optimality physical characteristic suggests that, in the course of evolution, an organ selected against one criterion could have been later used for a totally different reason. For example, once energetic efficiency for the transport of a viscous fluid like blood has been selected, the same genetic material could have been used for its optimized rapidity. This would have allowed the emergence of mammalian respiration made of inspiration-expiration cycles. For this phenomenon to exist, the rapid character is essential, as fresh air has to reach the gas exchange organs, the pulmonary acini, before the start of expiration.

Genetic Algorithm for Optimization: Preprocessor and Algorithm

NASA Technical Reports Server (NTRS)

Sen, S. K.; Shaykhian, Gholam A.

2006-01-01

Genetic algorithm (GA) inspired by Darwin's theory of evolution and employed to solve optimization problems - unconstrained or constrained - uses an evolutionary process. A GA has several parameters such the population size, search space, crossover and mutation probabilities, and fitness criterion. These parameters are not universally known/determined a priori for all problems. Depending on the problem at hand, these parameters need to be decided such that the resulting GA performs the best. We present here a preprocessor that achieves just that, i.e., it determines, for a specified problem, the foregoing parameters so that the consequent GA is a best for the problem. We stress also the need for such a preprocessor both for quality (error) and for cost (complexity) to produce the solution. The preprocessor includes, as its first step, making use of all the information such as that of nature/character of the function/system, search space, physical/laboratory experimentation (if already done/available), and the physical environment. It also includes the information that can be generated through any means - deterministic/nondeterministic/graphics. Instead of attempting a solution of the problem straightway through a GA without having/using the information/knowledge of the character of the system, we would do consciously a much better job of producing a solution by using the information generated/created in the very first step of the preprocessor. We, therefore, unstintingly advocate the use of a preprocessor to solve a real-world optimization problem including NP-complete ones before using the statistically most appropriate GA. We also include such a GA for unconstrained function optimization problems.

Harmony search method: theory and applications.

PubMed

Gao, X Z; Govindasamy, V; Xu, H; Wang, X; Zenger, K

2015-01-01

The Harmony Search (HS) method is an emerging metaheuristic optimization algorithm, which has been employed to cope with numerous challenging tasks during the past decade. In this paper, the essential theory and applications of the HS algorithm are first described and reviewed. Several typical variants of the original HS are next briefly explained. As an example of case study, a modified HS method inspired by the idea of Pareto-dominance-based ranking is also presented. It is further applied to handle a practical wind generator optimal design problem.

A new inertia weight control strategy for particle swarm optimization

NASA Astrophysics Data System (ADS)

Zhu, Xianming; Wang, Hongbo

2018-04-01

Particle Swarm Optimization is a member of swarm intelligence algorithms, which is inspired by the behavior of bird flocks. The inertia weight, one of the most important parameters of PSO, is crucial for PSO, for it balances the performance of exploration and exploitation of the algorithm. This paper proposes a new inertia weight control strategy and PSO with this new strategy is tested by four benchmark functions. The results shows that the new strategy provides the PSO with better performance.

Natural healing-inspired collagen-targeting surgical protein glue for accelerated scarless skin regeneration.

PubMed

Jeon, Eun Young; Choi, Bong-Hyuk; Jung, Dooyup; Hwang, Byeong Hee; Cha, Hyung Joon

2017-07-01

Skin scarring after deep dermal injuries is a major clinical problem due to the current therapies limited to established scars with poor understanding of healing mechanisms. From investigation of aberrations within the extracellular matrix involved in pathophysiologic scarring, it was revealed that one of the main factors responsible for impaired healing is abnormal collagen reorganization. Here, inspired by the fundamental roles of decorin, a collagen-targeting proteoglycan, in collagen remodeling, we created a scar-preventive collagen-targeting glue consisting of a newly designed collagen-binding mussel adhesive protein and a specific glycosaminoglycan. The collagen-targeting glue specifically bound to type I collagen in a dose-dependent manner and regulated the rate and the degree of fibrillogenesis. In a rat skin excisional model, the collagen-targeting glue successfully accelerated initial wound regeneration as defined by effective reepithelialization, neovascularization, and rapid collagen synthesis. Moreover, the improved dermal collagen architecture was demonstrated by uniform size of collagen fibrils, their regular packing, and a restoration of healthy tissue component. Collectively, our natural healing-inspired collagen-targeting glue may be a promising therapeutic option for improving the healing rate with high-quality and effective scar inhibition. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Geologic Symphony: Science, Artistic Inspiration and Community Engagement in Jeffrey Nytch's Symphony No 1: Formations

NASA Astrophysics Data System (ADS)

Nytch, J.

2017-12-01

While the natural world has inspired works of visual art and music for centuries, examples of music being created as a direct expression of scientific processes or principles are relatively rare. In his 2013 work, Symphony No. 1: Formations, composer Jeffrey Nytch created a work that explicitly communicated the geologic history of the Rocky Mountain west through a musical composition. Commissioned by the Geological Society of America and premiered at the GSA's 125th Anniversary meeting, the symphony is more than merely inspired by the Rocky Mountains; rather, specific episodes of geologic history are depicted in the music. Moreover, certain processes such as metamorphosis, erosion, vulcanism, plate tectonics, and the relative duration of geologic time guided the structure and form of the music. This unique approach to musical composition allowed the work to play a novel and potent role in community engagement and education, both at the premiere performances in Colorado and subsequent performances of the symphony elsewhere. This project is thus a powerful example of how the arts can help illuminate scientific principles to the general public, in turn engaging them and helping to establish a more personal connection to the natural world around them.

Coming Home: Developing a Sense of Place in Our Communities and Schools. Proceedings of the 1997 Forum (Jamestown, New York, May 16-17, 1997).

ERIC Educational Resources Information Center

Baldwin, Mark K., Ed.

Begun in 1992, the Selborne Project helps teachers, primarily in middle schools, to use the square kilometer around their school as a theme to integrate nature study into the curriculum. The inspiration for the project stemmed from the 18th-century book, "The Natural History of Selborne," in which Gilbert White detailed nature's presence…

Monsters or Good Guys: The Mediating Role of Emotions in Transforming a Young Child's Encounter with Nature

ERIC Educational Resources Information Center

Green, Carrie

2016-01-01

Nature-play inspires a sense of awe and wonder in young children, however, the uncertainty of elements in nature can also bring about fear and anxiety. Using sensory tours as a data collection method, this qualitative study explores the emotions of a four-year-old during his exploration of an imaginary "monster castle" in the forest, and…

You Can Fly

ERIC Educational Resources Information Center

Martin, Rebecca

2008-01-01

This paper profiles Faith Ringgold. The opening line of the beloved story "Tar Beach" resonates with the optimism that characterizes author-artist Faith Ringgold's outlook on life. Faith Ringgold has always cherished the inspiration found in stories of overcoming adversity--and her own family history is a revelation of strong women figures.…

Exploration of the Maximum Entropy/Optimal Projection Approach to Control Design Synthesis for Large Space Structures.

DTIC Science & Technology

1985-02-01

Energy Analysis , a branch of dynamic modal analysis developed for analyzing acoustic vibration problems, its present stage of development embodies a...Maximum Entropy Stochastic Modelling and Reduced-Order Design Synthesis is a rigorous new approach to this class of problems. Inspired by Statistical

Tubular structured hierarchical mesoporous titania material derived from natural cellulosic substances and application as photocatalyst for degradation of methylene blue

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

Huang, Haiqing; Liu, Xiaoyan; Huang, Jianguo, E-mail: jghuang@zju.edu.cn

Graphical abstract: Bio-inspired, tubular structured hierarchical mesoporous titania material with high photocatalytic activity under UV light was fabricated employing natural cellulosic substance (cotton) as hard template and cetyltrimethylammonium bromide (CTAB) surfactant as soft template using a one-pot sol-gel method. Highlights: {yields} Tubular structured mesoporous titania material was fabricated by sol-gel method. {yields} The titania material faithfully recorded the hierarchical structure of the template substrate (cotton). {yields} The titania material exhibited high photocatalytic activity in decomposition of methylene blue. -- Abstract: Bio-inspired, tubular structured hierarchical mesoporous titania material was designed and fabricated employing natural cellulosic substance (cotton) as hard template andmore » cetyltrimethylammonium bromide (CTAB) surfactant as soft template by one-pot sol-gel method. The tubular structured hierarchical mesoporous titania material processes large specific surface area (40.23 m{sup 2}/g) and shows high photocatalytic activity in the photodegradation of methylene blue under UV light irradiation.« less

Artificial Bee Colony Optimization for Short-Term Hydrothermal Scheduling

NASA Astrophysics Data System (ADS)

Basu, M.

2014-12-01

Artificial bee colony optimization is applied to determine the optimal hourly schedule of power generation in a hydrothermal system. Artificial bee colony optimization is a swarm-based algorithm inspired by the food foraging behavior of honey bees. The algorithm is tested on a multi-reservoir cascaded hydroelectric system having prohibited operating zones and thermal units with valve point loading. The ramp-rate limits of thermal generators are taken into consideration. The transmission losses are also accounted for through the use of loss coefficients. The algorithm is tested on two hydrothermal multi-reservoir cascaded hydroelectric test systems. The results of the proposed approach are compared with those of differential evolution, evolutionary programming and particle swarm optimization. From numerical results, it is found that the proposed artificial bee colony optimization based approach is able to provide better solution.

Towards Development of Innovative Bio-Inspired Materials by Analyzing the Hydrodynamic Properties of Polyondon Spathula (Paddlefish) Rostrum

DTIC Science & Technology

2013-09-01

Factors Multiply By To Obtain cubic inches 1.6387064 E -05 cubic meters inches 0.0254 meters pounds (force) 4.448222 newtons pounds (force) per...0.45359237 kilograms pounds (mass) per cubic foot 16.01846 kilograms per cubic meter pounds (mass) per cubic inch 2.757990 E +04 kilograms per cubic...14.59390 kilograms square inches 6.4516 E -04 square meters ERDC/ITL TR-13-4 1 1 Introduction 1.1 Bio–inspiration Nature has evolved from a

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

PubMed

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

2016-01-01

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

Materials taking a lesson from nature.

PubMed

Tian, Liangfei; Croisier, Emmanuel; Frauenrath, Holger

2013-01-01

Structural biomaterials with their often extraordinary properties and versatile functions are typically constructed from very limited sets of building blocks and types of supramolecular interactions. In this review we discuss how, inspired by nature's design principles for protein-based materials, oligopeptide-modified polymers can be used as a versatile toolbox to program nanostructure and hierarchical structure formation in synthetic materials.

Development of Students' Conceptual Thinking by Means of Video Analysis and Interactive Simulations at Technical Universities

ERIC Educational Resources Information Center

Hockicko, Peter; Krišták, Luboš; Nemec, Miroslav

2015-01-01

Video analysis, using the program Tracker (Open Source Physics), in the educational process introduces a new creative method of teaching physics and makes natural sciences more interesting for students. This way of exploring the laws of nature can amaze students because this illustrative and interactive educational software inspires them to think…

Pressure sensitive microparticle adhesion through biomimicry of the pollen-stigma interaction.

PubMed

Lin, Haisheng; Qu, Zihao; Meredith, J Carson

2016-03-21

Many soft biomimetic synthetic adhesives, optimized to support macroscopic masses (∼kg), have been inspired by geckos, insects and other animals. Far less work has investigated bioinspired adhesion that is tuned to micro- and nano-scale sizes and forces. However, such adhesive forces are extremely important in the adhesion of micro- and nanoparticles to surfaces, relevant to a wide range of industrial and biological systems. Pollens, whose adhesion is critical to plant reproduction, are an evolutionary-optimized system for biomimicry to engineer tunable adhesion between particles and micro-patterned soft matter surfaces. In addition, the adhesion of pollen particles is relevant to topics as varied as pollinator ecology, transport of allergens, and atmospheric phenomena. We report the first observation of structurally-derived pressure-sensitive adhesion of a microparticle by using the sunflower pollen and stigma surfaces as a model. This strong, pressure-sensitive adhesion results from interlocking between the pollen's conical spines and the stigma's receptive papillae. Inspired by this behavior, we fabricated synthetic polymeric patterned surfaces that mimic the stigma surface's receptivity to pollen. These soft mimics allow the magnitude of the pressure-sensitive response to be tuned by adjusting the size and spacing of surface features. These results provide an important new insight for soft material adhesion based on bio-inspired principles, namely that ornamented microparticles and micro-patterned surfaces can be designed with complementarity that enable a tunable, pressure-sensitive adhesion on the microparticle size and length scale.

Confronting and resolving competing values behind conservation objectives.

PubMed

Karp, Daniel S; Mendenhall, Chase D; Callaway, Elizabeth; Frishkoff, Luke O; Kareiva, Peter M; Ehrlich, Paul R; Daily, Gretchen C

2015-09-01

Diverse motivations for preserving nature both inspire and hinder its conservation. Optimal conservation strategies may differ radically depending on the objective. For example, creating nature reserves may prevent extinctions through protecting severely threatened species, whereas incentivizing farmland hedgerows may benefit people through bolstering pest-eating or pollinating species. Win-win interventions that satisfy multiple objectives are alluring, but can also be elusive. To achieve better outcomes, we developed and implemented a practical typology of nature conservation framed around seven common conservation objectives. Using an intensively studied bird assemblage in southern Costa Rica as a case study, we applied the typology in the context of biodiversity's most pervasive threat: habitat conversion. We found that rural habitats in a varied tropical landscape, comprising small farms, villages, forest fragments, and forest reserves, provided biodiversity-driven processes that benefit people, such as pollination, seed dispersal, and pest consumption. However, species valued for their rarity, endemism, and evolutionary distinctness declined in farmland. Conserving tropical forest on farmland increased species that international tourists value, but not species discussed in Costa Rican newspapers. Despite these observed trade-offs, our analyses also revealed promising synergies. For example, we found that maintaining forest cover surrounding farms in our study region would likely enhance most conservation objectives at minimal expense to others. Overall, our typology provides a framework for resolving the competing objectives of modern conservation.

Confronting and resolving competing values behind conservation objectives

PubMed Central

Karp, Daniel S.; Mendenhall, Chase D.; Callaway, Elizabeth; Frishkoff, Luke O.; Kareiva, Peter M.; Ehrlich, Paul R.; Daily, Gretchen C.

2015-01-01

Diverse motivations for preserving nature both inspire and hinder its conservation. Optimal conservation strategies may differ radically depending on the objective. For example, creating nature reserves may prevent extinctions through protecting severely threatened species, whereas incentivizing farmland hedgerows may benefit people through bolstering pest-eating or pollinating species. Win-win interventions that satisfy multiple objectives are alluring, but can also be elusive. To achieve better outcomes, we developed and implemented a practical typology of nature conservation framed around seven common conservation objectives. Using an intensively studied bird assemblage in southern Costa Rica as a case study, we applied the typology in the context of biodiversity’s most pervasive threat: habitat conversion. We found that rural habitats in a varied tropical landscape, comprising small farms, villages, forest fragments, and forest reserves, provided biodiversity-driven processes that benefit people, such as pollination, seed dispersal, and pest consumption. However, species valued for their rarity, endemism, and evolutionary distinctness declined in farmland. Conserving tropical forest on farmland increased species that international tourists value, but not species discussed in Costa Rican newspapers. Despite these observed trade-offs, our analyses also revealed promising synergies. For example, we found that maintaining forest cover surrounding farms in our study region would likely enhance most conservation objectives at minimal expense to others. Overall, our typology provides a framework for resolving the competing objectives of modern conservation. PMID:26283400

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

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.

Butterfly effects: novel functional materials inspired from the wings scales.

PubMed

Zhang, Wang; Gu, Jiajun; Liu, Qinglei; Su, Huilan; Fan, Tongxiang; Zhang, Di

2014-10-07

Through millions of years of evolutionary selection, nature has created biological materials with various functional properties for survival. Many complex natural architectures, such as shells, bones, and honeycombs, have been studied and imitated in the design and fabrication of materials with enhanced hardness and stiffness. Recently, more and more researchers have started to research the wings of butterflies, mostly because of their dazzling colors. It was found that most of these iridescent colors are caused by periodic photonic structures on the scales that make up the surfaces of these wings. These materials have recently become a focus of multidiscipline research because of their promising applications in the display of structural colors, and in advanced sensors, photonic crystals, and solar cells. This paper review aims to provide a perspective overview of the research inspired by these wing structures in recent years.

The art of war: beyond memory-one strategies in population games.

PubMed

Lee, Christopher; Harper, Marc; Fryer, Dashiell

2015-01-01

We show that the history of play in a population game contains exploitable information that can be successfully used by sophisticated strategies to defeat memory-one opponents, including zero determinant strategies. The history allows a player to label opponents by their strategies, enabling a player to determine the population distribution and to act differentially based on the opponent's strategy in each pairwise interaction. For the Prisoner's Dilemma, these advantages lead to the natural formation of cooperative coalitions among similarly behaving players and eventually to unilateral defection against opposing player types. We show analytically and empirically that optimal play in population games depends strongly on the population distribution. For example, the optimal strategy for a minority player type against a resident TFT population is ALLC, while for a majority player type the optimal strategy versus TFT players is ALLD. Such behaviors are not accessible to memory-one strategies. Drawing inspiration from Sun Tzu's the Art of War, we implemented a non-memory-one strategy for population games based on techniques from machine learning and statistical inference that can exploit the history of play in this manner. Via simulation we find that this strategy is essentially uninvadable and can successfully invade (significantly more likely than a neutral mutant) essentially all known memory-one strategies for the Prisoner's Dilemma, including ALLC (always cooperate), ALLD (always defect), tit-for-tat (TFT), win-stay-lose-shift (WSLS), and zero determinant (ZD) strategies, including extortionate and generous strategies.

Creating a Bio-Inspired Solution to Prevent Erosion

NASA Astrophysics Data System (ADS)

Reher, R.; Martinez, A.; Cola, J.; Frost, D.

2016-12-01

Through the study of geophysical sciences, lessons can be developed which allow for the introduction of bio-inspired design and art concepts to K-5 elementary students. Students are placed into an engineering mindset in which they must apply the concepts of bio-geotechnics to observe how we can use nature to prevent and abate erosion. Problems are staged for students using realistic engineering scenarios such as erosion prevention through biomimicry and the study of anchorage characteristics of root structures in regard to stability of soil. Specifically, a lesson is introduced where students research, learn, and present information about bio-inspired designs to understand these concepts. They lean how plant roots differ in size and shape to stabilize soil. In addition, students perform a series of hands-on experiments which demonstrate how bio-cements and roots can slow erosion.

Stretch-and-release fabrication, testing and optimization of a flexible ceramic armor inspired from fish scales.

PubMed

Martini, Roberto; Barthelat, Francois

2016-10-13

Protective systems that are simultaneously hard to puncture and compliant in flexion are desirable, but difficult to achieve because hard materials are usually stiff. However, we can overcome this conflicting design requirement by combining plates of a hard material with a softer substrate, and a strategy which is widely found in natural armors such as fish scales or osteoderms. Man-made segmented armors have a long history, but their systematic implementation in a modern and a protective system is still hampered by a limited understanding of the mechanics and the design of optimization guidelines, and by challenges in cost-efficient manufacturing. This study addresses these limitations with a flexible bioinspired armor based on overlapping ceramic scales. The fabrication combines laser engraving and a stretch-and-release method which allows for fine tuning of the size and overlap of the scales, and which is suitable for large scale fabrication. Compared to a continuous layer of uniform ceramic, our fish-scale like armor is not only more flexible, but it is also more resistant to puncture and more damage tolerant. The proposed armor is also about ten times more puncture resistant than soft elastomers, making it a very attractive alternative to traditional protective equipment.

Hierarchical Surface Architecture of Plants as an Inspiration for Biomimetic Fog Collectors.

PubMed

Azad, M A K; Barthlott, W; Koch, K

2015-12-08

Fog collectors can enable us to alleviate the water crisis in certain arid regions of the world. A continuous fog-collection cycle consisting of a persistent capture of fog droplets and their fast transport to the target is a prerequisite for developing an efficient fog collector. In regard to this topic, a biological superior design has been found in the hierarchical surface architecture of barley (Hordeum vulgare) awns. We demonstrate here the highly wettable (advancing contact angle 16° ± 2.7 and receding contact angle 9° ± 2.6) barbed (barb = conical structure) awn as a model to develop optimized fog collectors with a high fog-capturing capability, an effective water transport, and above all an efficient fog collection. We compare the fog-collection efficiency of the model sample with other plant samples naturally grown in foggy habitats that are supposed to be very efficient fog collectors. The model sample, consisting of dry hydrophilized awns (DH awns), is found to be about twice as efficient (fog-collection rate 563.7 ± 23.2 μg/cm(2) over 10 min) as any other samples investigated under controlled experimental conditions. Finally, a design based on the hierarchical surface architecture of the model sample is proposed for the development of optimized biomimetic fog collectors.

High-Order Model and Dynamic Filtering for Frame Rate Up-Conversion.

PubMed

Bao, Wenbo; Zhang, Xiaoyun; Chen, Li; Ding, Lianghui; Gao, Zhiyong

2018-08-01

This paper proposes a novel frame rate up-conversion method through high-order model and dynamic filtering (HOMDF) for video pixels. Unlike the constant brightness and linear motion assumptions in traditional methods, the intensity and position of the video pixels are both modeled with high-order polynomials in terms of time. Then, the key problem of our method is to estimate the polynomial coefficients that represent the pixel's intensity variation, velocity, and acceleration. We propose to solve it with two energy objectives: one minimizes the auto-regressive prediction error of intensity variation by its past samples, and the other minimizes video frame's reconstruction error along the motion trajectory. To efficiently address the optimization problem for these coefficients, we propose the dynamic filtering solution inspired by video's temporal coherence. The optimal estimation of these coefficients is reformulated into a dynamic fusion of the prior estimate from pixel's temporal predecessor and the maximum likelihood estimate from current new observation. Finally, frame rate up-conversion is implemented using motion-compensated interpolation by pixel-wise intensity variation and motion trajectory. Benefited from the advanced model and dynamic filtering, the interpolated frame has much better visual quality. Extensive experiments on the natural and synthesized videos demonstrate the superiority of HOMDF over the state-of-the-art methods in both subjective and objective comparisons.

Underwater sonar image detection: A combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm.

PubMed

Wang, Xingmei; Liu, Shu; Liu, Zhipeng

2017-01-01

This paper proposes a combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm to detect underwater objects in sonar images. Specifically, for the first time, the problem of inappropriate filtering degree parameter which commonly occurs in non-local spatial information and seriously affects the denoising performance in sonar images, was solved with the method utilizing a novel filtering degree parameter. Then, a quantum-inspired shuffled frog leaping algorithm based on new search mechanism (QSFLA-NSM) is proposed to precisely and quickly detect sonar images. Each frog individual is directly encoded by real numbers, which can greatly simplify the evolution process of the quantum-inspired shuffled frog leaping algorithm (QSFLA). Meanwhile, a fitness function combining intra-class difference with inter-class difference is adopted to evaluate frog positions more accurately. On this basis, recurring to an analysis of the quantum-behaved particle swarm optimization (QPSO) and the shuffled frog leaping algorithm (SFLA), a new search mechanism is developed to improve the searching ability and detection accuracy. At the same time, the time complexity is further reduced. Finally, the results of comparative experiments using the original sonar images, the UCI data sets and the benchmark functions demonstrate the effectiveness and adaptability of the proposed method.

Underwater sonar image detection: A combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm

PubMed Central

Liu, Zhipeng

2017-01-01

This paper proposes a combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm to detect underwater objects in sonar images. Specifically, for the first time, the problem of inappropriate filtering degree parameter which commonly occurs in non-local spatial information and seriously affects the denoising performance in sonar images, was solved with the method utilizing a novel filtering degree parameter. Then, a quantum-inspired shuffled frog leaping algorithm based on new search mechanism (QSFLA-NSM) is proposed to precisely and quickly detect sonar images. Each frog individual is directly encoded by real numbers, which can greatly simplify the evolution process of the quantum-inspired shuffled frog leaping algorithm (QSFLA). Meanwhile, a fitness function combining intra-class difference with inter-class difference is adopted to evaluate frog positions more accurately. On this basis, recurring to an analysis of the quantum-behaved particle swarm optimization (QPSO) and the shuffled frog leaping algorithm (SFLA), a new search mechanism is developed to improve the searching ability and detection accuracy. At the same time, the time complexity is further reduced. Finally, the results of comparative experiments using the original sonar images, the UCI data sets and the benchmark functions demonstrate the effectiveness and adaptability of the proposed method. PMID:28542266

Optimization as a Dispositive in the Production of Differences in Denmark Schools

ERIC Educational Resources Information Center

Hamre, Bjørn

2014-01-01

The theoretical framework of this paper is inspired by governmentality studies in education. The key concepts are problematization, formatting technologies, and dispositive. The paper begins with an empirical study conducted in Denmark of forty-four files from educational psychologists and articles from journals concerning schools and education.…

Fostering Innovation through an Active Learning Activity Inspired by the Baghdad Battery

ERIC Educational Resources Information Center

Lu, Xu; Anariba, Franklin

2014-01-01

A hands-on activity based on general electrochemistry concepts with the aim at introducing design science elements is presented. The main goals of the activity are to reinforce electrochemical principles while fostering innovation in the students through the assembly and optimization of a voltaic device and subsequent evaluation by powering…

Counseling for the Training of Leaders and Leadership Development: A Commentary

ERIC Educational Resources Information Center

Barreto, Alfonso

2012-01-01

Counseling is the instrument that empowers training and forges the development of leaders in their essential drive to inspire and guide others. As much a discipline and praxis as a professional practice, counseling increases consciousness and optimizes the management and synergy of human energy. This article addresses methods for sustaining…

Computational Intelligence‐Assisted Understanding of Nature‐Inspired Superhydrophobic Behavior

PubMed Central

Zhang, Xia; Ding, Bei; Dixon, Sebastian C.

2017-01-01

Abstract In recent years, state‐of‐the‐art computational modeling of physical and chemical systems has shown itself to be an invaluable resource in the prediction of the properties and behavior of functional materials. However, construction of a useful computational model for novel systems in both academic and industrial contexts often requires a great depth of physicochemical theory and/or a wealth of empirical data, and a shortage in the availability of either frustrates the modeling process. In this work, computational intelligence is instead used, including artificial neural networks and evolutionary computation, to enhance our understanding of nature‐inspired superhydrophobic behavior. The relationships between experimental parameters (water droplet volume, weight percentage of nanoparticles used in the synthesis of the polymer composite, and distance separating the superhydrophobic surface and the pendant water droplet in adhesive force measurements) and multiple objectives (water droplet contact angle, sliding angle, and adhesive force) are built and weighted. The obtained optimal parameters are consistent with the experimental observations. This new approach to materials modeling has great potential to be applied more generally to aid design, fabrication, and optimization for myriad functional materials. PMID:29375975

On the optimum signal constellation design for high-speed optical transport networks.

PubMed

Liu, Tao; Djordjevic, Ivan B

2012-08-27

In this paper, we first describe an optimum signal constellation design algorithm, which is optimum in MMSE-sense, called MMSE-OSCD, for channel capacity achieving source distribution. Secondly, we introduce a feedback channel capacity inspired optimum signal constellation design (FCC-OSCD) to further improve the performance of MMSE-OSCD, inspired by the fact that feedback channel capacity is higher than that of systems without feedback. The constellations obtained by FCC-OSCD are, however, OSNR dependent. The optimization is jointly performed together with regular quasi-cyclic low-density parity-check (LDPC) code design. Such obtained coded-modulation scheme, in combination with polarization-multiplexing, is suitable as both 400 Gb/s and multi-Tb/s optical transport enabling technology. Using large girth LDPC code, we demonstrate by Monte Carlo simulations that a 32-ary signal constellation, obtained by FCC-OSCD, outperforms previously proposed optimized 32-ary CIPQ signal constellation by 0.8 dB at BER of 10(-7). On the other hand, the LDPC-coded 16-ary FCC-OSCD outperforms 16-QAM by 1.15 dB at the same BER.

Planning energy-efficient bipedal locomotion on patterned terrain

NASA Astrophysics Data System (ADS)

Zamani, Ali; Bhounsule, Pranav A.; Taha, Ahmad

2016-05-01

Energy-efficient bipedal walking is essential in realizing practical bipedal systems. However, current energy-efficient bipedal robots (e.g., passive-dynamics-inspired robots) are limited to walking at a single speed and step length. The objective of this work is to address this gap by developing a method of synthesizing energy-efficient bipedal locomotion on patterned terrain consisting of stepping stones using energy-efficient primitives. A model of Cornell Ranger (a passive-dynamics inspired robot) is utilized to illustrate our technique. First, an energy-optimal trajectory control problem for a single step is formulated and solved. The solution minimizes the Total Cost Of Transport (TCOT is defined as the energy used per unit weight per unit distance travelled) subject to various constraints such as actuator limits, foot scuffing, joint kinematic limits, ground reaction forces. The outcome of the optimization scheme is a table of TCOT values as a function of step length and step velocity. Next, we parameterize the terrain to identify the location of the stepping stones. Finally, the TCOT table is used in conjunction with the parameterized terrain to plan an energy-efficient stepping strategy.

Self-assembled cationic amphiphiles as antimicrobial peptides mimics: Role of hydrophobicity, linkage type, and assembly state.

PubMed

Zhang, Yingyue; Algburi, Ammar; Wang, Ning; Kholodovych, Vladyslav; Oh, Drym O; Chikindas, Michael; Uhrich, Kathryn E

2017-02-01

Inspired by high promise using naturally occurring antimicrobial peptides (AMPs) to treat infections caused by antimicrobial-resistant bacteria, cationic amphiphiles (CAms) were strategically designed as synthetic mimics to overcome associated limitations, including high manufacture cost and low metabolic stability. CAms with facially amphiphilic conformation were expected to demonstrate membrane-lytic properties and thus reduce tendency of resistance development. By systematically tuning the hydrophobicity, CAms with optimized compositions exhibited potent broad-spectrum antimicrobial activity (with minimum inhibitory concentrations in low μg/mL range) as well as negligible hemolytic activity. Electron microscope images revealed the morphological and ultrastructure changes of bacterial membranes induced by CAm treatment and validated their membrane-disrupting mechanism. Additionally, an all-atom molecular dynamics simulation was employed to understand the CAm-membrane interaction on molecular level. This study shows that these CAms can serve as viable scaffolds for designing next generation of AMP mimics as antimicrobial alternatives to combat drug-resistant pathogens. Copyright © 2016 Elsevier Inc. All rights reserved.

Compression Molding of Composite of Recycled HDPE and Recycled Tire Particles

NASA Technical Reports Server (NTRS)

Liu, Ping; Waskom, Tommy L.; Chen, Zhengyu; Li, Yanze; Peng, Linda

1996-01-01

Plastic and rubber recycling is an effective means of reducing solid waste to the environment and preserving natural resources. A project aimed at developing a new composite material from recycled high density polyethylene (HDPE) and recycled rubber is currently being conducted at Eastern Illinois University. The recycled plastic pellets with recycled rubber particles are extruded into some HDPE/rubber composite strands. The strand can be further cut into pellets that can be used to fabricate other material forms or products. This experiment was inspired by the above-mentioned research activity. In order to measure Durometer hardness of the extruded composite, a specimen with relatively large dimensions was needed. Thus, compression molding was used to form a cylindrical specimen of 1 in. diameter and 1 in. thickness. The initial poor quality of the molded specimen prompted a need to optimize the processing parameters such as temperature, holding time, and pressure. Design of experiment (DOE) was used to obtain optimum combination of the parameters.

Meta-heuristic algorithm to solve two-sided assembly line balancing problems

NASA Astrophysics Data System (ADS)

Wirawan, A. D.; Maruf, A.

2016-02-01

Two-sided assembly line is a set of sequential workstations where task operations can be performed at two sides of the line. This type of line is commonly used for the assembly of large-sized products: cars, buses, and trucks. This paper propose a Decoding Algorithm with Teaching-Learning Based Optimization (TLBO), a recently developed nature-inspired search method to solve the two-sided assembly line balancing problem (TALBP). The algorithm aims to minimize the number of mated-workstations for the given cycle time without violating the synchronization constraints. The correlation between the input parameters and the emergence point of objective function value is tested using scenarios generated by design of experiments. A two-sided assembly line operated in an Indonesia's multinational manufacturing company is considered as the object of this paper. The result of the proposed algorithm shows reduction of workstations and indicates that there is negative correlation between the emergence point of objective function value and the size of population used.

Numerical solution to generalized Burgers'-Fisher equation using Exp-function method hybridized with heuristic computation.

PubMed

Malik, Suheel Abdullah; Qureshi, Ijaz Mansoor; Amir, Muhammad; Malik, Aqdas Naveed; Haq, Ihsanul

2015-01-01

In this paper, a new heuristic scheme for the approximate solution of the generalized Burgers'-Fisher equation is proposed. The scheme is based on the hybridization of Exp-function method with nature inspired algorithm. The given nonlinear partial differential equation (NPDE) through substitution is converted into a nonlinear ordinary differential equation (NODE). The travelling wave solution is approximated by the Exp-function method with unknown parameters. The unknown parameters are estimated by transforming the NODE into an equivalent global error minimization problem by using a fitness function. The popular genetic algorithm (GA) is used to solve the minimization problem, and to achieve the unknown parameters. The proposed scheme is successfully implemented to solve the generalized Burgers'-Fisher equation. The comparison of numerical results with the exact solutions, and the solutions obtained using some traditional methods, including adomian decomposition method (ADM), homotopy perturbation method (HPM), and optimal homotopy asymptotic method (OHAM), show that the suggested scheme is fairly accurate and viable for solving such problems.

Numerical Solution to Generalized Burgers'-Fisher Equation Using Exp-Function Method Hybridized with Heuristic Computation

PubMed Central

Malik, Suheel Abdullah; Qureshi, Ijaz Mansoor; Amir, Muhammad; Malik, Aqdas Naveed; Haq, Ihsanul

2015-01-01

In this paper, a new heuristic scheme for the approximate solution of the generalized Burgers'-Fisher equation is proposed. The scheme is based on the hybridization of Exp-function method with nature inspired algorithm. The given nonlinear partial differential equation (NPDE) through substitution is converted into a nonlinear ordinary differential equation (NODE). The travelling wave solution is approximated by the Exp-function method with unknown parameters. The unknown parameters are estimated by transforming the NODE into an equivalent global error minimization problem by using a fitness function. The popular genetic algorithm (GA) is used to solve the minimization problem, and to achieve the unknown parameters. The proposed scheme is successfully implemented to solve the generalized Burgers'-Fisher equation. The comparison of numerical results with the exact solutions, and the solutions obtained using some traditional methods, including adomian decomposition method (ADM), homotopy perturbation method (HPM), and optimal homotopy asymptotic method (OHAM), show that the suggested scheme is fairly accurate and viable for solving such problems. PMID:25811858

Beyond description. Comment on "Approaching human language with complex networks" by Cong and Liu

NASA Astrophysics Data System (ADS)

Ferrer-i-Cancho, R.

2014-12-01

In their historical overview, Cong & Liu highlight Sausurre as the father of modern linguistics [1]. They apparently miss G.K. Zipf as a pioneer of the view of language as a complex system. His idea of a balance between unification and diversification forces in the organization of natural systems, e.g., vocabularies [2], can be seen as a precursor of the view of complexity as a balance between order (unification) and disorder (diversification) near the edge of chaos [3]. Although not mentioned by Cong & Liu somewhere else, trade-offs between hearer and speaker needs are very important in Zipf's view, which has inspired research on the optimal networks mapping words into meanings [4-6]. Quantitative linguists regard G.K. Zipf as the funder of modern quantitative linguistics [7], a discipline where statistics plays a central role as in network science. Interestingly, that centrality of statistics is missing Saussure's work and that of many of his successors.

Aerodynamics of Ventilation in Termite Mounds

NASA Astrophysics Data System (ADS)

Bailoor, Shantanu; Yaghoobian, Neda; Turner, Scott; Mittal, Rajat

2017-11-01

Fungus-cultivating termites collectively build massive, complex mounds which are much larger than the size of an individual termite and effectively use natural wind and solar energy, as well as the energy generated by the colony's own metabolic activity to maintain the necessary environmental condition for the colony's survival. We seek to understand the aerodynamics of ventilation and thermoregulation of termite mounds through computational modeling. A simplified model accounting for key mound features, such as soil porosity and internal conduit network, is subjected to external draft conditions. The role of surface flow conditions in the generation of internal flow patterns and the ability of the mound to transport gases and heat from the nursery are examined. The understanding gained from our study could be used to guide sustainable bio-inspired passive HVAC system design, which could help optimize energy utilization in commercial and residential buildings. This research is supported by a seed Grant from the Environment, Energy Sustainability and Health Institute of the Johns Hopkins University.

Engineering growth factors for regenerative medicine applications.

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

Mitchell, Aaron C.; Briquez, Priscilla S.; Hubbell, Jeffrey A.

Growth factors are important morphogenetic proteins that instruct cell behavior and guide tissue repair and renewal. Although their therapeutic potential holds great promise in regenerative medicine applications, translation of growth factors into clinical treatments has been hindered by limitations including poor protein stability, low recombinant expression yield, and suboptimal efficacy. This review highlights current tools, technologies, and approaches to design integrated and effective growth factor-based therapies for regenerative medicine applications. The first section describes rational and combinatorial protein engineering approaches that have been utilized to improve growth factor stability, expression yield, biodistribution, and serum half-life, or alter their cell traffickingmore » behavior or receptor binding affinity. The second section highlights elegant biomaterial-based systems, inspired by the natural extracellular matrix milieu, that have been developed for effective spatial and temporal delivery of growth factors to cell surface receptors. Although appearing distinct, these two approaches are highly complementary and involve principles of molecular design and engineering to be considered in parallel when developing optimal materials for clinical applications.« less

Large-deformation and high-strength amorphous porous carbon nanospheres

NASA Astrophysics Data System (ADS)

Yang, Weizhu; Mao, Shimin; Yang, Jia; Shang, Tao; Song, Hongguang; Mabon, James; Swiech, Wacek; Vance, John R.; Yue, Zhufeng; Dillon, Shen J.; Xu, Hangxun; Xu, Baoxing

2016-04-01

Carbon is one of the most important materials extensively used in industry and our daily life. Crystalline carbon materials such as carbon nanotubes and graphene possess ultrahigh strength and toughness. In contrast, amorphous carbon is known to be very brittle and can sustain little compressive deformation. Inspired by biological shells and honeycomb-like cellular structures in nature, we introduce a class of hybrid structural designs and demonstrate that amorphous porous carbon nanospheres with a thin outer shell can simultaneously achieve high strength and sustain large deformation. The amorphous carbon nanospheres were synthesized via a low-cost, scalable and structure-controllable ultrasonic spray pyrolysis approach using energetic carbon precursors. In situ compression experiments on individual nanospheres show that the amorphous carbon nanospheres with an optimized structure can sustain beyond 50% compressive strain. Both experiments and finite element analyses reveal that the buckling deformation of the outer spherical shell dominates the improvement of strength while the collapse of inner nanoscale pores driven by twisting, rotation, buckling and bending of pore walls contributes to the large deformation.

Artificial Intelligence Application in Power Generation Industry: Initial considerations

NASA Astrophysics Data System (ADS)

Ismail, Rahmat Izaizi B.; Ismail Alnaimi, Firas B.; AL-Qrimli, Haidar F.

2016-03-01

With increased competitiveness in power generation industries, more resources are directed in optimizing plant operation, including fault detection and diagnosis. One of the most powerful tools in faults detection and diagnosis is artificial intelligence (AI). Faults should be detected early so correct mitigation measures can be taken, whilst false alarms should be eschewed to avoid unnecessary interruption and downtime. For the last few decades there has been major interest towards intelligent condition monitoring system (ICMS) application in power plant especially with AI development particularly in artificial neural network (ANN). ANN is based on quite simple principles, but takes advantage of their mathematical nature, non-linear iteration to demonstrate powerful problem solving ability. With massive possibility and room for improvement in AI, the inspiration for researching them are apparent, and literally, hundreds of papers have been published, discussing the findings of hybrid AI for condition monitoring purposes. In this paper, the studies of ANN and genetic algorithm (GA) application will be presented.

Coherent transport and energy flow patterns in photosynthesis under incoherent excitation.

PubMed

Pelzer, Kenley M; Can, Tankut; Gray, Stephen K; Morr, Dirk K; Engel, Gregory S

2014-03-13

Long-lived coherences have been observed in photosynthetic complexes after laser excitation, inspiring new theories regarding the extreme quantum efficiency of photosynthetic energy transfer. Whether coherent (ballistic) transport occurs in nature and whether it improves photosynthetic efficiency remain topics of debate. Here, we use a nonequilibrium Green's function analysis to model exciton transport after excitation from an incoherent source (as opposed to coherent laser excitation). We find that even with an incoherent source, the rate of environmental dephasing strongly affects exciton transport efficiency, suggesting that the relationship between dephasing and efficiency is not an artifact of coherent excitation. The Green's function analysis provides a clear view of both the pattern of excitonic fluxes among chromophores and the multidirectionality of energy transfer that is a feature of coherent transport. We see that even in the presence of an incoherent source, transport occurs by qualitatively different mechanisms as dephasing increases. Our approach can be generalized to complex synthetic systems and may provide a new tool for optimizing synthetic light harvesting materials.

A paleo-aerodynamic exploration of the evolution of nature's flyers, man's aircraft, and the needs and options for future technology innovations

NASA Astrophysics Data System (ADS)

Kulfan, Brenda M.

2009-03-01

Insights and observations of fascinating aspects of birds, bugs and flying seeds, of inspired aerodynamic concepts, and visions of past, present and future aircraft developments are presented. The evolution of nature's flyers, will be compared with the corresponding evolution of commercial aircraft. We will explore similarities between nature's creations and man's inventions. Many critical areas requiring future significant technology based solutions remain. With the advent of UAVs and MAVs, the gap between "possible" and "actual" is again very large. Allometric scaling procedures will be used to explore size implications on limitations and performance capabilities of nature's creations. Biologically related technology development concepts including: bionics, biomimicry, neo-bionic, pseudo-mimicry, cybernetic and non-bionic approaches will be discussed and illustrated with numerous examples. Technology development strategies will be discussed along with the pros and cons for each. Future technology developments should include a synergistic coupling of "discovery driven", "product led" and "technology acceleration" strategies. The objective of this presentation is to inspire the creative nature existing within all of us. This is a summary all text version of the complete report with the same title that report includes approximately 80 figures, photos and charts and much more information.

The Ignorant Environmental Education Teacher: Students Get Empowered and Teach Philosophy of Nature Inspired by Ancient Greek Philosophy

ERIC Educational Resources Information Center

Tsevreni, Irida

2018-01-01

This paper presents an attempt to apply Jacques Rancière's emancipatory pedagogy of "the ignorant schoolmaster" to environmental education, which emphasises environmental ethics. The paper tells the story of a philosophy of nature project in the framework of an environmental adult education course at a Second Chance School in Greece,…

The Nature and Nurture of Talent: A Bioecological Perspective on the Ontogeny of Exceptional Abilities

ERIC Educational Resources Information Center

Papierno, Paul B.; Ceci, Stephen J.; Makel, Matthew C.; Williams, Wendy M.

2005-01-01

Despite extensive research, questions underlying the nature and nurture of talent remain both numerous and diverse. In the current paper, we present an account that addresses 2 of the primary questions inspired by this debate: (a) the very existence of innate talents and (b) how exceptional abilities are developed. The development of exceptional…

Bio-inspired Optimal Locomotion Reconfigurability of Quadruped Rovers using Central Pattern Generators

NASA Astrophysics Data System (ADS)

Bohra, Murtaza

Legged rovers are often considered as viable solutions for traversing unknown terrain. This work addresses the optimal locomotion reconfigurability of quadruped rovers, which consists of obtaining optimal locomotion modes, and transitioning between them. A 2D sagittal plane rover model is considered based on a domestic cat. Using a Genetic Algorithm, the gait, pose and control variables that minimize torque or maximize speed are found separately. The optimization approach takes into account the elimination of leg impact, while considering the entire variable spectrum. The optimal solutions are consistent with other works on gait optimization, and are similar to gaits found in quadruped animals as well. An online model-free gait planning framework is also implemented, that is based on Central Pattern Generators is implemented. It is used to generate joint and control trajectories for any arbitrarily varying speed profile, and shown to regulate locomotion transition and speed modulation, both endogenously and continuously.

VDLLA: A virtual daddy-long legs optimization

NASA Astrophysics Data System (ADS)

Yaakub, Abdul Razak; Ghathwan, Khalil I.

2016-08-01

Swarm intelligence is a strong optimization algorithm based on a biological behavior of insects or animals. The success of any optimization algorithm is depending on the balance between exploration and exploitation. In this paper, we present a new swarm intelligence algorithm, which is based on daddy long legs spider (VDLLA) as a new optimization algorithm with virtual behavior. In VDLLA, each agent (spider) has nine positions which represent the legs of spider and each position represent one solution. The proposed VDLLA is tested on four standard functions using average fitness, Medium fitness and standard deviation. The results of proposed VDLLA have been compared against Particle Swarm Optimization (PSO), Differential Evolution (DE) and Bat Inspired Algorithm (BA). Additionally, the T-Test has been conducted to show the significant deference between our proposed and other algorithms. VDLLA showed very promising results on benchmark test functions for unconstrained optimization problems and also significantly improved the original swarm algorithms.

Ringed Seal Search for Global Optimization via a Sensitive Search Model

PubMed Central

Saadi, Younes; Yanto, Iwan Tri Riyadi; Herawan, Tutut; Balakrishnan, Vimala; Chiroma, Haruna; Risnumawan, Anhar

2016-01-01

The efficiency of a metaheuristic algorithm for global optimization is based on its ability to search and find the global optimum. However, a good search often requires to be balanced between exploration and exploitation of the search space. In this paper, a new metaheuristic algorithm called Ringed Seal Search (RSS) is introduced. It is inspired by the natural behavior of the seal pup. This algorithm mimics the seal pup movement behavior and its ability to search and choose the best lair to escape predators. The scenario starts once the seal mother gives birth to a new pup in a birthing lair that is constructed for this purpose. The seal pup strategy consists of searching and selecting the best lair by performing a random walk to find a new lair. Affected by the sensitive nature of seals against external noise emitted by predators, the random walk of the seal pup takes two different search states, normal state and urgent state. In the normal state, the pup performs an intensive search between closely adjacent lairs; this movement is modeled via a Brownian walk. In an urgent state, the pup leaves the proximity area and performs an extensive search to find a new lair from sparse targets; this movement is modeled via a Levy walk. The switch between these two states is realized by the random noise emitted by predators. The algorithm keeps switching between normal and urgent states until the global optimum is reached. Tests and validations were performed using fifteen benchmark test functions to compare the performance of RSS with other baseline algorithms. The results show that RSS is more efficient than Genetic Algorithm, Particles Swarm Optimization and Cuckoo Search in terms of convergence rate to the global optimum. The RSS shows an improvement in terms of balance between exploration (extensive) and exploitation (intensive) of the search space. The RSS can efficiently mimic seal pups behavior to find best lair and provide a new algorithm to be used in global optimization problems. PMID:26790131

Wine and maths: mathematical solutions to wine-inspired problems

NASA Astrophysics Data System (ADS)

Cadeddu, L.; Cauli, A.

2018-04-01

We deal with an application of partial differential equations to the correct definition of a wine cellar. We present some historical details about this problem. We also discuss how to build or renew a wine cellar, creating ideal conditions for the ageing process and improving the quality of wines. Our goal is to calculate the optimal depth z0 of a wine cellar in order to attenuate the periodic temperature fluctuations. What follows is a kind of survey of wine-related and optimization problems which have been solved by means of powerful math tools.

Harmony Search Method: Theory and Applications

PubMed Central

Gao, X. Z.; Govindasamy, V.; Xu, H.; Wang, X.; Zenger, K.

2015-01-01

The Harmony Search (HS) method is an emerging metaheuristic optimization algorithm, which has been employed to cope with numerous challenging tasks during the past decade. In this paper, the essential theory and applications of the HS algorithm are first described and reviewed. Several typical variants of the original HS are next briefly explained. As an example of case study, a modified HS method inspired by the idea of Pareto-dominance-based ranking is also presented. It is further applied to handle a practical wind generator optimal design problem. PMID:25945083

a Heuristic Approach for Multi Objective Distribution Feeder Reconfiguration: Using Fuzzy Sets in Normalization of Objective Functions

NASA Astrophysics Data System (ADS)

Milani, Armin Ebrahimi; Haghifam, Mahmood Reza

2008-10-01

The reconfiguration is an operation process used for optimization with specific objectives by means of changing the status of switches in a distribution network. In this paper each objectives is normalized with inspiration from fuzzy sets-to cause optimization more flexible- and formulized as a unique multi-objective function. The genetic algorithm is used for solving the suggested model, in which there is no risk of non-liner objective functions and constraints. The effectiveness of the proposed method is demonstrated through the examples.

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.

A Variety of Media Offers Inspirational Resources for Childbirth Educators and Parents

PubMed Central

Shilling, Teri

2006-01-01

In this column, reviewers offer perspectives and comments on Journey into Motherhood: Inspirational Stories of Natural Birth, a book by Sheri L. Menelli; Modern Mothering, a book by Tian Dayton; Breastfeeding in all the Right Spaces, a DVD by Marilyn Nolt; Postpartum: From Pregnant to Parent, a DVD production from Injoy Videos; MyMoonCards: Understanding My Body and Monthly Cycle, an instructional set of cards developed by Marina Alzugaray; Blessingways—A Guide to Mother-Centered Baby Showers, a book by Shari Maser; and A Meditation on the Sacred Journey of Birth, a book by Marie Beauchemin.

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.

Aurelia aurita bio-inspired tilt sensor

NASA Astrophysics Data System (ADS)

Smith, Colin; Villanueva, Alex; Priya, Shashank

2012-10-01

The quickly expanding field of mobile robots, unmanned underwater vehicles, and micro-air vehicles urgently needs a cheap and effective means for measuring vehicle inclination. Commonly, tilt or inclination has been mathematically derived from accelerometers; however, there is inherent error in any indirect measurement. This paper reports a bio-inspired tilt sensor that mimics the natural balance organ of jellyfish, called the ‘statocyst’. Biological statocysts from the species Aurelia aurita were characterized by scanning electron microscopy to investigate the morphology and size of the natural sensor. An artificial tilt sensor was then developed by using printed electronics that incorporates a novel voltage divider concept in conjunction with small surface mount devices. This sensor was found to have minimum sensitivity of 4.21° with a standard deviation of 1.77°. These results open the possibility of developing elegant tilt sensor architecture for both air and water based platforms.

Biopolymers and supramolecular polymers as biomaterials for biomedical applications

PubMed Central

Freeman, Ronit; Boekhoven, Job; Dickerson, Matthew B.; Naik, Rajesh R.

2015-01-01

Protein- and peptide-based structural biopolymers are abundant building blocks of biological systems. Either in their natural forms, such as collagen, silk or fibronectin, or as related synthetic materials they can be used in various technologies. An emerging area is that of biomimetic materials inspired by protein-based biopolymers, which are made up of small molecules rather than macromolecules and can therefore be described as supramolecular polymers. These materials are very useful in biomedical applications because of their ability to imitate the extracellular matrix both in architecture and their capacity to signal cells. This article describes important features of the natural extracellular matrix and highlight how these features are being incorporated into biomaterials composed of biopolymers and supramolecular polymers. We particularly focus on the structures, properties, and functions of collagen, fibronectin, silk, and the supramolecular polymers inspired by them as biomaterials for regenerative medicine. PMID:26989295

Naturally inspired SERS substrates fabricated by photocatalytically depositing silver nanoparticles on cicada wings

PubMed Central

2014-01-01

Densely stacked Ag nanoparticles with an average diameter of 199 nm were effectively deposited on TiO2-coated cicada wings (Ag/TiO2-coated wings) from a water-ethanol solution of AgNO3 using ultraviolet light irradiation at room temperature. It was seen that the surfaces of bare cicada wings contained nanopillar array structures. In the optical absorption spectra of the Ag/TiO2-coated wings, the absorption peak due to the localized surface plasmon resonance (LSPR) of Ag nanoparticles was observed at 440 nm. Strong Surface-enhanced Raman scattering (SERS) signals of Rhodamine 6G adsorbed on the Ag/TiO2-coated wings were clearly observed using the 514.5-nm line of an Ar+ laser. The Ag/TiO2-coated wings can be a promising candidate for naturally inspired SERS substrates. PMID:24959110

Naturally inspired SERS substrates fabricated by photocatalytically depositing silver nanoparticles on cicada wings

NASA Astrophysics Data System (ADS)

Tanahashi, Ichiro; Harada, Yoshiyuki

2014-06-01

Densely stacked Ag nanoparticles with an average diameter of 199 nm were effectively deposited on TiO2-coated cicada wings (Ag/TiO2-coated wings) from a water-ethanol solution of AgNO3 using ultraviolet light irradiation at room temperature. It was seen that the surfaces of bare cicada wings contained nanopillar array structures. In the optical absorption spectra of the Ag/TiO2-coated wings, the absorption peak due to the localized surface plasmon resonance (LSPR) of Ag nanoparticles was observed at 440 nm. Strong Surface-enhanced Raman scattering (SERS) signals of Rhodamine 6G adsorbed on the Ag/TiO2-coated wings were clearly observed using the 514.5-nm line of an Ar+ laser. The Ag/TiO2-coated wings can be a promising candidate for naturally inspired SERS substrates.

Swarm Intelligence in Text Document Clustering

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

Cui, Xiaohui; Potok, Thomas E

2008-01-01

Social animals or insects in nature often exhibit a form of emergent collective behavior. The research field that attempts to design algorithms or distributed problem-solving devices inspired by the collective behavior of social insect colonies is called Swarm Intelligence. Compared to the traditional algorithms, the swarm algorithms are usually flexible, robust, decentralized and self-organized. These characters make the swarm algorithms suitable for solving complex problems, such as document collection clustering. The major challenge of today's information society is being overwhelmed with information on any topic they are searching for. Fast and high-quality document clustering algorithms play an important role inmore » helping users to effectively navigate, summarize, and organize the overwhelmed information. In this chapter, we introduce three nature inspired swarm intelligence clustering approaches for document clustering analysis. These clustering algorithms use stochastic and heuristic principles discovered from observing bird flocks, fish schools and ant food forage.« less

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.

Learning from nature: binary cooperative complementary nanomaterials.

PubMed

Su, Bin; Guo, Wei; Jiang, Lei

2015-03-01

In this Review, nature-inspired binary cooperative complementary nanomaterials (BCCNMs), consisting of two components with entirely opposite physiochemical properties at the nanoscale, are presented as a novel concept for the building of promising materials. Once the distance between the two nanoscopic components is comparable to the characteristic length of some physical interactions, the cooperation between these complementary building blocks becomes dominant and endows the macroscopic materials with novel and superior properties. The first implementation of the BCCNMs is the design of bio-inspired smart materials with superwettability and their reversible switching between different wetting states in response to various kinds of external stimuli. Coincidentally, recent studies on other types of functional nanomaterials contribute more examples to support the idea of BCCNMs, which suggests a potential yet comprehensive range of future applications in both materials science and engineering. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Rice- and butterfly-wing effect inspired self-cleaning and low drag micro/nanopatterned surfaces in water, oil, and air flow.

PubMed

Bixler, Gregory D; Bhushan, Bharat

2014-01-07

In search of new solutions to complex challenges, researchers are turning to living nature for inspiration. For example, special surface characteristics of rice leaves and butterfly wings combine the shark skin (anisotropic flow leading to low drag) and lotus leaf (superhydrophobic and self-cleaning) effects, producing the so-called rice and butterfly wing effect. In this paper, we study four microstructured surfaces inspired by rice leaves and fabricated with photolithography techniques. We also present a method of creating such surfaces using a hot embossing procedure for scaled-up manufacturing. Fluid drag, self-cleaning, contact angle, and contact angle hysteresis data are presented to understand the role of sample geometrical dimensions. Conceptual modeling provides design guidance when developing novel low drag, self-cleaning, and potentially antifouling surfaces for medical, marine, and industrial applications.

Overcoming the brittleness of glass through bio-inspiration and micro-architecture.

PubMed

Mirkhalaf, M; Dastjerdi, A Khayer; Barthelat, F

2014-01-01

Highly mineralized natural materials such as teeth or mollusk shells boast unusual combinations of stiffness, strength and toughness currently unmatched by engineering materials. While high mineral contents provide stiffness and hardness, these materials also contain weaker interfaces with intricate architectures, which can channel propagating cracks into toughening configurations. Here we report the implementation of these features into glass, using a laser engraving technique. Three-dimensional arrays of laser-generated microcracks can deflect and guide larger incoming cracks, following the concept of 'stamp holes'. Jigsaw-like interfaces, infiltrated with polyurethane, furthermore channel cracks into interlocking configurations and pullout mechanisms, significantly enhancing energy dissipation and toughness. Compared with standard glass, which has no microstructure and is brittle, our bio-inspired glass displays built-in mechanisms that make it more deformable and 200 times tougher. This bio-inspired approach, based on carefully architectured interfaces, provides a new pathway to toughening glasses, ceramics or other hard and brittle materials.

Function through bio-inspired, synthesis-informed design: step-economical syntheses of designed kinase inhibitors†Dedicated to Max Malacria, a friend and scholar whose science and creative contributions to step-economical synthesis have inspired us all and moved the field closer to the ideal.‡Electronic supplementary information (ESI) available: Synthetic procedures and spectral data. See DOI: 10.1039/c4qo00228hClick here for additional data file.

PubMed

Wender, Paul A; Axtman, Alison D; Golden, Jennifer E; Kee, Jung-Min; Sirois, Lauren E; Quiroz, Ryan V; Stevens, Matthew C

2014-12-29

The human kinome comprises over 500 protein kinases. When mutated or over-expressed, many play critical roles in abnormal cellular functions associated with cancer, cardiovascular disease and neurological disorders. Here we report a step-economical approach to designed kinase inhibitors inspired by the potent, but non-selective, natural product staurosporine, and synthetically enabled by a novel, complexity-increasing, serialized [5 + 2]/[4 + 2] cycloaddition strategy. This function-oriented synthesis approach rapidly affords tunable scaffolds, and produced a low nanomolar inhibitor of protein kinase C.

Rice- and butterfly-wing effect inspired self-cleaning and low drag micro/nanopatterned surfaces in water, oil, and air flow

NASA Astrophysics Data System (ADS)

Bixler, Gregory D.; Bhushan, Bharat

2013-12-01

In search of new solutions to complex challenges, researchers are turning to living nature for inspiration. For example, special surface characteristics of rice leaves and butterfly wings combine the shark skin (anisotropic flow leading to low drag) and lotus leaf (superhydrophobic and self-cleaning) effects, producing the so-called rice and butterfly wing effect. In this paper, we study four microstructured surfaces inspired by rice leaves and fabricated with photolithography techniques. We also present a method of creating such surfaces using a hot embossing procedure for scaled-up manufacturing. Fluid drag, self-cleaning, contact angle, and contact angle hysteresis data are presented to understand the role of sample geometrical dimensions. Conceptual modeling provides design guidance when developing novel low drag, self-cleaning, and potentially antifouling surfaces for medical, marine, and industrial applications.

Overcoming the brittleness of glass through bio-inspiration and micro-architecture

NASA Astrophysics Data System (ADS)

Mirkhalaf, M.; Dastjerdi, A. Khayer; Barthelat, F.

2014-01-01

Highly mineralized natural materials such as teeth or mollusk shells boast unusual combinations of stiffness, strength and toughness currently unmatched by engineering materials. While high mineral contents provide stiffness and hardness, these materials also contain weaker interfaces with intricate architectures, which can channel propagating cracks into toughening configurations. Here we report the implementation of these features into glass, using a laser engraving technique. Three-dimensional arrays of laser-generated microcracks can deflect and guide larger incoming cracks, following the concept of ‘stamp holes’. Jigsaw-like interfaces, infiltrated with polyurethane, furthermore channel cracks into interlocking configurations and pullout mechanisms, significantly enhancing energy dissipation and toughness. Compared with standard glass, which has no microstructure and is brittle, our bio-inspired glass displays built-in mechanisms that make it more deformable and 200 times tougher. This bio-inspired approach, based on carefully architectured interfaces, provides a new pathway to toughening glasses, ceramics or other hard and brittle materials.

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.

Mussel byssus-inspired engineering of synergistic nanointerfacial interactions as sacrificial bonds into carbon nanotube-reinforced soy protein/nanofibrillated cellulose nanocomposites: Versatile mechanical enhancement

NASA Astrophysics Data System (ADS)

Wang, Zhong; Zhao, Shujun; Kang, Haijiao; Zhang, Wei; Zhang, Shifeng; Li, Jianzhang

2018-03-01

Achieving flexible and stretchable biobased nanocomposites combining high strength and toughness is still a very challenging endeavor. Herein, we described a novel and versatile biomimetic design for tough and high-performance TEMPO-oxidized nanofibrillated cellulose (TONFC)/soy protein isolate (SPI) nanocomposites, which are triggered by catechol-mimetic carbon nanotubes (PCT) and iron ions (Fe(III)) to yield a strong yet sacrificial metal-ligand motifs into a chemically cross-linked architecture network. Taking advantage of self-polymerization of catechol-inspired natural tannic acid, PCT nanohybrid was prepared through adhering reactive poly-(tannic acid) (PTA) layer onto surfaces of carbon nanotubes via a simple dip-coating process. The high-functionality PCT induced the formation of the metal-ligand bonds through the ionic coordinates between the catechol groups in PCT and -COOH groups of TONFC skeleton with Fe(III) mediation that mimicked mussel byssus. Upon stretching, this tailored TONFC-Fe(III)-catechol coordination bonds served as sacrificial bonds that preferentially detach prior to the covalent network, which gave rise to efficient energy dissipation that the nanocomposites integrity was survived. As a result of these kind of synergistic interfacial interactions (sacrificial and covalent bonding), the optimal nanocomposite films processed high tensile strength (ca. 11.5 MPa), large elongation (ca. 79.3%), remarkable toughness (ca. 6.9 MJ m-3), and favorable water resistance as well as electrical conductivity. The proposed bioinspired strategy for designing plant protein-based materials enables control over their mechanical performance through the synergistic engineering of sacrificial bonds into the composite interface.

Sensitivity analysis of multi-objective optimization of CPG parameters for quadruped robot locomotion

NASA Astrophysics Data System (ADS)

Oliveira, Miguel; Santos, Cristina P.; Costa, Lino

2012-09-01

In this paper, a study based on sensitivity analysis is performed for a gait multi-objective optimization system that combines bio-inspired Central Patterns Generators (CPGs) and a multi-objective evolutionary algorithm based on NSGA-II. In this system, CPGs are modeled as autonomous differential equations, that generate the necessary limb movement to perform the required walking gait. In order to optimize the walking gait, a multi-objective problem with three conflicting objectives is formulated: maximization of the velocity, the wide stability margin and the behavioral diversity. The experimental results highlight the effectiveness of this multi-objective approach and the importance of the objectives to find different walking gait solutions for the quadruped robot.

A biopolymer-like metal enabled hybrid material with exceptional mechanical prowess

DOE PAGES

Zhang, Junsong; Cui, Lishan; Jiang, Daqiang; ...

2015-02-10

In this study, the design principles for naturally occurring biological materials have inspired us to develop next-generation engineering materials with remarkable performance. Nacre, commonly referred to as nature's armor, is renowned for its unusual combination of strength and toughness. Nature's wisdom in nacre resides in its elaborate structural design and the judicious placement of a unique organic biopolymer with intelligent deformation features. However, up to now, it is still a challenge to transcribe the biopolymer's deformation attributes into a stronger substitute in the design of new materials. In this study, we propose a new design strategy that employs shape memorymore » alloy to transcribe the "J-curve'' mechanical response and uniform molecular/atomic level deformation of the organic biopolymer in the design of high-performance hybrid materials. This design strategy is verified in a TiNi-Ti 3Sn model material system. The model material demonstrates an exceptional combination of mechanical properties that are superior to other high-performance metal-based lamellar composites known to date. Our design strategy creates new opportunities for the development of high-performance bio-inspired materials.« less

A biopolymer-like metal enabled hybrid material with exceptional mechanical prowess

PubMed Central

Zhang, Junsong; Cui, Lishan; Jiang, Daqiang; Liu, Yinong; Hao, Shijie; Ren, Yang; Han, Xiaodong; Liu, Zhenyang; Wang, Yunzhi; Yu, Cun; Huan, Yong; Zhao, Xinqing; Zheng, Yanjun; Xu, Huibin; Ren, Xiaobing; Li, Xiaodong

2015-01-01

The design principles for naturally occurring biological materials have inspired us to develop next-generation engineering materials with remarkable performance. Nacre, commonly referred to as nature's armor, is renowned for its unusual combination of strength and toughness. Nature's wisdom in nacre resides in its elaborate structural design and the judicious placement of a unique organic biopolymer with intelligent deformation features. However, up to now, it is still a challenge to transcribe the biopolymer's deformation attributes into a stronger substitute in the design of new materials. In this study, we propose a new design strategy that employs shape memory alloy to transcribe the “J-curve” mechanical response and uniform molecular/atomic level deformation of the organic biopolymer in the design of high-performance hybrid materials. This design strategy is verified in a TiNi-Ti3Sn model material system. The model material demonstrates an exceptional combination of mechanical properties that are superior to other high-performance metal-based lamellar composites known to date. Our design strategy creates new opportunities for the development of high-performance bio-inspired materials. PMID:25665501

A biopolymer-like metal enabled hybrid material with exceptional mechanical prowess.

PubMed

Zhang, Junsong; Cui, Lishan; Jiang, Daqiang; Liu, Yinong; Hao, Shijie; Ren, Yang; Han, Xiaodong; Liu, Zhenyang; Wang, Yunzhi; Yu, Cun; Huan, Yong; Zhao, Xinqing; Zheng, Yanjun; Xu, Huibin; Ren, Xiaobing; Li, Xiaodong

2015-02-10

The design principles for naturally occurring biological materials have inspired us to develop next-generation engineering materials with remarkable performance. Nacre, commonly referred to as nature's armor, is renowned for its unusual combination of strength and toughness. Nature's wisdom in nacre resides in its elaborate structural design and the judicious placement of a unique organic biopolymer with intelligent deformation features. However, up to now, it is still a challenge to transcribe the biopolymer's deformation attributes into a stronger substitute in the design of new materials. In this study, we propose a new design strategy that employs shape memory alloy to transcribe the "J-curve" mechanical response and uniform molecular/atomic level deformation of the organic biopolymer in the design of high-performance hybrid materials. This design strategy is verified in a TiNi-Ti3Sn model material system. The model material demonstrates an exceptional combination of mechanical properties that are superior to other high-performance metal-based lamellar composites known to date. Our design strategy creates new opportunities for the development of high-performance bio-inspired materials.

Constraint factor in optimization of truss structures via flower pollination algorithm

NASA Astrophysics Data System (ADS)

Bekdaş, Gebrail; Nigdeli, Sinan Melih; Sayin, Baris

2017-07-01

The aim of the paper is to investigate the optimum design of truss structures by considering different stress and displacement constraints. For that reason, the flower pollination algorithm based methodology was applied for sizing optimization of space truss structures. Flower pollination algorithm is a metaheuristic algorithm inspired by the pollination process of flowering plants. By the imitation of cross-pollination and self-pollination processes, the randomly generation of sizes of truss members are done in two ways and these two types of optimization are controlled with a switch probability. In the study, a 72 bar space truss structure was optimized by using five different cases of the constraint limits. According to the results, a linear relationship between the optimum structure weight and constraint limits was observed.

Biomimetic-inspired joining of composite with metal structures: A survey of natural joints and application to single lap joints

NASA Astrophysics Data System (ADS)

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

2014-03-01

Joining composites with metal parts leads, inevitably, to high stress concentrations because of the material property mismatch. Since joining composite to metal is required in many high performance structures, there is a need to develop a new multifunctional approach to meet this challenge. This paper uses the biomimetics approach to help develop solutions to this problem. Nature has found many ingenious ways of joining dissimilar materials and making robust attachments, alleviating potential stress concentrations. A literature survey of natural joint systems has been carried out, identifying and analysing different natural joint methods from a mechanical perspective. A taxonomy table was developed based on the different methods/functions that nature successfully uses to attach dissimilar tissues (materials). This table is used to understand common themes or approaches used in nature for different joint configurations and functionalities. One of the key characteristics that nature uses to joint dissimilar materials is a transitional zone of stiffness in the insertion site. Several biomimetic-inspired metal-to-composite (steel-to-CFRP), adhesively bonded, Single Lap Joints (SLJs) were numerically investigated using a finite element analysis. The proposed solutions offer a transitional zone of stiffness of one joint part to reduce the material stiffness mismatch at the joint. An optimisation procedure was used to identify the variation in material stiffness which minimises potential failure of the joint. It was found that the proposed biomimetic SLJs reduce the asymmetry of the stress distribution along the adhesive area.

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.

Development of a Desalination Membrane Bioinspired by Mangrove Roots for Spontaneous Filtration of Sodium Ions.

PubMed

Kim, Kiwoong; Kim, Hyejeong; Lim, Jae Hong; Lee, Sang Joon

2016-12-27

The shortage of available fresh water is one of the global issues presently faced by humanity. To determine a solution to this problem, the survival strategies of plants have been examined. In this study, a nature-inspired membrane with a highly charged surface is proposed as an effective membrane for the filtration of saline water. To mimic the desalination characteristics of mangrove roots, a macroporous membrane based on polyethylene terephthalate is treated with polyelectrolytes using a layer-by-layer deposition method. The fabricated membrane surface has a highly negative charged ζ-potential value of -97.5 ± 4.3 mV, similar to that of the first layer of mangrove roots. Desalination of saline water using this membrane shows a high salt retention rate of 96.5%. The highly charged surface of the membrane may induce a relatively thick and stable ion depletion zone in front of the membrane. As a result, most co-ions are repelled from the membrane surface, and counterions are also rejected by virtue of their electroneutrality. The water permeability is found to be 7.60-7.69 L/m 2 ·h, which is 10 times higher than that of the reverse osmosis desalination method. This nature-inspired filtration membrane exhibits steady desalination performance over 72 h of operation, successfully demonstrating the stable filtration of saline water. This nature-inspired membrane is applicable to the design of a small-scale, portable, and energy-free desalination device for use in third-world countries or small villages.

BATMAV - A Bio-Inspired Micro-Aerial Vehicle for Flapping Flight

NASA Astrophysics Data System (ADS)

Bunget, Gheorghe

The main objective of the BATMAV project is the development of a biologically-inspired Micro Aerial Vehicle (MAV) with flexible and foldable wings for flapping flight. While flapping flight in MAV has been previously studied and a number of models were realized they usually had unfoldable wings actuated with DC motors and mechanical transmission to achieve flapping motion. This approach limits the system to a rather small number of degrees of freedom with little flexibility and introduces an additional disadvantage of a heavy flight platform. The BATMAV project aims at the development of a flight platform that features bat-inspired wings with smart materials-based flexible joints and artificial muscles, which has the potential to closely mimic the kinematics of the real mammalian flyer. The bat-like flight platform was selected after an extensive analysis of morphological and aerodynamic flight parameters of small birds, bats and large insects characterized by a superior maneuverability and wind gust rejection. Morphological and aerodynamic parameters were collected from existing literature and compared concluding that bat wing present a suitable platform that can be actuated efficiently using artificial muscles. Due to their wing camber variation, the bat species can operate effectively at a large range of speeds and exhibit a remarkably maneuverable and agile flight. Although numerous studies were recently investigated the flapping flight, flexible and foldable wings that reproduce the natural intricate and efficient flapping motion were not designed yet. A comprehensive analysis of flight styles in bats based on the data collected by Norberg (Norberg, 1976) and the engineering theory of robotic manipulators resulted in a 2 and 3-DOF models which managed to mimic the wingbeat cycle of the natural flyer. The flexible joints of the 2 and 2-DOF models were replicated using smart materials like superelastic Shape Memory Alloys (SMA). The results of these kinematic models can be used to optimize the lengths and the attachment locations of the actuator muscle-wires such that enough lift, thrust and wing stroke are obtained. Bat skeleton measurements were taken from real bats and modeled in SolidWorks to accurately reproduce bones and body via rapid prototyping methods. Much attention was paid specifically to achieving the comparable strength, elasticity, and range of motion of a naturally occurring bat. The wing joints of the BATMAV platform were fabricated using superelastic Shape Memory Alloys (SMA), a key technology for the development of an engineering skeleton structure. This has enabled a simple and straightforward connection between different bones while at the same time has preserved the full range of functionality of the natural role model. Therefore, several desktop models were designed, fabricated and assembled in order to study various materials used in design phase. As a whole, the BATMAV project consists of four major stages of development: the current phase -- design and fabrication of the skeletal structure of the flight platform, selection and testing different materials for the design of a compliant bat-like membrane, analysis of the kinematics and kinetics of bat flight in order to design a biomechanical muscle system for actuation, and design of the electrical control architecture to coordinate the platform flight.

Wine and Maths: Mathematical Solutions to Wine-Inspired Problems

ERIC Educational Resources Information Center

Cadeddu, L.; Cauli, A.

2018-01-01

We deal with an application of partial differential equations to the correct definition of a wine cellar. We present some historical details about this problem. We also discuss how to build or renew a wine cellar, creating ideal conditions for the ageing process and improving the quality of wines. Our goal is to calculate the optimal depth…

Past Forward: Nostalgia as a Motivational Force.

PubMed

Sedikides, Constantine; Wildschut, Tim

2016-05-01

Nostalgia has endured a negative reputation, being branded an unhealthy preoccupation with one's past. This reputation is unwarranted. Nostalgia has remarkable implications for one's future. It strengthens approach orientation, raises optimism, evokes inspiration, boosts creativity, and kindles prosociality. Far from reflecting escapism from the present, nostalgia potentiates an attainable future. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Unified Approach to Optimization

DTIC Science & Technology

2014-10-02

employee scheduling, ad placement, latin squares, disjunctions of linear systems, temporal modeling with interval variables, and traveling salesman problems ...integrating technologies. A key to integrated modeling is to formulate a problem with high-levelmetaconstraints, which are inspired by the “global... problem substructure to the solver. This contrasts with the atomistic modeling style of mixed integer programming (MIP) and satisfiability (SAT) solvers

Humanoids Learning to Walk: A Natural CPG-Actor-Critic Architecture.

PubMed

Li, Cai; Lowe, Robert; Ziemke, Tom

2013-01-01

The identification of learning mechanisms for locomotion has been the subject of much research for some time but many challenges remain. Dynamic systems theory (DST) offers a novel approach to humanoid learning through environmental interaction. Reinforcement learning (RL) has offered a promising method to adaptively link the dynamic system to the environment it interacts with via a reward-based value system. In this paper, we propose a model that integrates the above perspectives and applies it to the case of a humanoid (NAO) robot learning to walk the ability of which emerges from its value-based interaction with the environment. In the model, a simplified central pattern generator (CPG) architecture inspired by neuroscientific research and DST is integrated with an actor-critic approach to RL (cpg-actor-critic). In the cpg-actor-critic architecture, least-square-temporal-difference based learning converges to the optimal solution quickly by using natural gradient learning and balancing exploration and exploitation. Futhermore, rather than using a traditional (designer-specified) reward it uses a dynamic value function as a stability indicator that adapts to the environment. The results obtained are analyzed using a novel DST-based embodied cognition approach. Learning to walk, from this perspective, is a process of integrating levels of sensorimotor activity and value.

Humanoids Learning to Walk: A Natural CPG-Actor-Critic Architecture

PubMed Central

Li, Cai; Lowe, Robert; Ziemke, Tom

2013-01-01

The identification of learning mechanisms for locomotion has been the subject of much research for some time but many challenges remain. Dynamic systems theory (DST) offers a novel approach to humanoid learning through environmental interaction. Reinforcement learning (RL) has offered a promising method to adaptively link the dynamic system to the environment it interacts with via a reward-based value system. In this paper, we propose a model that integrates the above perspectives and applies it to the case of a humanoid (NAO) robot learning to walk the ability of which emerges from its value-based interaction with the environment. In the model, a simplified central pattern generator (CPG) architecture inspired by neuroscientific research and DST is integrated with an actor-critic approach to RL (cpg-actor-critic). In the cpg-actor-critic architecture, least-square-temporal-difference based learning converges to the optimal solution quickly by using natural gradient learning and balancing exploration and exploitation. Futhermore, rather than using a traditional (designer-specified) reward it uses a dynamic value function as a stability indicator that adapts to the environment. The results obtained are analyzed using a novel DST-based embodied cognition approach. Learning to walk, from this perspective, is a process of integrating levels of sensorimotor activity and value. PMID:23675345

Evaluation of Existing and New Periodic Tables of the Elements for the Chemistry Education of Blind Students

ERIC Educational Resources Information Center

Fantin, Dennis; Sutton, Marc; Daumann, Lena J.; Fischer, Kael F.

2016-01-01

As a symbol of the power and majesty of science, the periodic table has inspired many scientists-to-be to investigate the deep secrets of nature through the study of chemistry. In the spirit of inclusion, blind students too deserve and need to have their curiosity about the inner workings of nature stimulated through greater exposure to this…

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

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.

Shape and Color Features for Object Recognition Search

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Duong, Vu A.; Stubberud, Allen R.

2012-01-01

A bio-inspired shape feature of an object of interest emulates the integration of the saccadic eye movement and horizontal layer in vertebrate retina for object recognition search where a single object can be used one at a time. The optimal computational model for shape-extraction-based principal component analysis (PCA) was also developed to reduce processing time and enable the real-time adaptive system capability. A color feature of the object is employed as color segmentation to empower the shape feature recognition to solve the object recognition in the heterogeneous environment where a single technique - shape or color - may expose its difficulties. To enable the effective system, an adaptive architecture and autonomous mechanism were developed to recognize and adapt the shape and color feature of the moving object. The bio-inspired object recognition based on bio-inspired shape and color can be effective to recognize a person of interest in the heterogeneous environment where the single technique exposed its difficulties to perform effective recognition. Moreover, this work also demonstrates the mechanism and architecture of the autonomous adaptive system to enable the realistic system for the practical use in the future.

Internalized compartments encapsulated nanogels for targeted drug delivery

NASA Astrophysics Data System (ADS)

Yu, Jicheng; Zhang, Yuqi; Sun, Wujin; Wang, Chao; Ranson, Davis; Ye, Yanqi; Weng, Yuyan; Gu, Zhen

2016-04-01

Drug delivery systems inspired by natural particulates hold great promise for targeted cancer therapy. An endosome formed by internalization of plasma membrane has a massive amount of membrane proteins and receptors on the surface, which is able to specifically target the homotypic cells. Herein, we describe a simple method to fabricate an internalized compartments encapsulated nanogel with endosome membrane components (EM-NG) from source cancer cells. Following intracellular uptake of methacrylated hyaluronic acid (m-HA) adsorbed SiO2/Fe3O4 nanoparticles encapsulating a crosslinker and a photoinitiator, EM-NG was readily prepared through in situ crosslinking initiated under UV irradiation after internalization. The resulting nanogels loaded with doxorubicin (DOX) displayed enhanced internalization efficiency to the source cells through a specific homotypic affinity in vitro. However, when treated with the non-source cells, the EM-NGs exhibited insignificant difference in therapeutic efficiency compared to a bare HA nanogel with DOX. This study illustrates the potential of utilizing an internalized compartments encapsulated formulation for targeted cancer therapy, and offers guidelines for developing a natural particulate-inspired drug delivery system.Drug delivery systems inspired by natural particulates hold great promise for targeted cancer therapy. An endosome formed by internalization of plasma membrane has a massive amount of membrane proteins and receptors on the surface, which is able to specifically target the homotypic cells. Herein, we describe a simple method to fabricate an internalized compartments encapsulated nanogel with endosome membrane components (EM-NG) from source cancer cells. Following intracellular uptake of methacrylated hyaluronic acid (m-HA) adsorbed SiO2/Fe3O4 nanoparticles encapsulating a crosslinker and a photoinitiator, EM-NG was readily prepared through in situ crosslinking initiated under UV irradiation after internalization. The resulting nanogels loaded with doxorubicin (DOX) displayed enhanced internalization efficiency to the source cells through a specific homotypic affinity in vitro. However, when treated with the non-source cells, the EM-NGs exhibited insignificant difference in therapeutic efficiency compared to a bare HA nanogel with DOX. This study illustrates the potential of utilizing an internalized compartments encapsulated formulation for targeted cancer therapy, and offers guidelines for developing a natural particulate-inspired drug delivery system. Electronic supplementary information (ESI) available: Synthesis of m-HA; synthesis of rhodamine-HA derivative; supplementary data on relative fluorescence intensity of DOX-EN-NGs on HeLa cells. See DOI: 10.1039/c5nr08895j

Artemisinin, a miracle of traditional Chinese medicine.

PubMed

Kong, Ling Yi; Tan, Ren Xiang

2015-12-19

The 2015 Nobel Prize in Physiology or Medicine, shared by Professor Youyou Tu, focused worldwide attention on artemisinin, a natural product antimalarial drug inspired by traditional Chinese medicine (TCM). This is the first Nobel Prize in natural sciences presented to a Chinese scientist for her impactful research work in China in collaboration with other Chinese scientists. We are delighted to provide the background and implications of the discovery of artemisinin, along with our personal viewpoints toward the affordability of modern medicines from natural products.

Joint global optimization of tomographic data based on particle swarm optimization and decision theory

NASA Astrophysics Data System (ADS)

Paasche, H.; Tronicke, J.

2012-04-01

In many near surface geophysical applications multiple tomographic data sets are routinely acquired to explore subsurface structures and parameters. Linking the model generation process of multi-method geophysical data sets can significantly reduce ambiguities in geophysical data analysis and model interpretation. Most geophysical inversion approaches rely on local search optimization methods used to find an optimal model in the vicinity of a user-given starting model. The final solution may critically depend on the initial model. Alternatively, global optimization (GO) methods have been used to invert geophysical data. They explore the solution space in more detail and determine the optimal model independently from the starting model. Additionally, they can be used to find sets of optimal models allowing a further analysis of model parameter uncertainties. Here we employ particle swarm optimization (PSO) to realize the global optimization of tomographic data. PSO is an emergent methods based on swarm intelligence characterized by fast and robust convergence towards optimal solutions. The fundamental principle of PSO is inspired by nature, since the algorithm mimics the behavior of a flock of birds searching food in a search space. In PSO, a number of particles cruise a multi-dimensional solution space striving to find optimal model solutions explaining the acquired data. The particles communicate their positions and success and direct their movement according to the position of the currently most successful particle of the swarm. The success of a particle, i.e. the quality of the currently found model by a particle, must be uniquely quantifiable to identify the swarm leader. When jointly inverting disparate data sets, the optimization solution has to satisfy multiple optimization objectives, at least one for each data set. Unique determination of the most successful particle currently leading the swarm is not possible. Instead, only statements about the Pareto optimality of the found solutions can be made. Identification of the leading particle traditionally requires a costly combination of ranking and niching techniques. In our approach, we use a decision rule under uncertainty to identify the currently leading particle of the swarm. In doing so, we consider the different objectives of our optimization problem as competing agents with partially conflicting interests. Analysis of the maximin fitness function allows for robust and cheap identification of the currently leading particle. The final optimization result comprises a set of possible models spread along the Pareto front. For convex Pareto fronts, solution density is expected to be maximal in the region ideally compromising all objectives, i.e. the region of highest curvature.

Modified artificial bee colony algorithm for reactive power optimization

NASA Astrophysics Data System (ADS)

Sulaiman, Noorazliza; Mohamad-Saleh, Junita; Abro, Abdul Ghani

2015-05-01

Bio-inspired algorithms (BIAs) implemented to solve various optimization problems have shown promising results which are very important in this severely complex real-world. Artificial Bee Colony (ABC) algorithm, a kind of BIAs has demonstrated tremendous results as compared to other optimization algorithms. This paper presents a new modified ABC algorithm referred to as JA-ABC3 with the aim to enhance convergence speed and avoid premature convergence. The proposed algorithm has been simulated on ten commonly used benchmarks functions. Its performance has also been compared with other existing ABC variants. To justify its robust applicability, the proposed algorithm has been tested to solve Reactive Power Optimization problem. The results have shown that the proposed algorithm has superior performance to other existing ABC variants e.g. GABC, BABC1, BABC2, BsfABC dan IABC in terms of convergence speed. Furthermore, the proposed algorithm has also demonstrated excellence performance in solving Reactive Power Optimization problem.

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.

Astronomy. Inspiration. Art

NASA Astrophysics Data System (ADS)

Stanic, N.

2008-10-01

This paper speculates how poetry and other kind of arts are tightly related to astronomy. Hence the connection between art and natural sciences in general will be discussed in the frame of ongoing multidisciplinary project `Astronomy. Inspiration. Art' at Public Observatory in Belgrade (started in 2004). This project tends to inspire (better to say `infect') artist with a cosmic themes and fantastic sceneries of the Universe. At the very beginning of the project, Serbian poet and philosopher Laza Lazić (who published 49 books of poetry, stories and novels), as well as writer Gordana Maletić (with 25 published novels for children) were interested to work on The Inspiration by Astronomical Phenomena in Serbian Literature. Five young artists and scientists include their new ideas and new approach to multidisciplinary studies too (Srdjan Djukić, Nenad Jeremić, Olivera Obradović, Romana Vujasinović, Elena Dimoski). Two books that will be presented in details in the frame of this Project, "STARRY CITIES" (http://zavod.co.yu) and "ASTROLIES", don't offer only interesting illustrations, images from the latest astronomical observations and currently accepted cosmological theories -- those books induces, provoking curiosity in a specific and witty way, an adventure and challenge to explore and create.

Bioinspired Hierarchical Alumina-Graphene Oxide-Poly(vinyl alcohol) Artificial Nacre with Optimized Strength and Toughness.

PubMed

Wang, Jinrong; Qiao, Jinliang; Wang, Jianfeng; Zhu, Ying; Jiang, Lei

2015-05-06

Due to hierarchical organization of micro- and nanostructures, natural nacre exhibits extraordinary strength and toughness, and thus provides a superior model for the design and fabrication of high-performance artificial composite materials. Although great progress has been made in constructing layered composites by alternately stacking hard inorganic platelets and soft polymers, the real issue is that the excellent strength of these composites was obtained at the sacrifice of toughness. In this work, inspired by the layered aragonite microplatelets/chitin nanofibers-protein structure of natural nacre, alumina microplatelets-graphene oxide nanosheets-poly(vinyl alcohol) (Al2O3/GO-PVA) artificial nacre is successfully constructed through layer-by-layer bottom-up assembly, in which Al2O3 and GO-PVA act as "bricks" and "mortar", respectively. The artificial nacre has hierarchical "brick-and-mortar" structure and exhibits excellent strength (143 ± 13 MPa) and toughness (9.2 ± 2.7 MJ/m(3)), which are superior to those of natural nacre (80-135 MPa, 1.8 MJ/m(3)). It was demonstrated that the multiscale hierarchical structure of ultrathin GO nanosheets and submicrometer-thick Al2O3 platelets can deal with the conflict between strength and toughness, thus leading to the excellent mechanical properties that cannot be obtained using only one size of platelet. We strongly believe that the work presented here provides a creative strategy for designing and developing new composites with excellent strength and toughness.

LEWIS ACID CATALYZED FORMATION OF TETRAHYDROPYRANS IN IONIC LIQUID

EPA Science Inventory

Tetrahydropyrans are integral moieties in innumerable natural products and have inspired the development of a variety of different methodologies. A Prins-type cyclization involving the coupling of a homoallylic alcohol and an aldehyde in the presence of catalytic scandium triflat...

Re-naturing the city: a role for sustainable infrastructure and buildings

Treesearch

Hillary Brown

2009-01-01

One of 18 articles inspired by the Meristem 2007 Forum, "Restorative Commons for Community Health." The articles include interviews, case studies, thought pieces, and interdisciplinary theoretical works that explore the relationship between human health and the urban...

Angle dependent antireflection property of TiO2 inspired by cicada wings

NASA Astrophysics Data System (ADS)

Zada, Imran; Zhang, Wang; Li, Yao; Sun, Peng; Cai, Nianjin; Gu, Jiajun; Liu, Qinglei; Su, Huilan; Zhang, Di

2016-10-01

Inspired by cicada wings, biomorphic TiO2 with antireflective structures (ARSs) was precisely fabricated using a simple, inexpensive, and highly effective sol-gel process combined with subsequent calcination. It was confirmed that the fabricated biomorphic TiO2 not only effectively inherited the ARS but also exhibited high-performance angle dependent antireflective properties ranging from normal to 45°. Reflectance spectra demonstrated that the reflectivity of the biomorphic TiO2 with ARSs gradually changed from 1.4% to 7.8% with the increasing incidence angle over a large visible wavelength range. This angle dependent antireflective property is attributed to an optimized gradient refractive index between air and TiO2 via ARSs on the surface. Such surfaces with ARSs may have potential application in solar cells.

Magic trees in mammalians respiration or when evolution selected clever physical systems

NASA Astrophysics Data System (ADS)

Sapoval, B.; Filoche, M.

2014-03-01

The respiratory system of mammalians is made of two successive branched structures with different physiological functions. The upper structure, or bronchial tree, is a fluid transportation system made of approximately 15 generations of bifurcations leading to the order of 215= 30.000 bronchioles with a diameter of order 0.5 mm in the human lung.1 The branching pattern continues up to generation 23 but the structure and function of each of the subsequent structures, called the acini, is different. Each acinus is made of a branched system of ducts surrounded by alveolae and play the role of a diffusion cell where oxygen and carbon dioxide are exchanged with blood across the alveolar membrane.2 We show in this letter that the bronchial tree present simultaneously several optimal properties of totally different nature. It is first energy efficient3-6, second, it is space filling;7 and third it is "rapid" as discussed here. It is this multi-optimality that is qualified here as magic. The multioptimality physical characteristic suggests that, in the course of evolution, an organ selected against one criterion could have been later used later for a totally different reason. For example, once energetic efficiency for the transport of a viscous fluid like blood has been selected, the same genetic material could have been used for its optimized rapidity. This would have allowed the emergence of mammalian respiration made of inspiration-expiration cycles. For this phenomenon to exist, the rapid character is essential, as fresh air has to reach the gas exchange organs, the pulmonary acini, before the start of expiration.

Do Trees Have Personalities? Experiencing the Concepts of Texture and Form

ERIC Educational Resources Information Center

Kosta, Timothy J.

2012-01-01

Nature is all around, and can be the inspiration for some excellent creations in the classroom. How can a teacher bring these rich natural elements into the art class? As the author was exploring a hiking trail, he came across a large piece of bark from an old oak tree. A strong wind began to blow through the trees, the leaves began to rustle and…