A clustering method of Chinese medicine prescriptions based on modified firefly algorithm.

PubMed

Yuan, Feng; Liu, Hong; Chen, Shou-Qiang; Xu, Liang

2016-12-01

This paper is aimed to study the clustering method for Chinese medicine (CM) medical cases. The traditional K-means clustering algorithm had shortcomings such as dependence of results on the selection of initial value, trapping in local optimum when processing prescriptions form CM medical cases. Therefore, a new clustering method based on the collaboration of firefly algorithm and simulated annealing algorithm was proposed. This algorithm dynamically determined the iteration of firefly algorithm and simulates sampling of annealing algorithm by fitness changes, and increased the diversity of swarm through expansion of the scope of the sudden jump, thereby effectively avoiding premature problem. The results from confirmatory experiments for CM medical cases suggested that, comparing with traditional K-means clustering algorithms, this method was greatly improved in the individual diversity and the obtained clustering results, the computing results from this method had a certain reference value for cluster analysis on CM prescriptions.

A Firefly Algorithm-based Approach for Pseudo-Relevance Feedback: Application to Medical Database.

PubMed

Khennak, Ilyes; Drias, Habiba

2016-11-01

The difficulty of disambiguating the sense of the incomplete and imprecise keywords that are extensively used in the search queries has caused the failure of search systems to retrieve the desired information. One of the most powerful and promising method to overcome this shortcoming and improve the performance of search engines is Query Expansion, whereby the user's original query is augmented by new keywords that best characterize the user's information needs and produce more useful query. In this paper, a new Firefly Algorithm-based approach is proposed to enhance the retrieval effectiveness of query expansion while maintaining low computational complexity. In contrast to the existing literature, the proposed approach uses a Firefly Algorithm to find the best expanded query among a set of expanded query candidates. Moreover, this new approach allows the determination of the length of the expanded query empirically. Experimental results on MEDLINE, the on-line medical information database, show that our proposed approach is more effective and efficient compared to the state-of-the-art.

Basic firefly algorithm for document clustering

NASA Astrophysics Data System (ADS)

Mohammed, Athraa Jasim; Yusof, Yuhanis; Husni, Husniza

2015-12-01

The Document clustering plays significant role in Information Retrieval (IR) where it organizes documents prior to the retrieval process. To date, various clustering algorithms have been proposed and this includes the K-means and Particle Swarm Optimization. Even though these algorithms have been widely applied in many disciplines due to its simplicity, such an approach tends to be trapped in a local minimum during its search for an optimal solution. To address the shortcoming, this paper proposes a Basic Firefly (Basic FA) algorithm to cluster text documents. The algorithm employs the Average Distance to Document Centroid (ADDC) as the objective function of the search. Experiments utilizing the proposed algorithm were conducted on the 20Newsgroups benchmark dataset. Results demonstrate that the Basic FA generates a more robust and compact clusters than the ones produced by K-means and Particle Swarm Optimization (PSO).

The construction of support vector machine classifier using the firefly algorithm.

PubMed

Chao, Chih-Feng; Horng, Ming-Huwi

2015-01-01

The setting of parameters in the support vector machines (SVMs) is very important with regard to its accuracy and efficiency. In this paper, we employ the firefly algorithm to train all parameters of the SVM simultaneously, including the penalty parameter, smoothness parameter, and Lagrangian multiplier. The proposed method is called the firefly-based SVM (firefly-SVM). This tool is not considered the feature selection, because the SVM, together with feature selection, is not suitable for the application in a multiclass classification, especially for the one-against-all multiclass SVM. In experiments, binary and multiclass classifications are explored. In the experiments on binary classification, ten of the benchmark data sets of the University of California, Irvine (UCI), machine learning repository are used; additionally the firefly-SVM is applied to the multiclass diagnosis of ultrasonic supraspinatus images. The classification performance of firefly-SVM is also compared to the original LIBSVM method associated with the grid search method and the particle swarm optimization based SVM (PSO-SVM). The experimental results advocate the use of firefly-SVM to classify pattern classifications for maximum accuracy.

The Construction of Support Vector Machine Classifier Using the Firefly Algorithm

PubMed Central

Chao, Chih-Feng; Horng, Ming-Huwi

2015-01-01

The setting of parameters in the support vector machines (SVMs) is very important with regard to its accuracy and efficiency. In this paper, we employ the firefly algorithm to train all parameters of the SVM simultaneously, including the penalty parameter, smoothness parameter, and Lagrangian multiplier. The proposed method is called the firefly-based SVM (firefly-SVM). This tool is not considered the feature selection, because the SVM, together with feature selection, is not suitable for the application in a multiclass classification, especially for the one-against-all multiclass SVM. In experiments, binary and multiclass classifications are explored. In the experiments on binary classification, ten of the benchmark data sets of the University of California, Irvine (UCI), machine learning repository are used; additionally the firefly-SVM is applied to the multiclass diagnosis of ultrasonic supraspinatus images. The classification performance of firefly-SVM is also compared to the original LIBSVM method associated with the grid search method and the particle swarm optimization based SVM (PSO-SVM). The experimental results advocate the use of firefly-SVM to classify pattern classifications for maximum accuracy. PMID:25802511

Clustering PPI data by combining FA and SHC method.

PubMed

Lei, Xiujuan; Ying, Chao; Wu, Fang-Xiang; Xu, Jin

2015-01-01

Clustering is one of main methods to identify functional modules from protein-protein interaction (PPI) data. Nevertheless traditional clustering methods may not be effective for clustering PPI data. In this paper, we proposed a novel method for clustering PPI data by combining firefly algorithm (FA) and synchronization-based hierarchical clustering (SHC) algorithm. Firstly, the PPI data are preprocessed via spectral clustering (SC) which transforms the high-dimensional similarity matrix into a low dimension matrix. Then the SHC algorithm is used to perform clustering. In SHC algorithm, hierarchical clustering is achieved by enlarging the neighborhood radius of synchronized objects continuously, while the hierarchical search is very difficult to find the optimal neighborhood radius of synchronization and the efficiency is not high. So we adopt the firefly algorithm to determine the optimal threshold of the neighborhood radius of synchronization automatically. The proposed algorithm is tested on the MIPS PPI dataset. The results show that our proposed algorithm is better than the traditional algorithms in precision, recall and f-measure value.

Clustering PPI data by combining FA and SHC method

PubMed Central

2015-01-01

Clustering is one of main methods to identify functional modules from protein-protein interaction (PPI) data. Nevertheless traditional clustering methods may not be effective for clustering PPI data. In this paper, we proposed a novel method for clustering PPI data by combining firefly algorithm (FA) and synchronization-based hierarchical clustering (SHC) algorithm. Firstly, the PPI data are preprocessed via spectral clustering (SC) which transforms the high-dimensional similarity matrix into a low dimension matrix. Then the SHC algorithm is used to perform clustering. In SHC algorithm, hierarchical clustering is achieved by enlarging the neighborhood radius of synchronized objects continuously, while the hierarchical search is very difficult to find the optimal neighborhood radius of synchronization and the efficiency is not high. So we adopt the firefly algorithm to determine the optimal threshold of the neighborhood radius of synchronization automatically. The proposed algorithm is tested on the MIPS PPI dataset. The results show that our proposed algorithm is better than the traditional algorithms in precision, recall and f-measure value. PMID:25707632

A GPU-Based Implementation of the Firefly Algorithm for Variable Selection in Multivariate Calibration Problems

PubMed Central

de Paula, Lauro C. M.; Soares, Anderson S.; de Lima, Telma W.; Delbem, Alexandre C. B.; Coelho, Clarimar J.; Filho, Arlindo R. G.

2014-01-01

Several variable selection algorithms in multivariate calibration can be accelerated using Graphics Processing Units (GPU). Among these algorithms, the Firefly Algorithm (FA) is a recent proposed metaheuristic that may be used for variable selection. This paper presents a GPU-based FA (FA-MLR) with multiobjective formulation for variable selection in multivariate calibration problems and compares it with some traditional sequential algorithms in the literature. The advantage of the proposed implementation is demonstrated in an example involving a relatively large number of variables. The results showed that the FA-MLR, in comparison with the traditional algorithms is a more suitable choice and a relevant contribution for the variable selection problem. Additionally, the results also demonstrated that the FA-MLR performed in a GPU can be five times faster than its sequential implementation. PMID:25493625

A GPU-Based Implementation of the Firefly Algorithm for Variable Selection in Multivariate Calibration Problems.

PubMed

de Paula, Lauro C M; Soares, Anderson S; de Lima, Telma W; Delbem, Alexandre C B; Coelho, Clarimar J; Filho, Arlindo R G

2014-01-01

Several variable selection algorithms in multivariate calibration can be accelerated using Graphics Processing Units (GPU). Among these algorithms, the Firefly Algorithm (FA) is a recent proposed metaheuristic that may be used for variable selection. This paper presents a GPU-based FA (FA-MLR) with multiobjective formulation for variable selection in multivariate calibration problems and compares it with some traditional sequential algorithms in the literature. The advantage of the proposed implementation is demonstrated in an example involving a relatively large number of variables. The results showed that the FA-MLR, in comparison with the traditional algorithms is a more suitable choice and a relevant contribution for the variable selection problem. Additionally, the results also demonstrated that the FA-MLR performed in a GPU can be five times faster than its sequential implementation.

Firefly algorithm with chaos

NASA Astrophysics Data System (ADS)

Gandomi, A. H.; Yang, X.-S.; Talatahari, S.; Alavi, A. H.

2013-01-01

A recently developed metaheuristic optimization algorithm, firefly algorithm (FA), mimics the social behavior of fireflies based on the flashing and attraction characteristics of fireflies. In the present study, we will introduce chaos into FA so as to increase its global search mobility for robust global optimization. Detailed studies are carried out on benchmark problems with different chaotic maps. Here, 12 different chaotic maps are utilized to tune the attractive movement of the fireflies in the algorithm. The results show that some chaotic FAs can clearly outperform the standard FA.

Wireless sensor placement for structural monitoring using information-fusing firefly algorithm

NASA Astrophysics Data System (ADS)

Zhou, Guang-Dong; Yi, Ting-Hua; Xie, Mei-Xi; Li, Hong-Nan

2017-10-01

Wireless sensor networks (WSNs) are promising technology in structural health monitoring (SHM) applications for their low cost and high efficiency. The limited wireless sensors and restricted power resources in WSNs highlight the significance of optimal wireless sensor placement (OWSP) during designing SHM systems to enable the most useful information to be captured and to achieve the longest network lifetime. This paper presents a holistic approach, including an optimization criterion and a solution algorithm, for optimally deploying self-organizing multi-hop WSNs on large-scale structures. The combination of information effectiveness represented by the modal independence and the network performance specified by the network connectivity and network lifetime is first formulated to evaluate the performance of wireless sensor configurations. Then, an information-fusing firefly algorithm (IFFA) is developed to solve the OWSP problem. The step sizes drawn from a Lévy distribution are adopted to drive fireflies toward brighter individuals. Following the movement with Lévy flights, information about the contributions of wireless sensors to the objective function as carried by the fireflies is fused and applied to move inferior wireless sensors to better locations. The reliability of the proposed approach is verified via a numerical example on a long-span suspension bridge. The results demonstrate that the evaluation criterion provides a good performance metric of wireless sensor configurations, and the IFFA outperforms the simple discrete firefly algorithm.

A firefly algorithm for solving competitive location-design problem: a case study

NASA Astrophysics Data System (ADS)

Sadjadi, Seyed Jafar; Ashtiani, Milad Gorji; Ramezanian, Reza; Makui, Ahmad

2016-12-01

This paper aims at determining the optimal number of new facilities besides specifying both the optimal location and design level of them under the budget constraint in a competitive environment by a novel hybrid continuous and discrete firefly algorithm. A real-world application of locating new chain stores in the city of Tehran, Iran, is used and the results are analyzed. In addition, several examples have been solved to evaluate the efficiency of the proposed model and algorithm. The results demonstrate that the performed method provides good-quality results for the test problems.

Feature Selection for Motor Imagery EEG Classification Based on Firefly Algorithm and Learning Automata

PubMed Central

Liu, Aiming; Liu, Quan; Ai, Qingsong; Xie, Yi; Chen, Anqi

2017-01-01

Motor Imagery (MI) electroencephalography (EEG) is widely studied for its non-invasiveness, easy availability, portability, and high temporal resolution. As for MI EEG signal processing, the high dimensions of features represent a research challenge. It is necessary to eliminate redundant features, which not only create an additional overhead of managing the space complexity, but also might include outliers, thereby reducing classification accuracy. The firefly algorithm (FA) can adaptively select the best subset of features, and improve classification accuracy. However, the FA is easily entrapped in a local optimum. To solve this problem, this paper proposes a method of combining the firefly algorithm and learning automata (LA) to optimize feature selection for motor imagery EEG. We employed a method of combining common spatial pattern (CSP) and local characteristic-scale decomposition (LCD) algorithms to obtain a high dimensional feature set, and classified it by using the spectral regression discriminant analysis (SRDA) classifier. Both the fourth brain–computer interface competition data and real-time data acquired in our designed experiments were used to verify the validation of the proposed method. Compared with genetic and adaptive weight particle swarm optimization algorithms, the experimental results show that our proposed method effectively eliminates redundant features, and improves the classification accuracy of MI EEG signals. In addition, a real-time brain–computer interface system was implemented to verify the feasibility of our proposed methods being applied in practical brain–computer interface systems. PMID:29117100

Feature Selection for Motor Imagery EEG Classification Based on Firefly Algorithm and Learning Automata.

PubMed

Liu, Aiming; Chen, Kun; Liu, Quan; Ai, Qingsong; Xie, Yi; Chen, Anqi

2017-11-08

Motor Imagery (MI) electroencephalography (EEG) is widely studied for its non-invasiveness, easy availability, portability, and high temporal resolution. As for MI EEG signal processing, the high dimensions of features represent a research challenge. It is necessary to eliminate redundant features, which not only create an additional overhead of managing the space complexity, but also might include outliers, thereby reducing classification accuracy. The firefly algorithm (FA) can adaptively select the best subset of features, and improve classification accuracy. However, the FA is easily entrapped in a local optimum. To solve this problem, this paper proposes a method of combining the firefly algorithm and learning automata (LA) to optimize feature selection for motor imagery EEG. We employed a method of combining common spatial pattern (CSP) and local characteristic-scale decomposition (LCD) algorithms to obtain a high dimensional feature set, and classified it by using the spectral regression discriminant analysis (SRDA) classifier. Both the fourth brain-computer interface competition data and real-time data acquired in our designed experiments were used to verify the validation of the proposed method. Compared with genetic and adaptive weight particle swarm optimization algorithms, the experimental results show that our proposed method effectively eliminates redundant features, and improves the classification accuracy of MI EEG signals. In addition, a real-time brain-computer interface system was implemented to verify the feasibility of our proposed methods being applied in practical brain-computer interface systems.

Continuous Firefly Algorithm for Optimal Tuning of Pid Controller in Avr System

NASA Astrophysics Data System (ADS)

Bendjeghaba, Omar

2014-01-01

This paper presents a tuning approach based on Continuous firefly algorithm (CFA) to obtain the proportional-integral- derivative (PID) controller parameters in Automatic Voltage Regulator system (AVR). In the tuning processes the CFA is iterated to reach the optimal or the near optimal of PID controller parameters when the main goal is to improve the AVR step response characteristics. Conducted simulations show the effectiveness and the efficiency of the proposed approach. Furthermore the proposed approach can improve the dynamic of the AVR system. Compared with particle swarm optimization (PSO), the new CFA tuning method has better control system performance in terms of time domain specifications and set-point tracking.

Synchronous Firefly Algorithm for Cluster Head Selection in WSN.

PubMed

Baskaran, Madhusudhanan; Sadagopan, Chitra

2015-01-01

Wireless Sensor Network (WSN) consists of small low-cost, low-power multifunctional nodes interconnected to efficiently aggregate and transmit data to sink. Cluster-based approaches use some nodes as Cluster Heads (CHs) and organize WSNs efficiently for aggregation of data and energy saving. A CH conveys information gathered by cluster nodes and aggregates/compresses data before transmitting it to a sink. However, this additional responsibility of the node results in a higher energy drain leading to uneven network degradation. Low Energy Adaptive Clustering Hierarchy (LEACH) offsets this by probabilistically rotating cluster heads role among nodes with energy above a set threshold. CH selection in WSN is NP-Hard as optimal data aggregation with efficient energy savings cannot be solved in polynomial time. In this work, a modified firefly heuristic, synchronous firefly algorithm, is proposed to improve the network performance. Extensive simulation shows the proposed technique to perform well compared to LEACH and energy-efficient hierarchical clustering. Simulations show the effectiveness of the proposed method in decreasing the packet loss ratio by an average of 9.63% and improving the energy efficiency of the network when compared to LEACH and EEHC.

Arterial cannula shape optimization by means of the rotational firefly algorithm

NASA Astrophysics Data System (ADS)

Tesch, K.; Kaczorowska, K.

2016-03-01

This article presents global optimization results of arterial cannula shapes by means of the newly modified firefly algorithm. The search for the optimal arterial cannula shape is necessary in order to minimize losses and prepare the flow that leaves the circulatory support system of a ventricle (i.e. blood pump) before it reaches the heart. A modification of the standard firefly algorithm, the so-called rotational firefly algorithm, is introduced. It is shown that the rotational firefly algorithm allows for better exploration of search spaces which results in faster convergence and better solutions in comparison with its standard version. This is particularly pronounced for smaller population sizes. Furthermore, it maintains greater diversity of populations for a longer time. A small population size and a low number of iterations are necessary to keep to a minimum the computational cost of the objective function of the problem, which comes from numerical solution of the nonlinear partial differential equations. Moreover, both versions of the firefly algorithm are compared to the state of the art, namely the differential evolution and covariance matrix adaptation evolution strategies.

Synchronous Firefly Algorithm for Cluster Head Selection in WSN

PubMed Central

Baskaran, Madhusudhanan; Sadagopan, Chitra

2015-01-01

Wireless Sensor Network (WSN) consists of small low-cost, low-power multifunctional nodes interconnected to efficiently aggregate and transmit data to sink. Cluster-based approaches use some nodes as Cluster Heads (CHs) and organize WSNs efficiently for aggregation of data and energy saving. A CH conveys information gathered by cluster nodes and aggregates/compresses data before transmitting it to a sink. However, this additional responsibility of the node results in a higher energy drain leading to uneven network degradation. Low Energy Adaptive Clustering Hierarchy (LEACH) offsets this by probabilistically rotating cluster heads role among nodes with energy above a set threshold. CH selection in WSN is NP-Hard as optimal data aggregation with efficient energy savings cannot be solved in polynomial time. In this work, a modified firefly heuristic, synchronous firefly algorithm, is proposed to improve the network performance. Extensive simulation shows the proposed technique to perform well compared to LEACH and energy-efficient hierarchical clustering. Simulations show the effectiveness of the proposed method in decreasing the packet loss ratio by an average of 9.63% and improving the energy efficiency of the network when compared to LEACH and EEHC. PMID:26495431

Rayleigh wave nonlinear inversion based on the Firefly algorithm

NASA Astrophysics Data System (ADS)

Zhou, Teng-Fei; Peng, Geng-Xin; Hu, Tian-Yue; Duan, Wen-Sheng; Yao, Feng-Chang; Liu, Yi-Mou

2014-06-01

Rayleigh waves have high amplitude, low frequency, and low velocity, which are treated as strong noise to be attenuated in reflected seismic surveys. This study addresses how to identify useful shear wave velocity profile and stratigraphic information from Rayleigh waves. We choose the Firefly algorithm for inversion of surface waves. The Firefly algorithm, a new type of particle swarm optimization, has the advantages of being robust, highly effective, and allows global searching. This algorithm is feasible and has advantages for use in Rayleigh wave inversion with both synthetic models and field data. The results show that the Firefly algorithm, which is a robust and practical method, can achieve nonlinear inversion of surface waves with high resolution.

Motion Estimation Using the Firefly Algorithm in Ultrasonic Image Sequence of Soft Tissue

PubMed Central

Chao, Chih-Feng; Horng, Ming-Huwi; Chen, Yu-Chan

2015-01-01

Ultrasonic image sequence of the soft tissue is widely used in disease diagnosis; however, the speckle noises usually influenced the image quality. These images usually have a low signal-to-noise ratio presentation. The phenomenon gives rise to traditional motion estimation algorithms that are not suitable to measure the motion vectors. In this paper, a new motion estimation algorithm is developed for assessing the velocity field of soft tissue in a sequence of ultrasonic B-mode images. The proposed iterative firefly algorithm (IFA) searches for few candidate points to obtain the optimal motion vector, and then compares it to the traditional iterative full search algorithm (IFSA) via a series of experiments of in vivo ultrasonic image sequences. The experimental results show that the IFA can assess the vector with better efficiency and almost equal estimation quality compared to the traditional IFSA method. PMID:25873987

Motion estimation using the firefly algorithm in ultrasonic image sequence of soft tissue.

PubMed

Chao, Chih-Feng; Horng, Ming-Huwi; Chen, Yu-Chan

2015-01-01

Ultrasonic image sequence of the soft tissue is widely used in disease diagnosis; however, the speckle noises usually influenced the image quality. These images usually have a low signal-to-noise ratio presentation. The phenomenon gives rise to traditional motion estimation algorithms that are not suitable to measure the motion vectors. In this paper, a new motion estimation algorithm is developed for assessing the velocity field of soft tissue in a sequence of ultrasonic B-mode images. The proposed iterative firefly algorithm (IFA) searches for few candidate points to obtain the optimal motion vector, and then compares it to the traditional iterative full search algorithm (IFSA) via a series of experiments of in vivo ultrasonic image sequences. The experimental results show that the IFA can assess the vector with better efficiency and almost equal estimation quality compared to the traditional IFSA method.

An evolutionary firefly algorithm for the estimation of nonlinear biological model parameters.

PubMed

Abdullah, Afnizanfaizal; Deris, Safaai; Anwar, Sohail; Arjunan, Satya N V

2013-01-01

The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test.

An Evolutionary Firefly Algorithm for the Estimation of Nonlinear Biological Model Parameters

PubMed Central

Abdullah, Afnizanfaizal; Deris, Safaai; Anwar, Sohail; Arjunan, Satya N. V.

2013-01-01

The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test. PMID:23469172

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.

Support vector machine firefly algorithm based optimization of lens system.

PubMed

Shamshirband, Shahaboddin; Petković, Dalibor; Pavlović, Nenad T; Ch, Sudheer; Altameem, Torki A; Gani, Abdullah

2015-01-01

Lens system design is an important factor in image quality. The main aspect of the lens system design methodology is the optimization procedure. Since optimization is a complex, nonlinear task, soft computing optimization algorithms can be used. There are many tools that can be employed to measure optical performance, but the spot diagram is the most useful. The spot diagram gives an indication of the image of a point object. In this paper, the spot size radius is considered an optimization criterion. Intelligent soft computing scheme support vector machines (SVMs) coupled with the firefly algorithm (FFA) are implemented. The performance of the proposed estimators is confirmed with the simulation results. The result of the proposed SVM-FFA model has been compared with support vector regression (SVR), artificial neural networks, and generic programming methods. The results show that the SVM-FFA model performs more accurately than the other methodologies. Therefore, SVM-FFA can be used as an efficient soft computing technique in the optimization of lens system designs.

Adaptive firefly algorithm: parameter analysis and its application.

PubMed

Cheung, Ngaam J; Ding, Xue-Ming; Shen, Hong-Bin

2014-01-01

As a nature-inspired search algorithm, firefly algorithm (FA) has several control parameters, which may have great effects on its performance. In this study, we investigate the parameter selection and adaptation strategies in a modified firefly algorithm - adaptive firefly algorithm (AdaFa). There are three strategies in AdaFa including (1) a distance-based light absorption coefficient; (2) a gray coefficient enhancing fireflies to share difference information from attractive ones efficiently; and (3) five different dynamic strategies for the randomization parameter. Promising selections of parameters in the strategies are analyzed to guarantee the efficient performance of AdaFa. AdaFa is validated over widely used benchmark functions, and the numerical experiments and statistical tests yield useful conclusions on the strategies and the parameter selections affecting the performance of AdaFa. When applied to the real-world problem - protein tertiary structure prediction, the results demonstrated improved variants can rebuild the tertiary structure with the average root mean square deviation less than 0.4Å and 1.5Å from the native constrains with noise free and 10% Gaussian white noise.

Adaptive Firefly Algorithm: Parameter Analysis and its Application

PubMed Central

Shen, Hong-Bin

2014-01-01

As a nature-inspired search algorithm, firefly algorithm (FA) has several control parameters, which may have great effects on its performance. In this study, we investigate the parameter selection and adaptation strategies in a modified firefly algorithm — adaptive firefly algorithm (AdaFa). There are three strategies in AdaFa including (1) a distance-based light absorption coefficient; (2) a gray coefficient enhancing fireflies to share difference information from attractive ones efficiently; and (3) five different dynamic strategies for the randomization parameter. Promising selections of parameters in the strategies are analyzed to guarantee the efficient performance of AdaFa. AdaFa is validated over widely used benchmark functions, and the numerical experiments and statistical tests yield useful conclusions on the strategies and the parameter selections affecting the performance of AdaFa. When applied to the real-world problem — protein tertiary structure prediction, the results demonstrated improved variants can rebuild the tertiary structure with the average root mean square deviation less than 0.4Å and 1.5Å from the native constrains with noise free and 10% Gaussian white noise. PMID:25397812

The application of Firefly algorithm in an Adaptive Emergency Evacuation Centre Management (AEECM) for dynamic relocation of flood victims

NASA Astrophysics Data System (ADS)

ChePa, Noraziah; Hashim, Nor Laily; Yusof, Yuhanis; Hussain, Azham

2016-08-01

Flood evacuation centre is defined as a temporary location or area of people from disaster particularly flood as a rescue or precautionary measure. Gazetted evacuation centres are normally located at secure places which have small chances from being drowned by flood. However, due to extreme flood several evacuation centres in Kelantan were unexpectedly drowned. Currently, there is no study done on proposing a decision support aid to reallocate victims and resources of the evacuation centre when the situation getting worsens. Therefore, this study proposes a decision aid model to be utilized in realizing an adaptive emergency evacuation centre management system. This study undergoes two main phases; development of algorithm and models, and development of a web-based and mobile app. The proposed model operates using Firefly multi-objective optimization algorithm that creates an optimal schedule for the relocation of victims and resources for an evacuation centre. The proposed decision aid model and the adaptive system can be applied in supporting the National Security Council's respond mechanisms for handling disaster management level II (State level) especially in providing better management of the flood evacuating centres.

Firefly algorithm versus genetic algorithm as powerful variable selection tools and their effect on different multivariate calibration models in spectroscopy: A comparative study

NASA Astrophysics Data System (ADS)

Attia, Khalid A. M.; Nassar, Mohammed W. I.; El-Zeiny, Mohamed B.; Serag, Ahmed

2017-01-01

For the first time, a new variable selection method based on swarm intelligence namely firefly algorithm is coupled with three different multivariate calibration models namely, concentration residual augmented classical least squares, artificial neural network and support vector regression in UV spectral data. A comparative study between the firefly algorithm and the well-known genetic algorithm was developed. The discussion revealed the superiority of using this new powerful algorithm over the well-known genetic algorithm. Moreover, different statistical tests were performed and no significant differences were found between all the models regarding their predictabilities. This ensures that simpler and faster models were obtained without any deterioration of the quality of the calibration.

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.

Firefly algorithm versus genetic algorithm as powerful variable selection tools and their effect on different multivariate calibration models in spectroscopy: A comparative study.

PubMed

Attia, Khalid A M; Nassar, Mohammed W I; El-Zeiny, Mohamed B; Serag, Ahmed

2017-01-05

For the first time, a new variable selection method based on swarm intelligence namely firefly algorithm is coupled with three different multivariate calibration models namely, concentration residual augmented classical least squares, artificial neural network and support vector regression in UV spectral data. A comparative study between the firefly algorithm and the well-known genetic algorithm was developed. The discussion revealed the superiority of using this new powerful algorithm over the well-known genetic algorithm. Moreover, different statistical tests were performed and no significant differences were found between all the models regarding their predictabilities. This ensures that simpler and faster models were obtained without any deterioration of the quality of the calibration. Copyright © 2016 Elsevier B.V. All rights reserved.

Optimized extreme learning machine for urban land cover classification using hyperspectral imagery

NASA Astrophysics Data System (ADS)

Su, Hongjun; Tian, Shufang; Cai, Yue; Sheng, Yehua; Chen, Chen; Najafian, Maryam

2017-12-01

This work presents a new urban land cover classification framework using the firefly algorithm (FA) optimized extreme learning machine (ELM). FA is adopted to optimize the regularization coefficient C and Gaussian kernel σ for kernel ELM. Additionally, effectiveness of spectral features derived from an FA-based band selection algorithm is studied for the proposed classification task. Three sets of hyperspectral databases were recorded using different sensors, namely HYDICE, HyMap, and AVIRIS. Our study shows that the proposed method outperforms traditional classification algorithms such as SVM and reduces computational cost significantly.

Optimal groundwater remediation design of pump and treat systems via a simulation-optimization approach and firefly algorithm

NASA Astrophysics Data System (ADS)

Javad Kazemzadeh-Parsi, Mohammad; Daneshmand, Farhang; Ahmadfard, Mohammad Amin; Adamowski, Jan; Martel, Richard

2015-01-01

In the present study, an optimization approach based on the firefly algorithm (FA) is combined with a finite element simulation method (FEM) to determine the optimum design of pump and treat remediation systems. Three multi-objective functions in which pumping rate and clean-up time are design variables are considered and the proposed FA-FEM model is used to minimize operating costs, total pumping volumes and total pumping rates in three scenarios while meeting water quality requirements. The groundwater lift and contaminant concentration are also minimized through the optimization process. The obtained results show the applicability of the FA in conjunction with the FEM for the optimal design of groundwater remediation systems. The performance of the FA is also compared with the genetic algorithm (GA) and the FA is found to have a better convergence rate than the GA.

A Novel RSSI Prediction Using Imperialist Competition Algorithm (ICA), Radial Basis Function (RBF) and Firefly Algorithm (FFA) in Wireless Networks

PubMed Central

Goudarzi, Shidrokh; Haslina Hassan, Wan; Abdalla Hashim, Aisha-Hassan; Soleymani, Seyed Ahmad; Anisi, Mohammad Hossein; Zakaria, Omar M.

2016-01-01

This study aims to design a vertical handover prediction method to minimize unnecessary handovers for a mobile node (MN) during the vertical handover process. This relies on a novel method for the prediction of a received signal strength indicator (RSSI) referred to as IRBF-FFA, which is designed by utilizing the imperialist competition algorithm (ICA) to train the radial basis function (RBF), and by hybridizing with the firefly algorithm (FFA) to predict the optimal solution. The prediction accuracy of the proposed IRBF–FFA model was validated by comparing it to support vector machines (SVMs) and multilayer perceptron (MLP) models. In order to assess the model’s performance, we measured the coefficient of determination (R2), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results indicate that the IRBF–FFA model provides more precise predictions compared to different ANNs, namely, support vector machines (SVMs) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real-time RSSI measurements. The results also suggest that the IRBF–FFA model can be applied as an efficient technique for the accurate prediction of vertical handover. PMID:27438600

A Novel RSSI Prediction Using Imperialist Competition Algorithm (ICA), Radial Basis Function (RBF) and Firefly Algorithm (FFA) in Wireless Networks.

PubMed

Goudarzi, Shidrokh; Haslina Hassan, Wan; Abdalla Hashim, Aisha-Hassan; Soleymani, Seyed Ahmad; Anisi, Mohammad Hossein; Zakaria, Omar M

2016-01-01

This study aims to design a vertical handover prediction method to minimize unnecessary handovers for a mobile node (MN) during the vertical handover process. This relies on a novel method for the prediction of a received signal strength indicator (RSSI) referred to as IRBF-FFA, which is designed by utilizing the imperialist competition algorithm (ICA) to train the radial basis function (RBF), and by hybridizing with the firefly algorithm (FFA) to predict the optimal solution. The prediction accuracy of the proposed IRBF-FFA model was validated by comparing it to support vector machines (SVMs) and multilayer perceptron (MLP) models. In order to assess the model's performance, we measured the coefficient of determination (R2), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results indicate that the IRBF-FFA model provides more precise predictions compared to different ANNs, namely, support vector machines (SVMs) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real-time RSSI measurements. The results also suggest that the IRBF-FFA model can be applied as an efficient technique for the accurate prediction of vertical handover.

A firefly algorithm for optimum design of new-generation beams

NASA Astrophysics Data System (ADS)

Erdal, F.

2017-06-01

This research addresses the minimum weight design of new-generation steel beams with sinusoidal openings using a metaheuristic search technique, namely the firefly method. The proposed algorithm is also used to compare the optimum design results of sinusoidal web-expanded beams with steel castellated and cellular beams. Optimum design problems of all beams are formulated according to the design limitations stipulated by the Steel Construction Institute. The design methods adopted in these publications are consistent with BS 5950 specifications. The formulation of the design problem considering the above-mentioned limitations turns out to be a discrete programming problem. The design algorithms based on the technique select the optimum universal beam sections, dimensional properties of sinusoidal, hexagonal and circular holes, and the total number of openings along the beam as design variables. Furthermore, this selection is also carried out such that the behavioural limitations are satisfied. Numerical examples are presented, where the suggested algorithm is implemented to achieve the minimum weight design of these beams subjected to loading combinations.

Thermal buckling optimisation of composite plates using firefly algorithm

NASA Astrophysics Data System (ADS)

Kamarian, S.; Shakeri, M.; Yas, M. H.

2017-07-01

Composite plates play a very important role in engineering applications, especially in aerospace industry. Thermal buckling of such components is of great importance and must be known to achieve an appropriate design. This paper deals with stacking sequence optimisation of laminated composite plates for maximising the critical buckling temperature using a powerful meta-heuristic algorithm called firefly algorithm (FA) which is based on the flashing behaviour of fireflies. The main objective of present work was to show the ability of FA in optimisation of composite structures. The performance of FA is compared with the results reported in the previous published works using other algorithms which shows the efficiency of FA in stacking sequence optimisation of laminated composite structures.

Electricity Load Forecasting Using Support Vector Regression with Memetic Algorithms

PubMed Central

Hu, Zhongyi; Xiong, Tao

2013-01-01

Electricity load forecasting is an important issue that is widely explored and examined in power systems operation literature and commercial transactions in electricity markets literature as well. Among the existing forecasting models, support vector regression (SVR) has gained much attention. Considering the performance of SVR highly depends on its parameters; this study proposed a firefly algorithm (FA) based memetic algorithm (FA-MA) to appropriately determine the parameters of SVR forecasting model. In the proposed FA-MA algorithm, the FA algorithm is applied to explore the solution space, and the pattern search is used to conduct individual learning and thus enhance the exploitation of FA. Experimental results confirm that the proposed FA-MA based SVR model can not only yield more accurate forecasting results than the other four evolutionary algorithms based SVR models and three well-known forecasting models but also outperform the hybrid algorithms in the related existing literature. PMID:24459425

Electricity load forecasting using support vector regression with memetic algorithms.

PubMed

Hu, Zhongyi; Bao, Yukun; Xiong, Tao

2013-01-01

Electricity load forecasting is an important issue that is widely explored and examined in power systems operation literature and commercial transactions in electricity markets literature as well. Among the existing forecasting models, support vector regression (SVR) has gained much attention. Considering the performance of SVR highly depends on its parameters; this study proposed a firefly algorithm (FA) based memetic algorithm (FA-MA) to appropriately determine the parameters of SVR forecasting model. In the proposed FA-MA algorithm, the FA algorithm is applied to explore the solution space, and the pattern search is used to conduct individual learning and thus enhance the exploitation of FA. Experimental results confirm that the proposed FA-MA based SVR model can not only yield more accurate forecasting results than the other four evolutionary algorithms based SVR models and three well-known forecasting models but also outperform the hybrid algorithms in the related existing literature.

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.

Solution to automatic generation control problem using firefly algorithm optimized I(λ)D(µ) controller.

PubMed

Debbarma, Sanjoy; Saikia, Lalit Chandra; Sinha, Nidul

2014-03-01

Present work focused on automatic generation control (AGC) of a three unequal area thermal systems considering reheat turbines and appropriate generation rate constraints (GRC). A fractional order (FO) controller named as I(λ)D(µ) controller based on crone approximation is proposed for the first time as an appropriate technique to solve the multi-area AGC problem in power systems. A recently developed metaheuristic algorithm known as firefly algorithm (FA) is used for the simultaneous optimization of the gains and other parameters such as order of integrator (λ) and differentiator (μ) of I(λ)D(µ) controller and governor speed regulation parameters (R). The dynamic responses corresponding to optimized I(λ)D(µ) controller gains, λ, μ, and R are compared with that of classical integer order (IO) controllers such as I, PI and PID controllers. Simulation results show that the proposed I(λ)D(µ) controller provides more improved dynamic responses and outperforms the IO based classical controllers. Further, sensitivity analysis confirms the robustness of the so optimized I(λ)D(µ) controller to wide changes in system loading conditions and size and position of SLP. Proposed controller is also found to have performed well as compared to IO based controllers when SLP takes place simultaneously in any two areas or all the areas. Robustness of the proposed I(λ)D(µ) controller is also tested against system parameter variations. © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Solving Fractional Programming Problems based on Swarm Intelligence

NASA Astrophysics Data System (ADS)

Raouf, Osama Abdel; Hezam, Ibrahim M.

2014-04-01

This paper presents a new approach to solve Fractional Programming Problems (FPPs) based on two different Swarm Intelligence (SI) algorithms. The two algorithms are: Particle Swarm Optimization, and Firefly Algorithm. The two algorithms are tested using several FPP benchmark examples and two selected industrial applications. The test aims to prove the capability of the SI algorithms to solve any type of FPPs. The solution results employing the SI algorithms are compared with a number of exact and metaheuristic solution methods used for handling FPPs. Swarm Intelligence can be denoted as an effective technique for solving linear or nonlinear, non-differentiable fractional objective functions. Problems with an optimal solution at a finite point and an unbounded constraint set, can be solved using the proposed approach. Numerical examples are given to show the feasibility, effectiveness, and robustness of the proposed algorithm. The results obtained using the two SI algorithms revealed the superiority of the proposed technique among others in computational time. A better accuracy was remarkably observed in the solution results of the industrial application problems.

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.

A hyperbolastic type-I diffusion process: Parameter estimation by means of the firefly algorithm.

PubMed

Barrera, Antonio; Román-Román, Patricia; Torres-Ruiz, Francisco

2018-01-01

A stochastic diffusion process, whose mean function is a hyperbolastic curve of type I, is presented. The main characteristics of the process are studied and the problem of maximum likelihood estimation for the parameters of the process is considered. To this end, the firefly metaheuristic optimization algorithm is applied after bounding the parametric space by a stagewise procedure. Some examples based on simulated sample paths and real data illustrate this development. Copyright © 2017 Elsevier B.V. All rights reserved.

Sensitive Dual Color in vivo Bioluminescence Imaging Using a New Red Codon Optimized Firefly Luciferase and a Green Click Beetle Luciferase

DTIC Science & Technology

2011-04-01

Sensitive Dual Color In Vivo Bioluminescence Imaging Using a New Red Codon Optimized Firefly Luciferase and a Green Click Beetle Luciferase Laura...20 nm). Spectral unmixing algorithms were applied to the images where good separation of signals was observed. Furthermore, HEK293 cells that...spectral emissions using a suitable spectral unmixing algorithm . This new D-luciferin-dependent reporter gene couplet opens up the possibility in the future

Firefly Algorithm for Structural Search.

PubMed

Avendaño-Franco, Guillermo; Romero, Aldo H

2016-07-12

The problem of computational structure prediction of materials is approached using the firefly (FF) algorithm. Starting from the chemical composition and optionally using prior knowledge of similar structures, the FF method is able to predict not only known stable structures but also a variety of novel competitive metastable structures. This article focuses on the strengths and limitations of the algorithm as a multimodal global searcher. The algorithm has been implemented in software package PyChemia ( https://github.com/MaterialsDiscovery/PyChemia ), an open source python library for materials analysis. We present applications of the method to van der Waals clusters and crystal structures. The FF method is shown to be competitive when compared to other population-based global searchers.

Segmentation and classification of brain images using firefly and hybrid kernel-based support vector machine

NASA Astrophysics Data System (ADS)

Selva Bhuvaneswari, K.; Geetha, P.

2017-05-01

Magnetic resonance imaging segmentation refers to a process of assigning labels to set of pixels or multiple regions. It plays a major role in the field of biomedical applications as it is widely used by the radiologists to segment the medical images input into meaningful regions. In recent years, various brain tumour detection techniques are presented in the literature. The entire segmentation process of our proposed work comprises three phases: threshold generation with dynamic modified region growing phase, texture feature generation phase and region merging phase. by dynamically changing two thresholds in the modified region growing approach, the first phase of the given input image can be performed as dynamic modified region growing process, in which the optimisation algorithm, firefly algorithm help to optimise the two thresholds in modified region growing. After obtaining the region growth segmented image using modified region growing, the edges can be detected with edge detection algorithm. In the second phase, the texture feature can be extracted using entropy-based operation from the input image. In region merging phase, the results obtained from the texture feature-generation phase are combined with the results of dynamic modified region growing phase and similar regions are merged using a distance comparison between regions. After identifying the abnormal tissues, the classification can be done by hybrid kernel-based SVM (Support Vector Machine). The performance analysis of the proposed method will be carried by K-cross fold validation method. The proposed method will be implemented in MATLAB with various images.

Identification of DNA-binding proteins using multi-features fusion and binary firefly optimization algorithm.

PubMed

Zhang, Jian; Gao, Bo; Chai, Haiting; Ma, Zhiqiang; Yang, Guifu

2016-08-26

DNA-binding proteins (DBPs) play fundamental roles in many biological processes. Therefore, the developing of effective computational tools for identifying DBPs is becoming highly desirable. In this study, we proposed an accurate method for the prediction of DBPs. Firstly, we focused on the challenge of improving DBP prediction accuracy with information solely from the sequence. Secondly, we used multiple informative features to encode the protein. These features included evolutionary conservation profile, secondary structure motifs, and physicochemical properties. Thirdly, we introduced a novel improved Binary Firefly Algorithm (BFA) to remove redundant or noisy features as well as select optimal parameters for the classifier. The experimental results of our predictor on two benchmark datasets outperformed many state-of-the-art predictors, which revealed the effectiveness of our method. The promising prediction performance on a new-compiled independent testing dataset from PDB and a large-scale dataset from UniProt proved the good generalization ability of our method. In addition, the BFA forged in this research would be of great potential in practical applications in optimization fields, especially in feature selection problems. A highly accurate method was proposed for the identification of DBPs. A user-friendly web-server named iDbP (identification of DNA-binding Proteins) was constructed and provided for academic use.

Motion control of nonlinear gantry crane system via priority-based fitness scheme in firefly algorithm

NASA Astrophysics Data System (ADS)

Jaafar, Hazriq Izzuan; Latif, Norfaneysa Abd; Kassim, Anuar Mohamed; Abidin, Amar Faiz Zainal; Hussien, Sharifah Yuslinda Syed; Aras, Mohd Shahrieel Mohd

2015-05-01

Advanced manufacturing technology made Gantry Crane System (GCS) is one of the suitable heavy machinery transporters and frequently employed in handling with huge materials. The interconnection of trolley movement and payload oscillation has a technical impact which needs to be considered. Once the trolley moves to the desired position with high speed, this will induce undesirable's payload oscillation. This frequent unavoidable load swing causes an efficiency drop, load damages and even accidents. In this paper, a new control strategy of Firefly Algorithm (FA) will be developed to obtain five optimal controller parameters (PID and PD) via Priority-based Fitness Scheme (PFS). Combinations of these five parameters are utilized for controlling trolley movement and minimizing the angle of payload oscillation. This PFS is prioritized based on steady-state error (SSE), overshoot (OS) and settling time (Ts) according to the needs and circumstances. Lagrange equation will be chosen for modeling and simulation will be conducted by using related software. Simulation results show that the proposed control strategy is efficient to control the trolley movement to the desired position and minimize the angle of payload oscillation.

Biosynthesis of firefly luciferin in adult lantern: decarboxylation of L-cysteine is a key step for benzothiazole ring formation in firefly luciferin synthesis.

PubMed

Oba, Yuichi; Yoshida, Naoki; Kanie, Shusei; Ojika, Makoto; Inouye, Satoshi

2013-01-01

Bioluminescence in fireflies and click beetles is produced by a luciferase-luciferin reaction. The luminescence property and protein structure of firefly luciferase have been investigated, and its cDNA has been used for various assay systems. The chemical structure of firefly luciferin was identified as the D-form in 1963 and studies on the biosynthesis of firefly luciferin began early in the 1970's. Incorporation experiments using (14)C-labeled compounds were performed, and cysteine and benzoquinone/hydroquinone were proposed to be biosynthetic component for firefly luciferin. However, there have been no clear conclusions regarding the biosynthetic components of firefly luciferin over 30 years. Incorporation studies were performed by injecting stable isotope-labeled compounds, including L-[U-(13)C3]-cysteine, L-[1-(13)C]-cysteine, L-[3-(13)C]-cysteine, 1,4-[D6]-hydroquinone, and p-[2,3,5,6-D]-benzoquinone, into the adult lantern of the living Japanese firefly Luciola lateralis. After extracting firefly luciferin from the lantern, the incorporation of stable isotope-labeled compounds into firefly luciferin was identified by LC/ESI-TOF-MS. The positions of the stable isotope atoms in firefly luciferin were determined by the mass fragmentation of firefly luciferin. We demonstrated for the first time that D- and L-firefly luciferins are biosynthesized in the lantern of the adult firefly from two L-cysteine molecules with p-benzoquinone/1,4-hydroquinone, accompanied by the decarboxylation of L-cysteine.

Structure and weights optimisation of a modified Elman network emotion classifier using hybrid computational intelligence algorithms: a comparative study

NASA Astrophysics Data System (ADS)

Sheikhan, Mansour; Abbasnezhad Arabi, Mahdi; Gharavian, Davood

2015-10-01

Artificial neural networks are efficient models in pattern recognition applications, but their performance is dependent on employing suitable structure and connection weights. This study used a hybrid method for obtaining the optimal weight set and architecture of a recurrent neural emotion classifier based on gravitational search algorithm (GSA) and its binary version (BGSA), respectively. By considering the features of speech signal that were related to prosody, voice quality, and spectrum, a rich feature set was constructed. To select more efficient features, a fast feature selection method was employed. The performance of the proposed hybrid GSA-BGSA method was compared with similar hybrid methods based on particle swarm optimisation (PSO) algorithm and its binary version, PSO and discrete firefly algorithm, and hybrid of error back-propagation and genetic algorithm that were used for optimisation. Experimental tests on Berlin emotional database demonstrated the superior performance of the proposed method using a lighter network structure.

Escalated convergent artificial bee colony

NASA Astrophysics Data System (ADS)

Jadon, Shimpi Singh; Bansal, Jagdish Chand; Tiwari, Ritu

2016-03-01

Artificial bee colony (ABC) optimisation algorithm is a recent, fast and easy-to-implement population-based meta heuristic for optimisation. ABC has been proved a rival algorithm with some popular swarm intelligence-based algorithms such as particle swarm optimisation, firefly algorithm and ant colony optimisation. The solution search equation of ABC is influenced by a random quantity which helps its search process in exploration at the cost of exploitation. In order to find a fast convergent behaviour of ABC while exploitation capability is maintained, in this paper basic ABC is modified in two ways. First, to improve exploitation capability, two local search strategies, namely classical unidimensional local search and levy flight random walk-based local search are incorporated with ABC. Furthermore, a new solution search strategy, namely stochastic diffusion scout search is proposed and incorporated into the scout bee phase to provide more chance to abandon solution to improve itself. Efficiency of the proposed algorithm is tested on 20 benchmark test functions of different complexities and characteristics. Results are very promising and they prove it to be a competitive algorithm in the field of swarm intelligence-based algorithms.

An improved swarm optimization for parameter estimation and biological model selection.

PubMed

Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail

2013-01-01

One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This study is hoped to provide a new insight in developing more accurate and reliable biological models based on limited and low quality experimental data.

ECG based Myocardial Infarction detection using Hybrid Firefly Algorithm.

PubMed

Kora, Padmavathi

2017-12-01

Myocardial Infarction (MI) is one of the most frequent diseases, and can also cause demise, disability and monetary loss in patients who suffer from cardiovascular disorder. Diagnostic methods of this ailment by physicians are typically invasive, even though they do not fulfill the required detection accuracy. Recent feature extraction methods, for example, Auto Regressive (AR) modelling; Magnitude Squared Coherence (MSC); Wavelet Coherence (WTC) using Physionet database, yielded a collection of huge feature set. A large number of these features may be inconsequential containing some excess and non-discriminative components that present excess burden in computation and loss of execution performance. So Hybrid Firefly and Particle Swarm Optimization (FFPSO) is directly used to optimise the raw ECG signal instead of extracting features using the above feature extraction techniques. Provided results in this paper show that, for the detection of MI class, the FFPSO algorithm with ANN gives 99.3% accuracy, sensitivity of 99.97%, and specificity of 98.7% on MIT-BIH database by including NSR database also. The proposed approach has shown that methods that are based on the feature optimization of the ECG signals are the perfect to diagnosis the condition of the heart patients. Copyright © 2017 Elsevier B.V. All rights reserved.

A support vector regression-firefly algorithm-based model for limiting velocity prediction in sewer pipes.

PubMed

Ebtehaj, Isa; Bonakdari, Hossein

2016-01-01

Sediment transport without deposition is an essential consideration in the optimum design of sewer pipes. In this study, a novel method based on a combination of support vector regression (SVR) and the firefly algorithm (FFA) is proposed to predict the minimum velocity required to avoid sediment settling in pipe channels, which is expressed as the densimetric Froude number (Fr). The efficiency of support vector machine (SVM) models depends on the suitable selection of SVM parameters. In this particular study, FFA is used by determining these SVM parameters. The actual effective parameters on Fr calculation are generally identified by employing dimensional analysis. The different dimensionless variables along with the models are introduced. The best performance is attributed to the model that employs the sediment volumetric concentration (C(V)), ratio of relative median diameter of particles to hydraulic radius (d/R), dimensionless particle number (D(gr)) and overall sediment friction factor (λ(s)) parameters to estimate Fr. The performance of the SVR-FFA model is compared with genetic programming, artificial neural network and existing regression-based equations. The results indicate the superior performance of SVR-FFA (mean absolute percentage error = 2.123%; root mean square error =0.116) compared with other methods.

Numerical model updating technique for structures using firefly algorithm

NASA Astrophysics Data System (ADS)

Sai Kubair, K.; Mohan, S. C.

2018-03-01

Numerical model updating is a technique used for updating the existing experimental models for any structures related to civil, mechanical, automobiles, marine, aerospace engineering, etc. The basic concept behind this technique is updating the numerical models to closely match with experimental data obtained from real or prototype test structures. The present work involves the development of numerical model using MATLAB as a computational tool and with mathematical equations that define the experimental model. Firefly algorithm is used as an optimization tool in this study. In this updating process a response parameter of the structure has to be chosen, which helps to correlate the numerical model developed with the experimental results obtained. The variables for the updating can be either material or geometrical properties of the model or both. In this study, to verify the proposed technique, a cantilever beam is analyzed for its tip deflection and a space frame has been analyzed for its natural frequencies. Both the models are updated with their respective response values obtained from experimental results. The numerical results after updating show that there is a close relationship that can be brought between the experimental and the numerical models.

Prediction of protein-protein interaction network using a multi-objective optimization approach.

PubMed

Chowdhury, Archana; Rakshit, Pratyusha; Konar, Amit

2016-06-01

Protein-Protein Interactions (PPIs) are very important as they coordinate almost all cellular processes. This paper attempts to formulate PPI prediction problem in a multi-objective optimization framework. The scoring functions for the trial solution deal with simultaneous maximization of functional similarity, strength of the domain interaction profiles, and the number of common neighbors of the proteins predicted to be interacting. The above optimization problem is solved using the proposed Firefly Algorithm with Nondominated Sorting. Experiments undertaken reveal that the proposed PPI prediction technique outperforms existing methods, including gene ontology-based Relative Specific Similarity, multi-domain-based Domain Cohesion Coupling method, domain-based Random Decision Forest method, Bagging with REP Tree, and evolutionary/swarm algorithm-based approaches, with respect to sensitivity, specificity, and F1 score.

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.

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.

Design optimization of steel frames using an enhanced firefly algorithm

NASA Astrophysics Data System (ADS)

Carbas, Serdar

2016-12-01

Mathematical modelling of real-world-sized steel frames under the Load and Resistance Factor Design-American Institute of Steel Construction (LRFD-AISC) steel design code provisions, where the steel profiles for the members are selected from a table of steel sections, turns out to be a discrete nonlinear programming problem. Finding the optimum design of such design optimization problems using classical optimization techniques is difficult. Metaheuristic algorithms provide an alternative way of solving such problems. The firefly algorithm (FFA) belongs to the swarm intelligence group of metaheuristics. The standard FFA has the drawback of being caught up in local optima in large-sized steel frame design problems. This study attempts to enhance the performance of the FFA by suggesting two new expressions for the attractiveness and randomness parameters of the algorithm. Two real-world-sized design examples are designed by the enhanced FFA and its performance is compared with standard FFA as well as with particle swarm and cuckoo search algorithms.

Performance Enhancement of Radial Distributed System with Distributed Generators by Reconfiguration Using Binary Firefly Algorithm

NASA Astrophysics Data System (ADS)

Rajalakshmi, N.; Padma Subramanian, D.; Thamizhavel, K.

2015-03-01

The extent of real power loss and voltage deviation associated with overloaded feeders in radial distribution system can be reduced by reconfiguration. Reconfiguration is normally achieved by changing the open/closed state of tie/sectionalizing switches. Finding optimal switch combination is a complicated problem as there are many switching combinations possible in a distribution system. Hence optimization techniques are finding greater importance in reducing the complexity of reconfiguration problem. This paper presents the application of firefly algorithm (FA) for optimal reconfiguration of radial distribution system with distributed generators (DG). The algorithm is tested on IEEE 33 bus system installed with DGs and the results are compared with binary genetic algorithm. It is found that binary FA is more effective than binary genetic algorithm in achieving real power loss reduction and improving voltage profile and hence enhancing the performance of radial distribution system. Results are found to be optimum when DGs are added to the test system, which proved the impact of DGs on distribution system.

From nonlinear optimization to convex optimization through firefly algorithm and indirect approach with applications to CAD/CAM.

PubMed

Gálvez, Akemi; Iglesias, Andrés

2013-01-01

Fitting spline curves to data points is a very important issue in many applied fields. It is also challenging, because these curves typically depend on many continuous variables in a highly interrelated nonlinear way. In general, it is not possible to compute these parameters analytically, so the problem is formulated as a continuous nonlinear optimization problem, for which traditional optimization techniques usually fail. This paper presents a new bioinspired method to tackle this issue. In this method, optimization is performed through a combination of two techniques. Firstly, we apply the indirect approach to the knots, in which they are not initially the subject of optimization but precomputed with a coarse approximation scheme. Secondly, a powerful bioinspired metaheuristic technique, the firefly algorithm, is applied to optimization of data parameterization; then, the knot vector is refined by using De Boor's method, thus yielding a better approximation to the optimal knot vector. This scheme converts the original nonlinear continuous optimization problem into a convex optimization problem, solved by singular value decomposition. Our method is applied to some illustrative real-world examples from the CAD/CAM field. Our experimental results show that the proposed scheme can solve the original continuous nonlinear optimization problem very efficiently.

From Nonlinear Optimization to Convex Optimization through Firefly Algorithm and Indirect Approach with Applications to CAD/CAM

PubMed Central

Gálvez, Akemi; Iglesias, Andrés

2013-01-01

Fitting spline curves to data points is a very important issue in many applied fields. It is also challenging, because these curves typically depend on many continuous variables in a highly interrelated nonlinear way. In general, it is not possible to compute these parameters analytically, so the problem is formulated as a continuous nonlinear optimization problem, for which traditional optimization techniques usually fail. This paper presents a new bioinspired method to tackle this issue. In this method, optimization is performed through a combination of two techniques. Firstly, we apply the indirect approach to the knots, in which they are not initially the subject of optimization but precomputed with a coarse approximation scheme. Secondly, a powerful bioinspired metaheuristic technique, the firefly algorithm, is applied to optimization of data parameterization; then, the knot vector is refined by using De Boor's method, thus yielding a better approximation to the optimal knot vector. This scheme converts the original nonlinear continuous optimization problem into a convex optimization problem, solved by singular value decomposition. Our method is applied to some illustrative real-world examples from the CAD/CAM field. Our experimental results show that the proposed scheme can solve the original continuous nonlinear optimization problem very efficiently. PMID:24376380

Firefly as a novel swarm intelligence variable selection method in spectroscopy.

PubMed

Goodarzi, Mohammad; dos Santos Coelho, Leandro

2014-12-10

A critical step in multivariate calibration is wavelength selection, which is used to build models with better prediction performance when applied to spectral data. Up to now, many feature selection techniques have been developed. Among all different types of feature selection techniques, those based on swarm intelligence optimization methodologies are more interesting since they are usually simulated based on animal and insect life behavior to, e.g., find the shortest path between a food source and their nests. This decision is made by a crowd, leading to a more robust model with less falling in local minima during the optimization cycle. This paper represents a novel feature selection approach to the selection of spectroscopic data, leading to more robust calibration models. The performance of the firefly algorithm, a swarm intelligence paradigm, was evaluated and compared with genetic algorithm and particle swarm optimization. All three techniques were coupled with partial least squares (PLS) and applied to three spectroscopic data sets. They demonstrate improved prediction results in comparison to when only a PLS model was built using all wavelengths. Results show that firefly algorithm as a novel swarm paradigm leads to a lower number of selected wavelengths while the prediction performance of built PLS stays the same. Copyright © 2014. Published by Elsevier B.V.

A Grey Wolf Optimizer for Modular Granular Neural Networks for Human Recognition

PubMed Central

Sánchez, Daniela; Melin, Patricia

2017-01-01

A grey wolf optimizer for modular neural network (MNN) with a granular approach is proposed. The proposed method performs optimal granulation of data and design of modular neural networks architectures to perform human recognition, and to prove its effectiveness benchmark databases of ear, iris, and face biometric measures are used to perform tests and comparisons against other works. The design of a modular granular neural network (MGNN) consists in finding optimal parameters of its architecture; these parameters are the number of subgranules, percentage of data for the training phase, learning algorithm, goal error, number of hidden layers, and their number of neurons. Nowadays, there is a great variety of approaches and new techniques within the evolutionary computing area, and these approaches and techniques have emerged to help find optimal solutions to problems or models and bioinspired algorithms are part of this area. In this work a grey wolf optimizer is proposed for the design of modular granular neural networks, and the results are compared against a genetic algorithm and a firefly algorithm in order to know which of these techniques provides better results when applied to human recognition. PMID:28894461

A Grey Wolf Optimizer for Modular Granular Neural Networks for Human Recognition.

PubMed

Sánchez, Daniela; Melin, Patricia; Castillo, Oscar

2017-01-01

A grey wolf optimizer for modular neural network (MNN) with a granular approach is proposed. The proposed method performs optimal granulation of data and design of modular neural networks architectures to perform human recognition, and to prove its effectiveness benchmark databases of ear, iris, and face biometric measures are used to perform tests and comparisons against other works. The design of a modular granular neural network (MGNN) consists in finding optimal parameters of its architecture; these parameters are the number of subgranules, percentage of data for the training phase, learning algorithm, goal error, number of hidden layers, and their number of neurons. Nowadays, there is a great variety of approaches and new techniques within the evolutionary computing area, and these approaches and techniques have emerged to help find optimal solutions to problems or models and bioinspired algorithms are part of this area. In this work a grey wolf optimizer is proposed for the design of modular granular neural networks, and the results are compared against a genetic algorithm and a firefly algorithm in order to know which of these techniques provides better results when applied to human recognition.

Genome-Wide Analysis of Translational Control in Tuberous Sclerosis Complex

DTIC Science & Technology

2012-07-01

particular non-AUG codons in the 5’UTR. However, these data was “noisy” and required a machine-learning algorithm to identify TIS codons. We develop...To investigate how nutrient signaling affects the folding of nascent chains, we used firefly luciferase (Luc) as a reporter because of its high...folding as the structural basis for the rapid de novo folding of firefly luciferase. Nat Struct Biol 6(7):697-705. 12. Gupta R, Kasturi P, Bracher A

Firefly Algorithm in detection of TEC seismo-ionospheric anomalies

NASA Astrophysics Data System (ADS)

Akhoondzadeh, Mehdi

2015-07-01

Anomaly detection in time series of different earthquake precursors is an essential introduction to create an early warning system with an allowable uncertainty. Since these time series are more often non linear, complex and massive, therefore the applied predictor method should be able to detect the discord patterns from a large data in a short time. This study acknowledges Firefly Algorithm (FA) as a simple and robust predictor to detect the TEC (Total Electron Content) seismo-ionospheric anomalies around the time of the some powerful earthquakes including Chile (27 February 2010), Varzeghan (11 August 2012) and Saravan (16 April 2013). Outstanding anomalies were observed 7 and 5 days before the Chile and Varzeghan earthquakes, respectively and also 3 and 8 days prior to the Saravan earthquake.

An Improved Swarm Optimization for Parameter Estimation and Biological Model Selection

PubMed Central

Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail

2013-01-01

One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This study is hoped to provide a new insight in developing more accurate and reliable biological models based on limited and low quality experimental data. PMID:23593445

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.

Analyzing the impact of the Firefly Trail on economic development in northeast Georgia : final report.

DOT National Transportation Integrated Search

2016-10-01

This research report contains the findings of the analysis undertaken to measure the economic impact of the proposed Firefly Trail on the local economy. An input-output model was constructed to study the economic impact of the project on the local ec...

Computational Discovery of Materials Using the Firefly Algorithm

NASA Astrophysics Data System (ADS)

Avendaño-Franco, Guillermo; Romero, Aldo

Our current ability to model physical phenomena accurately, the increase computational power and better algorithms are the driving forces behind the computational discovery and design of novel materials, allowing for virtual characterization before their realization in the laboratory. We present the implementation of a novel firefly algorithm, a population-based algorithm for global optimization for searching the structure/composition space. This novel computation-intensive approach naturally take advantage of concurrency, targeted exploration and still keeping enough diversity. We apply the new method in both periodic and non-periodic structures and we present the implementation challenges and solutions to improve efficiency. The implementation makes use of computational materials databases and network analysis to optimize the search and get insights about the geometric structure of local minima on the energy landscape. The method has been implemented in our software PyChemia, an open-source package for materials discovery. We acknowledge the support of DMREF-NSF 1434897 and the Donors of the American Chemical Society Petroleum Research Fund for partial support of this research under Contract 54075-ND10.

Adaptive infinite impulse response system identification using modified-interior search algorithm with Lèvy flight.

PubMed

Kumar, Manjeet; Rawat, Tarun Kumar; Aggarwal, Apoorva

2017-03-01

In this paper, a new meta-heuristic optimization technique, called interior search algorithm (ISA) with Lèvy flight is proposed and applied to determine the optimal parameters of an unknown infinite impulse response (IIR) system for the system identification problem. ISA is based on aesthetics, which is commonly used in interior design and decoration processes. In ISA, composition phase and mirror phase are applied for addressing the nonlinear and multimodal system identification problems. System identification using modified-ISA (M-ISA) based method involves faster convergence, single parameter tuning and does not require derivative information because it uses a stochastic random search using the concepts of Lèvy flight. A proper tuning of control parameter has been performed in order to achieve a balance between intensification and diversification phases. In order to evaluate the performance of the proposed method, mean square error (MSE), computation time and percentage improvement are considered as the performance measure. To validate the performance of M-ISA based method, simulations has been carried out for three benchmarked IIR systems using same order and reduced order system. Genetic algorithm (GA), particle swarm optimization (PSO), cat swarm optimization (CSO), cuckoo search algorithm (CSA), differential evolution using wavelet mutation (DEWM), firefly algorithm (FFA), craziness based particle swarm optimization (CRPSO), harmony search (HS) algorithm, opposition based harmony search (OHS) algorithm, hybrid particle swarm optimization-gravitational search algorithm (HPSO-GSA) and ISA are also used to model the same examples and simulation results are compared. Obtained results confirm the efficiency of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Towards predictive data-driven simulations of wildfire spread - Part I: Reduced-cost Ensemble Kalman Filter based on a Polynomial Chaos surrogate model for parameter estimation

NASA Astrophysics Data System (ADS)

Rochoux, M. C.; Ricci, S.; Lucor, D.; Cuenot, B.; Trouvé, A.

2014-05-01

This paper is the first part in a series of two articles and presents a data-driven wildfire simulator for forecasting wildfire spread scenarios, at a reduced computational cost that is consistent with operational systems. The prototype simulator features the following components: a level-set-based fire propagation solver FIREFLY that adopts a regional-scale modeling viewpoint, treats wildfires as surface propagating fronts, and uses a description of the local rate of fire spread (ROS) as a function of environmental conditions based on Rothermel's model; a series of airborne-like observations of the fire front positions; and a data assimilation algorithm based on an ensemble Kalman filter (EnKF) for parameter estimation. This stochastic algorithm partly accounts for the non-linearities between the input parameters of the semi-empirical ROS model and the fire front position, and is sequentially applied to provide a spatially-uniform correction to wind and biomass fuel parameters as observations become available. A wildfire spread simulator combined with an ensemble-based data assimilation algorithm is therefore a promising approach to reduce uncertainties in the forecast position of the fire front and to introduce a paradigm-shift in the wildfire emergency response. In order to reduce the computational cost of the EnKF algorithm, a surrogate model based on a polynomial chaos (PC) expansion is used in place of the forward model FIREFLY in the resulting hybrid PC-EnKF algorithm. The performance of EnKF and PC-EnKF is assessed on synthetically-generated simple configurations of fire spread to provide valuable information and insight on the benefits of the PC-EnKF approach as well as on a controlled grassland fire experiment. The results indicate that the proposed PC-EnKF algorithm features similar performance to the standard EnKF algorithm, but at a much reduced computational cost. In particular, the re-analysis and forecast skills of data assimilation strongly relate to the spatial and temporal variability of the errors in the ROS model parameters.

Towards predictive data-driven simulations of wildfire spread - Part I: Reduced-cost Ensemble Kalman Filter based on a Polynomial Chaos surrogate model for parameter estimation

NASA Astrophysics Data System (ADS)

Rochoux, M. C.; Ricci, S.; Lucor, D.; Cuenot, B.; Trouvé, A.

2014-11-01

This paper is the first part in a series of two articles and presents a data-driven wildfire simulator for forecasting wildfire spread scenarios, at a reduced computational cost that is consistent with operational systems. The prototype simulator features the following components: an Eulerian front propagation solver FIREFLY that adopts a regional-scale modeling viewpoint, treats wildfires as surface propagating fronts, and uses a description of the local rate of fire spread (ROS) as a function of environmental conditions based on Rothermel's model; a series of airborne-like observations of the fire front positions; and a data assimilation (DA) algorithm based on an ensemble Kalman filter (EnKF) for parameter estimation. This stochastic algorithm partly accounts for the nonlinearities between the input parameters of the semi-empirical ROS model and the fire front position, and is sequentially applied to provide a spatially uniform correction to wind and biomass fuel parameters as observations become available. A wildfire spread simulator combined with an ensemble-based DA algorithm is therefore a promising approach to reduce uncertainties in the forecast position of the fire front and to introduce a paradigm-shift in the wildfire emergency response. In order to reduce the computational cost of the EnKF algorithm, a surrogate model based on a polynomial chaos (PC) expansion is used in place of the forward model FIREFLY in the resulting hybrid PC-EnKF algorithm. The performance of EnKF and PC-EnKF is assessed on synthetically generated simple configurations of fire spread to provide valuable information and insight on the benefits of the PC-EnKF approach, as well as on a controlled grassland fire experiment. The results indicate that the proposed PC-EnKF algorithm features similar performance to the standard EnKF algorithm, but at a much reduced computational cost. In particular, the re-analysis and forecast skills of DA strongly relate to the spatial and temporal variability of the errors in the ROS model parameters.

Comparison of penalty functions on a penalty approach to mixed-integer optimization

NASA Astrophysics Data System (ADS)

Francisco, Rogério B.; Costa, M. Fernanda P.; Rocha, Ana Maria A. C.; Fernandes, Edite M. G. P.

2016-06-01

In this paper, we present a comparative study involving several penalty functions that can be used in a penalty approach for globally solving bound mixed-integer nonlinear programming (bMIMLP) problems. The penalty approach relies on a continuous reformulation of the bMINLP problem by adding a particular penalty term to the objective function. A penalty function based on the `erf' function is proposed. The continuous nonlinear optimization problems are sequentially solved by the population-based firefly algorithm. Preliminary numerical experiments are carried out in order to analyze the quality of the produced solutions, when compared with other penalty functions available in the literature.

Simulation of optical signaling among nano-bio-sensors: enhancing of bioimaging contrast.

PubMed

SalmanOgli, A; Behzadi, S; Rostami, A

2014-09-01

In this article, the nanoparticle-dye systems is designed and simulated to illustrate the possibility of enhancement in optical imaging contrast. For this, the firefly optimization technique is used as an optical signaling mechanism among agents (nanoparticle-dye) because fireflies attract together due to their flashing light and optical signaling that is produced by a process of bioluminescence (also it has been investigated that other parameters such as neural response and brain function have essential role in attracting fireflies to each other). The first parameter is coincided with our work, because the nanoparticle-dye systems have ability to augment of received light and its amplification cause that the designed complex system act as a brightness particle. This induced behavior of nanoparticles can be considered as an optical communication and signaling. Indeed by functionalization of nanoparticles and then due to higher brightness of the tumor site because of active targeting, the other particles can be guided to reach toward the target point and the signaling among agents is done by optical relation similar to firefly nature. Moreover, the fundamental of this work is the use of surface plasmon resonance and plasmons hybridization, in which photonic signals can be manipulated on the nanoscale and can be used in biomedical applications such as electromagnetic field enhancement. Finally, it can be mentioned that by simultaneously using plasmon hybridization, near-field augmentation, and firefly algorithm, the optical imaging contrast can be impressively improved.

Searching for Extant Life on Mars - The ATP-Firefly LuciferinLuciferase Technique

NASA Astrophysics Data System (ADS)

Obousy, R. K.; Tziolas, A. C.; Kaltsas, K.; Sims, M. R.; Grant, W. D.

We have investigated the use of the ATP-Firefly Luciferin/Luciferase (FFL) enzymic photoluminescent reaction as a possible means of detecting extant life in the Martian environment. Experiments carried out by the authors illustrate the capacity of the method to successfully detect extant forms of life on Mars assuming ATP is an intrinsic part of the biochemistry of such life-forms. A photodiode based apparatus, built to test the assumptions and applicability of the ATP-Firefly Luciferase/Luciferin technique to an exobiologically inclined mission to Mars, revealed the adequate resolution and reproducibility of the methodology plus areas of improvement. Also detailed are extraction, delivery and analysis system concepts, proposed for future Mars missions.

Design and introduction of a disulfide bridge in firefly luciferase: increase of thermostability and decrease of pH sensitivity.

PubMed

Imani, Mehdi; Hosseinkhani, Saman; Ahmadian, Shahin; Nazari, Mahboobeh

2010-08-01

The thermal sensitivity and pH-sensitive spectral properties of firefly luciferase have hampered its application in a variety of fields. It is proposed that the stability of a protein can be increased by introduction of disulfide bridge that decreases the configurational entropy of unfolding. A disulfide bridge is introduced into Photinus pyralis firefly luciferase to make two separate mutant enzymes with a single bridge. Even though the A103C/S121C mutant showed remarkable thermal stability, its specific activity decreased, whereas the A296C/A326C mutant showed tremendous thermal stability, relative pH insensitivity and 7.3-fold increase of specific activity. Moreover, the bioluminescence emission spectrum of A296C/A326C was resistant against higher temperatures (37 degrees C). Far-UV CD analysis showed slight secondary structure changes for both mutants. Thermal denaturation analysis showed that conformational stabilities of A103C/S121C and A296C/A326C are more than native firefly luciferase. It is proposed that since A296 and A326 are situated in the vicinity of the enzyme active site microenvironment in comparison with A103 and S121, the formation of a disulfide bridge in this region has more impact on enzyme kinetic characteristics.

Deciphering the Mechanism of Alternative Cleavage and Polyadenylation in Mantle Cell Lymphoma (MCL)

DTIC Science & Technology

2013-10-01

also has human firefly luciferase cloned within the same reporter system allowing for intra-plasmid normalization of transfection eliminating problems...collaboration with Dr. Wei Li, a Bioinformaticist from Baylor College of Medicine whose lab specializes in developing complex algorithms to analyze genome...wide sequencing data. Dr. Wei Li and his postdoctoral fellow, Dr. Zheng Xia developed a customized algorithm that is able to detect and quantify

Design and analysis of tilt integral derivative controller with filter for load frequency control of multi-area interconnected power systems.

PubMed

Kumar Sahu, Rabindra; Panda, Sidhartha; Biswal, Ashutosh; Chandra Sekhar, G T

2016-03-01

In this paper, a novel Tilt Integral Derivative controller with Filter (TIDF) is proposed for Load Frequency Control (LFC) of multi-area power systems. Initially, a two-area power system is considered and the parameters of the TIDF controller are optimized using Differential Evolution (DE) algorithm employing an Integral of Time multiplied Absolute Error (ITAE) criterion. The superiority of the proposed approach is demonstrated by comparing the results with some recently published heuristic approaches such as Firefly Algorithm (FA), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) optimized PID controllers for the same interconnected power system. Investigations reveal that proposed TIDF controllers provide better dynamic response compared to PID controller in terms of minimum undershoots and settling times of frequency as well as tie-line power deviations following a disturbance. The proposed approach is also extended to two widely used three area test systems considering nonlinearities such as Generation Rate Constraint (GRC) and Governor Dead Band (GDB). To improve the performance of the system, a Thyristor Controlled Series Compensator (TCSC) is also considered and the performance of TIDF controller in presence of TCSC is investigated. It is observed that system performance improves with the inclusion of TCSC. Finally, sensitivity analysis is carried out to test the robustness of the proposed controller by varying the system parameters, operating condition and load pattern. It is observed that the proposed controllers are robust and perform satisfactorily with variations in operating condition, system parameters and load pattern. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Flash signal evolution in Photinus fireflies: character displacement and signal exploitation in a visual communication system.

PubMed

Stanger-Hall, Kathrin F; Lloyd, James E

2015-03-01

Animal communication is an intriguing topic in evolutionary biology. In this comprehensive study of visual signal evolution, we used a phylogenetic approach to study the evolution of the flash communication system of North American fireflies. The North American firefly genus Photinus contains 35 described species with simple ON-OFF visual signals, and information on habitat types, sympatric congeners, and predators. This makes them an ideal study system to test hypotheses on the evolution of male and female visual signal traits. Our analysis of 34 Photinus species suggests two temporal pattern generators: one for flash duration and one for flash intervals. Reproductive character displacement was a main factor for signal divergence in male flash duration among sympatric Photinus species. Male flash pattern intervals (i.e., the duration of the dark periods between signals) were positively correlated with the number of sympatric Photuris fireflies, which include predators of Photinus. Females of different Photinus species differ in their response preferences to male traits. As in other communication systems, firefly male sexual signals seem to be a compromise between optimizing mating success (sexual selection) and minimizing predation risk (natural selection). An integrative model for Photinus signal evolution is proposed. © 2015 The Author(s).

On Processing Hexagonally Sampled Images

DTIC Science & Technology

2011-07-01

Mersereau’s HDFT: Mersereau encountered an “insurmountable difficulty” when attempting to develop a fast algorithm to compute the hexagonal DFT...WNR GND 1-bit output CS1 . ------. (input for analog) j(-- -: I (analog out) ADC ,. __ I I I I l ______ l Power to Firefly C1 ~2 TT

C-5M Super Galaxy Utilization with Joint Precision Airdrop System

DTIC Science & Technology

2012-03-22

System Notes FireFly 900-2,200 Steerable Parafoil Screamer 500-2,200 Steerable Parafoil w/additional chutes to slow touchdown Dragonfly...setting . This initial feasible solution provides the Nonlinear Program algorithm a starting point to continue its calculations. The model continues...provides the NLP with a starting point of 1. This provides the NLP algorithm a point within the feasible region to begin its calculations in an attempt

Identifying People with Soft-Biometrics at Fleet Week

DTIC Science & Technology

2013-03-01

onboard sensors. This included:  Color Camera: Located in the right eye, Octavia stored 640x480 RGB images at ~4 Hz from a Point Grey Firefly camera. A...Face Detection The Fleet Week experiments demonstrated the potential of soft biometrics for recognition, but all of the existing algorithms currently

High-Performance AC Power Source by Applying Robust Stability Control Technology for Precision Material Machining

NASA Astrophysics Data System (ADS)

Chang, En-Chih

2018-02-01

This paper presents a high-performance AC power source by applying robust stability control technology for precision material machining (PMM). The proposed technology associates the benefits of finite-time convergent sliding function (FTCSF) and firefly optimization algorithm (FOA). The FTCSF maintains the robustness of conventional sliding mode, and simultaneously speeds up the convergence speed of the system state. Unfortunately, when a highly nonlinear loading is applied, the chatter will occur. The chatter results in high total harmonic distortion (THD) output voltage of AC power source, and even deteriorates the stability of PMM. The FOA is therefore used to remove the chatter, and the FTCSF still preserves finite system-state convergence time. By combining FTCSF with FOA, the AC power source of PMM can yield good steady-state and transient performance. Experimental results are performed in support of the proposed technology.

Mass spectrometry analysis and transcriptome sequencing reveal glowing squid crystal proteins are in the same superfamily as firefly luciferase

PubMed Central

Gimenez, Gregory; Metcalf, Peter; Paterson, Neil G.; Sharpe, Miriam L.

2016-01-01

The Japanese firefly squid Hotaru-ika (Watasenia scintillans) produces intense blue light from photophores at the tips of two arms. These photophores are densely packed with protein microcrystals that catalyse the bioluminescent reaction using ATP and the substrate coelenterazine disulfate. The squid is the only organism known to produce light using protein crystals. We extracted microcrystals from arm tip photophores and identified the constituent proteins using mass spectrometry and transcriptome libraries prepared from arm tip tissue. The crystals contain three proteins, wsluc1–3, all members of the ANL superfamily of adenylating enzymes. They share 19 to 21% sequence identity with firefly luciferases, which produce light using ATP and the unrelated firefly luciferin substrate. We propose that wsluc1–3 form a complex that crystallises inside the squid photophores, and that in the crystal one or more of the proteins catalyses the production of light using coelenterazine disulfate and ATP. These results suggest that ANL superfamily enzymes have independently evolved in distant species to produce light using unrelated substrates. PMID:27279452

Testing New Drugs for Treatment of Melanoma Patients Applying Connectivity Map Database Analysis with Melanoma Gene Signatures

DTIC Science & Technology

2012-10-01

use of R packages implemented in Bioconductor. Each dataset was normalized from raw data using the Frozen RMA (fRMA) algorithm . We applied the same...because development of the specific algorithms and fine tuning of the analytic strategy to accomplish this task was not immediately straightforward. We...express firefly luciferase using a retrovirus that encodes a fusion of luciferase and neomycin phosphotransferase (LucNeo), will be implanted and followed

Impossibility of asymptotic synchronization for pulse-coupled oscillators with delayed excitatory coupling.

PubMed

Wu, Wei; Chen, Tianping

2009-12-01

Fireflies, as one of the most spectacular examples of synchronization in nature, have been investigated widely. In 1990, Mirollo and Strogatz proposed a pulse-coupled oscillator model to explain the synchronization of South East Asian fireflies (Pteroptyx malaccae). However, transmission delays were not considered in their model. In fact, when transmission delays are introduced, the dynamic behaviors of pulse-coupled networks change a lot. In this paper, pulse-coupled oscillator networks with delayed excitatory coupling are studied. A concept of synchronization, named weak asymptotic synchronization, which is weaker than asymptotic synchronization, is proposed. We prove that for pulse-coupled oscillator networks with delayed excitatory coupling, weak asymptotic synchronization cannot occur.

Light-extraction enhancement for light-emitting diodes: a firefly-inspired structure refined by the genetic algorithm

NASA Astrophysics Data System (ADS)

Bay, Annick; Mayer, Alexandre

2014-09-01

The efficiency of light-emitting diodes (LED) has increased significantly over the past few years, but the overall efficiency is still limited by total internal reflections due to the high dielectric-constant contrast between the incident and emergent media. The bioluminescent organ of fireflies gave incentive for light-extraction enhance-ment studies. A specific factory-roof shaped structure was shown, by means of light-propagation simulations and measurements, to enhance light extraction significantly. In order to achieve a similar effect for light-emitting diodes, the structure needs to be adapted to the specific set-up of LEDs. In this context simulations were carried out to determine the best geometrical parameters. In the present work, the search for a geometry that maximizes the extraction of light has been conducted by using a genetic algorithm. The idealized structure considered previously was generalized to a broader variety of shapes. The genetic algorithm makes it possible to search simultaneously over a wider range of parameters. It is also significantly less time-consuming than the previous approach that was based on a systematic scan on parameters. The results of the genetic algorithm show that (1) the calculations can be performed in a smaller amount of time and (2) the light extraction can be enhanced even more significantly by using optimal parameters determined by the genetic algorithm for the generalized structure. The combination of the genetic algorithm with the Rigorous Coupled Waves Analysis method constitutes a strong simulation tool, which provides us with adapted designs for enhancing light extraction from light-emitting diodes.

Biochemical characteristics and gene expression profiles of two paralogous luciferases from the Japanese firefly Pyrocoelia atripennis (Coleoptera, Lampyridae, Lampyrinae): insight into the evolution of firefly luciferase genes.

PubMed

Bessho-Uehara, Manabu; Konishi, Kaori; Oba, Yuichi

2017-08-09

Two paralogous genes of firefly luciferase, Luc1 and Luc2, have been isolated from the species in two subfamilies, Luciolinae and Photurinae, of the family Lampyridae. The gene expression profiles have previously been examined only in the species of Luciolinae. Here we isolated Luc1 and Luc2 genes from the Japanese firefly Pyrocoelia atripennis. This is the first report of the presence of both Luc1 and Luc2 genes in the species of the subfamily Lampyrinae and of the exon-intron structure of Luc2 in the family Lampyridae. The luminescence of both gene products peaked at 547 nm under neutral buffer conditions, and the spectrum of Luc1, but not Luc2, was red-shifted under acidic conditions, as observed for Luc2 in the Luciolinae species. The semi-quantitative reverse transcription-polymerase chain reaction suggested that Luc1 was expressed in lanterns of all the stages except eggs, while Luc2 was expressed in the non-lantern bodies of eggs, prepupae, pupae, and female adults. These expression profiles are consistent with those in the Luciolinae species. Considering the distant phylogenetic relationship between Lampyrinae and Luciolinae in Lampyridae, we propose that fireflies generally possess two different luciferase genes and the biochemical properties and gene expression profiles for each paralog are conserved among lampyrid species.

Evolution of synchronization and desynchronization in digital organisms.

PubMed

Knoester, David B; McKinley, Philip K

2011-01-01

We present a study in the evolution of temporal behavior, specifically synchronization and desynchronization, through digital evolution and group selection. In digital evolution, a population of self-replicating computer programs exists in a user-defined computational environment and is subject to instruction-level mutations and natural selection. Group selection links the survival of the individual to the survival of its group, thus encouraging cooperation. Previous approaches to engineering synchronization and desynchronization algorithms have taken inspiration from nature: In the well-known firefly model, the only form of communication between agents is in the form of flash messages among neighbors. Here we demonstrate that populations of digital organisms, provided with a similar mechanism and minimal information about their environment, are capable of evolving algorithms for synchronization and desynchronization, and that the evolved behaviors are robust to message loss. We further describe how the evolved behavior for synchronization mimics that of the well-known Ermentrout model for firefly synchronization in biology. In addition to discovering self-organizing behaviors for distributed computing systems, this result indicates that digital evolution may be used to further our understanding of synchronization in biology.

Faster experimental validation of microRNA targets using cold fusion cloning and a dual firefly-Renilla luciferase reporter assay.

PubMed

Alvarez, M Lucrecia

2014-01-01

Different target prediction algorithms have been developed to provide a list of candidate target genes for a given animal microRNAs (miRNAs). However, these computational approaches provide both false-positive and false-negative predictions. Therefore, the target genes of a specific miRNA identified in silico should be experimentally validated. In this chapter, we describe a step-by-step protocol for the experimental validation of a direct miRNA target using a faster Dual Firefly-Renilla Luciferase Reporter Assay. We describe how to construct reporter plasmids using the simple, fast, and highly efficient cold fusion cloning technology, which does not require ligase, phosphatase, or restriction enzymes. In addition, we provide a protocol for co-transfection of reporter plasmids with either miRNA mimics or miRNA inhibitors in human embryonic kidney 293 (HEK293) cells, as well as a description on how to measure Firefly and Renilla luciferase activity using the Dual-Glo Luciferase Assay kit. As an example of the use of this technology, we will validate glucose-6-phosphate dehydrogenase (G6PD) as a direct target of miR-1207-5p.

Transcriptome analysis reveals candidate genes involved in luciferin metabolism in Luciola aquatilis (Coleoptera: Lampyridae)

PubMed Central

Vongsangnak, Wanwipa; Chumnanpuen, Pramote

2016-01-01

Bioluminescence, which living organisms such as fireflies emit light, has been studied extensively for over half a century. This intriguing reaction, having its origins in nature where glowing insects can signal things such as attraction or defense, is now widely used in biotechnology with applications of bioluminescence and chemiluminescence. Luciferase, a key enzyme in this reaction, has been well characterized; however, the enzymes involved in the biosynthetic pathway of its substrate, luciferin, remains unsolved at present. To elucidate the luciferin metabolism, we performed a de novo transcriptome analysis using larvae of the firefly species, Luciola aquatilis. Here, a comparative analysis is performed with the model coleopteran insect Tribolium casteneum to elucidate the metabolic pathways in L. aquatilis. Based on a template luciferin biosynthetic pathway, combined with a range of protein and pathway databases, and various prediction tools for functional annotation, the candidate genes, enzymes, and biochemical reactions involved in luciferin metabolism are proposed for L. aquatilis. The candidate gene expression is validated in the adult L. aquatilis using reverse transcription PCR (RT-PCR). This study provides useful information on the bio-production of luciferin in the firefly and will benefit to future applications of the valuable firefly bioluminescence system. PMID:27761329

Advanced FIREFLY Assessment Generalized Mechanization Requirements Report

DTIC Science & Technology

1979-06-01

Systems; Fire Control Computers ; Weapon Control 20. ABSTRACT (Continue on reverse side If necessary end tdentify by blockc number) -The requirements for...airborne digital computer which can be specialized to per- form successfully in a variety of tactical aircraft with differing avionics sensors, fire...AGG ........................................... 27 13 Time of Flight Computation Using a Modified (China Lake) Numerical Integration Algorithm

Comparison of two optimization algorithms for fuzzy finite element model updating for damage detection in a wind turbine blade

NASA Astrophysics Data System (ADS)

Turnbull, Heather; Omenzetter, Piotr

2018-03-01

vDifficulties associated with current health monitoring and inspection practices combined with harsh, often remote, operational environments of wind turbines highlight the requirement for a non-destructive evaluation system capable of remotely monitoring the current structural state of turbine blades. This research adopted a physics based structural health monitoring methodology through calibration of a finite element model using inverse techniques. A 2.36m blade from a 5kW turbine was used as an experimental specimen, with operational modal analysis techniques utilised to realize the modal properties of the system. Modelling the experimental responses as fuzzy numbers using the sub-level technique, uncertainty in the response parameters was propagated back through the model and into the updating parameters. Initially, experimental responses of the blade were obtained, with a numerical model of the blade created and updated. Deterministic updating was carried out through formulation and minimisation of a deterministic objective function using both firefly algorithm and virus optimisation algorithm. Uncertainty in experimental responses were modelled using triangular membership functions, allowing membership functions of updating parameters (Young's modulus and shear modulus) to be obtained. Firefly algorithm and virus optimisation algorithm were again utilised, however, this time in the solution of fuzzy objective functions. This enabled uncertainty associated with updating parameters to be quantified. Varying damage location and severity was simulated experimentally through addition of small masses to the structure intended to cause a structural alteration. A damaged model was created, modelling four variable magnitude nonstructural masses at predefined points and updated to provide a deterministic damage prediction and information in relation to the parameters uncertainty via fuzzy updating.

Pan evaporation prediction using a hybrid multilayer perceptron-firefly algorithm (MLP-FFA) model: case study in North Iran

NASA Astrophysics Data System (ADS)

Ghorbani, M. A.; Deo, Ravinesh C.; Yaseen, Zaher Mundher; H. Kashani, Mahsa; Mohammadi, Babak

2017-08-01

An accurate computational approach for the prediction of pan evaporation over daily time horizons is a useful decisive tool in sustainable agriculture and hydrological applications, particularly in designing the rural water resource systems, water use allocations, utilization and demand assessments, and the management of irrigation systems. In this study, a hybrid predictive model (Multilayer Perceptron-Firefly Algorithm (MLP-FFA)) based on the FFA optimizer that is embedded within the MLP technique is developed and evaluated for its suitability for the prediction of daily pan evaporation. To develop the hybrid MLP-FFA model, the pan evaporation data measured between 2012 and 2014 for two major meteorological stations (Talesh and Manjil) located at Northern Iran are employed to train and test the predictive model. The ability of the hybrid MLP-FFA model is compared with the traditional MLP and support vector machine (SVM) models. The results are evaluated using five performance criteria metrics: root mean square error (RMSE), mean absolute error (MAE), Nash-Sutcliffe efficiency (NS), and the Willmott's Index (WI). Taylor diagrams are also used to examine the similarity between the observed and predicted pan evaporation data in the test period. Results show that an optimal MLP-FFA model outperforms the MLP and SVM model for both tested stations. For Talesh, a value of WI = 0.926, NS = 0.791, and RMSE = 1.007 mm day-1 is obtained using MLP-FFA model, compared with 0.912, 0.713, and 1.181 mm day-1 (MLP) and 0.916, 0.726, and 1.153 mm day-1 (SVM), whereas for Manjil, a value of WI = 0.976, NS = 0.922, and 1.406 mm day-1 is attained that contrasts 0.972, 0.901, and 1.583 mm day-1 (MLP) and 0.971, 0.893, and 1.646 mm day-1 (SVM). The results demonstrate the importance of the Firefly Algorithm applied to improve the performance of the MLP-FFA model, as verified through its better predictive performance compared to the MLP and SVM model.

Four new species of Luciuranus fireflies from the Brazilian Atlantic Rainforest (Coleoptera: Lampyridae).

PubMed

Silveira, Luiz F L da; Souto, Paula M; Mermudes, J R M

2018-04-20

Luciuranus Silveira, Khattar Mermudes, 2016 is a firefly genus whose species bear an intricate, species-specific lock-and-key mechanism of reproductive isolation. Here we propose four new species, Luciuranus magnoculus sp. nov., L. desideratus sp. nov., L. takiyae sp. nov. and L. carioca sp. nov., and provide illustrations of their diagnostic features and an updated key to species. As previously reported for their congenerics, each of the four new species have stereotypical morphology of both male and female terminalia, and are regarded as prima facie endemics of single massifs of the Serra da Mantiqueira and Serra do Mar, in the Brazilian Atlantic Rainforest.

One-pot non-enzymatic formation of firefly luciferin in a neutral buffer from p-benzoquinone and cysteine

PubMed Central

Kanie, Shusei; Nishikawa, Toshio; Ojika, Makoto; Oba, Yuichi

2016-01-01

Firefly luciferin, the substrate for the bioluminescence reaction of luminous beetles, possesses a benzothiazole ring, which is rare in nature. Here, we demonstrate a novel one-pot reaction to give firefly luciferin in a neutral buffer from p-benzoquinone and cysteine without any synthetic reagents or enzymes. The formation of firefly luciferin was low in yield in various neutral buffers, whereas it was inhibited or completely prevented in acidic or basic buffers, in organic solvents, or under a nitrogen atmosphere. Labelling analysis of the firefly luciferin using stable isotopic cysteines showed that the benzothiazole ring was formed via the decarboxylation and carbon-sulfur bond rearrangement of cysteine. These findings imply that the biosynthesis of firefly luciferin can be developed/evolved from the non-enzymatic production of firefly luciferin using common primary biosynthetic units, p-benzoquinone and cysteine. PMID:27098929

One-pot non-enzymatic formation of firefly luciferin in a neutral buffer from p-benzoquinone and cysteine.

PubMed

Kanie, Shusei; Nishikawa, Toshio; Ojika, Makoto; Oba, Yuichi

2016-04-21

Firefly luciferin, the substrate for the bioluminescence reaction of luminous beetles, possesses a benzothiazole ring, which is rare in nature. Here, we demonstrate a novel one-pot reaction to give firefly luciferin in a neutral buffer from p-benzoquinone and cysteine without any synthetic reagents or enzymes. The formation of firefly luciferin was low in yield in various neutral buffers, whereas it was inhibited or completely prevented in acidic or basic buffers, in organic solvents, or under a nitrogen atmosphere. Labelling analysis of the firefly luciferin using stable isotopic cysteines showed that the benzothiazole ring was formed via the decarboxylation and carbon-sulfur bond rearrangement of cysteine. These findings imply that the biosynthesis of firefly luciferin can be developed/evolved from the non-enzymatic production of firefly luciferin using common primary biosynthetic units, p-benzoquinone and cysteine.

Assessment of environmental factors that affect the fireflies for ecotourism in Unesco Tasik Chini biosphere reserve

NASA Astrophysics Data System (ADS)

Roslan, Norzeana; Sulaiman, Norela

2015-09-01

This study was conducted to study the firefly species found in Tasik Chini, the soil factors that suitable for larval development fireflies flashes, and the sociological aspects of the community's availability to engage in firefly ecotourism. This was achieved through firefly sampling, soil analysis, abiotic data collection and by questionnaire surveys from local community perceptions and knowledge on fireflies and ecotourism. Fireflies sampling were conducted from December 2011 to January 2013 at Kampung Melai and Kampung Cenahan. Three non-synchronize fireflies genus were found, namely Colophotia sp., Pygoluciola sp., and Pyrocoelia sp. A total of 25 questionnaires were given to four groups of respondents consisting orang asli (5 respondents), boat operator (2 respondents), resort workers (5 respondents) and FELDA residents (13 respondents). The questionnaires were analysed using Rasch Winstep Software based on Rasch Measurement Model. Results of the survey indicated that the local community was not ready for ecotourism in their area. Meanwhile, the soil pH was very acidic and the heavy metals concentration was high, which is not good for the development of firefly larvae. In conclusion, Tasik Chini was not having the potential for ecotourism. Despite the fact, improvement of soils with soil remediation methods can be apply for enhancing larvae development and having more awareness campaign of ecotourism to local community.

Using the Firefly optimization method to weight an ensemble of rainfall forecasts from the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS)

NASA Astrophysics Data System (ADS)

dos Santos, A. F.; Freitas, S. R.; de Mattos, J. G. Z.; de Campos Velho, H. F.; Gan, M. A.; da Luz, E. F. P.; Grell, G. A.

2013-09-01

In this paper we consider an optimization problem applying the metaheuristic Firefly algorithm (FY) to weight an ensemble of rainfall forecasts from daily precipitation simulations with the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS) over South America during January 2006. The method is addressed as a parameter estimation problem to weight the ensemble of precipitation forecasts carried out using different options of the convective parameterization scheme. Ensemble simulations were performed using different choices of closures, representing different formulations of dynamic control (the modulation of convection by the environment) in a deep convection scheme. The optimization problem is solved as an inverse problem of parameter estimation. The application and validation of the methodology is carried out using daily precipitation fields, defined over South America and obtained by merging remote sensing estimations with rain gauge observations. The quadratic difference between the model and observed data was used as the objective function to determine the best combination of the ensemble members to reproduce the observations. To reduce the model rainfall biases, the set of weights determined by the algorithm is used to weight members of an ensemble of model simulations in order to compute a new precipitation field that represents the observed precipitation as closely as possible. The validation of the methodology is carried out using classical statistical scores. The algorithm has produced the best combination of the weights, resulting in a new precipitation field closest to the observations.

On the Effectiveness of Nature-Inspired Metaheuristic Algorithms for Performing Phase Equilibrium Thermodynamic Calculations

PubMed Central

Fateen, Seif-Eddeen K.; Bonilla-Petriciolet, Adrian

2014-01-01

The search for reliable and efficient global optimization algorithms for solving phase stability and phase equilibrium problems in applied thermodynamics is an ongoing area of research. In this study, we evaluated and compared the reliability and efficiency of eight selected nature-inspired metaheuristic algorithms for solving difficult phase stability and phase equilibrium problems. These algorithms are the cuckoo search (CS), intelligent firefly (IFA), bat (BA), artificial bee colony (ABC), MAKHA, a hybrid between monkey algorithm and krill herd algorithm, covariance matrix adaptation evolution strategy (CMAES), magnetic charged system search (MCSS), and bare bones particle swarm optimization (BBPSO). The results clearly showed that CS is the most reliable of all methods as it successfully solved all thermodynamic problems tested in this study. CS proved to be a promising nature-inspired optimization method to perform applied thermodynamic calculations for process design. PMID:24967430

On the effectiveness of nature-inspired metaheuristic algorithms for performing phase equilibrium thermodynamic calculations.

PubMed

Fateen, Seif-Eddeen K; Bonilla-Petriciolet, Adrian

2014-01-01

The search for reliable and efficient global optimization algorithms for solving phase stability and phase equilibrium problems in applied thermodynamics is an ongoing area of research. In this study, we evaluated and compared the reliability and efficiency of eight selected nature-inspired metaheuristic algorithms for solving difficult phase stability and phase equilibrium problems. These algorithms are the cuckoo search (CS), intelligent firefly (IFA), bat (BA), artificial bee colony (ABC), MAKHA, a hybrid between monkey algorithm and krill herd algorithm, covariance matrix adaptation evolution strategy (CMAES), magnetic charged system search (MCSS), and bare bones particle swarm optimization (BBPSO). The results clearly showed that CS is the most reliable of all methods as it successfully solved all thermodynamic problems tested in this study. CS proved to be a promising nature-inspired optimization method to perform applied thermodynamic calculations for process design.

Lowering effect of firefly squid powder on triacylglycerol content and glucose-6-phosphate dehydrogenase activity in rat liver.

PubMed

Takeuchi, Hiroyuki; Morita, Ritsuko; Shirai, Yoko; Nakagawa, Yoshihisa; Terashima, Teruya; Ushikubo, Shun; Matsuo, Tatsuhiro

2014-01-01

Effects of dietary firefly squid on serum and liver lipid levels were investigated. Male Wistar rats were fed a diet containing 5% freeze-dried firefly squid or Japanese flying squid for 2 weeks. There was no significant difference in the liver triacylglycerol level between the control and Japanese flying squid groups, but the rats fed the firefly squid diet had a significantly lower liver triacylglycerol content than those fed the control diet. No significant difference was observed in serum triacylglycerol levels between the control and firefly squid groups. The rats fed the firefly squid had a significantly lower activity of liver glucose-6-phosphate dehydrogenase compared to the rats fed the control diet. There was no significant difference in liver fatty acid synthetase activity among the three groups. Hepatic gene expression and lipogenic enzyme activity were investigated; a DNA microarray showed that the significantly enriched gene ontology category of down-regulated genes in the firefly squid group was "lipid metabolic process". The firefly squid group had lower mRNA level of glucose-6-phosphate dehydrogenase compared to the controls. These results suggest that an intake of firefly squid decreases hepatic triacylglycerol in rats, and the reduction of mRNA level and enzyme activity of glucose-6-phosphate dehydrogenase might be related to the mechanisms.

Study of firefly luciferin oxidation and isomerism as possible inhibition pathways for firefly bioluminescence

NASA Astrophysics Data System (ADS)

Pinto da Silva, Luís; Esteves da Silva, Joaquim C. G.

2014-01-01

Firefly bioluminescence presents a light emitting profile with a form of a flash, due to the firefly luciferase-catalyzed formation of inhibitory products. These impair the binding of the substrate luciferin to the active site of the enzyme. However, this luciferase catalyzed pathways may not be the only ones responsible for the flash profile. The oxidation and isomerisation of the substrate luciferin lead to the formation of compounds that are also known inhibitors of firefly bioluminescence. So, the objective of this Letter was to analyze if these reactions could be capable of interfering with the bioluminescence reaction.

The NSF Firefly Cubesat: Progress and status

NASA Astrophysics Data System (ADS)

Rowland, D. E.; Weatherwax, A. T.; Klenzing, J. H.; Hill, J.

2009-12-01

Firefly is a science investigation into the linkage between lightning and Terrestrial Gamma ray Flashes (TGFs). Firefly combines a gamma ray / electron scintillation detector, VLF radio receiver, and optical photometers to perform the first simultaneous measurements of lightning and TGFs from a single platform. Firefly will push the boundaries of TGF detection and build on the successes of past missions such as RHESSI, CGRO, AGILE, and Fermi by pursuing focused TGF science. In particular, Firefly will address the following science questions: a) What types of lightning do and do not produce TGFs? b) What is the occurrence rate of weak TGFs? c) How strong are TGFs, and to what extent were previous measurements affected by pileup and detector limitations? d) What is the relative timing of gamma ray, optical, and VLF signatures of TGFs? e) What are the characteristics of energetic electrons associated with TGFs? Firefly is scheduled for launch in August 2010, and will be delivered to the launch vehicle in spring 2010. We will present an update on the Firefly status, student training activities, tools we have developed for the community, and lessons learned.

Characterization of CG6178 gene product with high sequence similarity to firefly luciferase in Drosophila melanogaster.

PubMed

Oba, Yuichi; Ojika, Makoto; Inouye, Satoshi

2004-03-31

This is the first identification of a long-chain fatty acyl-CoA synthetase in Drosophila by enzymatic characterization. The gene product of CG6178 (CG6178) in Drosophila melanogaster genome, which has a high sequence similarity to firefly luciferase, has been expressed and characterized. CG6178 showed long-chain fatty acyl-CoA synthetic activity in the presence of ATP, CoA and Mg(2+), suggesting a fatty acyl adenylate is an intermediate. Recently, it was revealed that firefly luciferase has two catalytic functions, monooxygenase (luciferase) and AMP-mediated CoA ligase (fatty acyl-CoA synthetase). However, unlike firefly luciferase, CG6178 did not show luminescence activity in the presence of firefly luciferin, ATP, CoA and Mg(2+). The enzymatic properties of CG6178 including substrate specificity, pH dependency and optimal temperature were close to those of firefly luciferase and rat fatty acyl-CoA synthetase. Further, phylogenic analyses strongly suggest that the firefly luciferase gene may have evolved from a fatty acyl-CoA synthetase gene as a common ancestral gene.

Step-wise addition of disulfide bridge in firefly luciferase controls color shift through a flexible loop: a thermodynamic perspective.

PubMed

Nazari, Mahboobeh; Hosseinkhani, Saman; Hassani, Leila

2013-02-01

Multi-color bioluminescence is developed using the introduction of single/double disulfide bridges in firefly luciferase. The bioluminescence reaction, which uses luciferin, Mg(2+)-ATP and molecular oxygen to yield an electronically excited oxyluciferin, is carried out by the luciferase and emits visible light. The bioluminescence color of firefly luciferases is determined by the luciferase sequence and assay conditions. It has been proposed that the stability of a protein may increase through the introduction of a disulfide bridge that decreases the configurational entropy of unfolding. Single and double disulfide bridges are introduced into Photinus pyralis firefly luciferase to make separate mutant enzymes with a single/double bridge (C(81)-A(105)C, L(306)C-L(309)C, P(451)C-V(469)C; C(81)-A(105)C/P(451)C-V(469)C, and A(296)C-A(326)C/P(451)C-V(469)C). By introduction of disulfide bridges using site-directed mutagenesis in Photinus pyralis luciferase the color of emitted light was changed to red or kept in different extents. The bioluminescence color shift occurred with displacement of a critical loop in the luciferase structure without any change in green emitter mutants. Thermodynamic analysis revealed that among mutants, L(306)C-L(309)C shows a remarkable stability against urea denaturation and also a considerable increase in kinetic stability and a clear shift in bioluminescence spectra towards red.

Investigation into the efficiency of different bionic algorithm combinations for a COBRA meta-heuristic

NASA Astrophysics Data System (ADS)

Akhmedova, Sh; Semenkin, E.

2017-02-01

Previously, a meta-heuristic approach, called Co-Operation of Biology-Related Algorithms or COBRA, for solving real-parameter optimization problems was introduced and described. COBRA’s basic idea consists of a cooperative work of five well-known bionic algorithms such as Particle Swarm Optimization, the Wolf Pack Search, the Firefly Algorithm, the Cuckoo Search Algorithm and the Bat Algorithm, which were chosen due to the similarity of their schemes. The performance of this meta-heuristic was evaluated on a set of test functions and its workability was demonstrated. Thus it was established that the idea of the algorithms’ cooperative work is useful. However, it is unclear which bionic algorithms should be included in this cooperation and how many of them. Therefore, the five above-listed algorithms and additionally the Fish School Search algorithm were used for the development of five different modifications of COBRA by varying the number of component-algorithms. These modifications were tested on the same set of functions and the best of them was found. Ways of further improving the COBRA algorithm are then discussed.

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).

The Role of AhR in Breast Cancer Development

DTIC Science & Technology

2004-07-01

The renilla luciferase vectorphRL-TK (0.05 rtg) was co-transfected with firefly luciferase reporter constructs (0.1 ptg pGudLuc, 0.5-1.0 [tg wildtype...Glo Luciferase system (Promega, Madison, WI ) which allowed sequential reading of the firefly and renilla signals. Cells were lysed according to the...Madison, WI ). The renilla signal was read after quenching the firefly output, thus allowing normalization between sample wells. The normalized firefly

QSRR modeling for the chromatographic retention behavior of some β-lactam antibiotics using forward and firefly variable selection algorithms coupled with multiple linear regression.

PubMed

Fouad, Marwa A; Tolba, Enas H; El-Shal, Manal A; El Kerdawy, Ahmed M

2018-05-11

The justified continuous emerging of new β-lactam antibiotics provokes the need for developing suitable analytical methods that accelerate and facilitate their analysis. A face central composite experimental design was adopted using different levels of phosphate buffer pH, acetonitrile percentage at zero time and after 15 min in a gradient program to obtain the optimum chromatographic conditions for the elution of 31 β-lactam antibiotics. Retention factors were used as the target property to build two QSRR models utilizing the conventional forward selection and the advanced nature-inspired firefly algorithm for descriptor selection, coupled with multiple linear regression. The obtained models showed high performance in both internal and external validation indicating their robustness and predictive ability. Williams-Hotelling test and student's t-test showed that there is no statistical significant difference between the models' results. Y-randomization validation showed that the obtained models are due to significant correlation between the selected molecular descriptors and the analytes' chromatographic retention. These results indicate that the generated FS-MLR and FFA-MLR models are showing comparable quality on both the training and validation levels. They also gave comparable information about the molecular features that influence the retention behavior of β-lactams under the current chromatographic conditions. We can conclude that in some cases simple conventional feature selection algorithm can be used to generate robust and predictive models comparable to that are generated using advanced ones. Copyright © 2018 Elsevier B.V. All rights reserved.

Firefly: embracing future web technologies

NASA Astrophysics Data System (ADS)

Roby, W.; Wu, X.; Goldina, T.; Joliet, E.; Ly, L.; Mi, W.; Wang, C.; Zhang, Lijun; Ciardi, D.; Dubois-Felsmann, G.

2016-07-01

At IPAC/Caltech, we have developed the Firefly web archive and visualization system. Used in production for the last eight years in many missions, Firefly gives the scientist significant capabilities to study data. Firefly provided the first completely web based FITS viewer as well as a growing set of tabular and plotting visualizers. Further, it will be used for the science user interface of the LSST telescope which goes online in 2021. Firefly must meet the needs of archive access and visualization for the 2021 LSST telescope and must serve astronomers beyond the year 2030. Recently, our team has faced the fact that the technology behind Firefly software was becoming obsolete. We were searching for ways to utilize the current breakthroughs in maintaining stability, testability, speed, and reliability of large web applications, which Firefly exemplifies. In the last year, we have ported the Firefly to cutting edge web technologies. Embarking on this massive overhaul is no small feat to say the least. Choosing the technologies that will maintain a forward trajectory in a future development project is always hard and often overwhelming. When a team must port 150,000 lines of code for a production-level product there is little room to make poor choices. This paper will give an overview of the most modern web technologies and lessons learned in our conversion from GWT based system to React/Redux based system.

A new firefly luciferase with bimodal spectrum: identification of structural determinants of spectral pH-sensitivity in firefly luciferases.

PubMed

Viviani, Vadim R; Oehlmeyer, T L; Arnoldi, F G C; Brochetto-Braga, M R

2005-01-01

Fireflies emit flashes in the green-yellow region of the spectrum for the purpose of sexual attraction. The bioluminescence color is determined by the luciferases. It is well known that the in vitro bioluminescence color of firefly luciferases can be shifted toward the red by lower pH and higher temperature; for this reason they are classified as pH-sensitive luciferases. However, the mechanism and structural origin of pH sensitivity in fireflies remains unknown. Here we report the cloning of a new luciferase from the Brazilian twilight active firefly Macrolampis sp2, which displays an unusual bimodal spectrum. The recombinant luciferase displays a sensitive spectrum with the peak at 569 nm and a shoulder in the red region. Comparison of the bioluminescence spectra of Macrolampis, Photinus and Cratomorphus firefly luciferases shows that the distinct colors are determined by the ratio between green and red emitters under luciferase influence. Comparison of Macrolampis luciferase with the highly similar North American Photinus pyralis luciferase (91%) showed few substitutions potentially involved with the higher spectral sensitivity in Macrolampis luciferase. Site-directed mutagenesis showed that the natural substitution E354N determines the appearance of the shoulder in the red region of Macrolampis luciferase bioluminescence spectrum, helping to identify important interactions and residues involved in the pH-sensing mechanism in firefly luciferases.

Application of the Firefly and Luus-Jaakola algorithms in the calculation of a double reactive azeotrope

NASA Astrophysics Data System (ADS)

Mendes Platt, Gustavo; Pinheiro Domingos, Roberto; Oliveira de Andrade, Matheus

2014-01-01

The calculation of reactive azeotropes is an important task in the preliminary design and simulation of reactive distillation columns. Classically, homogeneous nonreactive azeotropes are vapor-liquid coexistence conditions where phase compositions are equal. For homogeneous reactive azeotropes, simultaneous phase and chemical equilibria occur concomitantly with equality of compositions (in the Ung-Doherty transformed space). The modeling of reactive azeotrope calculation is represented by a nonlinear algebraic system with phase equilibrium, chemical equilibrium and azeotropy equations. This nonlinear system can exhibit more than one solution, corresponding to a double reactive azeotrope. In a previous paper (Platt et al 2013 J. Phys.: Conf. Ser. 410 012020), we investigated some numerical aspects of the calculation of reactive azeotropes in the isobutene + methanol + methyl-tert-butyl-ether (with two reactive azeotropes) system using two metaheuristics: the Luus-Jaakola adaptive random search and the Firefly algorithm. Here, we use a hybrid structure (stochastic + deterministic) in order to produce accurate results for both azeotropes. After identifying the neighborhood of the reactive azeotrope, the nonlinear algebraic system is solved using Newton's method. The results indicate that using metaheuristics and some techniques devoted to the calculation of multiple minima allows both azeotropic coordinates in this reactive system to be obtains. In this sense, we provide a comprehensive analysis of a useful framework devoted to solving nonlinear systems, particularly in phase equilibrium problems.

Towards a unified understanding of event-related changes in the EEG: the firefly model of synchronization through cross-frequency phase modulation.

PubMed

Burgess, Adrian P

2012-01-01

Although event-related potentials (ERPs) are widely used to study sensory, perceptual and cognitive processes, it remains unknown whether they are phase-locked signals superimposed upon the ongoing electroencephalogram (EEG) or result from phase-alignment of the EEG. Previous attempts to discriminate between these hypotheses have been unsuccessful but here a new test is presented based on the prediction that ERPs generated by phase-alignment will be associated with event-related changes in frequency whereas evoked-ERPs will not. Using empirical mode decomposition (EMD), which allows measurement of narrow-band changes in the EEG without predefining frequency bands, evidence was found for transient frequency slowing in recognition memory ERPs but not in simulated data derived from the evoked model. Furthermore, the timing of phase-alignment was frequency dependent with the earliest alignment occurring at high frequencies. Based on these findings, the Firefly model was developed, which proposes that both evoked and induced power changes derive from frequency-dependent phase-alignment of the ongoing EEG. Simulated data derived from the Firefly model provided a close match with empirical data and the model was able to account for i) the shape and timing of ERPs at different scalp sites, ii) the event-related desynchronization in alpha and synchronization in theta, and iii) changes in the power density spectrum from the pre-stimulus baseline to the post-stimulus period. The Firefly Model, therefore, provides not only a unifying account of event-related changes in the EEG but also a possible mechanism for cross-frequency information processing.

Towards a Unified Understanding of Event-Related Changes in the EEG: The Firefly Model of Synchronization through Cross-Frequency Phase Modulation

PubMed Central

Burgess, Adrian P.

2012-01-01

Although event-related potentials (ERPs) are widely used to study sensory, perceptual and cognitive processes, it remains unknown whether they are phase-locked signals superimposed upon the ongoing electroencephalogram (EEG) or result from phase-alignment of the EEG. Previous attempts to discriminate between these hypotheses have been unsuccessful but here a new test is presented based on the prediction that ERPs generated by phase-alignment will be associated with event-related changes in frequency whereas evoked-ERPs will not. Using empirical mode decomposition (EMD), which allows measurement of narrow-band changes in the EEG without predefining frequency bands, evidence was found for transient frequency slowing in recognition memory ERPs but not in simulated data derived from the evoked model. Furthermore, the timing of phase-alignment was frequency dependent with the earliest alignment occurring at high frequencies. Based on these findings, the Firefly model was developed, which proposes that both evoked and induced power changes derive from frequency-dependent phase-alignment of the ongoing EEG. Simulated data derived from the Firefly model provided a close match with empirical data and the model was able to account for i) the shape and timing of ERPs at different scalp sites, ii) the event-related desynchronization in alpha and synchronization in theta, and iii) changes in the power density spectrum from the pre-stimulus baseline to the post-stimulus period. The Firefly Model, therefore, provides not only a unifying account of event-related changes in the EEG but also a possible mechanism for cross-frequency information processing. PMID:23049827

Japanese Interest in “Hotaru” (Fireflies) and “Kabuto-Mushi” (Japanese Rhinoceros Beetles) Corresponds with Seasonality in Visible Abundance

PubMed Central

Takada, Kenta

2012-01-01

Seasonal changes in the popularity of fireflies [usually Genji-fireflies (Luciola cruciata Motschulsky) in Japan] and Japanese rhinoceros beetles [Allomyrina dichotoma (Linne)] were investigated to examine whether contemporary Japanese are interested in visible emergence of these insects as seasonal events. The popularity of fireflies and Japanese rhinoceros beetles was assessed by the Google search volume of their Japanese names, “Hotaru” and “Kabuto-mushi” in Japanese Katakana script using Google Trends. The search volume index for fireflies and Japanese rhinoceros beetles was distributed across seasons with a clear peak in only particular times of each year from 2004 to 2011. In addition, the seasonal peak of popularity for fireflies occurred at the beginning of June, whereas that for Japanese rhinoceros beetles occurred from the middle of July to the beginning of August. Thus seasonal peak of each species coincided with the peak period of the emergence of each adult stage. These findings indicated that the Japanese are interested in these insects primarily during the time when the two species are most visibly abundant. Although untested, this could suggest that fireflies and Japanese rhinoceros beetles are perceived by the general public as indicators or symbols of summer in Japan. PMID:26466535

Long-read sequence assembly of the firefly Pyrocoelia pectoralis genome

PubMed Central

Fu, Xinhua; Li, Jingjing; Tian, Yu; Quan, Weipeng; Zhang, Shu; Liu, Qian; Liang, Fan; Zhu, Xinlei; Zhang, Liangsheng

2017-01-01

Abstract Background Fireflies are a family of insects within the beetle order Coleoptera, or winged beetles, and they are one of the most well-known and loved insect species because of their bioluminescence. However, the firefly is in danger of extinction because of the massive destruction of its living environment. In order to improve the understanding of fireflies and protect them effectively, we sequenced the whole genome of the terrestrial firefly Pyrocoelia pectoralis. Findings Here, we developed a highly reliable genome resource for the terrestrial firefly Pyrocoelia pectoralis (E. Oliv., 1883; Coleoptera: Lampyridae) using single molecule real time (SMRT) sequencing on the PacBio Sequel platform. In total, 57.8 Gb of long reads were generated and assembled into a 760.4-Mb genome, which is close to the estimated genome size and covered 98.7% complete and 0.7% partial insect Benchmarking Universal Single-Copy Orthologs. The k-mer analysis showed that this genome is highly heterozygous. However, our long-read assembly demonstrates continuousness with a contig N50 length of 3.04 Mb and the longest contig length of 13.69 Mb. Furthermore, 135 589 SSRs and 341 Mb of repeat sequences were detected. A total of 23 092 genes were predicted; 88.44% of genes were annotated with one or more related functions. Conclusions We assembled a high-quality firefly genome, which will not only provide insights into the conservation and biodiversity of fireflies, but also provide a wealth of information to study the mechanisms of their sexual communication, bio-luminescence, and evolution. PMID:29186486

Synthetic versions of firefly luciferase and Renilla luciferase reporter genes that resist transgene silencing in sugarcane

PubMed Central

2014-01-01

Background Down-regulation or silencing of transgene expression can be a major hurdle to both molecular studies and biotechnology applications in many plant species. Sugarcane is particularly effective at silencing introduced transgenes, including reporter genes such as the firefly luciferase gene. Synthesizing transgene coding sequences optimized for usage in the host plant is one method of enhancing transgene expression and stability. Using specified design rules we have synthesised new coding sequences for both the firefly luciferase and Renilla luciferase reporter genes. We have tested these optimized versions for enhanced levels of luciferase activity and for increased steady state luciferase mRNA levels in sugarcane. Results The synthetic firefly luciferase (luc*) and Renilla luciferase (Renluc*) coding sequences have elevated G + C contents in line with sugarcane codon usage, but maintain 75% identity to the native firefly or Renilla luciferase nucleotide sequences and 100% identity to the protein coding sequences. Under the control of the maize pUbi promoter, the synthetic luc* and Renluc* genes yielded 60x and 15x higher luciferase activity respectively, over the native firefly and Renilla luciferase genes in transient assays on sugarcane suspension cell cultures. Using a novel transient assay in sugarcane suspension cells combining co-bombardment and qRT-PCR, we showed that synthetic luc* and Renluc* genes generate increased transcript levels compared to the native firefly and Renilla luciferase genes. In stable transgenic lines, the luc* transgene generated significantly higher levels of expression than the native firefly luciferase transgene. The fold difference in expression was highest in the youngest tissues. Conclusions We developed synthetic versions of both the firefly and Renilla luciferase reporter genes that resist transgene silencing in sugarcane. These transgenes will be particularly useful for evaluating the expression patterns conferred by existing and newly isolated promoters in sugarcane tissues. The strategies used to design the synthetic luciferase transgenes could be applied to other transgenes that are aggressively silenced in sugarcane. PMID:24708613

Synthetic versions of firefly luciferase and Renilla luciferase reporter genes that resist transgene silencing in sugarcane.

PubMed

Chou, Ting-Chun; Moyle, Richard L

2014-04-08

Down-regulation or silencing of transgene expression can be a major hurdle to both molecular studies and biotechnology applications in many plant species. Sugarcane is particularly effective at silencing introduced transgenes, including reporter genes such as the firefly luciferase gene.Synthesizing transgene coding sequences optimized for usage in the host plant is one method of enhancing transgene expression and stability. Using specified design rules we have synthesised new coding sequences for both the firefly luciferase and Renilla luciferase reporter genes. We have tested these optimized versions for enhanced levels of luciferase activity and for increased steady state luciferase mRNA levels in sugarcane. The synthetic firefly luciferase (luc*) and Renilla luciferase (Renluc*) coding sequences have elevated G + C contents in line with sugarcane codon usage, but maintain 75% identity to the native firefly or Renilla luciferase nucleotide sequences and 100% identity to the protein coding sequences.Under the control of the maize pUbi promoter, the synthetic luc* and Renluc* genes yielded 60x and 15x higher luciferase activity respectively, over the native firefly and Renilla luciferase genes in transient assays on sugarcane suspension cell cultures.Using a novel transient assay in sugarcane suspension cells combining co-bombardment and qRT-PCR, we showed that synthetic luc* and Renluc* genes generate increased transcript levels compared to the native firefly and Renilla luciferase genes.In stable transgenic lines, the luc* transgene generated significantly higher levels of expression than the native firefly luciferase transgene. The fold difference in expression was highest in the youngest tissues. We developed synthetic versions of both the firefly and Renilla luciferase reporter genes that resist transgene silencing in sugarcane. These transgenes will be particularly useful for evaluating the expression patterns conferred by existing and newly isolated promoters in sugarcane tissues. The strategies used to design the synthetic luciferase transgenes could be applied to other transgenes that are aggressively silenced in sugarcane.

Efficient Stochastic Rendering of Static and Animated Volumes Using Visibility Sweeps.

PubMed

von Radziewsky, Philipp; Kroes, Thomas; Eisemann, Martin; Eisemann, Elmar

2017-09-01

Stochastically solving the rendering integral (particularly visibility) is the de-facto standard for physically-based light transport but it is computationally expensive, especially when displaying heterogeneous volumetric data. In this work, we present efficient techniques to speed-up the rendering process via a novel visibility-estimation method in concert with an unbiased importance sampling (involving environmental lighting and visibility inside the volume), filtering, and update techniques for both static and animated scenes. Our major contributions include a progressive estimate of partial occlusions based on a fast sweeping-plane algorithm. These occlusions are stored in an octahedral representation, which can be conveniently transformed into a quadtree-based hierarchy suited for a joint importance sampling. Further, we propose sweep-space filtering, which suppresses the occurrence of fireflies and investigate different update schemes for animated scenes. Our technique is unbiased, requires little precomputation, is highly parallelizable, and is applicable to a various volume data sets, dynamic transfer functions, animated volumes and changing environmental lighting.

Building Twilight "Light Sensors" to Study the Effects of Light Pollution on Fireflies

ERIC Educational Resources Information Center

Thancharoen, Anchana; Branham, Marc A.; Lloyd, James E.

2008-01-01

Light pollution negatively affects many nocturnal organisms. We outline two experiments that can be conducted by students to examine the effects of light pollution on firefly behavior. Inexpensive electronic light sensors, which are easy to construct and calibrate, are used to sample light levels along transects in spaces where fireflies are…

Bioinspired photonic structures by the reflector layer of firefly lantern for highly efficient chemiluminescence

PubMed Central

Chen, Linfeng; Shi, Xiaodi; Li, Mingzhu; Hu, Junping; Sun, Shufeng; Su, Bin; Wen, Yongqiang; Han, Dong; Jiang, Lei; Song, Yanlin

2015-01-01

Fireflies have drawn considerable attention for thousands of years due to their highly efficient bioluminescence, which is important for fundamental research and photonic applications. However, there are few reports on the reflector layer (RL) of firefly lantern, which contributes to the bright luminescence. Here we presented the detailed microstructure of the RL consisting of random hollow granules, which had high reflectance in the range from 450 nm to 800 nm. Inspired by the firefly lantern, artificial films with high reflectance in the visible region were fabricated using hollow silica microparticles mimicking the structure of the RL. Additionally, the bioinspired structures provided an efficient RL for the chemiluminescence system and could substantially enhance the initial chemiluminescence intensity. The work not only provides new insight into the bright bioluminescence of fireflies, but also is importance for the design of photonic materials for theranostics, detection, and imaging. PMID:26264643

Improvement of thermostability and activity of firefly luciferase through [TMG][Ac] ionic liquid mediator.

PubMed

Ebrahimi, Mehdi; Hosseinkhani, Saman; Heydari, Akbar; Khavari-Nejad, Ramazan Ali; Akbari, Jafar

2012-10-01

Firefly luciferase catalyzes production of light from luciferin in the presence of Mg(2+)-ATP and oxygen. This enzyme has wide range of applications in biotechnology and development of biosensors. The low thermal stability of wild-type firefly luciferase is a limiting factor in most applications. Improvements in activity and stability of few enzymes in the presence of ionic liquids were shown in many reports. In this study, kinetic and thermal stability of firefly luciferase from Photinus pyralis in the presence of three tetramethylguanidine-based ionic liquids was investigated. The enzyme has shown improved activity in the presence of [1, 1, 3, 3-tetramethylguanidine][acetate], but in the presence of [TMG][trichloroacetate] and [TMG][triflouroacetate] activity, it decreased or unchanged significantly. Among these ionic liquids, only [TMG][Ac] has increased the thermal stability of luciferase. Incubation of [TMG][Ac] with firefly luciferase brought about with decrease of K(m) for ATP.

Performance comparisons between PCA-EA-LBG and PCA-LBG-EA approaches in VQ codebook generation for image compression

NASA Astrophysics Data System (ADS)

Tsai, Jinn-Tsong; Chou, Ping-Yi; Chou, Jyh-Horng

2015-11-01

The aim of this study is to generate vector quantisation (VQ) codebooks by integrating principle component analysis (PCA) algorithm, Linde-Buzo-Gray (LBG) algorithm, and evolutionary algorithms (EAs). The EAs include genetic algorithm (GA), particle swarm optimisation (PSO), honey bee mating optimisation (HBMO), and firefly algorithm (FF). The study is to provide performance comparisons between PCA-EA-LBG and PCA-LBG-EA approaches. The PCA-EA-LBG approaches contain PCA-GA-LBG, PCA-PSO-LBG, PCA-HBMO-LBG, and PCA-FF-LBG, while the PCA-LBG-EA approaches contain PCA-LBG, PCA-LBG-GA, PCA-LBG-PSO, PCA-LBG-HBMO, and PCA-LBG-FF. All training vectors of test images are grouped according to PCA. The PCA-EA-LBG used the vectors grouped by PCA as initial individuals, and the best solution gained by the EAs was given for LBG to discover a codebook. The PCA-LBG approach is to use the PCA to select vectors as initial individuals for LBG to find a codebook. The PCA-LBG-EA used the final result of PCA-LBG as an initial individual for EAs to find a codebook. The search schemes in PCA-EA-LBG first used global search and then applied local search skill, while in PCA-LBG-EA first used local search and then employed global search skill. The results verify that the PCA-EA-LBG indeed gain superior results compared to the PCA-LBG-EA, because the PCA-EA-LBG explores a global area to find a solution, and then exploits a better one from the local area of the solution. Furthermore the proposed PCA-EA-LBG approaches in designing VQ codebooks outperform existing approaches shown in the literature.

Engineering the metal sensitive sites in Macrolampis sp2 firefly luciferase and use as a novel bioluminescent ratiometric biosensor for heavy metals.

PubMed

Gabriel, Gabriele V M; Viviani, Vadim R

2016-12-01

Most luminescent biosensors for heavy metals are fluorescent and rely on intensity measurements, whereas a few are ratiometric and rely on spectral changes. Bioluminescent biosensors for heavy metals are less common. Firefly luciferases have been coupled to responsive promoters for mercury and arsenium, and used as light on biosensors. Firefly luciferase bioluminescence spectrum is naturally sensitive to heavy metal cations such as zinc and mercury and to pH. Although pH sensitivity of firefly luciferases was shown to be useful for ratiometric estimation of intracellular pH, its potential use for ratiometric estimation of heavy metals was never considered. Using the yellow-emitting Macrolampis sp2 firefly luciferase and site-directed mutagenesis, we show that the residues H310 and E354 constitute two critical sites for metal sensitivity that can be engineered to increase sensitivity to zinc, nickel, and mercury. A linear relationship between cation concentration and the ratio of bioluminescence intensities at 550 and 610 nm allowed, for the first time, the ratiometric estimation of heavy metals concentrations down to 0.10 mM, demonstrating the potential applicability of firefly luciferases as enzymatic and intracellular ratiometric metal biosensors.

Modeling and image reconstruction in spectrally resolved bioluminescence tomography

NASA Astrophysics Data System (ADS)

Dehghani, Hamid; Pogue, Brian W.; Davis, Scott C.; Patterson, Michael S.

2007-02-01

Recent interest in modeling and reconstruction algorithms for Bioluminescence Tomography (BLT) has increased and led to the general consensus that non-spectrally resolved intensity-based BLT results in a non-unique problem. However, the light emitted from, for example firefly Luciferase, is widely distributed over the band of wavelengths from 500 nm to 650 nm and above, with the dominant fraction emitted from tissue being above 550 nm. This paper demonstrates the development of an algorithm used for multi-wavelength 3D spectrally resolved BLT image reconstruction in a mouse model. It is shown that using a single view data, bioluminescence sources of up to 15 mm deep can be successfully recovered given correct information about the underlying tissue absorption and scatter.

Firefly, Firefly: First Grade Students Learn, Talk, and Write about Light

ERIC Educational Resources Information Center

Mesa, Jennifer; Sorensen, Kirsten

2016-01-01

Inspired by a song to be sung by her daughter's first-grade class in an upcoming musical, a parent volunteer teacher used fireflies as the focus of a science lesson to build on the children's interest and experiences. She developed a 5E lesson (Bybee et al. 2006) using the backwards-design approach (Wiggins and McTighe 2005) to ensure meaningful…

Translational Regulation of PTEN/MMAC1 Expression in Prostate Cancer

DTIC Science & Technology

2003-05-01

the transcription of dicistronic RNA encoding Renilla luciferase as the first cistron and firefly luciferase as the second cistron. Translation of the...first cistron ( Renilla luciferase) serves as an indicator of cap-dependent translation while translation of the second cistron (firefly luciferase...cellular IRES (Sachs, 2000). These dicistronic constructs were transfected into HeLa cells and both Renilla and firefly luciferase activities were measured

Theoretical tuning of the firefly bioluminescence spectra by the modification of oxyluciferin

NASA Astrophysics Data System (ADS)

Cheng, Yuan-Yuan; Zhu, Jia; Liu, Ya-Jun

2014-01-01

Extending the firefly bioluminescence is of practical significance for the improved visualization of living cells and the development of a multicolor reporter. Tuning the color of bioluminescence in fireflies mainly involves the modification of luciferase and luciferin. In this Letter, we theoretically studied the emission spectra of 9 firefly oxyluciferin analogs in the gas phase and in solutions. Three density functionals, including B3LYP, CAM-B3LYP and M06-2X, were employed to theoretically predict the efficiently luminescent analogs. The reliable functionals for calculating the targeted systems were suggested. The luminescence efficiency, solvent effects, and substituent effects are discussed based on the calculated results.

Molecular Targeting of Prostate Cancer During Androgen Ablation: Inhibition of CHES1/FOXN3

DTIC Science & Technology

2011-05-01

activity (Firefly luciferase) was normalized to Renilla luciferase activity. Results are presented as fold-change in PSA reporter activity...reporter (DLR) assays performed. In each sample, the CHES1-RR1/3.5 reporter activity (Firefly luciferase) was normalized to Renilla luciferase...4.0) reporter activity (Firefly luciferase) was normalized to Renilla luciferase activity. Results are presented as fold-change in BNIP3 reporter

Variation in opsin genes correlates with signaling ecology in North American fireflies

PubMed Central

Sander, Sarah E.; Hall, David W.

2015-01-01

Genes underlying signal reception should evolve to maximize signal detection in a particular environment. In animals, opsins, the protein component of visual pigments, are predicted to evolve according to this expectation. Fireflies are known for their bioluminescent mating signals. The eyes of nocturnal species are expected to maximize detection of conspecific signal colors emitted in the typical low-light environment. This is not expected for species that have transitioned to diurnal activity in bright daytime environments. Here we test the hypothesis that opsin gene sequence plays a role in modifying firefly eye spectral sensitivity. We use genome and transcriptome sequencing in four firefly species, transcriptome sequencing in six additional species, and targeted gene sequencing in 28 other species to identify all opsin genes present in North American fireflies and to elucidate amino acid sites under positive selection. We also determine whether amino acid substitutions in opsins are linked to evolutionary changes in signal mode, signal color, and light environment. We find only two opsins, one long wavelength and one ultraviolet, in all firefly species and identify 25 candidate sites that may be involved in determining spectral sensitivity. In addition, we find elevated rates of evolution at transitions to diurnal activity, and changes in selective constraint on LW opsin associated with changes in light environment. Our results suggest that changes in eye spectral sensitivity are at least partially due to opsin sequence. Fireflies continue to be a promising system in which to investigate the evolution of signals, receptors, and signaling environments. PMID:26289828

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

PubMed

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

2014-01-01

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

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

PubMed Central

Deb, Suash; Yang, Xin-She

2014-01-01

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

Parameter optimization of an inerter-based isolator for passive vibration control of Michelangelo's Rondanini Pietà

NASA Astrophysics Data System (ADS)

Siami, A.; Karimi, H. R.; Cigada, A.; Zappa, E.; Sabbioni, E.

2018-01-01

Preserving cultural heritage against earthquake and ambient vibrations can be an attractive topic in the field of vibration control. This paper proposes a passive vibration isolator methodology based on inerters for improving the performance of the isolation system of the famous statue of Michelangelo Buonarroti Pietà Rondanini. More specifically, a five-degree-of-freedom (5DOF) model of the statue and the anti-seismic and anti-vibration base is presented and experimentally validated. The parameters of this model are tuned according to the experimental tests performed on the assembly of the isolator and the structure. Then, the developed model is used to investigate the impact of actuation devices such as tuned mass-damper (TMD) and tuned mass-damper-inerter (TMDI) in vibration reduction of the structure. The effect of implementation of TMDI on the 5DOF model is shown based on physical limitations of the system parameters. Simulation results are provided to illustrate effectiveness of the passive element of TMDI in reduction of the vibration transmitted to the statue in vertical direction. Moreover, the optimal design parameters of the passive system such as frequency and damping coefficient will be calculated using two different performance indexes. The obtained optimal parameters have been evaluated by using two different optimization algorithms: the sequential quadratic programming method and the Firefly algorithm. The results prove significant reduction in the transmitted vibration to the structure in the presence of the proposed tuned TMDI, without imposing a large amount of mass or modification to the structure of the isolator.

Flash Bulletin: Fireflies

ERIC Educational Resources Information Center

Brown, Debbie

1984-01-01

Explains the flashes of light emitted by fireflies as competition, species-specific code, species identification and mating behavior and ecology. Suggests activities to conduct to study the insects and their behavior. (ERB)

Genome size of 14 species of fireflies (Insecta, Coleoptera, Lampyridae)

PubMed Central

Liu, Gui-Chun; Dong, Zhi-Wei; He, Jin-Wu; Zhao, Ruo-Ping; Wang, Wen; Li, Xue-Yan

2017-01-01

Eukaryotic genome size data are important both as the basis for comparative research into genome evolution and as estimators of the cost and difficulty of genome sequencing programs for non-model organisms. In this study, the genome size of 14 species of fireflies (Lampyridae) (two genera in Lampyrinae, three genera in Luciolinae, and one genus in subfamily incertae sedis) were estimated by propidium iodide (PI)-based flow cytometry. The haploid genome sizes of Lampyridae ranged from 0. 42 to 1. 31 pg, a 3. 1-fold span. Genome sizes of the fireflies varied within the tested subfamilies and genera. Lamprigera and Pyrocoelia species had large and small genome sizes, respectively. No correlation was found between genome size and morphological traits such as body length, body width, eye width, and antennal length. Our data provide additional information on genome size estimation of the firefly family Lampyridae. Furthermore, this study will help clarify the cost and difficulty of genome sequencing programs for non-model organisms and will help promote studies on firefly genome evolution. PMID:29280364

Dragonflies and Fireflies

ERIC Educational Resources Information Center

Mannlein, Sally

2009-01-01

Most first-graders are interested in insects. In this article, the author describes a lesson, "Dragonflies and Fireflies," which is a first-grade lesson showing drawing, symmetry, neighboring colors (analogous) and watercolor techniques.

Bioluminescence.

ERIC Educational Resources Information Center

Jones, M. Gail

1993-01-01

Describes bioluminescence and the chemistry of how it occurs. Presents information for conducting the following classroom activities: (1) firefly mimic; (2) modeling deep-sea fish; (3) sea fireflies; and (4) the chemistry of light. (PR)

75 FR 39143 - Airworthiness Directives; Arrow Falcon Exporters, Inc. (previously Utah State University); AST...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-08

... Firefly Aviation Helicopter Services, and Erickson Air-Crane); Rotorcraft Development Corporation..., Inc. (Previously Firefly Aviation Helicopter Services, and Erickson Air-Crane); Rotorcraft Development...

Functional Geno,ic Analysis of Breast Cancer Cell Tumorigenicity Using a Noval Gene Silencing Resource

DTIC Science & Technology

2006-04-01

Fig. 2B). In addition, luciferase assay on cells co-transfected with constructs expressing firefly and renilla luciferase genes showed a significant...positive cells. (C) BT474 cells were co-transfected with pGL3 plasmid expressing firefly luciferase, pRL plasmid expressing renilla luciferase, and...genes Per1 (A) and Bmal1 (B). BT474 cells were transfected with Per1 (A) and Bmal1 (B) firefly luciferase reporters, pRL plasmid expressing renilla

Firefly courtship as the basis of the synchronization-response principle

NASA Astrophysics Data System (ADS)

Ramírez Ávila, G. M.; Deneubourg, J.-L.; Guisset, J.-L.; Wessel, N.; Kurths, J.

2011-06-01

Response to synchronization seems to be a widespread phenomenon specially in biological systems. We highlight this phenomenon studying the courtship of flashing fireflies in which a typical collective rhythm occurring only among the males arises and it is followed by a response of the females. Based on a model issued from electronic fireflies, we explain the synchronization of the males and the active responses of the females in the courtship of mingled (both sexes) populations of fireflies. The model also explains the courtship behavior of other species whose interactions follow the same logic even if their physical features are different. Moreover, the model can make predictions on the behavior of mingled and mixed (natural and artificial) groups of such animals. This finding could be considered as the basis of a new principle, namely the synchronization-response.

Comparison of the thermostability of recombinant luciferases from Brazilian bioluminescent beetles: Relationship with kinetics and bioluminescence colours.

PubMed

Oliveira, Gabriela; Viviani, Vadim R

2018-03-01

Firefly luciferases have been used extensively as bioanalytical reagents and their cDNAs as reporter genes for biosensors and bioimaging, but they are in general unstable at temperatures above 30°C. In the past few years, efforts have been made to stabilize some firefly luciferases for better application as analytical reagents. Novel luciferases from different beetle families, displaying distinct bioluminescence colours and kinetics, may offer desirable alternatives to extend the range of applications. In the past years, our group has cloned the largest variety of luciferases from the three main families of bioluminescent beetles (Elateridae: P. termitilluminans, F. bruchi, P. angustus; Phengodidae: P. hirtus, P. vivianii; and Lampyridae: A. vivianii, C. distinctus and Macrolampis sp2) occurring in Brazilian biomes. We compared the thermostability of these recombinant luciferases and investigated their relationships with bioluminescence spectra and kinetics. The most thermostable luciferases were those of Pyrearinus termitilluminans larval click beetle (534 nm), Amydetes vivianii firefly (539 nm) and Phrixotrix vivianii railroad worm (546 nm), which are the most blue-shifted examples in each family, confirming the trend that the most blue-shifted emitting luciferases are also the most thermostable. Comparatively, commercial P. pyralis firefly luciferase was less thermostable than P. termitilluminans click beetle and A. vivianii firefly luciferases. The higher thermostability in these luciferases could be related to higher degree of hydrophobic packing and disulfide bond content (for firefly luciferases). Copyright © 2017 John Wiley & Sons, Ltd.

Using Firefly Tools to Enhance Archive Web Pages

NASA Astrophysics Data System (ADS)

Roby, W.; Wu, X.; Ly, L.; Goldina, T.

2013-10-01

Astronomy web developers are looking for fast and powerful HTML 5/AJAX tools to enhance their web archives. We are exploring ways to make this easier for the developer. How could you have a full FITS visualizer or a Web 2.0 table that supports paging, sorting, and filtering in your web page in 10 minutes? Can it be done without even installing any software or maintaining a server? Firefly is a powerful, configurable system for building web-based user interfaces to access astronomy science archives. It has been in production for the past three years. Recently, we have made some of the advanced components available through very simple JavaScript calls. This allows a web developer, without any significant knowledge of Firefly, to have FITS visualizers, advanced table display, and spectrum plots on their web pages with minimal learning curve. Because we use cross-site JSONP, installing a server is not necessary. Web sites that use these tools can be created in minutes. Firefly was created in IRSA, the NASA/IPAC Infrared Science Archive (http://irsa.ipac.caltech.edu). We are using Firefly to serve many projects including Spitzer, Planck, WISE, PTF, LSST and others.

Experimental tests of light-pollution impacts on nocturnal insect courtship and dispersal.

PubMed

Firebaugh, Ariel; Haynes, Kyle J

2016-12-01

Though a number of effects of artificial light pollution on behavior and physiology have been described, there is little understanding of their consequences for the growth and distribution of populations. Here, we document impacts of light pollution on aspects of firefly population ecology and underlying mating behaviors. Many firefly species have a unique communication system whereby bioluminescent flashes are used in courtship displays to find and attract mates. We performed a series of manipulative field experiments in which we quantified the effects of adding artificial nighttime lighting on abundances and total flashing activity of fireflies, courtship behaviors and mating between tethered females and free-flying males, and dispersal distances of marked individuals. We show that light pollution reduces flashing activities in a dark-active firefly species (Photuris versicolor) by 69.69 % and courtship behavior and mating success in a twilight-active species (Photinus pyralis). Though courtship behavior and mating success of Photinus pyralis was reduced by light pollution, we found no effects of light pollution on male dispersal in this species. Our findings suggest that light pollution is likely to adversely impact firefly populations, and contribute to wider discussions about the ecological consequences of sensory pollution.

The nuclear factor κB inhibitor (E)-2-fluoro-4'-methoxystilbene inhibits firefly luciferase.

PubMed

Braeuning, Albert; Vetter, Silvia

2012-12-01

Photinus pyralis (firefly) luciferase is widely used as a reporter system to monitor alterations in gene promoter and/or signalling pathway activities in vitro. The enzyme catalyses the formation of oxyluciferin from D-luciferin in an ATP-consuming reaction involving photon emission. The purpose of the present study was to characterize the luciferase-inhibiting potential of (E)-2-fluoro-4'-methoxystilbene, which is known as a potent inhibitor of the NF-κB (nuclear factor κB) signalling pathway that is used to modulate the NF-κB signalling pathway in vitro. Results show that (E)-2-fluoro-4'-methoxystilbene effectively inhibits firefly luciferase activity in cell lysates and living cells in a non-competitive manner with respect to the luciferase substrates D-luciferin and ATP. By contrast, the compound has no effect on Renilla and Gaussia luciferases. The mechanism of firefly luciferase inhibition by (E)-2-fluoro-4'-methoxystilbene, as well as its potency is comparable to its structure analogue resveratrol. The in vitro use of trans-stilbenes such as (E)-2-fluoro-4'-methoxystilbene or resveratrol compromises firefly luciferase reporter assays as well as ATP/luciferase-based cell viability assays.

The nuclear factor κB inhibitor (E)-2-fluoro-4′-methoxystilbene inhibits firefly luciferase

PubMed Central

Braeuning, Albert; Vetter, Silvia

2012-01-01

Photinus pyralis (firefly) luciferase is widely used as a reporter system to monitor alterations in gene promoter and/or signalling pathway activities in vitro. The enzyme catalyses the formation of oxyluciferin from D-luciferin in an ATP-consuming reaction involving photon emission. The purpose of the present study was to characterize the luciferase-inhibiting potential of (E)-2-fluoro-4′-methoxystilbene, which is known as a potent inhibitor of the NF-κB (nuclear factor κB) signalling pathway that is used to modulate the NF-κB signalling pathway in vitro. Results show that (E)-2-fluoro-4′-methoxystilbene effectively inhibits firefly luciferase activity in cell lysates and living cells in a non-competitive manner with respect to the luciferase substrates D-luciferin and ATP. By contrast, the compound has no effect on Renilla and Gaussia luciferases. The mechanism of firefly luciferase inhibition by (E)-2-fluoro-4′-methoxystilbene, as well as its potency is comparable to its structure analogue resveratrol. The in vitro use of trans-stilbenes such as (E)-2-fluoro-4′-methoxystilbene or resveratrol compromises firefly luciferase reporter assays as well as ATP/luciferase-based cell viability assays. PMID:22789175

Different types of maximum power point tracking techniques for renewable energy systems: A survey

NASA Astrophysics Data System (ADS)

Khan, Mohammad Junaid; Shukla, Praveen; Mustafa, Rashid; Chatterji, S.; Mathew, Lini

2016-03-01

Global demand for electricity is increasing while production of energy from fossil fuels is declining and therefore the obvious choice of the clean energy source that is abundant and could provide security for development future is energy from the sun. In this paper, the characteristic of the supply voltage of the photovoltaic generator is nonlinear and exhibits multiple peaks, including many local peaks and a global peak in non-uniform irradiance. To keep global peak, MPPT is the important component of photovoltaic systems. Although many review articles discussed conventional techniques such as P & O, incremental conductance, the correlation ripple control and very few attempts have been made with intelligent MPPT techniques. This document also discusses different algorithms based on fuzzy logic, Ant Colony Optimization, Genetic Algorithm, artificial neural networks, Particle Swarm Optimization Algorithm Firefly, Extremum seeking control method and hybrid methods applied to the monitoring of maximum value of power at point in systems of photovoltaic under changing conditions of irradiance.

Full color modulation of firefly luciferase through engineering with unified Stark effect.

PubMed

Cai, Duanjun; Marques, Miguel A L; Nogueira, Fernando

2013-11-07

The firefly luciferase has been a unique marking tool used in various bioimaging techniques. Extensive color modulation is strongly required to meet special marking demands; however, intentional and accurate wavelength tuning has yet to be achieved. Here, we demonstrate that the color shift of the firefly chromophore (OxyLH2-1) by internal and external fields can be described as a unified Stark shift. Electrostatic microenvironmental effects on fluorescent spectroscopy are modeled in vacuo through effective electric fields by using time-dependent density functional theory. A complete visible fluorescence spectrum of firefly chromophore is depicted, which enables one to control the emission in a specific color. As an application, the widely observed pH-correlated color shift is proved to be associated with the local Stark field generated by the trace water-ions (vicinal hydronium and hydroxide ions) at active sites close to the OxyLH2-1.

FIREFLY: A cubesat mission to study terrestrial gamma-ray flashes

NASA Astrophysics Data System (ADS)

Klenzing, J. H.; Rowland, D. E.; Hill, J.; Weatherwax, A. T.

2009-12-01

FIREFLY is small satellite mission to investigate the link between atmospheric lightning and terrestrial gamma-ray flashes scheduled to launch in late 2010. The instrumentation includes a Gamma-Ray Detector (GRD), VLF receiver, and photometer. GRD will measure the energy and arrival time of x-ray and gamma-ray photons, as well as the energetic electron flux by using a phoswitch-style layered scintillator. The current status of the instrumentation will be discussed, including laboratory tests and simulations of the GRD. FIREFLY is the second in a series of NSF-funded cubesats designed to study the upper atmosphere.

Molecular characterization of firefly nuptial gifts: a multi-omics approach sheds light on postcopulatory sexual selection.

PubMed

Al-Wathiqui, Nooria; Fallon, Timothy R; South, Adam; Weng, Jing-Ke; Lewis, Sara M

2016-12-22

Postcopulatory sexual selection is recognized as a key driver of reproductive trait evolution, including the machinery required to produce endogenous nuptial gifts. Despite the importance of such gifts, the molecular composition of the non-gametic components of male ejaculates and their interactions with female reproductive tracts remain poorly understood. During mating, male Photinus fireflies transfer to females a spermatophore gift manufactured by multiple reproductive glands. Here we combined transcriptomics of both male and female reproductive glands with proteomics and metabolomics to better understand the synthesis, composition and fate of the spermatophore in the common Eastern firefly, Photinus pyralis. Our transcriptome of male glands revealed up-regulation of proteases that may enhance male fertilization success and activate female immune response. Using bottom-up proteomics we identified 208 functionally annotated proteins that males transfer to the female in their spermatophore. Targeted metabolomic analysis also provided the first evidence that Photinus nuptial gifts contain lucibufagin, a firefly defensive toxin. The reproductive tracts of female fireflies showed increased gene expression for several proteases that may be involved in egg production. This study offers new insights into the molecular composition of male spermatophores, and extends our understanding of how nuptial gifts may mediate postcopulatory interactions between the sexes.

Identification and characterization of the Luc2-type luciferase in the Japanese firefly, Luciola parvula, involved in a dim luminescence in immobile stages.

PubMed

Bessho-Uehara, Manabu; Oba, Yuichi

2017-09-01

Nocturnal Japanese fireflies, Luciola parvula, emit from their lanterns a yellow light, one of the most red-shifted colors found among fireflies. Previously, we isolated and characterized two different types of luciferase gene, Luc1 and Luc2, from the fireflies Luciola cruciata and Luciola lateralis; Luc1 is responsible for the green-yellow luminescence of larval and adult lanterns, whereas Luc2 is responsible for the dim greenish glow of eggs and pupal bodies. The biological role of firefly lanterns in adults is related to sexual communication, but why the eggs and pupae glow remains uncertain. In this study, we isolated the gene Luc2 from L. parvula, and compared its expression profiles and enzymatic characteristics with those of Luc1. A semi-quantitative reverse transcription polymerase chain reaction showed that Luc1 was predominantly expressed in larvae, prepupae, pupae and adults, whereas Luc2 was expressed in eggs, prepupae, pupae and adult females. Enzymatic analyses showed that the luminescent color of Luc1 matches the visual sensitivity of L. parvula eyes, whereas that of Luc2 is very different from it. These results suggest that the biological role of Luc2 expressed in immobile stages is not intraspecific communication. Copyright © 2017 John Wiley & Sons, Ltd.

Biosynthesis-inspired deracemizative production of d-luciferin by combining luciferase and thioesterase.

PubMed

Maeda, Juri; Kato, Dai-Ichiro; Okuda, Masatoshi; Takeo, Masahiro; Negoro, Seiji; Arima, Kazunari; Ito, Yuji; Niwa, Kazuki

2017-08-01

Due to the strict enantioselectivity of firefly luciferase, only d-luciferin can be used as a substrate for bioluminescence reactions. Unfortunately, luciferin racemizes easily and accumulation of nonluminous l-luciferin has negative influences on the light emitting reaction. Thus, maintaining the enantiopurity of luciferin in the reaction mixture is one of the most important demands in bioluminescence applications using firefly luciferase. In fireflies, however, l-luciferin is the biosynthetic precursor of d-luciferin, which is produced from the L-form undergoing deracemization. This deracemization consists of three successive reactions: l-enantioselective thioesterification by luciferase, in situ epimerization, and hydrolysis by thioesterase. In this work, we introduce a deracemizative luminescence system inspired by the biosynthetic pathway of d-luciferin using a combination of firefly luciferase from Luciola cruciata (LUC-G) and fatty acyl-CoA thioesterase II from Escherichia coli (TESB). The enzymatic reaction property analysis indicated the importance of the concentration balance between LUC-G and TESB for efficient d-luciferin production and light emission. Using this deracemizative luminescence system, a highly sensitive quantitative analysis method for l-cysteine was constructed. This LUC-G-TESB combination system can improve bioanalysis applications using the firefly bioluminescence reaction by efficient deracemization of D-luciferin. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification of the physiological promoter for spinocerebellar ataxia 2 gene reveals a CpG island for promoter activity situated into the exon 1 of this gene and provides data about the origin of the nonmethylated state of these types of islands.

PubMed

Aguiar, J; Santurlidis, S; Nowok, J; Alexander, C; Rudnicki, D; Gispert, S; Schulz, W; Auburger, G

1999-01-19

In order to further use the spinocerebellar ataxia 2 (SCA2) promoter for transgenic mice models of "CAG repeat" neurodegeneration, different fragments of this 5' end were ligated into pGL3-Luc plasmid to obtain the better promoter-activity of the physiological promoter for SCA2. Base-par composition of the SCA2-5' region, and promoter prediction algorithms such as TSSW and TSSG, together with the high firefly luciferase expression after 48 hours of transient transfection in mammalian cells lines, showed a typical CpG island for promoter-activity. The promoter activity was specifically localized into the exon 1 of the SCA2 gene. The higher expression of firefly luciferase in the embryonal F9 cells by the use of SCA2 promoter, rather than by the use of CMV promoter may be related with the origin of the nonmethylated CpG island during the early embryogenesis. Analysis of the 5' region from HD gene revealed to a CpG island, which could be containing the physiological promoter for this gene. Copyright 1999 Academic Press.

Hands-on Science. How Fireflies Communicate.

ERIC Educational Resources Information Center

Kepler, Lynne

1995-01-01

One creative way that elementary science educators can teach their students about animal communication is to give them glow sticks and a set of cards with descriptions of what different firefly flash signals mean. The paper describes such a project and presents related activities. (SM)

A new blue-shifted luciferase from the Brazilian Amydetes fanestratus (Coleoptera: Lampyridae) firefly: molecular evolution and structural/functional properties.

PubMed

Viviani, Vadim R; Amaral, Danilo; Prado, Rogilene; Arnoldi, Frederico G C

2011-12-01

Firefly luciferases usually produce bioluminescence in the yellow-green region, with colors in the green and yellow-orange extremes of the spectrum being less common. Several firefly luciferases have already been cloned and sequenced, and site-directed mutagenesis studies have already identified important regions and residues for bioluminescence colors. However the structural determinants and mechanisms of bioluminescence colors turned out to be elusive, mainly when comparing luciferases with a high degree of divergence. Thus comparison of more similar luciferases producing colors in the two extremes of the spectrum could be revealing. The South-American fauna of fireflies remains largely unstudied, with some unique taxa that are not found anywhere else in the world and that produce a wide range of bioluminescence colors. Among them, fireflies of the genus Amydetes are especially interesting because its taxonomical status as an independent subfamily or as a tribe is not yet solved, and because they usually produce a continuous bright blue-shifted bioluminescence. In this work we cloned the cDNA for the luciferase of the Atlantic rain forest Amydetes fanestratus firefly, which is found near Sorocaba municipality (São Paulo, Brazil). Despite showing a higher degree of identity with the South-American Cratomorphus, the European Lampyris and the Asiatic Pyrocoelia, phylogenetical analysis of the luciferase sequence support the inclusion of Amydetes as an independent subfamily. Amydetes luciferase displays one of the most blue-shifted emission spectra (λ(max) = 538 nm) among beetle luciferases, with lower pH-sensitivity and higher affinity for ATP when compared to other luciferases, making this luciferase attractive for sensitive ATP and reporter assays.

FIREFLY LUCIFERASE ATP ASSAY DEVELOPMENT FOR MONITORING BACTERIAL CONCENTRATIONS IN WATER SUPPLIES

EPA Science Inventory

This research program was initiated to develop a rapid, automatable system for measuring total viable microorganisms in potable drinking water supplies using the firefly luciferase ATP assay. The assay was adapted to an automatable flow system that provided comparable sensitivity...

Molecular Origin of Color Variation in Firefly (Beetle) Bioluminescence: A Chemical Basis for Biological Imaging.

PubMed

Hirano, Takashi

2016-01-01

Firefly shows bioluminescence by "luciferin-luciferase" (L-L) reaction using luciferin, luciferase, ATP and O2. The chemical photon generation by an enzymatic reaction is widely utilized for analytical methods including biological imaging in the life science fields. To expand photondetecting analyses with firefly bioluminescence, it is important for users to understand the chemical basis of the L-L reaction. In particular, the emission color variation of the L-L reaction is one of the distinguishing characteristics for multicolor luciferase assay and in vivo imaging. From the viewpoint of fundamental chemistry, this review explains the recent progress in the studies on the molecular mechanism of emission color variation after showing the outline of the reaction mechanism of the whole L-L reaction. On the basis of the mechanism, the progresses in organic synthesis of luciferin analogs modulating their emission colors are also presented to support further developments of red/near infrared in vivo biological imaging utility of firefly bioluminescence.

Impact of Site-Directed Mutant Luciferase on Quantitative Green and Orange/Red Emission Intensities in Firefly Bioluminescence

NASA Astrophysics Data System (ADS)

Wang, Yu; Akiyama, Hidefumi; Terakado, Kanako; Nakatsu, Toru

2013-08-01

Firefly bioluminescence has attracted great interest because of its high quantum yield and intriguing modifiable colours. Modifications to the structure of the enzyme luciferase can change the emission colour of firefly bioluminescence, and the mechanism of the colour change has been intensively studied by biochemists, structural biologists, optical physicists, and quantum-chemistry theorists. Here, we report on the quantitative spectra of firefly bioluminescence catalysed by wild-type and four site-directed mutant luciferases. While the mutation caused different emission spectra, the spectra differed only in the intensity of the green component (λmax ~ 560 nm). In contrast, the orange (λmax ~ 610 nm) and red (λmax ~ 650 nm) components present in all the spectra were almost unaffected by the modifications to the luciferases and changes in pH. Our results reveal that the intensity of the green component is the unique factor that is influenced by the luciferase structure and other reaction conditions.

Site-directed mutagenesis of firefly luciferase: implication of conserved residue(s) in bioluminescence emission spectra among firefly luciferases.

PubMed

Tafreshi, Narges Kh; Sadeghizadeh, Majid; Emamzadeh, Rahman; Ranjbar, Bijan; Naderi-Manesh, Hossein; Hosseinkhani, Saman

2008-05-15

The bioluminescence colours of firefly luciferases are determined by assay conditions and luciferase structure. Owing to red light having lower energy than green light and being less absorbed by biological tissues, red-emitting luciferases have been considered as useful reporters in imaging technology. A set of red-emitting mutants of Lampyris turkestanicus (Iranian firefly) luciferase has been made by site-directed mutagenesis. Among different beetle luciferases, those from Phrixothrix (railroad worm) emit either green or red bioluminescence colours naturally. By substitution of three specific amino acids using site-specific mutagenesis in a green-emitting luciferase (from L. turkestanicus), the colour of emitted light was changed to red concomitant with decreasing decay rate. Different specific mutations (H245N, S284T and H431Y) led to changes in the bioluminescence colour. Meanwhile, the luciferase reaction took place with relative retention of its basic kinetic properties such as K(m) and relative activity. Structural comparison of the native and mutant luciferases using intrinsic fluorescence, far-UV CD spectra and homology modelling revealed a significant conformational change in mutant forms. A change in the colour of emitted light indicates the critical role of these conserved residues in bioluminescence colour determination among firefly luciferases. Relatively high specific activity and emission of red light might make these mutants suitable as reporters for the study of gene expression and bioluminescence imaging.

Towards semi-automatic rock mass discontinuity orientation and set analysis from 3D point clouds

NASA Astrophysics Data System (ADS)

Guo, Jiateng; Liu, Shanjun; Zhang, Peina; Wu, Lixin; Zhou, Wenhui; Yu, Yinan

2017-06-01

Obtaining accurate information on rock mass discontinuities for deformation analysis and the evaluation of rock mass stability is important. Obtaining measurements for high and steep zones with the traditional compass method is difficult. Photogrammetry, three-dimensional (3D) laser scanning and other remote sensing methods have gradually become mainstream methods. In this study, a method that is based on a 3D point cloud is proposed to semi-automatically extract rock mass structural plane information. The original data are pre-treated prior to segmentation by removing outlier points. The next step is to segment the point cloud into different point subsets. Various parameters, such as the normal, dip/direction and dip, can be calculated for each point subset after obtaining the equation of the best fit plane for the relevant point subset. A cluster analysis (a point subset that satisfies some conditions and thus forms a cluster) is performed based on the normal vectors by introducing the firefly algorithm (FA) and the fuzzy c-means (FCM) algorithm. Finally, clusters that belong to the same discontinuity sets are merged and coloured for visualization purposes. A prototype system is developed based on this method to extract the points of the rock discontinuity from a 3D point cloud. A comparison with existing software shows that this method is feasible. This method can provide a reference for rock mechanics, 3D geological modelling and other related fields.

Synchronizing Fireflies

ERIC Educational Resources Information Center

Zhou, Ying; Gall, Walter; Nabb, Karen Mayumi

2006-01-01

"Imagine a tenth of a mile of river front with an unbroken line of trees with fireflies on ever leaf flashing in synchronism. ... Then, if one's imagination is sufficiently vivid, he may form some conception of this amazing spectacle." So wrote the naturalist Hugh Smith. In this article we consider how one might model mathematically the…

Histone Methylation and Epigenetic Silencing in Breast Cancer

DTIC Science & Technology

2010-07-01

bars show relative luciferase expression levels (firefly versus Renilla control) in SKBR3 cells treated with a control non-targeted dsRNA (NT2) and red...luciferase expression levels (firefly versus Renilla control) in SKBR3 cells treated with a control non-targeted dsRNA (NT2) and red bars depict

Improvement in detection of small wildfires

NASA Astrophysics Data System (ADS)

Sleigh, William J.

1991-12-01

Detecting and imaging small wildfires with an Airborne Scanner is done against generally high background levels. The Airborne Scanner System used is a two-channel thermal IR scanner, with one channel selected for imaging the terrain and the other channel sensitive to hotter targets. If a relationship can be determined between the two channels that quantifies the background signal for hotter targets, then an algorithm can be determined that removes the background signal in that channel leaving only the fire signal. The relationship can be determined anywhere between various points in the signal processing of the radiometric data from the radiometric input to the quantized output of the system. As long as only linear operations are performed on the signal, the relationship will only depend on the system gain and offsets within the range of interest. The algorithm can be implemented either by using a look-up table or performing the calculation in the system computer. The current presentation will describe the algorithm, its derivation, and its implementation in the Firefly Wildfire Detection System by means of an off-the-shelf commercial scanner. Improvement over the previous algorithm used and the margin gained for improving the imaging of the terrain will be demonstrated.

Improvement in detection of small wildfires

NASA Technical Reports Server (NTRS)

Sleigh, William J.

1991-01-01

Detecting and imaging small wildfires with an Airborne Scanner is done against generally high background levels. The Airborne Scanner System used is a two-channel thermal IR scanner, with one channel selected for imaging the terrain and the other channel sensitive to hotter targets. If a relationship can be determined between the two channels that quantifies the background signal for hotter targets, then an algorithm can be determined that removes the background signal in that channel leaving only the fire signal. The relationship can be determined anywhere between various points in the signal processing of the radiometric data from the radiometric input to the quantized output of the system. As long as only linear operations are performed on the signal, the relationship will only depend on the system gain and offsets within the range of interest. The algorithm can be implemented either by using a look-up table or performing the calculation in the system computer. The current presentation will describe the algorithm, its derivation, and its implementation in the Firefly Wildfire Detection System by means of an off-the-shelf commercial scanner. Improvement over the previous algorithm used and the margin gained for improving the imaging of the terrain will be demonstrated.

Total evidence phylogeny and the evolution of adult bioluminescence in fireflies (Coleoptera: Lampyridae).

PubMed

Martin, Gavin J; Branham, Marc A; Whiting, Michael F; Bybee, Seth M

2017-02-01

Fireflies are some of the most captivating organisms on the planet. They have a rich history as subjects of scientific study, especially in relation to their bioluminescent behavior. Yet, the phylogenetic relationships of fireflies are still poorly understood. Here, we present the first total evidence approach to reconstruct lampyrid phylogeny using both a molecular matrix from six loci and an extensive morphological matrix. Using this phylogeny we test the hypothesis that adult bioluminescence evolved after the origin of the firefly clade. The ancestral state of adult bioluminescence is recovered as non-bioluminescent with one to six gains and five to ten subsequent losses. The monophyly of the family, as well as the subfamilies is also tested. Ototretinae, Cyphonocerinae, Luciolinae (incl. Pristolycus), Amydetinae, "cheguevarinae" sensu Jeng 2008, and Photurinae are highly supported as monophyletic. With the exception of four taxa, Lampyrinae is also recovered as monophyletic with high support. Based on phylogenetic and morphological data Lamprohiza, Phausis, and Lamprigera are transferred to Lampyridae incertae sedis. Copyright © 2016 Elsevier Inc. All rights reserved.

Crystal structure of native and a mutant of Lampyris turkestanicus luciferase implicate in bioluminescence color shift.

PubMed

Kheirabadi, Mitra; Sharafian, Zohreh; Naderi-Manesh, Hossein; Heineman, Udo; Gohlke, Ulrich; Hosseinkhani, Saman

2013-12-01

Firefly bioluminescence reaction in the presence of Mg(2+), ATP and molecular oxygen is carried out by luciferase. The luciferase structure alterations or modifications of assay conditions determine the bioluminescence color of firefly luciferase. Among different beetle luciferases, Phrixothrix hirtus railroad worm emits either yellow or red bioluminescence color. Sequence alignment analysis shows that the red-emitter luciferase from Phrixothrix hirtus has an additional arginine residue at 353 that is absent in other firefly luciferases. It was reported that insertion of Arg in an important flexible loop350-359 showed changes in bioluminescence color from green to red and the optimum temperature activity was also increased. To explain the color tuning mechanism of firefly luciferase, the structure of native and a mutant (E354R/356R/H431Y) of Lampyris turkestanicus luciferase is determined at 2.7Å and 2.2Å resolutions, respectively. The comparison of structure of both types of Lampyris turkestanicus luciferases reveals that the conformation of this flexible loop is significantly changed by addition of two Arg in this region. Moreover, its surface accessibility is affected considerably and some ionic bonds are made by addition of two positive charge residues. Furthermore, we noticed that the hydrogen bonding pattern of His431 with the flexible loop is changed by replacing this residue with Tyr at this position. Juxtaposition of a flexible loop (residues 351-359) in firefly luciferase and corresponding ionic and hydrogen bonds are essential for color emission. © 2013.

A Firefly Learning Module for Environmental Sustainable Development in Samutsongkhram Province, Thailand

ERIC Educational Resources Information Center

To-Im, Jongdee; Klunklueng, Arunwan

2012-01-01

A firefly learning module for the sustainable development was developed for Thai secondary school students in the study province. A deeper connection between environment, social and economic dimensions, which lies at the core of sustainability, became the key issue for this learning module. Also an important dimension of the module was the…

Dual Luciferase Assay System for Rapid Assessment of Gene Expression in Saccharomyces cerevisiae

PubMed Central

McNabb, David S.; Reed, Robin; Marciniak, Robert A.

2005-01-01

A new reporter system has been developed for quantifying gene expression in the yeast Saccharomyces cerevisiae. The system relies on two different reporter genes, Renilla and firefly luciferase, to evaluate regulated gene expression. The gene encoding Renilla luciferase is fused to a constitutive promoter (PGK1 or SPT15) and integrated into the yeast genome at the CAN1 locus as a control for normalizing the assay. The firefly luciferase gene is fused to the test promoter and integrated into the yeast genome at the ura3 or leu2 locus. The dual luciferase assay is performed by sequentially measuring the firefly and Renilla luciferase activities of the same sample, with the results expressed as the ratio of firefly to Renilla luciferase activity (Fluc/Rluc). The yeast dual luciferase reporter (DLR) was characterized and shown to be very efficient, requiring approximately 1 minute to complete each assay, and has proven to yield data that accurately and reproducibly reflect promoter activity. A series of integrating plasmids were generated that contain either the firefly or Renilla luciferase gene preceded by a multicloning region in two different orientations and the three reading frames to make possible the generation of translational fusions. Additionally, each set of plasmids contains either the URA3 or LEU2 marker for genetic selection in yeast. A series of S288C-based yeast strains, including a two-hybrid strain, were developed to facilitate the use of the yeast DLR assay. This assay can be readily adapted to a high-throughput platform for studies requiring numerous measurements. PMID:16151247

GENERATION OF TWO NOVEL CELL LINES THAT STABLY EXPRESS HAR AND FIREFLY LUCIFERASE GENES FOR ENDOCRINE SCREENING

EPA Science Inventory

Generation of Two Novel Cell Lines that Stably Express hAR and Firefly Luciferase Genes for Endocrine Screening
K.L. Bobseine*1, W.R. Kelce2, P.C. Hartig*1, and L.E. Gray, Jr.1
1USEPA, NHEERL, Reproductive Toxicology Division, RTP, NC, 2Searle, Reproductive Toxicology Divi...

Firefly: an optical lithographic system for the fabrication of holographic security labels

NASA Astrophysics Data System (ADS)

Calderón, Jorge; Rincón, Oscar; Amézquita, Ricardo; Pulido, Iván.; Amézquita, Sebastián.; Bernal, Andrés.; Romero, Luis; Agudelo, Viviana

2016-03-01

This paper introduces Firefly, an optical lithography origination system that has been developed to produce holographic masters of high quality. This mask-less lithography system has a resolution of 418 nm half-pitch, and generates holographic masters with the optical characteristics required for security applications of level 1 (visual verification), level 2 (pocket reader verification) and level 3 (forensic verification). The holographic master constitutes the main core of the manufacturing process of security holographic labels used for the authentication of products and documents worldwide. Additionally, the Firefly is equipped with a software tool that allows for the hologram design from graphic formats stored in bitmaps. The software is capable of generating and configuring basic optical effects such as animation and color, as well as effects of high complexity such as Fresnel lenses, engraves and encrypted images, among others. The Firefly technology gathers together optical lithography, digital image processing and the most advanced control systems, making possible a competitive equipment that challenges the best technologies in the industry of holographic generation around the world. In this paper, a general description of the origination system is provided as well as some examples of its capabilities.

Bifunctional role of leucine 300 of firefly luciferase in structural rigidity.

PubMed

Yousefi, Farzad; Ataei, Farangis; Mortazavi, Mojtaba; Hosseinkhani, Saman

2017-08-01

Firefly luciferase is susceptible to thermal inactivation, thereby its intracellular half-life decreased. Previous reports indicated that L 300 R mutation (LRR mutant) in E 354 R/Arg 356 double mutant (ERR mutant) from Lampyris turkestanicus luciferase has increased its thermal stability and rigidity through induction of some ionic bonds with Asp 270 and 271. Disruption of the deduced ionic bonds in an ultra-rigid mutant of firefly luciferase did not reverse the flexibility of the protein. In this study, we investigated the effects of this residue to find the truth behind an extraordinary increase in thermal stability and rigidity of luciferase after replacement of leucine 300 by arginine based on previous reports. For this purpose, L 300 R, L 300 K and L 300 E mutations were performed to compare the effects of these mutations on the native firefly luciferase. In spite of increase of intrinsic fluorescence of the mutants a slight increase in thermostability and retention of kinetic properties was observed. Based on our results, we can conclude that L 300 R mutation in LRR mutant accompanying with alteration in a flexible loop (352-359) increased thermostability and rigidity of luciferase. Copyright © 2017 Elsevier B.V. All rights reserved.

Luciferin Amides Enable in Vivo Bioluminescence Detection of Endogenous Fatty Acid Amide Hydrolase Activity.

PubMed

Mofford, David M; Adams, Spencer T; Reddy, G S Kiran Kumar; Reddy, Gadarla Randheer; Miller, Stephen C

2015-07-15

Firefly luciferase is homologous to fatty acyl-CoA synthetases. We hypothesized that the firefly luciferase substrate d-luciferin and its analogs are fatty acid mimics that are ideally suited to probe the chemistry of enzymes that release fatty acid products. Here, we synthesized luciferin amides and found that these molecules are hydrolyzed to substrates for firefly luciferase by the enzyme fatty acid amide hydrolase (FAAH). In the presence of luciferase, these molecules enable highly sensitive and selective bioluminescent detection of FAAH activity in vitro, in live cells, and in vivo. The potency and tissue distribution of FAAH inhibitors can be imaged in live mice, and luciferin amides serve as exemplary reagents for greatly improved bioluminescence imaging in FAAH-expressing tissues such as the brain.

Luciferin Amides Enable in Vivo Bioluminescence Detection of Endogenous Fatty Acid Amide Hydrolase Activity

PubMed Central

2015-01-01

Firefly luciferase is homologous to fatty acyl-CoA synthetases. We hypothesized that the firefly luciferase substrate d-luciferin and its analogs are fatty acid mimics that are ideally suited to probe the chemistry of enzymes that release fatty acid products. Here, we synthesized luciferin amides and found that these molecules are hydrolyzed to substrates for firefly luciferase by the enzyme fatty acid amide hydrolase (FAAH). In the presence of luciferase, these molecules enable highly sensitive and selective bioluminescent detection of FAAH activity in vitro, in live cells, and in vivo. The potency and tissue distribution of FAAH inhibitors can be imaged in live mice, and luciferin amides serve as exemplary reagents for greatly improved bioluminescence imaging in FAAH-expressing tissues such as the brain. PMID:26120870

Two techniques for eliminating luminol interference material and flow system configurations for luminol and firefly luciferase systems

NASA Technical Reports Server (NTRS)

Thomas, R. R.

1976-01-01

Two methods for eliminating luminol interference materials are described. One method eliminates interference from organic material by pre-reacting a sample with dilute hydrogen peroxide. The reaction rate resolution method for eliminating inorganic forms of interference is also described. The combination of the two methods makes the luminol system more specific for bacteria. Flow system designs for both the firefly luciferase and luminol bacteria detection systems are described. The firefly luciferase flow system incorporating nitric acid extraction and optimal dilutions has a functional sensitivity of 3 x 100,000 E. coli/ml. The luminol flow system incorporates the hydrogen peroxide pretreatment and the reaction rate resolution techniques for eliminating interference. The functional sensitivity of the luminol flow system is 1 x 10,000 E. coli/ml.

Novel multistep BRET-FRET energy transfer using nanoconjugates of firefly proteins, quantum dots, and red fluorescent proteins

NASA Astrophysics Data System (ADS)

Alam, Rabeka; Zylstra, Joshua; Fontaine, Danielle M.; Branchini, Bruce R.; Maye, Mathew M.

2013-05-01

Sequential bioluminescence resonance energy transfer (BRET) and fluorescence resonance energy transfer (FRET) from firefly luciferase to red fluorescent proteins using quantum dot or rod acceptor/donor linkers is described. The effect of morphology and tuned optical properties on the efficiency of this unique BRET-FRET system was evaluated.Sequential bioluminescence resonance energy transfer (BRET) and fluorescence resonance energy transfer (FRET) from firefly luciferase to red fluorescent proteins using quantum dot or rod acceptor/donor linkers is described. The effect of morphology and tuned optical properties on the efficiency of this unique BRET-FRET system was evaluated. Electronic supplementary information (ESI) available: Experimental details, Fig. S1 and Table S1-S4. See DOI: 10.1039/c3nr01842c

Calculation of a double reactive azeotrope using stochastic optimization approaches

NASA Astrophysics Data System (ADS)

Mendes Platt, Gustavo; Pinheiro Domingos, Roberto; Oliveira de Andrade, Matheus

2013-02-01

An homogeneous reactive azeotrope is a thermodynamic coexistence condition of two phases under chemical and phase equilibrium, where compositions of both phases (in the Ung-Doherty sense) are equal. This kind of nonlinear phenomenon arises from real world situations and has applications in chemical and petrochemical industries. The modeling of reactive azeotrope calculation is represented by a nonlinear algebraic system with phase equilibrium, chemical equilibrium and azeotropy equations. This nonlinear system can exhibit more than one solution, corresponding to a double reactive azeotrope. The robust calculation of reactive azeotropes can be conducted by several approaches, such as interval-Newton/generalized bisection algorithms and hybrid stochastic-deterministic frameworks. In this paper, we investigate the numerical aspects of the calculation of reactive azeotropes using two metaheuristics: the Luus-Jaakola adaptive random search and the Firefly algorithm. Moreover, we present results for a system (with industrial interest) with more than one azeotrope, the system isobutene/methanol/methyl-tert-butyl-ether (MTBE). We present convergence patterns for both algorithms, illustrating - in a bidimensional subdomain - the identification of reactive azeotropes. A strategy for calculation of multiple roots in nonlinear systems is also applied. The results indicate that both algorithms are suitable and robust when applied to reactive azeotrope calculations for this "challenging" nonlinear system.

Integrated Optoelectronic Networks for Application-Driven Multicore Computing

DTIC Science & Technology

2017-05-08

hybrid photonic torus, the all-optical Corona crossbar, and the hybrid hierarchical Firefly crossbar. • The key challenges for waveguide photonics...improves SXR but with relatively higher EDP overhead. Our evaluation results indicate that the encoding schemes improve worst-case-SXR in Corona and...photonic crossbar architectures ( Corona and Firefly) indicate that our approach improves worst-case signal-to-noise ratio (SNR) by up to 51.7

GENERATION OF TWO STABLE CELL LINES THAT EXPRESS HER-ALPHA OR HER-ALPHA AND -BETA AND FIREFLY LUCIFERASE GENES FOR ENDOCRINE SCREENING

EPA Science Inventory

Generation of Two Stable Cell Lines that Express hERa or
hERa and b and Firefly Luciferase Genes for Endocrine Screening

K.L. Bobseine*1, W.R. Kelce2, P.C. Hartig*1, and L.E. Gray, Jr.1

1USEPA, NHEERL, Reproductive Toxicology Division, RTP, NC, 2Searle, Reprod...

Regulation of AR and (Beta)-Catenin Signaling by Pin 1 in Prostate Cancer

DTIC Science & Technology

2005-10-01

Renilla luciferase activities were determined using a dual-luciferase reporter assay kit (Promega, Madison, WI), and Renilla activities were not...consistently affected by any of the cotransfected vectors. The firefly luciferase was divided by the control Renilla luciferase and the results, given as...transfected with pTopflash (50 ng) and CMV- Renilla (2.5 ng) reporter plasmids. Firefly versus Renilla luciferase activities were determined and

Modulation of Beta-catenin Activity With PKD1 Prostate Cancer

DTIC Science & Technology

2009-04-01

mutated site as a negative control (FOPFlash) with pRL-TK ( Renilla luciferase) in C4-2- PKD1-GFP cells activated with Bryostatin 1 or DMSO. The...firefly and Renilla luciferase activities were measured with the Dual-Luciferase Reporter (DLR) Assay System. After normalizing the firefly luciferase...activity to that of Renilla luciferase, the FOPFlash reporter plasmid luciferase values were subtracted from the normalized values obtained with the

MicroRNA Inhibitors as Anticancer Therapies

DTIC Science & Technology

2007-08-17

Promoter activity was determined by co-transfection of the pGL3 promoter reporter (400 ng/well) with pRLSV40 ( Renilla luciferase, Promega)(100 ng/well) into...performed in triplicate and standard deviations calculated. Activitywas defined as Firefly/ Renilla ratio, normalized to control vector transfection. For...was defined as Firefly/ Renilla ratio normalized to activity in the absence of transfected E2F1. 5-RACE Mapping of Transcript—HEK-293 cells were tran

The Role of AHR in Breast Cancer Development

DTIC Science & Technology

2005-07-01

Carlsbad, CA) was used according to the manufacturer’s instructions to transfect cells. The renilla luciferase vectorphRL-TK (0.5 [tg/well) was co...the firefly and renilla signals. Briefly, cells were lysed in equal volumes of cell lysis buffer (Promega) and RPMI for 20 min, transferred to a 96...well white wall plate, and analyzed using a Reporter Luminometer (Promega). The renilla signal was read after quenching the firefly output, thus

Near infrared bioluminescence resonance energy transfer from firefly luciferase—quantum dot bionanoconjugates

NASA Astrophysics Data System (ADS)

Alam, Rabeka; Karam, Liliana M.; Doane, Tennyson L.; Zylstra, Joshua; Fontaine, Danielle M.; Branchini, Bruce R.; Maye, Mathew M.

2014-12-01

The bioluminescence resonance energy transfer (BRET) between firefly luciferase enzymes and semiconductive quantum dots (QDs) with near infrared emission is described. The QD were phase transferred to aqueous buffers using a histidine mediated phase transfer route, and incubated with a hexahistidine tagged, green emitting variant of firefly luciferase from Photinus pyralis (PPyGRTS). The PPyGRTS were bound to the QD interface via the hexahistidine tag, which effectively displaces the histidine layer and binds directly to the QD interfaces, allowing for short donor-acceptor distances (˜5.5 nm). Due to this, high BRET efficiency ratios of ˜5 were obtained. These PPyGRTS-QD bio-nano conjugates were characterized by transmission electron microscopy, thermal gravimetric analysis, Fourier transform infrared spectroscopy and BRET emission studies. The final optimized conjugate was easily observable by night vision imaging, demonstrating the potential of these materials in imaging and signaling/sensing applications.

Firefly: A HOT camera core for thermal imagers with enhanced functionality

NASA Astrophysics Data System (ADS)

Pillans, Luke; Harmer, Jack; Edwards, Tim

2015-06-01

Raising the operating temperature of mercury cadmium telluride infrared detectors from 80K to above 160K creates new applications for high performance infrared imagers by vastly reducing the size, weight and power consumption of the integrated cryogenic cooler. Realizing the benefits of Higher Operating Temperature (HOT) requires a new kind of infrared camera core with the flexibility to address emerging applications in handheld, weapon mounted and UAV markets. This paper discusses the Firefly core developed to address these needs by Selex ES in Southampton UK. Firefly represents a fundamental redesign of the infrared signal chain reducing power consumption and providing compatibility with low cost, low power Commercial Off-The-Shelf (COTS) computing technology. This paper describes key innovations in this signal chain: a ROIC purpose built to minimize power consumption in the proximity electronics, GPU based image processing of infrared video, and a software customisable infrared core which can communicate wirelessly with other Battlespace systems.

Phase diagram for the Winfree model of coupled nonlinear oscillators.

PubMed

Ariaratnam, J T; Strogatz, S H

2001-05-07

In 1967 Winfree proposed a mean-field model for the spontaneous synchronization of chorusing crickets, flashing fireflies, circadian pacemaker cells, or other large populations of biological oscillators. Here we give the first bifurcation analysis of the model, for a tractable special case. The system displays rich collective dynamics as a function of the coupling strength and the spread of natural frequencies. Besides incoherence, frequency locking, and oscillator death, there exist hybrid solutions that combine two or more of these states. We present the phase diagram and derive several of the stability boundaries analytically.

Phase Diagram for the Winfree Model of Coupled Nonlinear Oscillators

NASA Astrophysics Data System (ADS)

Ariaratnam, Joel T.; Strogatz, Steven H.

2001-05-01

In 1967 Winfree proposed a mean-field model for the spontaneous synchronization of chorusing crickets, flashing fireflies, circadian pacemaker cells, or other large populations of biological oscillators. Here we give the first bifurcation analysis of the model, for a tractable special case. The system displays rich collective dynamics as a function of the coupling strength and the spread of natural frequencies. Besides incoherence, frequency locking, and oscillator death, there exist hybrid solutions that combine two or more of these states. We present the phase diagram and derive several of the stability boundaries analytically.

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.

Identification of Small Molecules Targeting the Posttranscriptional Control of ERG Expression

DTIC Science & Technology

2012-10-01

ied. To establish a cell line expressing lucife rase-ERG fusion protein, the vector along pRL-CMV-Rluc expressing Renilla luciferase gene was...expanded, and examined for the e xpression of t wo different luciferases. A clone expressing both Firefly luciferase and Renilla luciferase was selected...treated with the individual chemical at 10 μM for 24 h. The dual luciferase activities were measured. The ratio of Firefly to Renilla lu ciferase

A novel firefly luciferase biosensor enhances the detection of apoptosis induced by ESAT-6 family proteins of Mycobacterium tuberculosis

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

Shi, Junwei; Zhang, Huan; Fang, Liurong

Highlights: • We developed a novel firefly luciferase based biosensor to detect apoptosis. • The novel biosensor 233-DnaE-DEVDG was reliable, sensitive and convenient. • 233-DnaE-DEVDG faithfully indicated ESAT-6 family proteins of Mycobacterium tuberculosis induced apoptosis. • EsxA, esxT and esxL in ESAT-6 family proteins induced apoptosis. • Activation of nuclear factor-κB (NF-κB) participated in esxT-induced apoptosis. - Abstract: The activation of caspase-3 is a key surrogate marker for detecting apoptosis. To quantitate caspase-3 activity, we constructed a biosensor comprising a recombinant firefly luciferase containing a caspase-3 cleavage site. When apoptosis was induced, caspase-3 cleavage of the biosensor activated firefly luciferasemore » by a factor greater than 25. The assay conveniently detected apoptosis in real time, indicating that it will facilitate drug discovery. We screened ESAT-6 family proteins of Mycobacterium tuberculosis and found that esxA, esxT and esxL induced apoptosis. Further, activation of nuclear factor-κB (NF-κB) and the NF-κB-regulated genes encoding tumor necrosis factor-α (TNF-α) and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) participated in esxT-induced apoptosis. We conclude that this assay is useful for high-throughput screening to identify and characterize proteins and drugs that regulate apoptosis.« less

FIREFLY (Fitting IteRativEly For Likelihood analYsis): a full spectral fitting code

NASA Astrophysics Data System (ADS)

Wilkinson, David M.; Maraston, Claudia; Goddard, Daniel; Thomas, Daniel; Parikh, Taniya

2017-12-01

We present a new spectral fitting code, FIREFLY, for deriving the stellar population properties of stellar systems. FIREFLY is a chi-squared minimization fitting code that fits combinations of single-burst stellar population models to spectroscopic data, following an iterative best-fitting process controlled by the Bayesian information criterion. No priors are applied, rather all solutions within a statistical cut are retained with their weight. Moreover, no additive or multiplicative polynomials are employed to adjust the spectral shape. This fitting freedom is envisaged in order to map out the effect of intrinsic spectral energy distribution degeneracies, such as age, metallicity, dust reddening on galaxy properties, and to quantify the effect of varying input model components on such properties. Dust attenuation is included using a new procedure, which was tested on Integral Field Spectroscopic data in a previous paper. The fitting method is extensively tested with a comprehensive suite of mock galaxies, real galaxies from the Sloan Digital Sky Survey and Milky Way globular clusters. We also assess the robustness of the derived properties as a function of signal-to-noise ratio (S/N) and adopted wavelength range. We show that FIREFLY is able to recover age, metallicity, stellar mass, and even the star formation history remarkably well down to an S/N ∼ 5, for moderately dusty systems. Code and results are publicly available.1

The influence of the loop between residues 223-235 in beetle luciferase bioluminescence spectra: a solvent gate for the active site of pH-sensitive luciferases.

PubMed

Viviani, Vadim R; Silva Neto, Antonio J; Arnoldi, Frederico G C; Barbosa, João A R G; Ohmiya, Yoshihiro

2008-01-01

Beetle luciferases emit a wide range of bioluminescence colors, ranging from green to red. Firefly luciferases can shift the spectrum to red in response to pH and temperature changes, whereas click beetle and railroadworm luciferases do not. Despite many studies on firefly luciferases, the origin of pH-sensitivity is far from being understood. Through comparative site-directed mutagenesis and modeling studies, using the pH-sensitive luciferases (Macrolampis and Cratomorphus distinctus fireflies) and the pH-insensitive luciferases (Pyrearinus termitilluminans, Phrixotrix viviani and Phrixotrix hirtus) cloned by our group, here we show that substitutions dramatically affecting bioluminescence colors in both groups of luciferases are clustered in the loop between residues 223-235 (Photinus pyralis sequence). The substitutions at positions 227, 228 and 229 (P. pyralis sequence) cause dramatic redshift and temporal shift in both groups of luciferases, indicating their involvement in labile interactions. Modeling studies showed that the residues Y227 and N229 are buried in the protein core, fixing the loop to other structural elements participating at the bottom of the luciferin binding site. Changes in pH and temperature (in firefly luciferases), as well as point mutations in this loop, may disrupt the interactions of these structural elements exposing the active site and modulating bioluminescence colors.

Different Types of Luciferase Reporters Show Distinct Susceptibility to T3-Evoked Downregulation.

PubMed

Kollár, Anna; Kvárta-Papp, Zsuzsanna; Egri, Péter; Gereben, Balázs

2016-01-01

The firefly luciferase reporter protein is a crucial tool for studies targeting a broad range of biological questions. Importantly, luciferase assays are also widely used to explore mechanisms underlying thyroid hormone dependent regulation of gene expression. However, it was demonstrated that the firefly luciferase reporter is subject to triiodothyronine (T3)-evoked, promoter independent downregulation that is mediated by the thyroid hormone receptor. Since this effect can interfere with readout accuracy, the study aimed to find luciferase reporters that are not susceptible to this phenomenon. Luciferase reporter constructs were generated under the control of a minimal thymidine kinase (TK) promoter and transiently transfected into JEG-3 cells to test their activity upon T3 treatment. Activity of the TK-(dCpG)Luc encoding a synthetic (dCpG)Luciferase and TK-NanoLuc expressing the NanoLuc reporter was not significantly changed by T3 treatment while the firefly luciferase control was suppressed by ∼2.6-fold. T3 also downregulated the activity of Renilla luciferase by ∼30%. Novel types of luciferase reporters, especially the synthetic (dCpG)Luciferase, can be more accurate to study T3-regulated gene expression than the classical firefly luciferase reporter. Renilla luciferase, a popular transfection control of dual luciferase assays, should be used with caution in conditions with T3 treatment.

An integrated model of water resources optimization allocation based on projection pursuit model - Grey wolf optimization method in a transboundary river basin

NASA Astrophysics Data System (ADS)

Yu, Sen; Lu, Hongwei

2018-04-01

Under the effects of global change, water crisis ranks as the top global risk in the future decade, and water conflict in transboundary river basins as well as the geostrategic competition led by it is most concerned. This study presents an innovative integrated PPMGWO model of water resources optimization allocation in a transboundary river basin, which is integrated through the projection pursuit model (PPM) and Grey wolf optimization (GWO) method. This study uses the Songhua River basin and 25 control units as examples, adopting the PPMGWO model proposed in this study to allocate the water quantity. Using water consumption in all control units in the Songhua River basin in 2015 as reference to compare with optimization allocation results of firefly algorithm (FA) and Particle Swarm Optimization (PSO) algorithms as well as the PPMGWO model, results indicate that the average difference between corresponding allocation results and reference values are 0.195 bil m3, 0.151 bil m3, and 0.085 bil m3, respectively. Obviously, the average difference of the PPMGWO model is the lowest and its optimization allocation result is closer to reality, which further confirms the reasonability, feasibility, and accuracy of the PPMGWO model. And then the PPMGWO model is adopted to simulate allocation of available water quantity in Songhua River basin in 2018, 2020, and 2030. The simulation results show water quantity which could be allocated in all controls demonstrates an overall increasing trend with reasonable and equal exploitation and utilization of water resources in the Songhua River basin in future. In addition, this study has a certain reference value and application meaning to comprehensive management and water resources allocation in other transboundary river basins.

Regulation of AR and (beta)-Catenin Signaling by Pin 1 in Prostate Cancer

DTIC Science & Technology

2006-10-01

hrs. cells were harvested for Luciferase reporter Assay. C, CV-1 cells were transfected with Renilla (2.5ng), G5-Luc (10ng), pBIND-LBD (50ng), pACT-AR...stimulation, cells were cultured in 5 to 10% CDS-FBS. Firefly and internal control Renilla lucif- erase activities were determined using a dual luciferase...reporter assay kit (Pro- mega, Madison, WI), and Renilla activities were not consistently affected by any of the cotransfected vectors. The firefly

A Firefly-Inspired Method for Protein Structure Prediction in Lattice Models

PubMed Central

Maher, Brian; Albrecht, Andreas A.; Loomes, Martin; Yang, Xin-She; Steinhöfel, Kathleen

2014-01-01

We introduce a Firefly-inspired algorithmic approach for protein structure prediction over two different lattice models in three-dimensional space. In particular, we consider three-dimensional cubic and three-dimensional face-centred-cubic (FCC) lattices. The underlying energy models are the Hydrophobic-Polar (H-P) model, the Miyazawa–Jernigan (M-J) model and a related matrix model. The implementation of our approach is tested on ten H-P benchmark problems of a length of 48 and ten M-J benchmark problems of a length ranging from 48 until 61. The key complexity parameter we investigate is the total number of objective function evaluations required to achieve the optimum energy values for the H-P model or competitive results in comparison to published values for the M-J model. For H-P instances and cubic lattices, where data for comparison are available, we obtain an average speed-up over eight instances of 2.1, leaving out two extreme values (otherwise, 8.8). For six M-J instances, data for comparison are available for cubic lattices and runs with a population size of 100, where, a priori, the minimum free energy is a termination criterion. The average speed-up over four instances is 1.2 (leaving out two extreme values, otherwise 1.1), which is achieved for a population size of only eight instances. The present study is a test case with initial results for ad hoc parameter settings, with the aim of justifying future research on larger instances within lattice model settings, eventually leading to the ultimate goal of implementations for off-lattice models. PMID:24970205

A firefly-inspired method for protein structure prediction in lattice models.

PubMed

Maher, Brian; Albrecht, Andreas A; Loomes, Martin; Yang, Xin-She; Steinhöfel, Kathleen

2014-01-07

We introduce a Firefly-inspired algorithmic approach for protein structure prediction over two different lattice models in three-dimensional space. In particular, we consider three-dimensional cubic and three-dimensional face-centred-cubic (FCC) lattices. The underlying energy models are the Hydrophobic-Polar (H-P) model, the Miyazawa-Jernigan (M-J) model and a related matrix model. The implementation of our approach is tested on ten H-P benchmark problems of a length of 48 and ten M-J benchmark problems of a length ranging from 48 until 61. The key complexity parameter we investigate is the total number of objective function evaluations required to achieve the optimum energy values for the H-P model or competitive results in comparison to published values for the M-J model. For H-P instances and cubic lattices, where data for comparison are available, we obtain an average speed-up over eight instances of 2.1, leaving out two extreme values (otherwise, 8.8). For six M-J instances, data for comparison are available for cubic lattices and runs with a population size of 100, where, a priori, the minimum free energy is a termination criterion. The average speed-up over four instances is 1.2 (leaving out two extreme values, otherwise 1.1), which is achieved for a population size of only eight instances. The present study is a test case with initial results for ad hoc parameter settings, with the aim of justifying future research on larger instances within lattice model settings, eventually leading to the ultimate goal of implementations for off-lattice models.

Effects of Epigenetic Modulation on Reporter Gene Expression: Implications for Stem Cell Imaging

PubMed Central

Krishnan, Manickam; Park, Jinha M.; Cao, Feng; Wang, Dongxu; Paulmurugan, Ramasay; Tseng, Jeffrey R.; Gonzalgo, Mark L.; Gambhir, Sanjiv S.; Wu, Joseph C.

2013-01-01

Tracking stem cell localization, survival, differentiation, and proliferation following transplantation in living subjects is essential for understanding stem cell biology and physiology. In this study, we investigated the long-term stability of reporter gene expression in an embryonic rat cardiomyoblast cell line and the role of epigenetic modulation on reversing reporter gene silencing. Cells were stably transfected with plasmids carrying cytomegalovirus promoter driving firefly luciferase reporter gene (CMV-Fluc) and passaged repeatedly for 3–8 months. Within the highest expressor clone, the firefly luciferase activity decreased progressively from passage-1 (843±28) to passage-20 (250±10) to passage-40 (44±3) to passage-60 (3±1 RLU/µg) (P<0.05 vs. passage-1). Firefly luciferase activity was maximally rescued by treatment with 5-azacytidine (DNA methyltransferase inhibitor) compared to trichostatin A (histone deacetylase inhibitor) and retinoic acid (transcriptional activator) (P<0.05). Increasing dosages of 5-azacytidine treatment led to higher levels of firefly luciferase mRNA (RT-PCR) and protein (Western blots) and inversely lower levels of methylation in the CMV promoter (DNA nucleotide sequence). These in vitro results were extended to in vivo bioluminescence imaging (BLI) of cell transplant in living animals. Cells treated with 5-azacytidine were monitored for 2 weeks compared to 1 week for untreated cells (P<0.05). These findings should have important implications for reporter gene-based imaging of stem cell transplantation. PMID:16246867

Brominated Luciferins Are Versatile Bioluminescent Probes

DOE PAGES

Steinhardt, Rachel C.; Rathbun, Colin M.; Krull, Brandon T.; ...

2016-12-08

Here, we report a set of brominated luciferins for bioluminescence imaging. These regioisomeric scaffolds were accessed by using a common synthetic route. All analogues produced light with firefly luciferase, although varying levels of emission were observed. Differences in photon output were analyzed by computation and photophysical measurements. The brightest brominated luciferin was further evaluated in cell and animal models. At low doses, the analogue outperformed the native substrate in cells. The remaining luciferins, although weak emitters with firefly luciferase, were inherently capable of light production and thus potential substrates for orthogonal mutant enzymes.

AR-NcoR Interaction as a Therapeutic Target for Prostate Cancer Prevention and Treatment

DTIC Science & Technology

2005-10-01

mutant AR, VP16-NCoRc, ARE4-luciferase reporter, and control pRL-CMV ( Renilla ) reporter. They were then treated for 24 hrs with 10 nM DHT, 10 nM RU486...or no hormone. Firefly versus Renilla luciferase activities were measure from triplicate samples. Relative light units (RLU) reflect normalized...firefly/ Renilla (+SD). NCoR binding to the RU486 liganded AR is mediated by the C-terminal N1 CoRNR box in NCoR. As NCoR deletion mutants indicated

GAS-611 firefly in zero gravity

NASA Technical Reports Server (NTRS)

Williams, Tony

1988-01-01

The Get Away Special 611 (GAS-611) project will carry a small, self-contained biological experiment into a microgravity environment for a period of 120 hours. The payload will be a colony of Lampyridae (fireflies). The ability of this beetle to produce light with an efficiency of 98 pct will be evaluated in the micro-G environment. The chemical process that occurs could be assisted by the earth's gravitational pull and the very complex tracheae system found within this species of beetle. The effects of microgravity on mating and beetle larvae will also be studied.

Quantum/molecular mechanics study of firefly bioluminescence on luciferase oxidative conformation

NASA Astrophysics Data System (ADS)

Pinto da Silva, Luís; Esteves da Silva, Joaquim C. G.

2014-07-01

This is the first report of a computational study of the color tuning mechanism of firefly bioluminescence, using the oxidative conformation of luciferase. The results of these calculations demonstrated that the electrostatic field generated by luciferase is fundamental both for the emission shift and efficiency. Further calculations indicated that a shift in emission is achieved by modulating the energy, at different degrees, of the emissive and ground states. These differences in energy modulation will then lead to changes in the energy gap between the states.

Preclinical Evaluation of Robotic-Assisted Sentinel Lymph Node Fluorescence Imaging

PubMed Central

Liss, Michael A.; Farshchi-Heydari, Salman; Qin, Zhengtao; Hickey, Sean A.; Hall, David J.; Kane, Christopher J.; Vera, David R.

2015-01-01

An ideal substance to provide convenient and accurate targeting for sentinel lymph node (SLN) mapping during robotic-assisted surgery has yet to be found. We used an animal model to determine the ability of the FireFly camera system to detect fluorescent SLNs after administration of a dual-labeled molecular imaging agent. Methods We injected the footpads of New Zealand White rabbits with 1.7 or 8.4 nmol of tilmanocept labeled with 99mTc and a near-infrared fluorophore, IRDye800CW. One and 36 h after injection, popliteal lymph nodes, representing the SLNs, were dissected with the assistance of the FireFly camera system, a fluorescence-capable endoscopic imaging system. After excision of the paraaortic lymph nodes, which represented non-SLNs, we assayed all lymph nodes for radioactivity and fluorescence intensity. Results Fluorescence within all popliteal lymph nodes was easily detected by the FireFly camera system. Fluorescence within the lymph channel could be imaged during the 1-h studies. When compared with the paraaortic lymph nodes, the popliteal lymph nodes retain greater than 95% of the radioactivity at both 1 and 36 h after injection. At both doses (1.7 and 8.4 nmol), the popliteal nodes had higher (P < 0.050) optical fluorescence intensity than the paraaortic nodes at the 1- and 36-h time points. Conclusion The FireFly camera system can easily detect tilmanocept labeled with a near-infrared fluorophore at least 36 h after administration. This ability will permit image acquisition and subsequent verification of fluorescence-labeled SLNs during robotic-assisted surgery. PMID:25024425

Preclinical evaluation of robotic-assisted sentinel lymph node fluorescence imaging.

PubMed

Liss, Michael A; Farshchi-Heydari, Salman; Qin, Zhengtao; Hickey, Sean A; Hall, David J; Kane, Christopher J; Vera, David R

2014-09-01

An ideal substance to provide convenient and accurate targeting for sentinel lymph node (SLN) mapping during robotic-assisted surgery has yet to be found. We used an animal model to determine the ability of the FireFly camera system to detect fluorescent SLNs after administration of a dual-labeled molecular imaging agent. We injected the footpads of New Zealand White rabbits with 1.7 or 8.4 nmol of tilmanocept labeled with (99m)Tc and a near-infrared fluorophore, IRDye800CW. One and 36 h after injection, popliteal lymph nodes, representing the SLNs, were dissected with the assistance of the FireFly camera system, a fluorescence-capable endoscopic imaging system. After excision of the paraaortic lymph nodes, which represented non-SLNs, we assayed all lymph nodes for radioactivity and fluorescence intensity. Fluorescence within all popliteal lymph nodes was easily detected by the FireFly camera system. Fluorescence within the lymph channel could be imaged during the 1-h studies. When compared with the paraaortic lymph nodes, the popliteal lymph nodes retain greater than 95% of the radioactivity at both 1 and 36 h after injection. At both doses (1.7 and 8.4 nmol), the popliteal nodes had higher (P < 0.050) optical fluorescence intensity than the paraaortic nodes at the 1- and 36-h time points. The FireFly camera system can easily detect tilmanocept labeled with a near-infrared fluorophore at least 36 h after administration. This ability will permit image acquisition and subsequent verification of fluorescence-labeled SLNs during robotic-assisted surgery. © 2014 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

A Luciferase Reporter Gene System for High-Throughput Screening of γ-Globin Gene Activators.

PubMed

Xie, Wensheng; Silvers, Robert; Ouellette, Michael; Wu, Zining; Lu, Quinn; Li, Hu; Gallagher, Kathleen; Johnson, Kathy; Montoute, Monica

2016-01-01

Luciferase reporter gene assays have long been used for drug discovery due to their high sensitivity and robust signal. A dual reporter gene system contains a gene of interest and a control gene to monitor non-specific effects on gene expression. In our dual luciferase reporter gene system, a synthetic promoter of γ-globin gene was constructed immediately upstream of the firefly luciferase gene, followed downstream by a synthetic β-globin gene promoter in front of the Renilla luciferase gene. A stable cell line with the dual reporter gene was cloned and used for all assay development and HTS work. Due to the low activity of the control Renilla luciferase, only the firefly luciferase activity was further optimized for HTS. Several critical factors, such as cell density, serum concentration, and miniaturization, were optimized using tool compounds to achieve maximum robustness and sensitivity. Using the optimized reporter assay, the HTS campaign was successfully completed and approximately 1000 hits were identified. In this chapter, we also describe strategies to triage hits that non-specifically interfere with firefly luciferase.

Ultrawidefield microscope for high-speed fluorescence imaging and targeted optogenetic stimulation.

PubMed

Werley, Christopher A; Chien, Miao-Ping; Cohen, Adam E

2017-12-01

The rapid increase in the number and quality of fluorescent reporters and optogenetic actuators has yielded a powerful set of tools for recording and controlling cellular state and function. To achieve the full benefit of these tools requires improved optical systems with high light collection efficiency, high spatial and temporal resolution, and patterned optical stimulation, in a wide field of view (FOV). Here we describe our 'Firefly' microscope, which achieves these goals in a Ø6 mm FOV. The Firefly optical system is optimized for simultaneous photostimulation and fluorescence imaging in cultured cells. All but one of the optical elements are commercially available, yet the microscope achieves 10-fold higher light collection efficiency at its design magnification than the comparable commercially available microscope using the same objective. The Firefly microscope enables all-optical electrophysiology ('Optopatch') in cultured neurons with a throughput and information content unmatched by other neuronal phenotyping systems. This capability opens possibilities in disease modeling and phenotypic drug screening. We also demonstrate applications of the system to voltage and calcium recordings in human induced pluripotent stem cell derived cardiomyocytes.

The evolution of adult light emission color in North American fireflies

PubMed Central

Hall, David W.; Sander, Sarah E.; Pallansch, Jennifer C.; Stanger-Hall, Kathrin F.

2016-01-01

Firefly species (Lampyridae) vary in the color of their adult bioluminescence. It has been hypothesized that color is selected to enhance detection by conspecifics. One mechanism to improve visibility of the signal is to increase contrast against ambient light. High contrast implies that fireflies active early in the evening will emit yellower luminescence to contrast against ambient light reflected from green vegetation, especially in habitats with high vegetation cover. Another mechanism to improve visibility is to use reflection off the background to enhance the light signal. Reflectance predicts that sedentary females will produce greener light to maximize reflection off the green vegetation on which they signal. To test these predictions, we recorded over 7500 light emission spectra and determined peak emission wavelength for 675 males, representing 24 species, at 57 field sites across the Eastern United States. We found support for both hypotheses: males active early in more vegetated habitats produced yellower flashes in comparison to later-active males with greener flashes. Further, in 2 of the 8 species with female data, female light emissions were significantly greener as compared to males. PMID:27412777

Adenosine triphosphate (ATP) as a possible indicator of extraterrestrial biology

NASA Technical Reports Server (NTRS)

Chappelle, E. W.; Picciolo, G. L.

1974-01-01

The ubiquity of adenosine triphosphate (ATP) in terrestrial organisms provides the basis for proposing the assay of this vital metabolic intermediate for detecting extraterrestrial biological activity. If an organic carbon chemistry is present on the planets, the occurrence of ATP is possible either from biosynthetic or purely chemical reactions. However, ATP's relative complexity minimizes the probability of abiogenic synthesis. A sensitive technique for the quantitative detection of ATP was developed using the firefly bioluminescent reaction. The procedure was used successfully for the determination of the ATP content of soil and bacteria. This technique is also being investigated from the standpoint of its application in clinical medicine.

Robotic Low Ligation of the Inferior Mesenteric Artery for Rectal Cancer Using the Firefly Technique.

PubMed

Bae, Sung Uk; Min, Byung Soh; Kim, Nam Kyu

2015-07-01

By integrating intraoperative near infrared fluorescence imaging into a robotic system, surgeons can identify the vascular anatomy in real-time with the technical advantages of robotics that is useful for meticulous lymphovascular dissection. Herein, we report our initial experience of robotic low ligation of the inferior mesenteric artery (IMA) with real-time identification of the vascular system for rectal cancer using the Firefly technique. The study group included 11 patients who underwent a robotic total mesorectal excision with preservation of the left colic artery for rectal cancer using the Firefly technique between July 2013 and December 2013. The procedures included five low anterior resections and six ultra-low anterior resections with loop ileostomy. The median total operation time was 327 min (226-490). The low ligation time was 10 min (6-20), and the time interval between indocyanine green injection and division of the sigmoid artery was 5 min (2-8). The estimated blood loss was 200 mL (100-500). The median time to soft diet was 4 days (4-5), and the median length of stay was 7 days (5-9). Three patients developed postoperative complications; one patients developed anal stricture, one developed ileus, and one developed non-complicated intraabdominal fluid collection. The median total number of lymph nodes harvested was 17 (9-29). Robotic low ligation of the IMA with real-time identification of the vascular system for rectal cancer using the Firefly technique is safe and feasible. This technique can allow for precise lymph node dissection along the IMA and facilitate the identification of the left colic branch of the IMA.

Reporter enzyme inhibitor study to aid assembly of orthogonal reporter gene assays.

PubMed

Ho, Pei-i; Yue, Kimberley; Pandey, Pramod; Breault, Lyne; Harbinski, Fred; McBride, Aaron J; Webb, Brian; Narahari, Janaki; Karassina, Natasha; Wood, Keith V; Hill, Adam; Auld, Douglas S

2013-05-17

Reporter gene assays (RGAs) are commonly used to measure biological pathway modulation by small molecules. Understanding how such compounds interact with the reporter enzyme is critical to accurately interpret RGA results. To improve our understanding of reporter enzymes and to develop optimal RGA systems, we investigated eight reporter enzymes differing in brightness, emission spectrum, stability, and substrate requirements. These included common reporter enzymes such as firefly luciferase (Photinus pyralis), Renilla reniformis luciferase, and β-lactamase, as well as mutated forms of R. reniformis luciferase emitting either blue- or green-shifted luminescence, a red-light emitting form of Luciola cruciata firefly luciferase, a mutated form of Gaussia princeps luciferase, and a proprietary luciferase termed "NanoLuc" derived from the luminescent sea shrimp Oplophorus gracilirostris. To determine hit rates and structure-activity relationships, we screened a collection of 42,460 PubChem compounds at 10 μM using purified enzyme preparations. We then compared hit rates and chemotypes of actives for each enzyme. The hit rates ranged from <0.1% for β-lactamase to as high as 10% for mutated forms of Renilla luciferase. Related luciferases such as Renilla luciferase mutants showed high degrees of inhibitor overlap (40-70%), while unrelated luciferases such as firefly luciferases, Gaussia luciferase, and NanoLuc showed <10% overlap. Examination of representative inhibitors in cell-based assays revealed that inhibitor-based enzyme stabilization can lead to increases in bioluminescent signal for firefly luciferase, Renilla luciferase, and NanoLuc, with shorter half-life reporters showing increased activation responses. From this study we suggest strategies to improve the construction and interpretation of assays employing these reporter enzymes.

Caged ATP - an internal calibration method for ATP bioluminescence assays.

PubMed

Calvert, R M; Hopkins, H C; Reilly, M J; Forsythe, S J

2000-03-01

ATP bioluminescence, based on the firefly luciferase system, is used for the rapid determination of hygienic practices in the food industry. This study has demonstrated the use of caged ATP as an internal ATP standard and quantified the effects of industrial cleansing solutions, alcoholic beverages and pH on firefly luciferase activity. The light signal was quenched 6-47% by five cleansing solutions at standard working concentrations. Ethanol at 1% (v/v) inhibited bioluminescence by 15% (w/v) whereas concentrations above 4% enhanced the light output. The light signal was quenched by 20-25% at pH values below pH 4 and above pH 10.

Several methods for concentrating bacteria in fluid samples

NASA Technical Reports Server (NTRS)

Thomas, R. R.

1976-01-01

The sensitivities of the firefly luciferase - ATP flow system and luminol flow system were established as 300,000 E. coli per milliliter and 10,000 E. coli per milliliter respectively. To achieve the detection limit of 1,000 bacteria per milliliter previously established, a method of concentrating microorganisms using a sartorius membrane filter system is investigated. Catalase in 50% ethanol is found to be a stable luminol standard and can be used up to 24 hours with only a 10% loss of activity. The luminol reagent is also stable over a 24 hour period. A method of preparing relatively inexpensive luciferase from desiccated firefly tails is developed.

Comparative theoretical study of the binding of luciferyl-adenylate and dehydroluciferyl-adenylate to firefly luciferase

NASA Astrophysics Data System (ADS)

Pinto da Silva, Luís; Vieira, João; Esteves da Silva, Joaquim C. G.

2012-08-01

This is the first report of a study employing a computational approach to study the binding of (D/L)-luciferyl-adenlyates and dehydroluciferyl-adenylate to firefly luciferase. A semi-empirical/molecular mechanics methodology was used to study the interaction between these ligands and active site molecules. All adenylates are complexed with the enzyme, mostly due to electrostatic interactions with cationic residues. Dehydroluciferyl-adenylate is expected to be a competitive inhibitor of luciferyl-adenylate, as their binding mechanism and affinity to luciferase are very similar. Both luciferyl-adenylates adopt the L-orientation in the active site of luciferase.

HABITAT EVALUATIONS OF AQUATIC CREATURES USING HSI MODEL CONSIDERING THE RIVER WATER TEMPERATURE

NASA Astrophysics Data System (ADS)

Nukazawa, Kei; Shiraiwa, Jun-Ichi; Kazama, So

Habitats of aquatic creatures (fishes Oncorhynchus masou masou, Plecoglossus altivelis altivel and Cyprinus carpio, fireflies Luciola cruciata and Luciola lateralis, and frogs Anura sp) in the Natori River basin located at the middle of Miyagi prefecture were evaluated dynamically using the water temperature as one of the environmental indices. HSI (Habitat Suitability Index) and WUA (Weighted Useable Area) of aquatic creatures were quantitatively calculated from numerical map information and hydrological simulation with a heat budget model. As results, general HSI of fireflies increased but of frogs decreased by adding the factor water temperature. Migration of Plecoglossus altivelis altivel could be represented by the variation of WUA.

Sound imaging of nocturnal animal calls in their natural habitat.

PubMed

Mizumoto, Takeshi; Aihara, Ikkyu; Otsuka, Takuma; Takeda, Ryu; Aihara, Kazuyuki; Okuno, Hiroshi G

2011-09-01

We present a novel method for imaging acoustic communication between nocturnal animals. Investigating the spatio-temporal calling behavior of nocturnal animals, e.g., frogs and crickets, has been difficult because of the need to distinguish many animals' calls in noisy environments without being able to see them. Our method visualizes the spatial and temporal dynamics using dozens of sound-to-light conversion devices (called "Firefly") and an off-the-shelf video camera. The Firefly, which consists of a microphone and a light emitting diode, emits light when it captures nearby sound. Deploying dozens of Fireflies in a target area, we record calls of multiple individuals through the video camera. We conduct two experiments, one indoors and the other in the field, using Japanese tree frogs (Hyla japonica). The indoor experiment demonstrates that our method correctly visualizes Japanese tree frogs' calling behavior. It has confirmed the known behavior; two frogs call synchronously or in anti-phase synchronization. The field experiment (in a rice paddy where Japanese tree frogs live) also visualizes the same calling behavior to confirm anti-phase synchronization in the field. Experimental results confirm that our method can visualize the calling behavior of nocturnal animals in their natural habitat.

A transgenic rat with ubiquitous expression of firefly luciferase gene

NASA Astrophysics Data System (ADS)

Hakamata, Yoji; Murakami, Takashi; Kobayashi, Eiji

2006-02-01

In vivo imaging strategies provide cellular and molecular events in real time that helps us to understand biological processes in living animals. The development of molecular tags such as green fluorescent proteins and luciferase from the firefly Photinus pyralis has lead to a revolution in the visualization of complex biochemical processes. We developed a novel inbred transgenic rat strain containing firefly luciferase based on the transgenic (Tg) technique in rats. This Tg rat expressed the luciferase gene ubiquitously under control of the ROSA26 promoter. Cellular immune responsiveness against the luciferase protein was evaluated using conventional skin grafting and resulted in the long-term acceptance of Tg rat skin on wild-type rats. Strikingly, organ transplant with heart and small bowel demonstrated organ viability and graft survival, suggesting that cells from luciferase-Tg are transplantable to track their fate. Taking advantage of the less immunogenic luciferase, we also tested the role of hepatocyte-infusion in a liver injury model, and bone marrow-derived cells in a skin defect model. Employed in conjunction with modern advances in optical imaging, this luciferase-Tg rat system provides an innovative animal tool and a new means of facilitating biomedical research such as in the case of regeneration medicine.

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

PubMed

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

2018-04-17

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

The evolution of adult light emission color in North American fireflies.

PubMed

Hall, David W; Sander, Sarah E; Pallansch, Jennifer C; Stanger-Hall, Kathrin F

2016-09-01

Firefly species (Lampyridae) vary in the color of their adult bioluminescence. It has been hypothesized that color is selected to enhance detection by conspecifics. One mechanism to improve visibility of the signal is to increase contrast against ambient light. High contrast implies that fireflies active early in the evening will emit yellower luminescence to contrast against ambient light reflected from green vegetation, especially in habitats with high vegetation cover. Another mechanism to improve visibility is to use reflection off the background to enhance the light signal. Reflectance predicts that sedentary females will produce greener light to maximize reflection off the green vegetation on which they signal. To test these predictions, we recorded over 7500 light emission spectra and determined peak emission wavelength for 675 males, representing 24 species, at 57 field sites across the Eastern United States. We found support for both hypotheses: males active early in more vegetated habitats produced yellower flashes in comparison to later-active males with greener flashes. Further, in two of the eight species with female data, female light emissions were significantly greener as compared to males. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Robust Lentiviral Gene Delivery But Limited Transduction Capacity of Commonly Used Adeno-Associated Viral Serotypes in Xenotransplanted Human Skin.

PubMed

Jakobsen, Maria; Askou, Anne Louise; Stenderup, Karin; Rosada, Cecilia; Dagnæs-Hansen, Frederik; Jensen, Thomas G; Corydon, Thomas J; Mikkelsen, Jacob Giehm; Aagaard, Lars

2015-08-01

Skin is an easily accessible organ, and therapeutic gene transfer to skin remains an attractive alternative for the treatment of skin diseases. Although we have previously documented potent lentiviral gene delivery to human skin, vectors based on adeno-associated virus (AAV) rank among the most promising gene delivery tools for in vivo purposes. Thus, we compared the potential usefulness of various serotypes of recombinant AAV vectors and lentiviral vectors for gene transfer to human skin in a xenotransplanted mouse model. Vector constructs encoding firefly luciferase were packaged in AAV capsids of serotype 1, 2, 5, 6, 8, and 9 and separately administered by intradermal injection in human skin transplants. For all serotypes, live bioimaging demonstrated low levels of transgene expression in the human skin graft, and firefly luciferase expression was observed primarily in neighboring tissue outside of the graft. In contrast, gene delivery by intradermally injected lentiviral vectors was efficient and led to extensive and persistent firefly luciferase expression within the human skin graft only. The study demonstrates the limited capacity of single-stranded AAV vectors of six commonly used serotypes for gene delivery to human skin in vivo.

Robust Lentiviral Gene Delivery But Limited Transduction Capacity of Commonly Used Adeno-Associated Viral Serotypes in Xenotransplanted Human Skin

PubMed Central

Jakobsen, Maria; Askou, Anne Louise; Stenderup, Karin; Rosada, Cecilia; Dagnæs-Hansen, Frederik; Jensen, Thomas G.; Corydon, Thomas J.; Mikkelsen, Jacob Giehm; Aagaard, Lars

2015-01-01

Skin is an easily accessible organ, and therapeutic gene transfer to skin remains an attractive alternative for the treatment of skin diseases. Although we have previously documented potent lentiviral gene delivery to human skin, vectors based on adeno-associated virus (AAV) rank among the most promising gene delivery tools for in vivo purposes. Thus, we compared the potential usefulness of various serotypes of recombinant AAV vectors and lentiviral vectors for gene transfer to human skin in a xenotransplanted mouse model. Vector constructs encoding firefly luciferase were packaged in AAV capsids of serotype 1, 2, 5, 6, 8, and 9 and separately administered by intradermal injection in human skin transplants. For all serotypes, live bioimaging demonstrated low levels of transgene expression in the human skin graft, and firefly luciferase expression was observed primarily in neighboring tissue outside of the graft. In contrast, gene delivery by intradermally injected lentiviral vectors was efficient and led to extensive and persistent firefly luciferase expression within the human skin graft only. The study demonstrates the limited capacity of single-stranded AAV vectors of six commonly used serotypes for gene delivery to human skin in vivo. PMID:26204415

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

Mutagenesis of solvent-exposed amino acids in Photinus pyralis luciferase improves thermostability and pH-tolerance

PubMed Central

Law, G. H. Erica; Gandelman, Olga A.; Tisi, Laurence C.; Lowe, Christopher R.; Murray, James A. H.

2006-01-01

Firefly luciferase catalyses a two-step reaction, using ATP-Mg2+, firefly luciferin and molecular oxygen as substrates, leading to the efficient emission of yellow–green light. We report the identification of novel luciferase mutants which combine improved pH-tolerance and thermostability and that retain the specific activity of the wild-type enzyme. These were identified by the mutagenesis of solvent-exposed non-conserved hydrophobic amino acids to hydrophilic residues in Photinus pyralis firefly luciferase followed by in vivo activity screening. Mutants F14R, L35Q, V182K, I232K and F465R were found to be the preferred substitutions at the respective positions. The effects of these amino acid replacements are additive, since combination of the five substitutions produced an enzyme with greatly improved pH-tolerance and stability up to 45 °C. All mutants, including the mutant with all five substitutions, showed neither a decrease in specific activity relative to the recombinant wild-type enzyme, nor any substantial differences in kinetic constants. It is envisaged that the combined mutant will be superior to wild-type luciferase for many in vitro and in vivo applications. PMID:16551268

The Application of Collaborative Business Intelligence Technology in the Hospital SPD Logistics Management Model.

PubMed

Liu, Tongzhu; Shen, Aizong; Hu, Xiaojian; Tong, Guixian; Gu, Wei

2017-06-01

We aimed to apply collaborative business intelligence (BI) system to hospital supply, processing and distribution (SPD) logistics management model. We searched Engineering Village database, China National Knowledge Infrastructure (CNKI) and Google for articles (Published from 2011 to 2016), books, Web pages, etc., to understand SPD and BI related theories and recent research status. For the application of collaborative BI technology in the hospital SPD logistics management model, we realized this by leveraging data mining techniques to discover knowledge from complex data and collaborative techniques to improve the theories of business process. For the application of BI system, we: (i) proposed a layered structure of collaborative BI system for intelligent management in hospital logistics; (ii) built data warehouse for the collaborative BI system; (iii) improved data mining techniques such as supporting vector machines (SVM) and swarm intelligence firefly algorithm to solve key problems in hospital logistics collaborative BI system; (iv) researched the collaborative techniques oriented to data and business process optimization to improve the business processes of hospital logistics management. Proper combination of SPD model and BI system will improve the management of logistics in the hospitals. The successful implementation of the study requires: (i) to innovate and improve the traditional SPD model and make appropriate implement plans and schedules for the application of BI system according to the actual situations of hospitals; (ii) the collaborative participation of internal departments in hospital including the department of information, logistics, nursing, medical and financial; (iii) timely response of external suppliers.

A Multifeatures Fusion and Discrete Firefly Optimization Method for Prediction of Protein Tyrosine Sulfation Residues.

PubMed

Guo, Song; Liu, Chunhua; Zhou, Peng; Li, Yanling

2016-01-01

Tyrosine sulfation is one of the ubiquitous protein posttranslational modifications, where some sulfate groups are added to the tyrosine residues. It plays significant roles in various physiological processes in eukaryotic cells. To explore the molecular mechanism of tyrosine sulfation, one of the prerequisites is to correctly identify possible protein tyrosine sulfation residues. In this paper, a novel method was presented to predict protein tyrosine sulfation residues from primary sequences. By means of informative feature construction and elaborate feature selection and parameter optimization scheme, the proposed predictor achieved promising results and outperformed many other state-of-the-art predictors. Using the optimal features subset, the proposed method achieved mean MCC of 94.41% on the benchmark dataset, and a MCC of 90.09% on the independent dataset. The experimental performance indicated that our new proposed method could be effective in identifying the important protein posttranslational modifications and the feature selection scheme would be powerful in protein functional residues prediction research fields.

A Multifeatures Fusion and Discrete Firefly Optimization Method for Prediction of Protein Tyrosine Sulfation Residues

PubMed Central

Liu, Chunhua; Zhou, Peng; Li, Yanling

2016-01-01

Tyrosine sulfation is one of the ubiquitous protein posttranslational modifications, where some sulfate groups are added to the tyrosine residues. It plays significant roles in various physiological processes in eukaryotic cells. To explore the molecular mechanism of tyrosine sulfation, one of the prerequisites is to correctly identify possible protein tyrosine sulfation residues. In this paper, a novel method was presented to predict protein tyrosine sulfation residues from primary sequences. By means of informative feature construction and elaborate feature selection and parameter optimization scheme, the proposed predictor achieved promising results and outperformed many other state-of-the-art predictors. Using the optimal features subset, the proposed method achieved mean MCC of 94.41% on the benchmark dataset, and a MCC of 90.09% on the independent dataset. The experimental performance indicated that our new proposed method could be effective in identifying the important protein posttranslational modifications and the feature selection scheme would be powerful in protein functional residues prediction research fields. PMID:27034949

Long-term ex vivo and in vivo monitoring of tumor progression by using dual luciferases.

PubMed

Morita, Naoki; Haga, Sanae; Ohmiya, Yoshihiro; Ozaki, Michitaka

2016-03-15

We propose a new concept of tumor progression monitoring using dual luciferases in living animals to reduce stress for small animals and the cost of luciferin. The secreted Cypridina luciferase (CLuc) was used as an ex vivo indicator to continuously monitor tumor progression. On the other hand, the non-secreted firefly luciferase was used as an in vivo indicator to analyze the spatial distribution of the tumor at suitable time points indicated by CLuc. Thus, the new monitoring systems that use dual luciferases are available, allowing long-term bioluminescence imaging under minimal stress for the experimental animals. Copyright © 2015 Elsevier Inc. All rights reserved.

Gross anatomy of central nervous system in firefly, Pteroptyx tener (Coleoptera: Lampyridae)

NASA Astrophysics Data System (ADS)

Hudawiyah, Nur; Wahida, O. Nurul; Norela, S.

2015-09-01

This paper describes for the first time the organization and fine structure of the central nervous system (CNS) in the fireflies, Pteroptyx tener (Coleoptera: Lampyridae). The morphology of the CNS was examined by using Carl Zeiss AxioScope A1 photomicroscope with iSolution Lite software. Some specific structural features such as the localization of protocerebrum, deutocerebrum and tritocerebrum in the brain region were analyzed. Other than that, the nerve cord and its peripheral structure were also analyzed. This study suggests that, there is a very obvious difference between male and female central nervous system which illustrates that they may differ in function in controlling physiological and behavioral activities.

Creation of High Efficient Firefly Luciferase

NASA Astrophysics Data System (ADS)

Nakatsu, Toru

Firefly emits visible yellow-green light. The bioluminescence reaction is carried out by the enzyme luciferase. The bioluminescence of luciferase is widely used as an excellent tool for monitoring gene expression, the measurement of the amount of ATP and in vivo imaging. Recently a study of the cancer metastasis is carried out by in vivo luminescence imaging system, because luminescence imaging is less toxic and more useful for long-term assay than fluorescence imaging by GFP. However the luminescence is much dimmer than fluorescence. Then bioluminescence imaging in living organisms demands the high efficient luciferase which emits near infrared lights or enhances the emission intensity. Here I introduce an idea for creating the high efficient luciferase based on the crystal structure.

Use of near infrared fluorescence during robot-assisted laparoscopic partial nephrectomy.

PubMed

Cornejo-Dávila, V; Nazmy, M; Kella, N; Palmeros-Rodríguez, M A; Morales-Montor, J G; Pacheco-Gahbler, C

2016-04-01

Partial nephrectomy is the treatment of choice for T1a tumours. The open approach is still the standard method. Robot-assisted laparoscopic surgery offers advantages that are applicable to partial nephrectomy, such as the use of the Firefly® system with near-infrared fluorescence. To demonstrate the implementation of fluorescence in nephron-sparing surgery. This case concerned a 37-year-old female smoker, with obesity. The patient had a right kidney tumour measuring 31 mm, which was found using tomography. She therefore underwent robot-assisted laparoscopic partial nephrectomy, with a warm ischaemia time of 22 minutes and the use of fluorescence with the Firefly® system to guide the resection. There were no complications. The tumour was a pT1aN0M0 renal cell carcinoma, with negative margins. Robot-assisted renal laparoscopic surgery is employed for nephron-sparing surgery, with good oncological and functional results. The combination of the Firefly® technology and intraoperative ultrasound can more accurately delimit the extent of the lesion, increase the negative margins and decrease the ischaemia time. Near-infrared fluorescence in robot-assisted partial nephrectomy is useful for guiding the tumour resection and can potentially improve the oncological and functional results. Copyright © 2015 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

Visual Servoing for an Autonomous Hexarotor Using a Neural Network Based PID Controller.

PubMed

Lopez-Franco, Carlos; Gomez-Avila, Javier; Alanis, Alma Y; Arana-Daniel, Nancy; Villaseñor, Carlos

2017-08-12

In recent years, unmanned aerial vehicles (UAVs) have gained significant attention. However, we face two major drawbacks when working with UAVs: high nonlinearities and unknown position in 3D space since it is not provided with on-board sensors that can measure its position with respect to a global coordinate system. In this paper, we present a real-time implementation of a servo control, integrating vision sensors, with a neural proportional integral derivative (PID), in order to develop an hexarotor image based visual servo control (IBVS) that knows the position of the robot by using a velocity vector as a reference to control the hexarotor position. This integration requires a tight coordination between control algorithms, models of the system to be controlled, sensors, hardware and software platforms and well-defined interfaces, to allow the real-time implementation, as well as the design of different processing stages with their respective communication architecture. All of these issues and others provoke the idea that real-time implementations can be considered as a difficult task. For the purpose of showing the effectiveness of the sensor integration and control algorithm to address these issues on a high nonlinear system with noisy sensors as cameras, experiments were performed on the Asctec Firefly on-board computer, including both simulation and experimenta results.

Visual Servoing for an Autonomous Hexarotor Using a Neural Network Based PID Controller

PubMed Central

Lopez-Franco, Carlos; Alanis, Alma Y.; Arana-Daniel, Nancy; Villaseñor, Carlos

2017-01-01

In recent years, unmanned aerial vehicles (UAVs) have gained significant attention. However, we face two major drawbacks when working with UAVs: high nonlinearities and unknown position in 3D space since it is not provided with on-board sensors that can measure its position with respect to a global coordinate system. In this paper, we present a real-time implementation of a servo control, integrating vision sensors, with a neural proportional integral derivative (PID), in order to develop an hexarotor image based visual servo control (IBVS) that knows the position of the robot by using a velocity vector as a reference to control the hexarotor position. This integration requires a tight coordination between control algorithms, models of the system to be controlled, sensors, hardware and software platforms and well-defined interfaces, to allow the real-time implementation, as well as the design of different processing stages with their respective communication architecture. All of these issues and others provoke the idea that real-time implementations can be considered as a difficult task. For the purpose of showing the effectiveness of the sensor integration and control algorithm to address these issues on a high nonlinear system with noisy sensors as cameras, experiments were performed on the Asctec Firefly on-board computer, including both simulation and experimenta results. PMID:28805689

Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model

NASA Astrophysics Data System (ADS)

Yaseen, Zaher Mundher; Ebtehaj, Isa; Bonakdari, Hossein; Deo, Ravinesh C.; Danandeh Mehr, Ali; Mohtar, Wan Hanna Melini Wan; Diop, Lamine; El-shafie, Ahmed; Singh, Vijay P.

2017-11-01

The present study proposes a new hybrid evolutionary Adaptive Neuro-Fuzzy Inference Systems (ANFIS) approach for monthly streamflow forecasting. The proposed method is a novel combination of the ANFIS model with the firefly algorithm as an optimizer tool to construct a hybrid ANFIS-FFA model. The results of the ANFIS-FFA model is compared with the classical ANFIS model, which utilizes the fuzzy c-means (FCM) clustering method in the Fuzzy Inference Systems (FIS) generation. The historical monthly streamflow data for Pahang River, which is a major river system in Malaysia that characterized by highly stochastic hydrological patterns, is used in the study. Sixteen different input combinations with one to five time-lagged input variables are incorporated into the ANFIS-FFA and ANFIS models to consider the antecedent seasonal variations in historical streamflow data. The mean absolute error (MAE), root mean square error (RMSE) and correlation coefficient (r) are used to evaluate the forecasting performance of ANFIS-FFA model. In conjunction with these metrics, the refined Willmott's Index (Drefined), Nash-Sutcliffe coefficient (ENS) and Legates and McCabes Index (ELM) are also utilized as the normalized goodness-of-fit metrics. Comparison of the results reveals that the FFA is able to improve the forecasting accuracy of the hybrid ANFIS-FFA model (r = 1; RMSE = 0.984; MAE = 0.364; ENS = 1; ELM = 0.988; Drefined = 0.994) applied for the monthly streamflow forecasting in comparison with the traditional ANFIS model (r = 0.998; RMSE = 3.276; MAE = 1.553; ENS = 0.995; ELM = 0.950; Drefined = 0.975). The results also show that the ANFIS-FFA is not only superior to the ANFIS model but also exhibits a parsimonious modelling framework for streamflow forecasting by incorporating a smaller number of input variables required to yield the comparatively better performance. It is construed that the FFA optimizer can thus surpass the accuracy of the traditional ANFIS model in general, and is able to remove the false (inaccurately) forecasted data in the ANFIS model for extremely low flows. The present results have wider implications not only for streamflow forecasting purposes, but also for other hydro-meteorological forecasting variables requiring only the historical data input data, and attaining a greater level of predictive accuracy with the incorporation of the FFA algorithm as an optimization tool in an ANFIS model.

Proton mediated control of biochemical reactions with bioelectronic pH modulation

NASA Astrophysics Data System (ADS)

Deng, Yingxin; Miyake, Takeo; Keene, Scott; Josberger, Erik E.; Rolandi, Marco

2016-04-01

In Nature, protons (H+) can mediate metabolic process through enzymatic reactions. Examples include glucose oxidation with glucose dehydrogenase to regulate blood glucose level, alcohol dissolution into carboxylic acid through alcohol dehydrogenase, and voltage-regulated H+ channels activating bioluminescence in firefly and jellyfish. Artificial devices that control H+ currents and H+ concentration (pH) are able to actively influence biochemical processes. Here, we demonstrate a biotransducer that monitors and actively regulates pH-responsive enzymatic reactions by monitoring and controlling the flow of H+ between PdHx contacts and solution. The present transducer records bistable pH modulation from an “enzymatic flip-flop” circuit that comprises glucose dehydrogenase and alcohol dehydrogenase. The transducer also controls bioluminescence from firefly luciferase by affecting solution pH.

Robust red-emission spectra and yields in firefly bioluminescence against temperature changes

NASA Astrophysics Data System (ADS)

Mochizuki, Toshimitsu; Wang, Yu; Hiyama, Miyabi; Akiyama, Hidefumi

2014-05-01

We measured the quantitative spectra of firefly (Photinus pyralis) bioluminescence at various temperatures to investigate the temperature dependence of the luciferin-luciferase reaction at 15-34 °C. The quantitative spectra were decomposed very well into red (1.9 eV), orange (2.0 eV), and green (2.2 eV) Gaussian components. The intensity of the green component was the only temperature sensitive quantity that linearly decreased as the temperature increased at pH 7 and 8. We found the quantitative bioluminescence spectra to be robust below 2.0 eV against temperature and other experimental conditions. The revealed robustness of the red emissions should be useful for quantitative applications such as adenosine-5'-triphosphate detection.

Design and feasibility study for a portable oil recovery turbopump

NASA Technical Reports Server (NTRS)

1982-01-01

A portable oil recovery turbopump concept, using the Firefly module as primer mover, for the offloading of distressed tank vessels is examined. The demands to be met both in terms of the type of petroleum to be offloaded, as well as the operational requirements placed on the pump, are studied with respect to the capability of different pump configurations. Two configurations, one a centrifugal type and the other a screw type pump, are developed and evaluated. While the centrifugal configuration is found to be effective in a large proportion of tank vessel offloading situations, the screw type will be required where high viscosity cargoes are involved. The feasibility of the turbopump concept, with the Firefly module as prime mover, is established.

In vivo quantitative bioluminescence tomography using heterogeneous and homogeneous mouse models.

PubMed

Liu, Junting; Wang, Yabin; Qu, Xiaochao; Li, Xiangsi; Ma, Xiaopeng; Han, Runqiang; Hu, Zhenhua; Chen, Xueli; Sun, Dongdong; Zhang, Rongqing; Chen, Duofang; Chen, Dan; Chen, Xiaoyuan; Liang, Jimin; Cao, Feng; Tian, Jie

2010-06-07

Bioluminescence tomography (BLT) is a new optical molecular imaging modality, which can monitor both physiological and pathological processes by using bioluminescent light-emitting probes in small living animal. Especially, this technology possesses great potential in drug development, early detection, and therapy monitoring in preclinical settings. In the present study, we developed a dual modality BLT prototype system with Micro-computed tomography (MicroCT) registration approach, and improved the quantitative reconstruction algorithm based on adaptive hp finite element method (hp-FEM). Detailed comparisons of source reconstruction between the heterogeneous and homogeneous mouse models were performed. The models include mice with implanted luminescence source and tumor-bearing mice with firefly luciferase report gene. Our data suggest that the reconstruction based on heterogeneous mouse model is more accurate in localization and quantification than the homogeneous mouse model with appropriate optical parameters and that BLT allows super-early tumor detection in vivo based on tomographic reconstruction of heterogeneous mouse model signal.

The Application of Collaborative Business Intelligence Technology in the Hospital SPD Logistics Management Model

PubMed Central

LIU, Tongzhu; SHEN, Aizong; HU, Xiaojian; TONG, Guixian; GU, Wei

2017-01-01

Background: We aimed to apply collaborative business intelligence (BI) system to hospital supply, processing and distribution (SPD) logistics management model. Methods: We searched Engineering Village database, China National Knowledge Infrastructure (CNKI) and Google for articles (Published from 2011 to 2016), books, Web pages, etc., to understand SPD and BI related theories and recent research status. For the application of collaborative BI technology in the hospital SPD logistics management model, we realized this by leveraging data mining techniques to discover knowledge from complex data and collaborative techniques to improve the theories of business process. Results: For the application of BI system, we: (i) proposed a layered structure of collaborative BI system for intelligent management in hospital logistics; (ii) built data warehouse for the collaborative BI system; (iii) improved data mining techniques such as supporting vector machines (SVM) and swarm intelligence firefly algorithm to solve key problems in hospital logistics collaborative BI system; (iv) researched the collaborative techniques oriented to data and business process optimization to improve the business processes of hospital logistics management. Conclusion: Proper combination of SPD model and BI system will improve the management of logistics in the hospitals. The successful implementation of the study requires: (i) to innovate and improve the traditional SPD model and make appropriate implement plans and schedules for the application of BI system according to the actual situations of hospitals; (ii) the collaborative participation of internal departments in hospital including the department of information, logistics, nursing, medical and financial; (iii) timely response of external suppliers. PMID:28828316

The Bioluminescence Resonance Energy Transfer from Firefly Luciferase to a Synthetic Dye and its Application for the Rapid Homogeneous Immunoassay of Progesterone.

PubMed

Smirnova, Daria V; Samsonova, Jeanne V; Ugarova, Natalia N

2016-01-01

The sensitive BRET system for the homogeneous immunoassay of a low-molecular weight antigen was developed using progesterone as an example. Two thermostable mutants of the Luciola mingrelica firefly luciferase (Luc)-the "red" mutant with λmax.em = 590 nm (RedLuc) and the "green" mutant with λmax.em = 550 nm (GreenLuc)-were tested as the donors. The water-soluble Alexa Fluor 610× (AF) dye was selected as the acceptor because its two absorption maxima, located at 550 and 610 nm, are close to the bioluminescence maxima of the GreenLuc and RedLuc, respectively. The methods for the synthesis of the luciferase-progesterone (Luc-Pg) conjugate and the conjugate of the dye and the polyclonal antiprogesterone antibody (AF-Ab) were developed. Both conjugates retained their functional properties, had high antigen-antibody binding activity, and demonstrated a high BRET signal. The homogeneous immunoassay system based on the BRET from the firefly luciferase to the synthetic dye was established to assay progesterone as a model antigen. Optimization of the assay conditions, the composition of the reaction mixture, and the concentrations of the donor and the acceptor made it possible to reach the minimum detectable progesterone concentration of 0.5 ng mL(-1) . © 2015 The American Society of Photobiology.

Absorption spectrum of the firefly luciferin anion isolated in vacuo.

PubMed

Støchkel, Kristian; Milne, Bruce F; Brøndsted Nielsen, Steen

2011-03-24

The excited-state physics of the firefly luciferin anion depends on its chemical environment, and it is therefore important to establish the intrinsic behavior of the bare ion. Here we report electronic absorption spectra of the anion isolated in vacuo obtained at an electrostatic ion storage ring and an accelerator mass spectrometer where ionic dissociation is monitored on a long time scale (from 33 μs and up to 3 ms) and on a short time scale (0-3 μs), respectively. In the ring experiment the yield of all neutrals (mainly CO(2)) as a function of wavelength was measured whereas in the single pass experiment, the abundance of daughter ions formed after loss of CO(2) was recorded to provide action spectra. We find maxima at 535 and 265 nm, and that the band shape is largely determined by the sampling time interval, which is due to the kinetics of the dissociation process. Calculations at the TD-B3LYP/TZVPP++ level predict maximum absorption at 533 and 275 nm for the carboxylate isomer in excellent agreement with the experimental findings. The phenolate isomer lies higher in energy by 0.22 eV, and also its absorption maximum is calculated to be at 463 nm, which is far away from the experimental value. Our data serve to benchmark future theoretical models for bioluminescence from fireflies.

Novel hybrid linear stochastic with non-linear extreme learning machine methods for forecasting monthly rainfall a tropical climate.

PubMed

Zeynoddin, Mohammad; Bonakdari, Hossein; Azari, Arash; Ebtehaj, Isa; Gharabaghi, Bahram; Riahi Madavar, Hossein

2018-09-15

A novel hybrid approach is presented that can more accurately predict monthly rainfall in a tropical climate by integrating a linear stochastic model with a powerful non-linear extreme learning machine method. This new hybrid method was then evaluated by considering four general scenarios. In the first scenario, the modeling process is initiated without preprocessing input data as a base case. While in other three scenarios, the one-step and two-step procedures are utilized to make the model predictions more precise. The mentioned scenarios are based on a combination of stationarization techniques (i.e., differencing, seasonal and non-seasonal standardization and spectral analysis), and normality transforms (i.e., Box-Cox, John and Draper, Yeo and Johnson, Johnson, Box-Cox-Mod, log, log standard, and Manly). In scenario 2, which is a one-step scenario, the stationarization methods are employed as preprocessing approaches. In scenario 3 and 4, different combinations of normality transform, and stationarization methods are considered as preprocessing techniques. In total, 61 sub-scenarios are evaluated resulting 11013 models (10785 linear methods, 4 nonlinear models, and 224 hybrid models are evaluated). The uncertainty of the linear, nonlinear and hybrid models are examined by Monte Carlo technique. The best preprocessing technique is the utilization of Johnson normality transform and seasonal standardization (respectively) (R 2  = 0.99; RMSE = 0.6; MAE = 0.38; RMSRE = 0.1, MARE = 0.06, UI = 0.03 &UII = 0.05). The results of uncertainty analysis indicated the good performance of proposed technique (d-factor = 0.27; 95PPU = 83.57). Moreover, the results of the proposed methodology in this study were compared with an evolutionary hybrid of adaptive neuro fuzzy inference system (ANFIS) with firefly algorithm (ANFIS-FFA) demonstrating that the new hybrid methods outperformed ANFIS-FFA method. Copyright © 2018 Elsevier Ltd. All rights reserved.

Problem areas in the use of the firefly luciferase assay for bacterial detection

NASA Technical Reports Server (NTRS)

Picciolo, G. L.; Chappelle, E. W.; Knust, E. A.; Tuttle, S. A.; Curtis, C. A.

1975-01-01

By purifying the firefly luciferase extract and adding all necessary chemicals but ATP in excess, an assay for ATP was performed by measuring the amount of light produced when a sample containing soluble ATP is added to the luciferase reaction mixture. Instrumentation, applications, and basic characteristics of the luciferase assay are presented. Effect of the growth medium and length of time grown in this medium on ATP per viable E. coli values is shown in graphic form, along with an ATP concentration curve showing relative light units versus ATP injected. Reagent functions and concentration methods are explored. Efforts to develop a fast automatable system to detect the presence of bacteria in biological fluids, especially urine, resulted in the optimization of procedures for use with different types of samples.

Quenching the firefly bioluminescence by various ions.

PubMed

Zhang, Huateng; Bai, Haixiu; Jiang, Tianyu; Ma, Zhao; Cheng, Yanna; Zhou, Yubin; Du, Lupei; Li, Minyong

2016-02-01

The luciferase reporter gene assay system is broadly applied in various biomedical aspects, including signaling pathway dissection, transcriptional activity analysis, and genetic toxicity testing. It significantly improves the experimental accuracy and reduces the experimental error by the addition of an internal control. In the current research, we discovered some specific ions that could selectively inhibit firefly luciferase while having a negligible effect on renilla luciferase in vitro in the dual-reporter gene assay. We showed that these ionic compounds had a high potential of being utilized as quench-and-activate reagents in the dual-reporter assay. Furthermore, results from kinetic studies on ion-mediated quenching effects indicated that different ions have distinct inhibition modes. Our study is anticipated to guide a more affordable design of quench-and-activate reagents in biomedicine and pharmaceutical analysis.

Proton mediated control of biochemical reactions with bioelectronic pH modulation

DOE PAGES

Deng, Yingxin; Miyake, Takeo; Keene, Scott; ...

2016-04-07

In Nature, protons (H +) can mediate metabolic process through enzymatic reactions. Examples include glucose oxidation with glucose dehydrogenase to regulate blood glucose level, alcohol dissolution into carboxylic acid through alcohol dehydrogenase, and voltage-regulated H + channels activating bioluminescence in firefly and jellyfish. Artificial devices that control H + currents and H + concentration (pH) are able to actively influence biochemical processes. Here, we demonstrate a biotransducer that monitors and actively regulates pH-responsive enzymatic reactions by monitoring and controlling the flow of H + between PdH x contacts and solution. The present transducer records bistable pH modulation from an “enzymaticmore » flip-flop” circuit that comprises glucose dehydrogenase and alcohol dehydrogenase. Furthermore, the transducer also controls bioluminescence from firefly luciferase by affecting solution pH.« less

Proton mediated control of biochemical reactions with bioelectronic pH modulation

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

Deng, Yingxin; Miyake, Takeo; Keene, Scott

In Nature, protons (H +) can mediate metabolic process through enzymatic reactions. Examples include glucose oxidation with glucose dehydrogenase to regulate blood glucose level, alcohol dissolution into carboxylic acid through alcohol dehydrogenase, and voltage-regulated H + channels activating bioluminescence in firefly and jellyfish. Artificial devices that control H + currents and H + concentration (pH) are able to actively influence biochemical processes. Here, we demonstrate a biotransducer that monitors and actively regulates pH-responsive enzymatic reactions by monitoring and controlling the flow of H + between PdH x contacts and solution. The present transducer records bistable pH modulation from an “enzymaticmore » flip-flop” circuit that comprises glucose dehydrogenase and alcohol dehydrogenase. Furthermore, the transducer also controls bioluminescence from firefly luciferase by affecting solution pH.« less

Real time imaging of live cell ATP leaking or release events by chemiluminescence microscopy

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

Zhang, Yun

The purpose of this research was to expand the chemiluminescence microscopy applications in live bacterial/mammalian cell imaging and to improve the detection sensitivity for ATP leaking or release events. We first demonstrated that chemiluminescence (CL) imaging can be used to interrogate single bacterial cells. While using a luminometer allows detecting ATP from cell lysate extracted from at least 10 bacterial cells, all previous cell CL detection never reached this sensitivity of single bacteria level. We approached this goal with a different strategy from before: instead of breaking bacterial cell membrane and trying to capture the transiently diluted ATP with themore » firefly luciferase CL assay, we introduced the firefly luciferase enzyme into bacteria using the modern genetic techniques and placed the CL reaction substrate D-luciferin outside the cells. By damaging the cell membrane with various antibacterial drugs including antibiotics such as Penicillins and bacteriophages, the D-luciferin molecules diffused inside the cell and initiated the reaction that produces CL light. As firefly luciferases are large protein molecules which are retained within the cells before the total rupture and intracellular ATP concentration is high at the millmolar level, the CL reaction of firefly luciferase, ATP and D-luciferin can be kept for a relatively long time within the cells acting as a reaction container to generate enough photons for detection by the extremely sensitive intensified charge coupled device (ICCD) camera. The result was inspiring as various single bacterium lysis and leakage events were monitored with 10-s temporal resolution movies. We also found a new way of enhancing diffusion D-luciferin into cells by dehydrating the bacteria. Then we started with this novel single bacterial CL imaging technique, and applied it for quantifying gene expression levels from individual bacterial cells. Previous published result in single cell gene expression quantification mainly used a fluorescence method; CL detection is limited because of the difficulty to introduce enough D-luciferin molecules. Since dehydration could easily cause proper size holes in bacterial cell membranes and facilitate D-luciferin diffusion, we used this method and recorded CL from individual cells each hour after induction. The CL light intensity from each individual cell was integrated and gene expression levels of two strain types were compared. Based on our calculation, the overall sensitivity of our system is already approaching the single enzyme level. The median enzyme number inside a single bacterium from the higher expression strain after 2 hours induction was quantified to be about 550 molecules. Finally we imaged ATP release from astrocyte cells. Upon mechanical stimulation, astrocyte cells respond by increasing intracellular Ca 2+ level and releasing ATP to extracellular spaces as signaling molecules. The ATP release imaged by direct CL imaging using free firefly luciferase and D-luciferin outside cells reflects the transient release as well as rapid ATP diffusion. Therefore ATP release detection at the cell surface is critical to study the ATP release mechanism and signaling propagation pathway. We realized this cell surface localized ATP release imaging detection by immobilizing firefly luciferase to streptavidin beads that attached to the cell surface via streptavidin-biotin interactions. Both intracellular Ca 2+ propagation wave and extracellular ATP propagation wave at the cell surface were recorded with fluorescence and CL respectively. The results imply that at close distances from the stimulation center (<120 μm) extracellular ATP pathway is faster, while at long distances (>120 μm) intracellular Ca 2+ signaling through gap junctions seems more effective.« less

75 FR 20933 - Airworthiness Directives; Arrow Falcon Exporters, Inc. (previously Utah State University...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-22

... Helicopter Services (previously Erickson Air-Crane Co.); Garlick Helicopters, Inc.; Global Helicopter... Forestry; Firefly Aviation Helicopter Services (previously Erickson Air-Crane Co.); Garlick Helicopters...

Immunocompetent Mouse Model for Tracking Cancer Progression | NCI Technology Transfer Center | TTC

Cancer.gov

The National Cancer Institute seeks licensees or research collaborators to develop and commercialize transgenic mice having immunocompetent rat growth hormone-firefly Luciferase-enhanced green fluorescent protein.

Analytical Applications of Bioluminescence and Chemiluminescence

NASA Technical Reports Server (NTRS)

Chappelle, E. W. (Editor); Picciolo, G. L. (Editor)

1975-01-01

Bioluminescence and chemiluminescence studies were used to measure the amount of adenosine triphosphate and therefore the amount of energy available. Firefly luciferase - luciferin enzyme system was emphasized. Photometer designs are also considered.

Footprints, Fireflies and Flight: Primary Science Magic.

ERIC Educational Resources Information Center

Fine, Edith H.; Josephson, Judith P.

1984-01-01

Provides primary grade level science activities that focus on insects, tracks and trails, water, and flight. For each topic, six major ideas plus related activities and suggestions about resources are given. (RH)

Starshade Test in Nevada

NASA Image and Video Library

2016-08-09

A test of a small-scale starshade model in a dry lake bed in central Nevada's Smith Creek by Northrup Grumman in May-June 2014. A telescope points toward a bright light, which mimics the conditions of starlight in space. Other lights, which are up to 10 million times fainter than the light source standing in for the star, represent the reflected light of planets. Telescopes searching for the relatively dim light of an exoplanet next to its much bright star are faced with a challenge as difficult as searching from Los Angeles for a firefly in New York– if the firefly is also beside a lighthouse. These tests determined that a starshade, or external occulter, is indeed capable of blocking starlight to a degree that reveals the light of a planet. http://photojournal.jpl.nasa.gov/catalog/PIA20908

SpyTag/SpyCatcher Cyclization Enhances the Thermostability of Firefly Luciferase

PubMed Central

Si, Meng; Xu, Qing

2016-01-01

SpyTag can spontaneously form a covalent isopeptide bond with its protein partner SpyCatcher. Firefly luciferase from Photinus pyralis was cyclized in vivo by fusing SpyCatcher at the N terminus and SpyTag at the C terminus. Circular LUC was more thermostable and alkali-tolerant than the wild type, without compromising the specific activity. Structural analysis indicated that the cyclized LUC increased the thermodynamic stability of the structure and remained more properly folded at high temperatures when compared with the wild type. We also prepared an N-terminally and C-terminally shortened form of the SpyCatcher protein and cyclization using this truncated form led to even more thermostability than the original form. Our findings suggest that cyclization with SpyTag and SpyCatcher is a promising and effective strategy to enhance thermostability of enzymes. PMID:27658030

A comparison of certain extracting agents for extraction of adenosine triphosphate (ATP) from microorganisms for use in the firefly luciferase ATP assay

NASA Technical Reports Server (NTRS)

Knust, E. A.; Chappelle, E. W.; Picciolo, G. L.

1975-01-01

Firefly luciferase ATP assay is used in clinical and industrial applications, such as determination of urinary infection levels, microbial susceptibility testing, and monitoring of yeast levels in beverages. Three categories of extractants were investigated for their extracting efficiency. They were ionizing organic solvents, nonionizing organic solvents, and inorganic acids. Dimethylsulfoxide and formamide represented the ionizing organic solvents, while n-butanol, chloroform, ethanol, acetone, and methylene chloride were used for the nonionizing organic solvents. Nitric acid and perchloric acid were chosen for the inorganic acids category. Pathogens were tested with each solvent. They included: Saccharomyces carlsbergensis, E. coli, Staphylococcus aureus, Klebsiella pneumoniae, Enterobacter species, Proteus mirabilis, Proteus vulgaris, Staphylococcus epidermidis, Streptococcus faecalis, Pseudomonas aeruginosa, and Candida albicans. These results are shown in graphic representations.

Next Generation Search Interfaces

NASA Astrophysics Data System (ADS)

Roby, W.; Wu, X.; Ly, L.; Goldina, T.

2015-09-01

Astronomers are constantly looking for easier ways to access multiple data sets. While much effort is spent on VO, little thought is given to the types of User Interfaces we need to effectively search this sort of data. For instance, an astronomer might need to search Spitzer, WISE, and 2MASS catalogs and images then see the results presented together in one UI. Moving seamlessly between data sets is key to presenting integrated results. Results need to be viewed using first class, web based, integrated FITS viewers, XY Plots, and advanced table display tools. These components should be able to handle very large datasets. To make a powerful Web based UI that can manage and present multiple searches to the user requires taking advantage of many HTML5 features. AJAX is used to start searches and present results. Push notifications (Server Sent Events) monitor background jobs. Canvas is required for advanced result displays. Lesser known CSS3 technologies makes it all flow seamlessly together. At IPAC, we have been developing our Firefly toolkit for several years. We are now using it to solve this multiple data set, multiple queries, and integrated presentation problem to create a powerful research experience. Firefly was created in IRSA, the NASA/IPAC Infrared Science Archive (http://irsa.ipac.caltech.edu). Firefly is the core for applications serving many project archives, including Spitzer, Planck, WISE, PTF, LSST and others. It is also used in IRSA's new Finder Chart and catalog and image displays.

Large-scale protein-protein interaction analysis in Arabidopsis mesophyll protoplasts by split firefly luciferase complementation.

PubMed

Li, Jian-Feng; Bush, Jenifer; Xiong, Yan; Li, Lei; McCormack, Matthew

2011-01-01

Protein-protein interactions (PPIs) constitute the regulatory network that coordinates diverse cellular functions. There are growing needs in plant research for creating protein interaction maps behind complex cellular processes and at a systems biology level. However, only a few approaches have been successfully used for large-scale surveys of PPIs in plants, each having advantages and disadvantages. Here we present split firefly luciferase complementation (SFLC) as a highly sensitive and noninvasive technique for in planta PPI investigation. In this assay, the separate halves of a firefly luciferase can come into close proximity and transiently restore its catalytic activity only when their fusion partners, namely the two proteins of interest, interact with each other. This assay was conferred with quantitativeness and high throughput potential when the Arabidopsis mesophyll protoplast system and a microplate luminometer were employed for protein expression and luciferase measurement, respectively. Using the SFLC assay, we could monitor the dynamics of rapamycin-induced and ascomycin-disrupted interaction between Arabidopsis FRB and human FKBP proteins in a near real-time manner. As a proof of concept for large-scale PPI survey, we further applied the SFLC assay to testing 132 binary PPIs among 8 auxin response factors (ARFs) and 12 Aux/IAA proteins from Arabidopsis. Our results demonstrated that the SFLC assay is ideal for in vivo quantitative PPI analysis in plant cells and is particularly powerful for large-scale binary PPI screens.

A hybrid SVM-FFA method for prediction of monthly mean global solar radiation

NASA Astrophysics Data System (ADS)

Shamshirband, Shahaboddin; Mohammadi, Kasra; Tong, Chong Wen; Zamani, Mazdak; Motamedi, Shervin; Ch, Sudheer

2016-07-01

In this study, a hybrid support vector machine-firefly optimization algorithm (SVM-FFA) model is proposed to estimate monthly mean horizontal global solar radiation (HGSR). The merit of SVM-FFA is assessed statistically by comparing its performance with three previously used approaches. Using each approach and long-term measured HGSR, three models are calibrated by considering different sets of meteorological parameters measured for Bandar Abbass situated in Iran. It is found that the model (3) utilizing the combination of relative sunshine duration, difference between maximum and minimum temperatures, relative humidity, water vapor pressure, average temperature, and extraterrestrial solar radiation shows superior performance based upon all approaches. Moreover, the extraterrestrial radiation is introduced as a significant parameter to accurately estimate the global solar radiation. The survey results reveal that the developed SVM-FFA approach is greatly capable to provide favorable predictions with significantly higher precision than other examined techniques. For the SVM-FFA (3), the statistical indicators of mean absolute percentage error (MAPE), root mean square error (RMSE), relative root mean square error (RRMSE), and coefficient of determination ( R 2) are 3.3252 %, 0.1859 kWh/m2, 3.7350 %, and 0.9737, respectively which according to the RRMSE has an excellent performance. As a more evaluation of SVM-FFA (3), the ratio of estimated to measured values is computed and found that 47 out of 48 months considered as testing data fall between 0.90 and 1.10. Also, by performing a further verification, it is concluded that SVM-FFA (3) offers absolute superiority over the empirical models using relatively similar input parameters. In a nutshell, the hybrid SVM-FFA approach would be considered highly efficient to estimate the HGSR.

Gradient Evolution-based Support Vector Machine Algorithm for Classification

NASA Astrophysics Data System (ADS)

Zulvia, Ferani E.; Kuo, R. J.

2018-03-01

This paper proposes a classification algorithm based on a support vector machine (SVM) and gradient evolution (GE) algorithms. SVM algorithm has been widely used in classification. However, its result is significantly influenced by the parameters. Therefore, this paper aims to propose an improvement of SVM algorithm which can find the best SVMs’ parameters automatically. The proposed algorithm employs a GE algorithm to automatically determine the SVMs’ parameters. The GE algorithm takes a role as a global optimizer in finding the best parameter which will be used by SVM algorithm. The proposed GE-SVM algorithm is verified using some benchmark datasets and compared with other metaheuristic-based SVM algorithms. The experimental results show that the proposed GE-SVM algorithm obtains better results than other algorithms tested in this paper.

Gait-Event-Based Synchronization Method for Gait Rehabilitation Robots via a Bioinspired Adaptive Oscillator.

PubMed

Chen, Gong; Qi, Peng; Guo, Zhao; Yu, Haoyong

2017-06-01

In the field of gait rehabilitation robotics, achieving human-robot synchronization is very important. In this paper, a novel human-robot synchronization method using gait event information is proposed. This method includes two steps. First, seven gait events in one gait cycle are detected in real time with a hidden Markov model; second, an adaptive oscillator is utilized to estimate the stride percentage of human gait using any one of the gait events. Synchronous reference trajectories for the robot are then generated with the estimated stride percentage. This method is based on a bioinspired adaptive oscillator, which is a mathematical tool, first proposed to explain the phenomenon of synchronous flashing among fireflies. The proposed synchronization method is implemented in a portable knee-ankle-foot robot and tested in 15 healthy subjects. This method has the advantages of simple structure, flexible selection of gait events, and fast adaptation. Gait event is the only information needed, and hence the performance of synchronization holds when an abnormal gait pattern is involved. The results of the experiments reveal that our approach is efficient in achieving human-robot synchronization and feasible for rehabilitation robotics application.

Starshade Night Test

NASA Image and Video Library

2016-08-09

A night test of a small-scale starshade model, in a dry lake bed in central Nevada's Smith Creek by Northrup Grumman, took place in May to June 2014. A telescope points toward a bright light, which in the darkness of the desert mimics the conditions of starlight in space. Other lights, which are up to 10 million times fainter than the light source standing in for the star, represent the reflected light of planets. Telescopes searching for the relatively dim light of an exoplanet next to its much brighter star are faced with a challenge as difficult as searching from Los Angeles for a firefly in New York -- if the firefly is next to the brightness of a lighthouse. The tests by Northrup Grumman determined that a starshade, or external occulter, is capable of blocking starlight to a degree that can indeed reveal the light of a planet. http://photojournal.jpl.nasa.gov/catalog/PIA20901

Particles Co-orbital to Janus and to Epimetheus: A Firefly Planetary Ring

NASA Astrophysics Data System (ADS)

Winter, Othon C.; Souza, Alexandre P. S.; Sfair, Rafael; Giuliatti Winter, Silvia M.; Mourão, Daniela C.; Foryta, Dietmar W.

2018-01-01

The Cassini spacecraft found a new and unique ring that shares the trajectory of Janus and Epimetheus, co-orbital satellites of Saturn. Performing image analysis, we found this to be a continuous ring. Its width is between 30% and 50% larger than previously announced. We also verified that the ring behaves like a firefly. It can only be seen from time to time, when Cassini, the ring, and the Sun are arranged in a particular geometric configuration, in very high phase angles. Otherwise, it remains “in the dark,” invisible to Cassini’s cameras. Through numerical simulations, we found a very short lifetime for the ring particles, less than a couple of decades. Consequently, the ring needs to be constantly replenished. Using a model of particle production due to micrometeorites impacts on the surfaces of Janus and Epimetheus, we reproduce the ring, explaining its existence and the “firefly” behavior.

Illuminating insights into firefly luciferase and other bioluminescent reporters used in chemical biology

PubMed Central

Thorne, Natasha; Inglese, James; Auld, Douglas S.

2010-01-01

Summary Understanding luciferase enzymology and the structure of compounds that modulate luciferase activity can be used to improve the design of luminescence-based assays. This review provides an overview of these popular reporters with an emphasis on the commonly used firefly luciferase from Photinus pyralis (FLuc). Large-scale chemical profile studies have identified a variety of scaffolds that inhibit FLuc. In some cell-based assays these inhibitors can act in a counter-intuitive way –leading to a gain in luminescent signal. Although formerly attributed to transcriptional activation, intracellular stabilization of FLuc is the primary mechanism underlying this observation. FLuc inhibition/stabilization can be complex, as illustrated by the compound PTC124, which is converted by FLuc in the presence of ATP to a high affinity multi-substrate-adduct inhibitor, PTC124-AMP. The potential influence these findings can have on drug discovery efforts is provided here. PMID:20609414

Posttranslationally caused bioluminescence burst of the Escherichia coli luciferase reporter strain.

PubMed

Ideguchi, Yamato; Oshikoshi, Yuta; Ryo, Masashi; Motoki, Shogo; Kuwano, Takashi; Tezuka, Takafumi; Aoki, Setsuyuki

2016-01-01

We continuously monitored bioluminescence from a wild-type reporter strain of Escherichia coli (lacp::luc+/WT), which carries the promoter of the lac operon (lacp) fused with the firefly luciferase gene (luc+). This strain showed a bioluminescence burst when shifted into the stationary growth phase. Bioluminescence profiles of other wild-type reporter strains (rpsPp::luc+ and argAp::luc+) and gene-deletion reporter strains (lacp::luc+/crp- and lacp::luc+/lacI-) indicate that transcriptional regulation is not responsible for generation of the burst. Consistently, changes in the luciferase protein levels did not recapitulate the profile of the burst. On the other hand, dissolved oxygen levels increased over the period across the burst, suggesting that the burst is, at least partially, caused by an increase in intracellular oxygen levels. We discuss limits of the firefly luciferase when used as a reporter for gene expression and its potential utility for monitoring metabolic changes in cells.

A potential role for imaging technology in anticancer efficacy evaluations.

PubMed

Hollingshead, M G; Bonomi, C A; Borgel, S D; Carter, J P; Shoemaker, R; Melillo, G; Sausville, E A

2004-04-01

The introduction of imaging methods suitable for rodents offers opportunities for new anticancer efficacy models. Traditional models do not provide the level of sensitivity afforded by these precise and quantitative techniques. Bioluminescent endpoints, now feasible because of sensitive charge-coupled device cameras, can be non-invasively detected in live animals. Currently, the most common luminescence endpoint is firefly luciferase, which, in the presence of O(2) and ATP, catalyses the cleavage of the substrate luciferin and results in the emission of a photon of light. In vivo implantation of tumour cells transfected with the luciferase gene allows sequential monitoring of tumour growth within the viscera by measuring these photon signals. Furthermore, tumour cell lines containing the luciferase gene transcribed from an inducible promoter offer opportunities to study molecular-target modulation without the need for ex vivo evaluations of serial tumour samples. In conjunction with this, transgenic mice bearing a luciferase reporter mechanism can be used to monitor the tumour microenvironment as well as to signal when transforming events occur. This technology has the potential to reshape the efficacy evaluations and drug-testing algorithms of the future.

River flow simulation using a multilayer perceptron-firefly algorithm model

NASA Astrophysics Data System (ADS)

Darbandi, Sabereh; Pourhosseini, Fatemeh Akhoni

2018-06-01

River flow estimation using records of past time series is importance in water resources engineering and management and is required in hydrologic studies. In the past two decades, the approaches based on the artificial neural networks (ANN) were developed. River flow modeling is a non-linear process and highly affected by the inputs to the modeling. In this study, the best input combination of the models was identified using the Gamma test then MLP-ANN and hybrid multilayer perceptron (MLP-FFA) is used to forecast monthly river flow for a set of time intervals using observed data. The measurements from three gauge at Ajichay watershed, East Azerbaijani, were used to train and test the models approach for the period from January 2004 to July 2016. Calibration and validation were performed within the same period for MLP-ANN and MLP-FFA models after the preparation of the required data. Statistics, the root mean square error and determination coefficient, are used to verify outputs from MLP-ANN to MLP-FFA models. The results show that MLP-FFA model is satisfactory for monthly river flow simulation in study area.

A novel hybrid meta-heuristic technique applied to the well-known benchmark optimization problems

NASA Astrophysics Data System (ADS)

Abtahi, Amir-Reza; Bijari, Afsane

2017-03-01

In this paper, a hybrid meta-heuristic algorithm, based on imperialistic competition algorithm (ICA), harmony search (HS), and simulated annealing (SA) is presented. The body of the proposed hybrid algorithm is based on ICA. The proposed hybrid algorithm inherits the advantages of the process of harmony creation in HS algorithm to improve the exploitation phase of the ICA algorithm. In addition, the proposed hybrid algorithm uses SA to make a balance between exploration and exploitation phases. The proposed hybrid algorithm is compared with several meta-heuristic methods, including genetic algorithm (GA), HS, and ICA on several well-known benchmark instances. The comprehensive experiments and statistical analysis on standard benchmark functions certify the superiority of the proposed method over the other algorithms. The efficacy of the proposed hybrid algorithm is promising and can be used in several real-life engineering and management problems.

Inhibitory effects associated with use of modified Photinus pyralis and Renilla reniformis luciferase vectors in dual reporter assays and implications for analysis of ISGs.

PubMed

Ghazawi, Ibtisam; Cutler, Samuel J; Low, Pauline; Mellick, Albert S; Ralph, Stephen J

2005-02-01

Luciferase reporter constructs are widely used for analysis of gene regulation when characterizing promoter and enhancer elements. We report that the recently developed codon-modified Renilla luciferase construct included as an internal standard for cotransfection must be used with great caution with respect to the amount of DNA transfected. Also, the dual-luciferase reporter vectors encoding Photinus pyralis firefly or Renilla reniformis luciferase showed a linear increase in dose-response with increasing amounts of transfected DNA, but at higher levels of transfected DNA, a reduction in expressed levels of luciferase activity resulted. In addition, treatment with type I interferon (IFN) was found to significantly reduce levels of P. pyralis firefly and Renilla luciferase activity. In contrast, cells transfected with a green fluorescent protein (GFP) reporter construct showed no significant IFN-associated change. The reduction in luciferase activity resulting from IFN treatment was not due to IFN-mediated cytotoxicity, as no change in cellular propidium iodide (PI) staining was observed by flow cytometry. IFN treatment did not alter the levels of firefly luciferase activity in cell culture supernatants or the luciferase mRNA levels determined by quantitative real-time RT-PCR analysis. Based on these results, it is probable that the IFN-induced reduction in levels of luciferase activity detected in reporter assays occurs via a posttranscriptional mechanism. Thus, it is important to be aware of these complications when using luciferase reporter systems in general or for analyzing cytokine-mediated responsive regulation of target genes, particularly by the type I IFNs.

Molecular characterisation of four double-flowered mutants of Silene dioica representing four centuries of variation

PubMed Central

Ingle, Elizabeth K. S.; Gilmartin, Philip M.

2015-01-01

Records of double-flowered Silene dioica date from the late sixteenth century and four named varieties are grown today, as previously, for their horticultural interest. Although double-flowered mutants have been characterized in several plants, their study in dioecious species is of particular interest due to influences of the homeotic mutation on the different floral whorl configurations in males and females. We have analysed four double-flowered varieties of Silene dioica: Flore Pleno and Rosea Plena date back to the seventeenth and nineteenth centuries, Thelma Kay and Firefly were recognized in the latter part of the twentieth and early twenty-first centuries. We have analysed the floral structure of the four varieties, which have distinct floral architectures. Based on Y chromosome-specific PCR analysis we show that Firefly is male and that the other three varieties are female: Random Amplification of Polymorphic DNA (RAPD) analyses suggested a common origin for the three female varieties. The double-flowered phenotype in all four varieties is caused by mutation of the C-function MADS-box transcription factor gene SDM1. We show that Firefly carries a unique 44bp insertion into SDM1, revealing an independent origin for this variety. Comparative analysis of SDM1 cDNA and genomic sequences in Flore Pleno, Rosea Plena and Thelma Kay shows that all three are caused by the same 7bp insertion within SDM1 and therefore share a common origin. The three alleles also differ by several single nucleotide polymorphisms, which represent somatic mutations accumulated over four centuries of asexual propagation. PMID:25878355

Hsa-miR-195 targets PCMT1 in hepatocellular carcinoma that increases tumor life span.

PubMed

Amer, Marwa; Elhefnawi, M; El-Ahwany, Eman; Awad, A F; Gawad, Nermen Abdel; Zada, Suher; Tawab, F M Abdel

2014-11-01

MicroRNAs are small 19-25 nucleotides which have been shown to play important roles in the regulation of gene expression in many organisms. Downregulation or accumulation of miRNAs implies either tumor suppression or oncogenic activation. In this study, differentially expressed hsa-miR-195 in hepatocellular carcinoma (HCC) was identified and analyzed. The prediction was done using a consensus approach of tools. The validation steps were done at two different levels in silico and in vitro. FGF7, GHR, PCMT1, CITED2, PEX5, PEX13, NOVA1, AXIN2, and TSPYL2 were detected with high significant (P < 0.005). These genes are involved in important pathways in cancer like MAPK signaling pathway, Jak-STAT signaling pathways, regulation of actin cytoskeleton, angiogenesis, Wnt signaling pathway, and TGF-beta signaling pathway. In vitro target validation was done for protein-L-isoaspartate (D-aspartate) O-methyltransferase (PCMT1). The co-transfection of pmirGLO-PCMT1 and pEGP-miR-195 showed highly significant results. Firefly luciferase was detected using Lumiscensor and t test analysis was done. Firefly luciferase expression was significantly decreased (P < 0.001) in comparison to the control. The low expression of firefly luciferase validates the method of target prediction that we used in this work by working on PCMT1 as a target for miR-195. Furthermore, the rest of the predicted genes are suspected to be real targets for hsa-miR-195. These target genes control almost all the hallmarks of liver cancer which can be used as therapeutic targets in cancer treatment.

Laboratory procedures manual for the firefly luciferase assay for adenosine triphosphate (ATP)

NASA Technical Reports Server (NTRS)

Chappelle, E. W.; Picciolo, G. L.; Curtis, C. A.; Knust, E. A.; Nibley, D. A.; Vance, R. B.

1975-01-01

A manual on the procedures and instruments developed for the adenosine triphosphate (ATP) luciferase assay is presented. Data cover, laboratory maintenance, maintenance of bacterial cultures, bacteria measurement, reagents, luciferase procedures, and determination of microbal susceptibility to antibiotics.

Constrained independent component analysis approach to nonobtrusive pulse rate measurements

NASA Astrophysics Data System (ADS)

Tsouri, Gill R.; Kyal, Survi; Dianat, Sohail; Mestha, Lalit K.

2012-07-01

Nonobtrusive pulse rate measurement using a webcam is considered. We demonstrate how state-of-the-art algorithms based on independent component analysis suffer from a sorting problem which hinders their performance, and propose a novel algorithm based on constrained independent component analysis to improve performance. We present how the proposed algorithm extracts a photoplethysmography signal and resolves the sorting problem. In addition, we perform a comparative study between the proposed algorithm and state-of-the-art algorithms over 45 video streams using a finger probe oxymeter for reference measurements. The proposed algorithm provides improved accuracy: the root mean square error is decreased from 20.6 and 9.5 beats per minute (bpm) for existing algorithms to 3.5 bpm for the proposed algorithm. An error of 3.5 bpm is within the inaccuracy expected from the reference measurements. This implies that the proposed algorithm provided performance of equal accuracy to the finger probe oximeter.

Constrained independent component analysis approach to nonobtrusive pulse rate measurements.

PubMed

Tsouri, Gill R; Kyal, Survi; Dianat, Sohail; Mestha, Lalit K

2012-07-01

Nonobtrusive pulse rate measurement using a webcam is considered. We demonstrate how state-of-the-art algorithms based on independent component analysis suffer from a sorting problem which hinders their performance, and propose a novel algorithm based on constrained independent component analysis to improve performance. We present how the proposed algorithm extracts a photoplethysmography signal and resolves the sorting problem. In addition, we perform a comparative study between the proposed algorithm and state-of-the-art algorithms over 45 video streams using a finger probe oxymeter for reference measurements. The proposed algorithm provides improved accuracy: the root mean square error is decreased from 20.6 and 9.5 beats per minute (bpm) for existing algorithms to 3.5 bpm for the proposed algorithm. An error of 3.5 bpm is within the inaccuracy expected from the reference measurements. This implies that the proposed algorithm provided performance of equal accuracy to the finger probe oximeter.

21 CFR 864.7040 - Adenosine triphosphate release assay.

Code of Federal Regulations, 2014 CFR

2014-04-01

... device that measures the release of adenosine triphosphate (ATP) from platelets following aggregation. This measurement is made on platelet-rich plasma using a photometer and a luminescent firefly extract. Simultaneous measurements of platelet aggregation and ATP release are used to evaluate platelet function...

21 CFR 864.7040 - Adenosine triphosphate release assay.

Code of Federal Regulations, 2011 CFR

2011-04-01

... device that measures the release of adenosine triphosphate (ATP) from platelets following aggregation. This measurement is made on platelet-rich plasma using a photometer and a luminescent firefly extract. Simultaneous measurements of platelet aggregation and ATP release are used to evaluate platelet function...

21 CFR 864.7040 - Adenosine triphosphate release assay.

Code of Federal Regulations, 2013 CFR

2013-04-01

... device that measures the release of adenosine triphosphate (ATP) from platelets following aggregation. This measurement is made on platelet-rich plasma using a photometer and a luminescent firefly extract. Simultaneous measurements of platelet aggregation and ATP release are used to evaluate platelet function...

21 CFR 864.7040 - Adenosine triphosphate release assay.

Code of Federal Regulations, 2010 CFR

2010-04-01

... device that measures the release of adenosine triphosphate (ATP) from platelets following aggregation. This measurement is made on platelet-rich plasma using a photometer and a luminescent firefly extract. Simultaneous measurements of platelet aggregation and ATP release are used to evaluate platelet function...

21 CFR 864.7040 - Adenosine triphosphate release assay.

Code of Federal Regulations, 2012 CFR

2012-04-01

... device that measures the release of adenosine triphosphate (ATP) from platelets following aggregation. This measurement is made on platelet-rich plasma using a photometer and a luminescent firefly extract. Simultaneous measurements of platelet aggregation and ATP release are used to evaluate platelet function...

An EEG blind source separation algorithm based on a weak exclusion principle.

PubMed

Lan Ma; Blu, Thierry; Wang, William S-Y

2016-08-01

The question of how to separate individual brain and non-brain signals, mixed by volume conduction in electroencephalographic (EEG) and other electrophysiological recordings, is a significant problem in contemporary neuroscience. This study proposes and evaluates a novel EEG Blind Source Separation (BSS) algorithm based on a weak exclusion principle (WEP). The chief point in which it differs from most previous EEG BSS algorithms is that the proposed algorithm is not based upon the hypothesis that the sources are statistically independent. Our first step was to investigate algorithm performance on simulated signals which have ground truth. The purpose of this simulation is to illustrate the proposed algorithm's efficacy. The results show that the proposed algorithm has good separation performance. Then, we used the proposed algorithm to separate real EEG signals from a memory study using a revised version of Sternberg Task. The results show that the proposed algorithm can effectively separate the non-brain and brain sources.

A voting-based star identification algorithm utilizing local and global distribution

NASA Astrophysics Data System (ADS)

Fan, Qiaoyun; Zhong, Xuyang; Sun, Junhua

2018-03-01

A novel star identification algorithm based on voting scheme is presented in this paper. In the proposed algorithm, the global distribution and local distribution of sensor stars are fully utilized, and the stratified voting scheme is adopted to obtain the candidates for sensor stars. The database optimization is employed to reduce its memory requirement and improve the robustness of the proposed algorithm. The simulation shows that the proposed algorithm exhibits 99.81% identification rate with 2-pixel standard deviations of positional noises and 0.322-Mv magnitude noises. Compared with two similar algorithms, the proposed algorithm is more robust towards noise, and the average identification time and required memory is less. Furthermore, the real sky test shows that the proposed algorithm performs well on the real star images.

Hybrid Particle Swarm Optimization for Hybrid Flowshop Scheduling Problem with Maintenance Activities

PubMed Central

Li, Jun-qing; Pan, Quan-ke; Mao, Kun

2014-01-01

A hybrid algorithm which combines particle swarm optimization (PSO) and iterated local search (ILS) is proposed for solving the hybrid flowshop scheduling (HFS) problem with preventive maintenance (PM) activities. In the proposed algorithm, different crossover operators and mutation operators are investigated. In addition, an efficient multiple insert mutation operator is developed for enhancing the searching ability of the algorithm. Furthermore, an ILS-based local search procedure is embedded in the algorithm to improve the exploitation ability of the proposed algorithm. The detailed experimental parameter for the canonical PSO is tuning. The proposed algorithm is tested on the variation of 77 Carlier and Néron's benchmark problems. Detailed comparisons with the present efficient algorithms, including hGA, ILS, PSO, and IG, verify the efficiency and effectiveness of the proposed algorithm. PMID:24883414

Protein sterilization method of firefly luciferase using reduced pressure and molecular sieves

NASA Technical Reports Server (NTRS)

Chappelle, E. W.; Rich, E., Jr. (Inventor)

1973-01-01

The sterilization of the protein fruitfly luciferase under conditions that prevent denaturation is examined. Denaturation is prevented by heating the protein in contact with molecular seives and under a reduced pressure of the order of 0.00005 millimeters of mercury.

Application of firefly luciferase assay for adenosine triphosphate (ATP) to antimicrobial drug sensitivity testing

NASA Technical Reports Server (NTRS)

Picciolo, G. L.; Tuttle, S. A.; Schrock, C. G.; Deming, J. W.; Barza, M. J.; Wienstein, L.; Chappelle, E. W.

1977-01-01

The development of a rapid method for determining microbial susceptibilities to antibiotics using the firefly luciferase assay for adenosine triphosphate (ATP) is documented. The reduction of bacterial ATP by an antimicrobial agent was determined to be a valid measure of drug effect in most cases. The effect of 12 antibiotics on 8 different bacterial species gave a 94 percent correlation with the standard Kirby-Buer-Agar disc diffusion method. A 93 percent correlation was obtained when the ATP assay method was applied directly to 50 urine specimens from patients with urinary tract infections. Urine samples were centrifuged first to that bacterial pellets could be suspended in broth. No primary isolation or subculturing was required. Mixed cultures in which one species was predominant gave accurate results for the most abundant organism. Since the method is based on an increase in bacterial ATP with time, the presence of leukocytes did not interfere with the interpretation of results. Both the incubation procedure and the ATP assays are compatible with automation.

Highly specific expression of luciferase gene in lungs of naive nude mice directed by prostate-specific antigen promoter

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

Li Hongwei; Department of Neurological Surgery, University of Virginia Health System, Charlottesville, VA 22908; Li Jinzhong

PSA promoter has been demonstrated the utility for tissue-specific toxic gene therapy in prostate cancer models. Characterization of foreign gene overexpression in normal animals elicited by PSA promoter should help evaluate therapy safety. Here we constructed an adenovirus vector (AdPSA-Luc), containing firefly luciferase gene under the control of the 5837 bp long prostate-specific antigen promoter. A charge coupled device video camera was used to non-invasively image expression of firefly luciferase in nude mice on days 3, 7, 11 after injection of 2 x 10{sup 9} PFU of AdPSA-Luc virus via tail vein. The result showed highly specific expression of themore » luciferase gene in lungs of mice from day 7. The finding indicates the potential limitations of the suicide gene therapy of prostate cancer based on selectivity of PSA promoter. By contrary, it has encouraging implications for further development of vectors via PSA promoter to enable gene therapy for pulmonary diseases.« less

Long Term Non-Invasive Imaging of Embryonic Stem Cells Using Reporter Genes

PubMed Central

Sun, Ning; Lee, Andrew; Wu, Joseph C.

2013-01-01

Development of non-invasive and accurate methods to track cell fate following delivery will greatly expedite transition of embryonic stem (ES) cell therapy to the clinic. Here we describe a protocol for the in vivo monitoring of stem cell survival, proliferation, and migration using reporter genes. We established stable ES cell lines constitutively expressing double fusion (DF; enhanced green fluorescent protein and firefly luciferase) or triple fusion (TF; monomeric red fluorescent protein, firefly luciferase, and herpes simplex virus thymidine kinase) reporter genes using lentiviral transduction. We used fluorescence activated cell sorting to purify these populations in vitro, bioluminescence imaging and positron emission tomography imaging to track them in vivo, and fluorescence immunostaining to confirm the results ex vivo. Unlike other methods of cell tracking such as iron particle and radionuclide labeling, reporter genes are inherited genetically and can be used to monitor cell proliferation and survival for the lifetime of transplanted cells and their progeny. PMID:19617890

First-principles investigation on Rydberg and resonance excitations: A case study of the firefly luciferin anion

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

Noguchi, Yoshifumi, E-mail: y.noguchi@issp.u-tokyo.ac.jp; Hiyama, Miyabi; Akiyama, Hidefumi

2014-07-28

The optical properties of an isolated firefly luciferin anion are investigated by using first-principles calculations, employing the many-body perturbation theory to take into account the excitonic effect. The calculated photoabsorption spectra are compared with the results obtained using the time-dependent density functional theory (TDDFT) employing the localized atomic orbital (AO) basis sets and a recent experiment in vacuum. The present method well reproduces the line shape at the photon energy corresponding to the Rydberg and resonance excitations but overestimates the peak positions by about 0.5 eV. However, the TDDFT-calculated positions of some peaks are closer to those of the experiment.more » We also investigate the basis set dependency in describing the free electron states above vacuum level and the excitons involving the transitions to the free electron states and conclude that AO-only basis sets are inaccurate for free electron states and the use of a plane wave basis set is required.« less

Click beetle luciferase mutant and near infrared naphthyl-luciferins for improved bioluminescence imaging.

PubMed

Hall, Mary P; Woodroofe, Carolyn C; Wood, Monika G; Que, Ivo; Van't Root, Moniek; Ridwan, Yanto; Shi, Ce; Kirkland, Thomas A; Encell, Lance P; Wood, Keith V; Löwik, Clemens; Mezzanotte, Laura

2018-01-09

The sensitivity of bioluminescence imaging in animals is primarily dependent on the amount of photons emitted by the luciferase enzyme at wavelengths greater than 620 nm where tissue penetration is high. This area of work has been dominated by firefly luciferase and its substrate, D-luciferin, due to the system's peak emission (~ 600 nm), high signal to noise ratio, and generally favorable biodistribution of D-luciferin in mice. Here we report on the development of a codon optimized mutant of click beetle red luciferase that produces substantially more light output than firefly luciferase when the two enzymes are compared in transplanted cells within the skin of black fur mice or in deep brain. The mutant enzyme utilizes two new naphthyl-luciferin substrates to produce near infrared emission (730 nm and 743 nm). The stable luminescence signal and near infrared emission enable unprecedented sensitivity and accuracy for performing deep tissue multispectral tomography in mice.

Comparison of human optimized bacterial luciferase, firefly luciferase, and green fluorescent protein for continuous imaging of cell culture and animal models

NASA Astrophysics Data System (ADS)

Close, Dan M.; Hahn, Ruth E.; Patterson, Stacey S.; Baek, Seung J.; Ripp, Steven A.; Sayler, Gary S.

2011-04-01

Bioluminescent and fluorescent reporter systems have enabled the rapid and continued growth of the optical imaging field over the last two decades. Of particular interest has been noninvasive signal detection from mammalian tissues under both cell culture and whole animal settings. Here we report on the advantages and limitations of imaging using a recently introduced bacterial luciferase (lux) reporter system engineered for increased bioluminescent expression in the mammalian cellular environment. Comparison with the bioluminescent firefly luciferase (Luc) system and green fluorescent protein system under cell culture conditions demonstrated a reduced average radiance, but maintained a more constant level of bioluminescent output without the need for substrate addition or exogenous excitation to elicit the production of signal. Comparison with the Luc system following subcutaneous and intraperitoneal injection into nude mice hosts demonstrated the ability to obtain similar detection patterns with in vitro experiments at cell population sizes above 2.5 × 104 cells but at the cost of increasing overall image integration time.

Hyperspectral feature mapping classification based on mathematical morphology

NASA Astrophysics Data System (ADS)

Liu, Chang; Li, Junwei; Wang, Guangping; Wu, Jingli

2016-03-01

This paper proposed a hyperspectral feature mapping classification algorithm based on mathematical morphology. Without the priori information such as spectral library etc., the spectral and spatial information can be used to realize the hyperspectral feature mapping classification. The mathematical morphological erosion and dilation operations are performed respectively to extract endmembers. The spectral feature mapping algorithm is used to carry on hyperspectral image classification. The hyperspectral image collected by AVIRIS is applied to evaluate the proposed algorithm. The proposed algorithm is compared with minimum Euclidean distance mapping algorithm, minimum Mahalanobis distance mapping algorithm, SAM algorithm and binary encoding mapping algorithm. From the results of the experiments, it is illuminated that the proposed algorithm's performance is better than that of the other algorithms under the same condition and has higher classification accuracy.

Novel cooperative neural fusion algorithms for image restoration and image fusion.

PubMed

Xia, Youshen; Kamel, Mohamed S

2007-02-01

To deal with the problem of restoring degraded images with non-Gaussian noise, this paper proposes a novel cooperative neural fusion regularization (CNFR) algorithm for image restoration. Compared with conventional regularization algorithms for image restoration, the proposed CNFR algorithm can relax need of the optimal regularization parameter to be estimated. Furthermore, to enhance the quality of restored images, this paper presents a cooperative neural fusion (CNF) algorithm for image fusion. Compared with existing signal-level image fusion algorithms, the proposed CNF algorithm can greatly reduce the loss of contrast information under blind Gaussian noise environments. The performance analysis shows that the proposed two neural fusion algorithms can converge globally to the robust and optimal image estimate. Simulation results confirm that in different noise environments, the proposed two neural fusion algorithms can obtain a better image estimate than several well known image restoration and image fusion methods.

Evaluation of the CDC proposed laboratory HIV testing algorithm among men who have sex with men (MSM) from five US metropolitan statistical areas using specimens collected in 2011.

PubMed

Masciotra, Silvina; Smith, Amanda J; Youngpairoj, Ae S; Sprinkle, Patrick; Miles, Isa; Sionean, Catlainn; Paz-Bailey, Gabriela; Johnson, Jeffrey A; Owen, S Michele

2013-12-01

Until recently most testing algorithms in the United States (US) utilized Western blot (WB) as the supplemental test. CDC has proposed an algorithm for HIV diagnosis which includes an initial screen with a Combo Antigen/Antibody 4th generation-immunoassay (IA), followed by an HIV-1/2 discriminatory IA of initially reactive-IA specimens. Discordant results in the proposed algorithm are resolved by nucleic acid-amplification testing (NAAT). Evaluate the results obtained with the CDC proposed laboratory-based algorithm using specimens from men who have sex with men (MSM) obtained in five metropolitan statistical areas (MSAs). Specimens from 992 MSM from five MSAs participating in the CDC's National HIV Behavioral Surveillance System in 2011 were tested at local facilities and CDC. The five MSAs utilized algorithms of various screening assays and specimen types, and WB as the supplemental test. At the CDC, serum/plasma specimens were screened with 4th generation-IA and the Multispot HIV-1/HIV-2 discriminatory assay was used as the supplemental test. NAAT was used to resolve discordant results and to further identify acute HIV infections from all screened-non-reactive missed by the proposed algorithm. Performance of the proposed algorithm was compared to site-specific WB-based algorithms. The proposed algorithm detected 254 infections. The WB-based algorithms detected 19 fewer infections; 4 by oral fluid (OF) rapid testing and 15 by WB supplemental testing (12 OF and 3 blood). One acute infection was identified by NAAT from all screened-non-reactive specimens. The proposed algorithm identified more infections than the WB-based algorithms in a high-risk MSM population. OF testing was associated with most of the discordant results between algorithms. HIV testing with the proposed algorithm can increase diagnosis of infected individuals, including early infections. Published by Elsevier B.V.

Travelling Wave Pulse Coupled Oscillator (TWPCO) Using a Self-Organizing Scheme for Energy-Efficient Wireless Sensor Networks.

PubMed

Al-Mekhlafi, Zeyad Ghaleb; Hanapi, Zurina Mohd; Othman, Mohamed; Zukarnain, Zuriati Ahmad

2017-01-01

Recently, Pulse Coupled Oscillator (PCO)-based travelling waves have attracted substantial attention by researchers in wireless sensor network (WSN) synchronization. Because WSNs are generally artificial occurrences that mimic natural phenomena, the PCO utilizes firefly synchronization of attracting mating partners for modelling the WSN. However, given that sensor nodes are unable to receive messages while transmitting data packets (due to deafness), the PCO model may not be efficient for sensor network modelling. To overcome this limitation, this paper proposed a new scheme called the Travelling Wave Pulse Coupled Oscillator (TWPCO). For this, the study used a self-organizing scheme for energy-efficient WSNs that adopted travelling wave biologically inspired network systems based on phase locking of the PCO model to counteract deafness. From the simulation, it was found that the proposed TWPCO scheme attained a steady state after a number of cycles. It also showed superior performance compared to other mechanisms, with a reduction in the total energy consumption of 25%. The results showed that the performance improved by 13% in terms of data gathering. Based on the results, the proposed scheme avoids the deafness that occurs in the transmit state in WSNs and increases the data collection throughout the transmission states in WSNs.

Travelling Wave Pulse Coupled Oscillator (TWPCO) Using a Self-Organizing Scheme for Energy-Efficient Wireless Sensor Networks

PubMed Central

Hanapi, Zurina Mohd; Othman, Mohamed; Zukarnain, Zuriati Ahmad

2017-01-01

Recently, Pulse Coupled Oscillator (PCO)-based travelling waves have attracted substantial attention by researchers in wireless sensor network (WSN) synchronization. Because WSNs are generally artificial occurrences that mimic natural phenomena, the PCO utilizes firefly synchronization of attracting mating partners for modelling the WSN. However, given that sensor nodes are unable to receive messages while transmitting data packets (due to deafness), the PCO model may not be efficient for sensor network modelling. To overcome this limitation, this paper proposed a new scheme called the Travelling Wave Pulse Coupled Oscillator (TWPCO). For this, the study used a self-organizing scheme for energy-efficient WSNs that adopted travelling wave biologically inspired network systems based on phase locking of the PCO model to counteract deafness. From the simulation, it was found that the proposed TWPCO scheme attained a steady state after a number of cycles. It also showed superior performance compared to other mechanisms, with a reduction in the total energy consumption of 25%. The results showed that the performance improved by 13% in terms of data gathering. Based on the results, the proposed scheme avoids the deafness that occurs in the transmit state in WSNs and increases the data collection throughout the transmission states in WSNs. PMID:28056020

Bug City: Ladybugs & Fireflies [Videotape].

ERIC Educational Resources Information Center

1998

"Bug City" is a video series created to help children (grades 1-6) learn about insects and other small critters. All aspects of bug life are touched upon, including body structure, food, habitat, life cycle, mating habits, camouflage, mutualism (symbiosis), adaptations, social behavior, and more. Each program features dramatic…

Fireflies in the Coalmine: Luciferase Technologies in Next-Generation Toxicity Testing

EPA Science Inventory

Whole-animal studies have been the mainstay of toxicity testing for decades. These approaches are too expensive and laborious to effectively characterize all of the chemicals currently in commercial use. In addition, there are social and ethical pressures to reduce, refine and re...

3-Dimensional stereo implementation of photoacoustic imaging based on a new image reconstruction algorithm without using discrete Fourier transform

NASA Astrophysics Data System (ADS)

Ham, Woonchul; Song, Chulgyu

2017-05-01

In this paper, we propose a new three-dimensional stereo image reconstruction algorithm for a photoacoustic medical imaging system. We also introduce and discuss a new theoretical algorithm by using the physical concept of Radon transform. The main key concept of proposed theoretical algorithm is to evaluate the existence possibility of the acoustic source within a searching region by using the geometric distance between each sensor element of acoustic detector and the corresponding searching region denoted by grid. We derive the mathematical equation for the magnitude of the existence possibility which can be used for implementing a new proposed algorithm. We handle and derive mathematical equations of proposed algorithm for the one-dimensional sensing array case as well as two dimensional sensing array case too. A mathematical k-wave simulation data are used for comparing the image quality of the proposed algorithm with that of general conventional algorithm in which the FFT should be necessarily used. From the k-wave Matlab simulation results, we can prove the effectiveness of the proposed reconstruction algorithm.

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.

Cryptanalysis of "an improvement over an image encryption method based on total shuffling"

NASA Astrophysics Data System (ADS)

Akhavan, A.; Samsudin, A.; Akhshani, A.

2015-09-01

In the past two decades, several image encryption algorithms based on chaotic systems had been proposed. Many of the proposed algorithms are meant to improve other chaos based and conventional cryptographic algorithms. Whereas, many of the proposed improvement methods suffer from serious security problems. In this paper, the security of the recently proposed improvement method for a chaos-based image encryption algorithm is analyzed. The results indicate the weakness of the analyzed algorithm against chosen plain-text.

A new approach to the convective parameterization of the regional atmospheric model BRAMS

NASA Astrophysics Data System (ADS)

Dos Santos, A. F.; Freitas, S. R.; de Campos Velho, H. F.; Luz, E. F.; Gan, M. A.; de Mattos, J. Z.; Grell, G. A.

2013-05-01

The summer characteristics of January 2010 was performed using the atmospheric model Brazilian developments on the Regional Atmospheric Modeling System (BRAMS). The convective parameterization scheme of Grell and Dévényi was used to represent clouds and their interaction with the large scale environment. As a result, the precipitation forecasts can be combined in several ways, generating a numerical representation of precipitation and atmospheric heating and moistening rates. The purpose of this study was to generate a set of weights to compute a best combination of the hypothesis of the convective scheme. It is an inverse problem of parameter estimation and the problem is solved as an optimization problem. To minimize the difference between observed data and forecasted precipitation, the objective function was computed with the quadratic difference between five simulated precipitation fields and observation. The precipitation field estimated by the Tropical Rainfall Measuring Mission satellite was used as observed data. Weights were obtained using the firefly algorithm and the mass fluxes of each closure of the convective scheme were weighted generating a new set of mass fluxes. The results indicated the better skill of the model with the new methodology compared with the old ensemble mean calculation.

A modified genetic algorithm with fuzzy roulette wheel selection for job-shop scheduling problems

NASA Astrophysics Data System (ADS)

Thammano, Arit; Teekeng, Wannaporn

2015-05-01

The job-shop scheduling problem is one of the most difficult production planning problems. Since it is in the NP-hard class, a recent trend in solving the job-shop scheduling problem is shifting towards the use of heuristic and metaheuristic algorithms. This paper proposes a novel metaheuristic algorithm, which is a modification of the genetic algorithm. This proposed algorithm introduces two new concepts to the standard genetic algorithm: (1) fuzzy roulette wheel selection and (2) the mutation operation with tabu list. The proposed algorithm has been evaluated and compared with several state-of-the-art algorithms in the literature. The experimental results on 53 JSSPs show that the proposed algorithm is very effective in solving the combinatorial optimization problems. It outperforms all state-of-the-art algorithms on all benchmark problems in terms of the ability to achieve the optimal solution and the computational time.

New Dandelion Algorithm Optimizes Extreme Learning Machine for Biomedical Classification Problems

PubMed Central

Li, Xiguang; Zhao, Liang; Gong, Changqing; Liu, Xiaojing

2017-01-01

Inspired by the behavior of dandelion sowing, a new novel swarm intelligence algorithm, namely, dandelion algorithm (DA), is proposed for global optimization of complex functions in this paper. In DA, the dandelion population will be divided into two subpopulations, and different subpopulations will undergo different sowing behaviors. Moreover, another sowing method is designed to jump out of local optimum. In order to demonstrate the validation of DA, we compare the proposed algorithm with other existing algorithms, including bat algorithm, particle swarm optimization, and enhanced fireworks algorithm. Simulations show that the proposed algorithm seems much superior to other algorithms. At the same time, the proposed algorithm can be applied to optimize extreme learning machine (ELM) for biomedical classification problems, and the effect is considerable. At last, we use different fusion methods to form different fusion classifiers, and the fusion classifiers can achieve higher accuracy and better stability to some extent. PMID:29085425

An improved VSS NLMS algorithm for active noise cancellation

NASA Astrophysics Data System (ADS)

Sun, Yunzhuo; Wang, Mingjiang; Han, Yufei; Zhang, Congyan

2017-08-01

In this paper, an improved variable step size NLMS algorithm is proposed. NLMS has fast convergence rate and low steady state error compared to other traditional adaptive filtering algorithm. But there is a contradiction between the convergence speed and steady state error that affect the performance of the NLMS algorithm. Now, we propose a new variable step size NLMS algorithm. It dynamically changes the step size according to current error and iteration times. The proposed algorithm has simple formulation and easily setting parameters, and effectively solves the contradiction in NLMS. The simulation results show that the proposed algorithm has a good tracking ability, fast convergence rate and low steady state error simultaneously.

A genetic algorithm for replica server placement

NASA Astrophysics Data System (ADS)

Eslami, Ghazaleh; Toroghi Haghighat, Abolfazl

2012-01-01

Modern distribution systems use replication to improve communication delay experienced by their clients. Some techniques have been developed for web server replica placement. One of the previous studies was Greedy algorithm proposed by Qiu et al, that needs knowledge about network topology. In This paper, first we introduce a genetic algorithm for web server replica placement. Second, we compare our algorithm with Greedy algorithm proposed by Qiu et al, and Optimum algorithm. We found that our approach can achieve better results than Greedy algorithm proposed by Qiu et al but it's computational time is more than Greedy algorithm.

A genetic algorithm for replica server placement

NASA Astrophysics Data System (ADS)

Eslami, Ghazaleh; Toroghi Haghighat, Abolfazl

2011-12-01

Modern distribution systems use replication to improve communication delay experienced by their clients. Some techniques have been developed for web server replica placement. One of the previous studies was Greedy algorithm proposed by Qiu et al, that needs knowledge about network topology. In This paper, first we introduce a genetic algorithm for web server replica placement. Second, we compare our algorithm with Greedy algorithm proposed by Qiu et al, and Optimum algorithm. We found that our approach can achieve better results than Greedy algorithm proposed by Qiu et al but it's computational time is more than Greedy algorithm.

A Genetic Approach to the Identification of Plant Genes Involved in Viral Movement

DTIC Science & Technology

1999-09-30

Arabidopsis.. We plan to create two transgenic plant lines of Arabidopsis, one that expresses the firefly luciferase (Luc) gene, and one that... transgenic plant lines that express Luc or CD upon infection with RCNMV. Phenotypically these lines will either be luminescent (Luc) or sensitive to 5

Automated detection of bacteria in urine

NASA Technical Reports Server (NTRS)

Fleig, A. J.; Picciolo, G. L.; Chappelle, E. W.; Kelbaugh, B. N.

1972-01-01

A method for detecting the presence of bacteria in urine was developed which utilizes the bioluminescent reaction of adenosine triphosphate with luciferin and luciferase derived from the tails of fireflies. The method was derived from work on extraterrestrial life detection. A device was developed which completely automates the assay process.

Efficient Pricing Technique for Resource Allocation Problem in Downlink OFDM Cognitive Radio Networks

NASA Astrophysics Data System (ADS)

Abdulghafoor, O. B.; Shaat, M. M. R.; Ismail, M.; Nordin, R.; Yuwono, T.; Alwahedy, O. N. A.

2017-05-01

In this paper, the problem of resource allocation in OFDM-based downlink cognitive radio (CR) networks has been proposed. The purpose of this research is to decrease the computational complexity of the resource allocation algorithm for downlink CR network while concerning the interference constraint of primary network. The objective has been secured by adopting pricing scheme to develop power allocation algorithm with the following concerns: (i) reducing the complexity of the proposed algorithm and (ii) providing firm power control to the interference introduced to primary users (PUs). The performance of the proposed algorithm is tested for OFDM- CRNs. The simulation results show that the performance of the proposed algorithm approached the performance of the optimal algorithm at a lower computational complexity, i.e., O(NlogN), which makes the proposed algorithm suitable for more practical applications.

Variable forgetting factor mechanisms for diffusion recursive least squares algorithm in sensor networks

NASA Astrophysics Data System (ADS)

Zhang, Ling; Cai, Yunlong; Li, Chunguang; de Lamare, Rodrigo C.

2017-12-01

In this work, we present low-complexity variable forgetting factor (VFF) techniques for diffusion recursive least squares (DRLS) algorithms. Particularly, we propose low-complexity VFF-DRLS algorithms for distributed parameter and spectrum estimation in sensor networks. For the proposed algorithms, they can adjust the forgetting factor automatically according to the posteriori error signal. We develop detailed analyses in terms of mean and mean square performance for the proposed algorithms and derive mathematical expressions for the mean square deviation (MSD) and the excess mean square error (EMSE). The simulation results show that the proposed low-complexity VFF-DRLS algorithms achieve superior performance to the existing DRLS algorithm with fixed forgetting factor when applied to scenarios of distributed parameter and spectrum estimation. Besides, the simulation results also demonstrate a good match for our proposed analytical expressions.

Super-resolution algorithm based on sparse representation and wavelet preprocessing for remote sensing imagery

NASA Astrophysics Data System (ADS)

Ren, Ruizhi; Gu, Lingjia; Fu, Haoyang; Sun, Chenglin

2017-04-01

An effective super-resolution (SR) algorithm is proposed for actual spectral remote sensing images based on sparse representation and wavelet preprocessing. The proposed SR algorithm mainly consists of dictionary training and image reconstruction. Wavelet preprocessing is used to establish four subbands, i.e., low frequency, horizontal, vertical, and diagonal high frequency, for an input image. As compared to the traditional approaches involving the direct training of image patches, the proposed approach focuses on the training of features derived from these four subbands. The proposed algorithm is verified using different spectral remote sensing images, e.g., moderate-resolution imaging spectroradiometer (MODIS) images with different bands, and the latest Chinese Jilin-1 satellite images with high spatial resolution. According to the visual experimental results obtained from the MODIS remote sensing data, the SR images using the proposed SR algorithm are superior to those using a conventional bicubic interpolation algorithm or traditional SR algorithms without preprocessing. Fusion algorithms, e.g., standard intensity-hue-saturation, principal component analysis, wavelet transform, and the proposed SR algorithms are utilized to merge the multispectral and panchromatic images acquired by the Jilin-1 satellite. The effectiveness of the proposed SR algorithm is assessed by parameters such as peak signal-to-noise ratio, structural similarity index, correlation coefficient, root-mean-square error, relative dimensionless global error in synthesis, relative average spectral error, spectral angle mapper, and the quality index Q4, and its performance is better than that of the standard image fusion algorithms.

A learning approach to the bandwidth multicolouring problem

NASA Astrophysics Data System (ADS)

Akbari Torkestani, Javad

2016-05-01

In this article, a generalisation of the vertex colouring problem known as bandwidth multicolouring problem (BMCP), in which a set of colours is assigned to each vertex such that the difference between the colours, assigned to each vertex and its neighbours, is by no means less than a predefined threshold, is considered. It is shown that the proposed method can be applied to solve the bandwidth colouring problem (BCP) as well. BMCP is known to be NP-hard in graph theory, and so a large number of approximation solutions, as well as exact algorithms, have been proposed to solve it. In this article, two learning automata-based approximation algorithms are proposed for estimating a near-optimal solution to the BMCP. We show, for the first proposed algorithm, that by choosing a proper learning rate, the algorithm finds the optimal solution with a probability close enough to unity. Moreover, we compute the worst-case time complexity of the first algorithm for finding a 1/(1-ɛ) optimal solution to the given problem. The main advantage of this method is that a trade-off between the running time of algorithm and the colour set size (colouring optimality) can be made, by a proper choice of the learning rate also. Finally, it is shown that the running time of the proposed algorithm is independent of the graph size, and so it is a scalable algorithm for large graphs. The second proposed algorithm is compared with some well-known colouring algorithms and the results show the efficiency of the proposed algorithm in terms of the colour set size and running time of algorithm.

An improved non-uniformity correction algorithm and its hardware implementation on FPGA

NASA Astrophysics Data System (ADS)

Rong, Shenghui; Zhou, Huixin; Wen, Zhigang; Qin, Hanlin; Qian, Kun; Cheng, Kuanhong

2017-09-01

The Non-uniformity of Infrared Focal Plane Arrays (IRFPA) severely degrades the infrared image quality. An effective non-uniformity correction (NUC) algorithm is necessary for an IRFPA imaging and application system. However traditional scene-based NUC algorithm suffers the image blurring and artificial ghosting. In addition, few effective hardware platforms have been proposed to implement corresponding NUC algorithms. Thus, this paper proposed an improved neural-network based NUC algorithm by the guided image filter and the projection-based motion detection algorithm. First, the guided image filter is utilized to achieve the accurate desired image to decrease the artificial ghosting. Then a projection-based moving detection algorithm is utilized to determine whether the correction coefficients should be updated or not. In this way the problem of image blurring can be overcome. At last, an FPGA-based hardware design is introduced to realize the proposed NUC algorithm. A real and a simulated infrared image sequences are utilized to verify the performance of the proposed algorithm. Experimental results indicated that the proposed NUC algorithm can effectively eliminate the fix pattern noise with less image blurring and artificial ghosting. The proposed hardware design takes less logic elements in FPGA and spends less clock cycles to process one frame of image.

An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors

PubMed Central

Luo, Liyan; Xu, Luping; Zhang, Hua

2015-01-01

In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms. PMID:26198233

An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors.

PubMed

Luo, Liyan; Xu, Luping; Zhang, Hua

2015-07-07

In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms.

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.

Intermediate view reconstruction using adaptive disparity search algorithm for real-time 3D processing

NASA Astrophysics Data System (ADS)

Bae, Kyung-hoon; Park, Changhan; Kim, Eun-soo

2008-03-01

In this paper, intermediate view reconstruction (IVR) using adaptive disparity search algorithm (ASDA) is for realtime 3-dimensional (3D) processing proposed. The proposed algorithm can reduce processing time of disparity estimation by selecting adaptive disparity search range. Also, the proposed algorithm can increase the quality of the 3D imaging. That is, by adaptively predicting the mutual correlation between stereo images pair using the proposed algorithm, the bandwidth of stereo input images pair can be compressed to the level of a conventional 2D image and a predicted image also can be effectively reconstructed using a reference image and disparity vectors. From some experiments, stereo sequences of 'Pot Plant' and 'IVO', it is shown that the proposed algorithm improves the PSNRs of a reconstructed image to about 4.8 dB by comparing with that of conventional algorithms, and reduces the Synthesizing time of a reconstructed image to about 7.02 sec by comparing with that of conventional algorithms.

Iterative Nonlocal Total Variation Regularization Method for Image Restoration

PubMed Central

Xu, Huanyu; Sun, Quansen; Luo, Nan; Cao, Guo; Xia, Deshen

2013-01-01

In this paper, a Bregman iteration based total variation image restoration algorithm is proposed. Based on the Bregman iteration, the algorithm splits the original total variation problem into sub-problems that are easy to solve. Moreover, non-local regularization is introduced into the proposed algorithm, and a method to choose the non-local filter parameter locally and adaptively is proposed. Experiment results show that the proposed algorithms outperform some other regularization methods. PMID:23776560

Functional grouping of similar genes using eigenanalysis on minimum spanning tree based neighborhood graph.

PubMed

Jothi, R; Mohanty, Sraban Kumar; Ojha, Aparajita

2016-04-01

Gene expression data clustering is an important biological process in DNA microarray analysis. Although there have been many clustering algorithms for gene expression analysis, finding a suitable and effective clustering algorithm is always a challenging problem due to the heterogeneous nature of gene profiles. Minimum Spanning Tree (MST) based clustering algorithms have been successfully employed to detect clusters of varying shapes and sizes. This paper proposes a novel clustering algorithm using Eigenanalysis on Minimum Spanning Tree based neighborhood graph (E-MST). As MST of a set of points reflects the similarity of the points with their neighborhood, the proposed algorithm employs a similarity graph obtained from k(') rounds of MST (k(')-MST neighborhood graph). By studying the spectral properties of the similarity matrix obtained from k(')-MST graph, the proposed algorithm achieves improved clustering results. We demonstrate the efficacy of the proposed algorithm on 12 gene expression datasets. Experimental results show that the proposed algorithm performs better than the standard clustering algorithms. Copyright © 2016 Elsevier Ltd. All rights reserved.

A noniterative greedy algorithm for multiframe point correspondence.

PubMed

Shafique, Khurram; Shah, Mubarak

2005-01-01

This paper presents a framework for finding point correspondences in monocular image sequences over multiple frames. The general problem of multiframe point correspondence is NP-hard for three or more frames. A polynomial time algorithm for a restriction of this problem is presented and is used as the basis of the proposed greedy algorithm for the general problem. The greedy nature of the proposed algorithm allows it to be used in real-time systems for tracking and surveillance, etc. In addition, the proposed algorithm deals with the problems of occlusion, missed detections, and false positives by using a single noniterative greedy optimization scheme and, hence, reduces the complexity of the overall algorithm as compared to most existing approaches where multiple heuristics are used for the same purpose. While most greedy algorithms for point tracking do not allow for entry and exit of the points from the scene, this is not a limitation for the proposed algorithm. Experiments with real and synthetic data over a wide range of scenarios and system parameters are presented to validate the claims about the performance of the proposed algorithm.

Simultaneous and semi-alternating projection algorithms for solving split equality problems.

PubMed

Dong, Qiao-Li; Jiang, Dan

2018-01-01

In this article, we first introduce two simultaneous projection algorithms for solving the split equality problem by using a new choice of the stepsize, and then propose two semi-alternating projection algorithms. The weak convergence of the proposed algorithms is analyzed under standard conditions. As applications, we extend the results to solve the split feasibility problem. Finally, a numerical example is presented to illustrate the efficiency and advantage of the proposed algorithms.

Compressive sensing of electrocardiogram signals by promoting sparsity on the second-order difference and by using dictionary learning.

PubMed

Pant, Jeevan K; Krishnan, Sridhar

2014-04-01

A new algorithm for the reconstruction of electrocardiogram (ECG) signals and a dictionary learning algorithm for the enhancement of its reconstruction performance for a class of signals are proposed. The signal reconstruction algorithm is based on minimizing the lp pseudo-norm of the second-order difference, called as the lp(2d) pseudo-norm, of the signal. The optimization involved is carried out using a sequential conjugate-gradient algorithm. The dictionary learning algorithm uses an iterative procedure wherein a signal reconstruction and a dictionary update steps are repeated until a convergence criterion is satisfied. The signal reconstruction step is implemented by using the proposed signal reconstruction algorithm and the dictionary update step is implemented by using the linear least-squares method. Extensive simulation results demonstrate that the proposed algorithm yields improved reconstruction performance for temporally correlated ECG signals relative to the state-of-the-art lp(1d)-regularized least-squares and Bayesian learning based algorithms. Also for a known class of signals, the reconstruction performance of the proposed algorithm can be improved by applying it in conjunction with a dictionary obtained using the proposed dictionary learning algorithm.

Efficient FFT Algorithm for Psychoacoustic Model of the MPEG-4 AAC

NASA Astrophysics Data System (ADS)

Lee, Jae-Seong; Lee, Chang-Joon; Park, Young-Cheol; Youn, Dae-Hee

This paper proposes an efficient FFT algorithm for the Psycho-Acoustic Model (PAM) of MPEG-4 AAC. The proposed algorithm synthesizes FFT coefficients using MDCT and MDST coefficients through circular convolution. The complexity of the MDCT and MDST coefficients is approximately half of the original FFT. We also design a new PAM based on the proposed FFT algorithm, which has 15% lower computational complexity than the original PAM without degradation of sound quality. Subjective as well as objective test results are presented to confirm the efficiency of the proposed FFT computation algorithm and the PAM.

Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

PubMed

Alshamlan, Hala M; Badr, Ghada H; Alohali, Yousef A

2015-06-01

Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene selection method, namely Genetic Bee Colony (GBC) algorithm. The proposed algorithm combines the used of a Genetic Algorithm (GA) along with Artificial Bee Colony (ABC) algorithm. The goal is to integrate the advantages of both algorithms. The proposed algorithm is applied to a microarray gene expression profile in order to select the most predictive and informative genes for cancer classification. In order to test the accuracy performance of the proposed algorithm, extensive experiments were conducted. Three binary microarray datasets are use, which include: colon, leukemia, and lung. In addition, another three multi-class microarray datasets are used, which are: SRBCT, lymphoma, and leukemia. Results of the GBC algorithm are compared with our recently proposed technique: mRMR when combined with the Artificial Bee Colony algorithm (mRMR-ABC). We also compared the combination of mRMR with GA (mRMR-GA) and Particle Swarm Optimization (mRMR-PSO) algorithms. In addition, we compared the GBC algorithm with other related algorithms that have been recently published in the literature, using all benchmark datasets. The GBC algorithm shows superior performance as it achieved the highest classification accuracy along with the lowest average number of selected genes. This proves that the GBC algorithm is a promising approach for solving the gene selection problem in both binary and multi-class cancer classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

Filtered-x generalized mixed norm (FXGMN) algorithm for active noise control

NASA Astrophysics Data System (ADS)

Song, Pucha; Zhao, Haiquan

2018-07-01

The standard adaptive filtering algorithm with a single error norm exhibits slow convergence rate and poor noise reduction performance under specific environments. To overcome this drawback, a filtered-x generalized mixed norm (FXGMN) algorithm for active noise control (ANC) system is proposed. The FXGMN algorithm is developed by using a convex mixture of lp and lq norms as the cost function that it can be viewed as a generalized version of the most existing adaptive filtering algorithms, and it will reduce to a specific algorithm by choosing certain parameters. Especially, it can be used to solve the ANC under Gaussian and non-Gaussian noise environments (including impulsive noise with symmetric α -stable (SαS) distribution). To further enhance the algorithm performance, namely convergence speed and noise reduction performance, a convex combination of the FXGMN algorithm (C-FXGMN) is presented. Moreover, the computational complexity of the proposed algorithms is analyzed, and a stability condition for the proposed algorithms is provided. Simulation results show that the proposed FXGMN and C-FXGMN algorithms can achieve better convergence speed and higher noise reduction as compared to other existing algorithms under various noise input conditions, and the C-FXGMN algorithm outperforms the FXGMN.

CLEMSON UNIVERSITY’S VANISHING FIREFLY PROJECT: USING A MOBILE PHONE APP AS EDUCATIONAL AND RESEARCH TOOLS FOR SUSTAINABILITY

EPA Science Inventory

This mobile phone app provides an opportunity for citizens to participate in community-based research project.  This unique hands-on experience will educate general public about the value of forest and natural ecosystems and the concept of sustainable development. The ...

Novel Cell-Based Assays for Detecting Low Levels of Active Ricin Following Decontamination

DTIC Science & Technology

2011-12-01

fluorescent protein, are powerful tools, which have been used for detection assays for ricin protein ( DeWet , 1987). Zhao et al. (2005) have reported a...toxic Type 2 Ribosome-Inactivating Proteins. FEBS Lett. 2004, 563, pp 219–222. DeWet , J.R. et al. Firefly Luciferase Gene: Structure and

Inhibition of Th17 Cell Differentiation as a Treatment for Multiple Sclerosis

DTIC Science & Technology

2012-10-01

sequence) using Lipofectamine . After 48 hours Dual Glo substrate was added to the cells and luciferase activity and Renilla Luciferase activity were...pmirGLO326 and pMR04 (encoding mir-326) using Lipofectamine . After 48 hours Dual Glo substrate was added to the cells and Firefly and Renilla

Geolocating thermal binoculars based on a software defined camera core incorporating HOT MCT grown by MOVPE

NASA Astrophysics Data System (ADS)

Pillans, Luke; Harmer, Jack; Edwards, Tim; Richardson, Lee

2016-05-01

Geolocation is the process of calculating a target position based on bearing and range relative to the known location of the observer. A high performance thermal imager with integrated geolocation functions is a powerful long range targeting device. Firefly is a software defined camera core incorporating a system-on-a-chip processor running the AndroidTM operating system. The processor has a range of industry standard serial interfaces which were used to interface to peripheral devices including a laser rangefinder and a digital magnetic compass. The core has built in Global Positioning System (GPS) which provides the third variable required for geolocation. The graphical capability of Firefly allowed flexibility in the design of the man-machine interface (MMI), so the finished system can give access to extensive functionality without appearing cumbersome or over-complicated to the user. This paper covers both the hardware and software design of the system, including how the camera core influenced the selection of peripheral hardware, and the MMI design process which incorporated user feedback at various stages.

Bioluminescent system for dynamic imaging of cell and animal behavior

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

Hara-Miyauchi, Chikako; Laboratory for Cell Function Dynamics, Brain Science Institute, RIKEN, Saitama 351-0198; Department of Biophysics and Biochemistry, Graduate School of Health Care Sciences, Tokyo Medical and Dental University, Tokyo 113-8510

2012-03-09

Highlights: Black-Right-Pointing-Pointer We combined a yellow variant of GFP and firefly luciferase to make ffLuc-cp156. Black-Right-Pointing-Pointer ffLuc-cp156 showed improved photon yield in cultured cells and transgenic mice. Black-Right-Pointing-Pointer ffLuc-cp156 enabled video-rate bioluminescence imaging of freely-moving animals. Black-Right-Pointing-Pointer ffLuc-cp156 mice enabled tracking real-time drug delivery in conscious animals. -- Abstract: The current utility of bioluminescence imaging is constrained by a low photon yield that limits temporal sensitivity. Here, we describe an imaging method that uses a chemiluminescent/fluorescent protein, ffLuc-cp156, which consists of a yellow variant of Aequorea GFP and firefly luciferase. We report an improvement in photon yield by over threemore » orders of magnitude over current bioluminescent systems. We imaged cellular movement at high resolution including neuronal growth cones and microglial cell protrusions. Transgenic ffLuc-cp156 mice enabled video-rate bioluminescence imaging of freely moving animals, which may provide a reliable assay for drug distribution in behaving animals for pre-clinical studies.« less

Modelling chemical reactions by QM/MM calculations: the case of the tautomerization in fireflies bioluminescent systems

NASA Astrophysics Data System (ADS)

Berraud-Pache, Romain; Garcia-Iriepa, Cristina; Navizet, Isabelle

2018-04-01

In less than half a century, the hybrid QM/MM method has become one of the most used technique to model molecules embedded in a complex environment. A well-known application of the QM/MM method is for biological systems. Nowadays, one can understand how enzymatic reactions work or compute spectroscopic properties, like the wavelength of emission. Here, we have tackled the issue of modelling chemical reactions inside proteins. We have studied a bioluminescent system, fireflies, and deciphered if a keto-enol tautomerization is possible inside the protein. The two tautomers are candidates to be the emissive molecule of the bioluminescence but no outcome has been reached. One hypothesis is to consider a possible keto-enol tautomerization to treat this issue, as it has been already observed in water. A joint approach combining extensive MD simulations as well as computation of key intermediates like TS using QM/MM calculations is presented in this publication. We also emphasize the procedure and difficulties met during this approach in order to give a guide for this kind of chemical reactions using QM/MM methods.

Excited-state proton transfer dynamics of firefly's chromophore D-luciferin in DMSO-water binary mixture.

PubMed

Kuchlyan, Jagannath; Banik, Debasis; Roy, Arpita; Kundu, Niloy; Sarkar, Nilmoni

2014-12-04

In this article we have investigated intermolecular excited-state proton transfer (ESPT) of firefly's chromophore D-luciferin in DMSO-water binary mixtures using steady-state and time-resolved fluorescence spectroscopy. The unusual behavior of DMSO-water binary mixture as reported by Bagchi et al. (J. Phys. Chem. B 2010, 114, 12875-12882) was also found using D-luciferin as intermolecular ESPT probe. The binary mixture has given evidence of its anomalous nature at low mole fractions of DMSO (below XD = 0.4) in our systematic investigation. Upon excitation of neutral D-luciferin molecule, dual fluorescence emissions (protonated and deprotonated form) are observed in DMSO-water binary mixture. A clear isoemissive point in the time-resolved area normalized emission spectra further indicates two emissive species in the excited state of D-luciferin in DMSO-water binary mixture. DMSO-water binary mixtures of different compositions are fascinating hydrogen bonding systems. Therefore, we have observed unusual changes in the fluorescence emission intensity, fluorescence quantum yield, and fluorescence lifetime of more hydrogen bonding sensitive anionic form of D-luciferin in low DMSO content of DMSO-water binary mixture.

Ultrawidefield microscope for high-speed fluorescence imaging and targeted optogenetic stimulation

PubMed Central

Werley, Christopher A.; Chien, Miao-Ping; Cohen, Adam E.

2017-01-01

The rapid increase in the number and quality of fluorescent reporters and optogenetic actuators has yielded a powerful set of tools for recording and controlling cellular state and function. To achieve the full benefit of these tools requires improved optical systems with high light collection efficiency, high spatial and temporal resolution, and patterned optical stimulation, in a wide field of view (FOV). Here we describe our ‘Firefly’ microscope, which achieves these goals in a Ø6 mm FOV. The Firefly optical system is optimized for simultaneous photostimulation and fluorescence imaging in cultured cells. All but one of the optical elements are commercially available, yet the microscope achieves 10-fold higher light collection efficiency at its design magnification than the comparable commercially available microscope using the same objective. The Firefly microscope enables all-optical electrophysiology (‘Optopatch’) in cultured neurons with a throughput and information content unmatched by other neuronal phenotyping systems. This capability opens possibilities in disease modeling and phenotypic drug screening. We also demonstrate applications of the system to voltage and calcium recordings in human induced pluripotent stem cell derived cardiomyocytes. PMID:29296505

Modeling Chemical Reactions by QM/MM Calculations: The Case of the Tautomerization in Fireflies Bioluminescent Systems

PubMed Central

Berraud-Pache, Romain; Garcia-Iriepa, Cristina; Navizet, Isabelle

2018-01-01

In less than half a century, the hybrid QM/MM method has become one of the most used technique to model molecules embedded in a complex environment. A well-known application of the QM/MM method is for biological systems. Nowadays, one can understand how enzymatic reactions work or compute spectroscopic properties, like the wavelength of emission. Here, we have tackled the issue of modeling chemical reactions inside proteins. We have studied a bioluminescent system, fireflies, and deciphered if a keto-enol tautomerization is possible inside the protein. The two tautomers are candidates to be the emissive molecule of the bioluminescence but no outcome has been reached. One hypothesis is to consider a possible keto-enol tautomerization to treat this issue, as it has been already observed in water. A joint approach combining extensive MD simulations as well as computation of key intermediates like TS using QM/MM calculations is presented in this publication. We also emphasize the procedure and difficulties met during this approach in order to give a guide for this kind of chemical reactions using QM/MM methods. PMID:29719820

Modeling Chemical Reactions by QM/MM Calculations: The Case of the Tautomerization in Fireflies Bioluminescent Systems.

PubMed

Berraud-Pache, Romain; Garcia-Iriepa, Cristina; Navizet, Isabelle

2018-01-01

In less than half a century, the hybrid QM/MM method has become one of the most used technique to model molecules embedded in a complex environment. A well-known application of the QM/MM method is for biological systems. Nowadays, one can understand how enzymatic reactions work or compute spectroscopic properties, like the wavelength of emission. Here, we have tackled the issue of modeling chemical reactions inside proteins. We have studied a bioluminescent system, fireflies, and deciphered if a keto-enol tautomerization is possible inside the protein. The two tautomers are candidates to be the emissive molecule of the bioluminescence but no outcome has been reached. One hypothesis is to consider a possible keto-enol tautomerization to treat this issue, as it has been already observed in water. A joint approach combining extensive MD simulations as well as computation of key intermediates like TS using QM/MM calculations is presented in this publication. We also emphasize the procedure and difficulties met during this approach in order to give a guide for this kind of chemical reactions using QM/MM methods.

Interaction of firefly luciferase and silver nanoparticles and its impact on enzyme activity

NASA Astrophysics Data System (ADS)

Käkinen, Aleksandr; Ding, Feng; Chen, Pengyu; Mortimer, Monika; Kahru, Anne; Ke, Pu Chun

2013-08-01

We report on the dose-dependent inhibition of firefly luciferase activity induced by exposure of the enzyme to 20 nm citrate-coated silver nanoparticles (AgNPs). The inhibition mechanism was examined by characterizing the physicochemical properties and biophysical interactions of the enzyme and the AgNPs. Consistently, binding of the enzyme induced an increase in zeta potential from -22 to 6 mV for the AgNPs, triggered a red-shift of 44 nm in the absorbance peak of the AgNPs, and rendered a ‘protein corona’ of 20 nm in thickness on the nanoparticle surfaces. However, the secondary structures of the enzyme were only marginally affected upon formation of the protein corona, as verified by circular dichroism spectroscopy measurement and multiscale discrete molecular dynamics simulations. Rather, inductively coupled plasma mass spectrometry measurement revealed a significant ion release from the AgNPs. The released silver ions could readily react with the cysteine residues and N-groups of the enzyme to alter the physicochemical environment of their neighboring catalytic site and subsequently impair the enzymatic activity.

FT-IR, FT-Raman spectra and DFT calculations of melaminium perchlorate monohydrate

NASA Astrophysics Data System (ADS)

Kanagathara, N.; Marchewka, M. K.; Drozd, M.; Renganathan, N. G.; Gunasekaran, S.; Anbalagan, G.

2013-08-01

Melaminium perchlorate monohydrate (MPM), an organic material has been synthesized by slow solvent evaporation method at room temperature. Powder X-ray diffraction analysis confirms that MPM crystal belongs to triclinic system with space group P-1. FTIR and FT Raman spectra are recorded at room temperature. Functional group assignment has been made for the melaminium cations and perchlorate anions. Vibrational spectra have also been discussed on the basis of quantum chemical density functional theory (DFT) calculations using Firefly (PC GAMESS) version 7.1 G. Vibrational frequencies are calculated and scaled values are compared with experimental values. The assignment of the bands has been made on the basis of the calculated PED. The Mulliken charges, HOMO-LUMO orbital energies are analyzed directly from Firefly program log files and graphically illustrated. HOMO-LUMO energy gap and other related molecular properties are also calculated. The theoretically constructed FT-IR and FT-Raman spectra of MPM coincide with the experimental one. The chemical structure of the compound has been established by 1H and 13C NMR spectra. No detectable signal was observed during powder test for second harmonic generation.

Guided particle swarm optimization method to solve general nonlinear optimization problems

NASA Astrophysics Data System (ADS)

Abdelhalim, Alyaa; Nakata, Kazuhide; El-Alem, Mahmoud; Eltawil, Amr

2018-04-01

The development of hybrid algorithms is becoming an important topic in the global optimization research area. This article proposes a new technique in hybridizing the particle swarm optimization (PSO) algorithm and the Nelder-Mead (NM) simplex search algorithm to solve general nonlinear unconstrained optimization problems. Unlike traditional hybrid methods, the proposed method hybridizes the NM algorithm inside the PSO to improve the velocities and positions of the particles iteratively. The new hybridization considers the PSO algorithm and NM algorithm as one heuristic, not in a sequential or hierarchical manner. The NM algorithm is applied to improve the initial random solution of the PSO algorithm and iteratively in every step to improve the overall performance of the method. The performance of the proposed method was tested over 20 optimization test functions with varying dimensions. Comprehensive comparisons with other methods in the literature indicate that the proposed solution method is promising and competitive.

Efficient 3D geometric and Zernike moments computation from unstructured surface meshes.

PubMed

Pozo, José María; Villa-Uriol, Maria-Cruz; Frangi, Alejandro F

2011-03-01

This paper introduces and evaluates a fast exact algorithm and a series of faster approximate algorithms for the computation of 3D geometric moments from an unstructured surface mesh of triangles. Being based on the object surface reduces the computational complexity of these algorithms with respect to volumetric grid-based algorithms. In contrast, it can only be applied for the computation of geometric moments of homogeneous objects. This advantage and restriction is shared with other proposed algorithms based on the object boundary. The proposed exact algorithm reduces the computational complexity for computing geometric moments up to order N with respect to previously proposed exact algorithms, from N(9) to N(6). The approximate series algorithm appears as a power series on the rate between triangle size and object size, which can be truncated at any desired degree. The higher the number and quality of the triangles, the better the approximation. This approximate algorithm reduces the computational complexity to N(3). In addition, the paper introduces a fast algorithm for the computation of 3D Zernike moments from the computed geometric moments, with a computational complexity N(4), while the previously proposed algorithm is of order N(6). The error introduced by the proposed approximate algorithms is evaluated in different shapes and the cost-benefit ratio in terms of error, and computational time is analyzed for different moment orders.

Block-Based Connected-Component Labeling Algorithm Using Binary Decision Trees

PubMed Central

Chang, Wan-Yu; Chiu, Chung-Cheng; Yang, Jia-Horng

2015-01-01

In this paper, we propose a fast labeling algorithm based on block-based concepts. Because the number of memory access points directly affects the time consumption of the labeling algorithms, the aim of the proposed algorithm is to minimize neighborhood operations. Our algorithm utilizes a block-based view and correlates a raster scan to select the necessary pixels generated by a block-based scan mask. We analyze the advantages of a sequential raster scan for the block-based scan mask, and integrate the block-connected relationships using two different procedures with binary decision trees to reduce unnecessary memory access. This greatly simplifies the pixel locations of the block-based scan mask. Furthermore, our algorithm significantly reduces the number of leaf nodes and depth levels required in the binary decision tree. We analyze the labeling performance of the proposed algorithm alongside that of other labeling algorithms using high-resolution images and foreground images. The experimental results from synthetic and real image datasets demonstrate that the proposed algorithm is faster than other methods. PMID:26393597

Combined Partial Penectomy With Bilateral Robotic Inguinal Lymphadenectomy Using Near-infrared Fluorescence Guidance.

PubMed

Sávio, Luís Felipe; Panizzutti Barboza, Marcelo; Alameddine, Mahmoud; Ahdoot, Michael; Alonzo, David; Ritch, Chad R

2018-03-01

To describe our novel technique for performing a combined partial penectomy and bilateral robotic inguinal lymphadenectomy using intraoperative near-infrared (NIR) fluorescence guidance with indocyanine green (ICG) and the DaVinci Firefly camera system. A 58-year-old man presented status post recent excisional biopsy of a 2-cm lesion on the left coronal aspect of the glans penis. Pathology revealed "invasive squamous cell carcinoma of the penis with multifocal positive margins." His examination was suspicious for cT2 primary and his inguinal nodes were cN0. He was counseled to undergo partial penectomy with possible combined vs staged bilateral robotic inguinal lymphadenectomy. Preoperative computed tomography scan was negative for pathologic lymphadenopathy. Before incision, 5 mL of ICG was injected subcutaneously beneath the tumor. Bilateral thigh pockets were then developed simultaneously and a right, then left robotic modified inguinal lymphadenectomy was performed using NIR fluorescence guidance via the DaVinci Firefly camera. A partial penectomy was then performed in the standard fashion. The combined procedure was performed successfully without complication. Total operative time was 379 minutes and total robotic console time was 95 minutes for the right and 58 minutes to the left. Estimated blood loss on the right and left were 15 and 25 mL, respectively. A total of 24 lymph nodes were retrieved. This video demonstrates a safe and feasible approach for combined partial penectomy and bilateral inguinal lymphadenectomy with NIR guidance using ICG and the DaVinci Firefly camera system. The combined robotic approach has minimal morbidity and avoids the need for a staged procedure. Furthermore, use of NIR guidance with ICG during robotic inguinal lymphadenectomy is feasible and may help identify sentinel lymph nodes and improve the quality of dissection. Further studies are needed to confirm the utility of NIR guidance for robotic sentinel lymph node dissection. Copyright © 2017 Elsevier Inc. All rights reserved.

An ultrasensitive NanoLuc-based luminescence system for monitoring Plasmodium berghei throughout its life cycle.

PubMed

De Niz, Mariana; Stanway, Rebecca R; Wacker, Rahel; Keller, Derya; Heussler, Volker T

2016-04-21

Bioluminescence imaging is widely used for cell-based assays and animal imaging studies, both in biomedical research and drug development. Its main advantages include its high-throughput applicability, affordability, high sensitivity, operational simplicity, and quantitative outputs. In malaria research, bioluminescence has been used for drug discovery in vivo and in vitro, exploring host-pathogen interactions, and studying multiple aspects of Plasmodium biology. While the number of fluorescent proteins available for imaging has undergone a great expansion over the last two decades, enabling simultaneous visualization of multiple molecular and cellular events, expansion of available luciferases has lagged behind. The most widely used bioluminescent probe in malaria research is the Photinus pyralis firefly luciferase, followed by the more recently introduced Click-beetle and Renilla luciferases. Ultra-sensitive imaging of Plasmodium at low parasite densities has not been previously achieved. With the purpose of overcoming these challenges, a Plasmodium berghei line expressing the novel ultra-bright luciferase enzyme NanoLuc, called PbNLuc has been generated, and is presented in this work. NanoLuc shows at least 150 times brighter signal than firefly luciferase in vitro, allowing single parasite detection in mosquito, liver, and sexual and asexual blood stages. As a proof-of-concept, the PbNLuc parasites were used to image parasite development in the mosquito, liver and blood stages of infection, and to specifically explore parasite liver stage egress, and pre-patency period in vivo. PbNLuc is a suitable parasite line for sensitive imaging of the entire Plasmodium life cycle. Its sensitivity makes it a promising line to be used as a reference for drug candidate testing, as well as the characterization of mutant parasites to explore the function of parasite proteins, host-parasite interactions, and the better understanding of Plasmodium biology. Since the substrate requirements of NanoLuc are different from those of firefly luciferase, dual bioluminescence imaging for the simultaneous characterization of two lines, or two separate biological processes, is possible, as demonstrated in this work.

Dynamic routing and spectrum assignment based on multilayer virtual topology and ant colony optimization in elastic software-defined optical networks

NASA Astrophysics Data System (ADS)

Wang, Fu; Liu, Bo; Zhang, Lijia; Zhang, Qi; Tian, Qinghua; Tian, Feng; Rao, Lan; Xin, Xiangjun

2017-07-01

Elastic software-defined optical networks greatly improve the flexibility of the optical switching network while it has brought challenges to the routing and spectrum assignment (RSA). A multilayer virtual topology model is proposed to solve RSA problems. Two RSA algorithms based on the virtual topology are proposed, which are the ant colony optimization (ACO) algorithm of minimum consecutiveness loss and the ACO algorithm of maximum spectrum consecutiveness. Due to the computing power of the control layer in the software-defined network, the routing algorithm avoids the frequent link-state information between routers. Based on the effect of the spectrum consecutiveness loss on the pheromone in the ACO, the path and spectrum of the minimal impact on the network are selected for the service request. The proposed algorithms have been compared with other algorithms. The results show that the proposed algorithms can reduce the blocking rate by at least 5% and perform better in spectrum efficiency. Moreover, the proposed algorithms can effectively decrease spectrum fragmentation and enhance available spectrum consecutiveness.

An Improved Perturb and Observe Algorithm for Photovoltaic Motion Carriers

NASA Astrophysics Data System (ADS)

Peng, Lele; Xu, Wei; Li, Liming; Zheng, Shubin

2018-03-01

An improved perturbation and observation algorithm for photovoltaic motion carriers is proposed in this paper. The model of the proposed algorithm is given by using Lambert W function and tangent error method. Moreover, by using matlab and experiment of photovoltaic system, the tracking performance of the proposed algorithm is tested. And the results demonstrate that the improved algorithm has fast tracking speed and high efficiency. Furthermore, the energy conversion efficiency by the improved method has increased by nearly 8.2%.

Detection of dominant flow and abnormal events in surveillance video

NASA Astrophysics Data System (ADS)

Kwak, Sooyeong; Byun, Hyeran

2011-02-01

We propose an algorithm for abnormal event detection in surveillance video. The proposed algorithm is based on a semi-unsupervised learning method, a kind of feature-based approach so that it does not detect the moving object individually. The proposed algorithm identifies dominant flow without individual object tracking using a latent Dirichlet allocation model in crowded environments. It can also automatically detect and localize an abnormally moving object in real-life video. The performance tests are taken with several real-life databases, and their results show that the proposed algorithm can efficiently detect abnormally moving objects in real time. The proposed algorithm can be applied to any situation in which abnormal directions or abnormal speeds are detected regardless of direction.

Distributed k-Means Algorithm and Fuzzy c-Means Algorithm for Sensor Networks Based on Multiagent Consensus Theory.

PubMed

Qin, Jiahu; Fu, Weiming; Gao, Huijun; Zheng, Wei Xing

2016-03-03

This paper is concerned with developing a distributed k-means algorithm and a distributed fuzzy c-means algorithm for wireless sensor networks (WSNs) where each node is equipped with sensors. The underlying topology of the WSN is supposed to be strongly connected. The consensus algorithm in multiagent consensus theory is utilized to exchange the measurement information of the sensors in WSN. To obtain a faster convergence speed as well as a higher possibility of having the global optimum, a distributed k-means++ algorithm is first proposed to find the initial centroids before executing the distributed k-means algorithm and the distributed fuzzy c-means algorithm. The proposed distributed k-means algorithm is capable of partitioning the data observed by the nodes into measure-dependent groups which have small in-group and large out-group distances, while the proposed distributed fuzzy c-means algorithm is capable of partitioning the data observed by the nodes into different measure-dependent groups with degrees of membership values ranging from 0 to 1. Simulation results show that the proposed distributed algorithms can achieve almost the same results as that given by the centralized clustering algorithms.

Detection of the ice assertion on aircraft using empirical mode decomposition enhanced by multi-objective optimization

NASA Astrophysics Data System (ADS)

Bagherzadeh, Seyed Amin; Asadi, Davood

2017-05-01

In search of a precise method for analyzing nonlinear and non-stationary flight data of an aircraft in the icing condition, an Empirical Mode Decomposition (EMD) algorithm enhanced by multi-objective optimization is introduced. In the proposed method, dissimilar IMF definitions are considered by the Genetic Algorithm (GA) in order to find the best decision parameters of the signal trend. To resolve disadvantages of the classical algorithm caused by the envelope concept, the signal trend is estimated directly in the proposed method. Furthermore, in order to simplify the performance and understanding of the EMD algorithm, the proposed method obviates the need for a repeated sifting process. The proposed enhanced EMD algorithm is verified by some benchmark signals. Afterwards, the enhanced algorithm is applied to simulated flight data in the icing condition in order to detect the ice assertion on the aircraft. The results demonstrate the effectiveness of the proposed EMD algorithm in aircraft ice detection by providing a figure of merit for the icing severity.

Noisy image magnification with total variation regularization and order-changed dictionary learning

NASA Astrophysics Data System (ADS)

Xu, Jian; Chang, Zhiguo; Fan, Jiulun; Zhao, Xiaoqiang; Wu, Xiaomin; Wang, Yanzi

2015-12-01

Noisy low resolution (LR) images are always obtained in real applications, but many existing image magnification algorithms can not get good result from a noisy LR image. We propose a two-step image magnification algorithm to solve this problem. The proposed algorithm takes the advantages of both regularization-based method and learning-based method. The first step is based on total variation (TV) regularization and the second step is based on sparse representation. In the first step, we add a constraint on the TV regularization model to magnify the LR image and at the same time to suppress the noise in it. In the second step, we propose an order-changed dictionary training algorithm to train the dictionaries which is dominated by texture details. Experimental results demonstrate that the proposed algorithm performs better than many other algorithms when the noise is not serious. The proposed algorithm can also provide better visual quality on natural LR images.

Active control of impulsive noise with symmetric α-stable distribution based on an improved step-size normalized adaptive algorithm

NASA Astrophysics Data System (ADS)

Zhou, Yali; Zhang, Qizhi; Yin, Yixin

2015-05-01

In this paper, active control of impulsive noise with symmetric α-stable (SαS) distribution is studied. A general step-size normalized filtered-x Least Mean Square (FxLMS) algorithm is developed based on the analysis of existing algorithms, and the Gaussian distribution function is used to normalize the step size. Compared with existing algorithms, the proposed algorithm needs neither the parameter selection and thresholds estimation nor the process of cost function selection and complex gradient computation. Computer simulations have been carried out to suggest that the proposed algorithm is effective for attenuating SαS impulsive noise, and then the proposed algorithm has been implemented in an experimental ANC system. Experimental results show that the proposed scheme has good performance for SαS impulsive noise attenuation.

Multiple-algorithm parallel fusion of infrared polarization and intensity images based on algorithmic complementarity and synergy

NASA Astrophysics Data System (ADS)

Zhang, Lei; Yang, Fengbao; Ji, Linna; Lv, Sheng

2018-01-01

Diverse image fusion methods perform differently. Each method has advantages and disadvantages compared with others. One notion is that the advantages of different image methods can be effectively combined. A multiple-algorithm parallel fusion method based on algorithmic complementarity and synergy is proposed. First, in view of the characteristics of the different algorithms and difference-features among images, an index vector-based feature-similarity is proposed to define the degree of complementarity and synergy. This proposed index vector is a reliable evidence indicator for algorithm selection. Second, the algorithms with a high degree of complementarity and synergy are selected. Then, the different degrees of various features and infrared intensity images are used as the initial weights for the nonnegative matrix factorization (NMF). This avoids randomness of the NMF initialization parameter. Finally, the fused images of different algorithms are integrated using the NMF because of its excellent data fusing performance on independent features. Experimental results demonstrate that the visual effect and objective evaluation index of the fused images obtained using the proposed method are better than those obtained using traditional methods. The proposed method retains all the advantages that individual fusion algorithms have.

Fuzzy logic-based approach to detecting a passive RFID tag in an outpatient clinic.

PubMed

Min, Daiki; Yih, Yuehwern

2011-06-01

This study is motivated by the observations on the data collected by radio frequency identification (RFID) readers in a pilot study, which was used to investigate the feasibility of implementing an RFID-based monitoring system in an outpatient eye clinic. The raw RFID data collected from RFID readers contain noise and missing reads, which prevent us from determining the tag location. In this paper, fuzzy logic-based algorithms are proposed to interpret the raw RFID data to extract accurate information. The proposed algorithms determine the location of an RFID tag by evaluating its possibility of presence and absence. To evaluate the performance of the proposed algorithms, numerical experiments are conducted using the data observed in the outpatient eye clinic. Experiments results showed that the proposed algorithms outperform existing static smoothing method in terms of minimizing both false positives and false negatives. Furthermore, the proposed algorithms are applied to a set of simulated data to show the robustness of the proposed algorithms at various levels of RFID reader reliability.

Removal of impulse noise clusters from color images with local order statistics

NASA Astrophysics Data System (ADS)

Ruchay, Alexey; Kober, Vitaly

2017-09-01

This paper proposes a novel algorithm for restoring images corrupted with clusters of impulse noise. The noise clusters often occur when the probability of impulse noise is very high. The proposed noise removal algorithm consists of detection of bulky impulse noise in three color channels with local order statistics followed by removal of the detected clusters by means of vector median filtering. With the help of computer simulation we show that the proposed algorithm is able to effectively remove clustered impulse noise. The performance of the proposed algorithm is compared in terms of image restoration metrics with that of common successful algorithms.

Dynamic Inertia Weight Binary Bat Algorithm with Neighborhood Search

PubMed Central

2017-01-01

Binary bat algorithm (BBA) is a binary version of the bat algorithm (BA). It has been proven that BBA is competitive compared to other binary heuristic algorithms. Since the update processes of velocity in the algorithm are consistent with BA, in some cases, this algorithm also faces the premature convergence problem. This paper proposes an improved binary bat algorithm (IBBA) to solve this problem. To evaluate the performance of IBBA, standard benchmark functions and zero-one knapsack problems have been employed. The numeric results obtained by benchmark functions experiment prove that the proposed approach greatly outperforms the original BBA and binary particle swarm optimization (BPSO). Compared with several other heuristic algorithms on zero-one knapsack problems, it also verifies that the proposed algorithm is more able to avoid local minima. PMID:28634487

Dynamic Inertia Weight Binary Bat Algorithm with Neighborhood Search.

PubMed

Huang, Xingwang; Zeng, Xuewen; Han, Rui

2017-01-01

Binary bat algorithm (BBA) is a binary version of the bat algorithm (BA). It has been proven that BBA is competitive compared to other binary heuristic algorithms. Since the update processes of velocity in the algorithm are consistent with BA, in some cases, this algorithm also faces the premature convergence problem. This paper proposes an improved binary bat algorithm (IBBA) to solve this problem. To evaluate the performance of IBBA, standard benchmark functions and zero-one knapsack problems have been employed. The numeric results obtained by benchmark functions experiment prove that the proposed approach greatly outperforms the original BBA and binary particle swarm optimization (BPSO). Compared with several other heuristic algorithms on zero-one knapsack problems, it also verifies that the proposed algorithm is more able to avoid local minima.

An Orthogonal Evolutionary Algorithm With Learning Automata for Multiobjective Optimization.

PubMed

Dai, Cai; Wang, Yuping; Ye, Miao; Xue, Xingsi; Liu, Hailin

2016-12-01

Research on multiobjective optimization problems becomes one of the hottest topics of intelligent computation. In order to improve the search efficiency of an evolutionary algorithm and maintain the diversity of solutions, in this paper, the learning automata (LA) is first used for quantization orthogonal crossover (QOX), and a new fitness function based on decomposition is proposed to achieve these two purposes. Based on these, an orthogonal evolutionary algorithm with LA for complex multiobjective optimization problems with continuous variables is proposed. The experimental results show that in continuous states, the proposed algorithm is able to achieve accurate Pareto-optimal sets and wide Pareto-optimal fronts efficiently. Moreover, the comparison with the several existing well-known algorithms: nondominated sorting genetic algorithm II, decomposition-based multiobjective evolutionary algorithm, decomposition-based multiobjective evolutionary algorithm with an ensemble of neighborhood sizes, multiobjective optimization by LA, and multiobjective immune algorithm with nondominated neighbor-based selection, on 15 multiobjective benchmark problems, shows that the proposed algorithm is able to find more accurate and evenly distributed Pareto-optimal fronts than the compared ones.

Two-wavelength Lidar inversion algorithm for determining planetary boundary layer height

NASA Astrophysics Data System (ADS)

Liu, Boming; Ma, Yingying; Gong, Wei; Jian, Yang; Ming, Zhang

2018-02-01

This study proposes a two-wavelength Lidar inversion algorithm to determine the boundary layer height (BLH) based on the particles clustering. Color ratio and depolarization ratio are used to analyze the particle distribution, based on which the proposed algorithm can overcome the effects of complex aerosol layers to calculate the BLH. The algorithm is used to determine the top of the boundary layer under different mixing state. Experimental results demonstrate that the proposed algorithm can determine the top of the boundary layer even in a complex case. Moreover, it can better deal with the weak convection conditions. Finally, experimental data from June 2015 to December 2015 were used to verify the reliability of the proposed algorithm. The correlation between the results of the proposed algorithm and the manual method is R2 = 0.89 with a RMSE of 131 m and mean bias of 49 m; the correlation between the results of the ideal profile fitting method and the manual method is R2 = 0.64 with a RMSE of 270 m and a mean bias of 165 m; and the correlation between the results of the wavelet covariance transform method and manual method is R2 = 0.76, with a RMSE of 196 m and mean bias of 23 m. These findings indicate that the proposed algorithm has better reliability and stability than traditional algorithms.

Cooperative optimization and their application in LDPC codes

NASA Astrophysics Data System (ADS)

Chen, Ke; Rong, Jian; Zhong, Xiaochun

2008-10-01

Cooperative optimization is a new way for finding global optima of complicated functions of many variables. The proposed algorithm is a class of message passing algorithms and has solid theory foundations. It can achieve good coding gains over the sum-product algorithm for LDPC codes. For (6561, 4096) LDPC codes, the proposed algorithm can achieve 2.0 dB gains over the sum-product algorithm at BER of 4×10-7. The decoding complexity of the proposed algorithm is lower than the sum-product algorithm can do; furthermore, the former can achieve much lower error floor than the latter can do after the Eb / No is higher than 1.8 dB.

Frequency and phase synchronization in large groups: Low dimensional description of synchronized clapping, firefly flashing, and cricket chirping

NASA Astrophysics Data System (ADS)

Ott, Edward; Antonsen, Thomas M.

2017-05-01

A common observation is that large groups of oscillatory biological units often have the ability to synchronize. A paradigmatic model of such behavior is provided by the Kuramoto model, which achieves synchronization through coupling of the phase dynamics of individual oscillators, while each oscillator maintains a different constant inherent natural frequency. Here we consider the biologically likely possibility that the oscillatory units may be capable of enhancing their synchronization ability by adaptive frequency dynamics. We propose a simple augmentation of the Kuramoto model which does this. We also show that, by the use of a previously developed technique [Ott and Antonsen, Chaos 18, 037113 (2008)], it is possible to reduce the resulting dynamics to a lower dimensional system for the macroscopic evolution of the oscillator ensemble. By employing this reduction, we investigate the dynamics of our system, finding a characteristic hysteretic behavior and enhancement of the quality of the achieved synchronization.

Collective signaling behavior in a networked-oscillator model

NASA Astrophysics Data System (ADS)

Liu, Z.-H.; Hui, P. M.

2007-09-01

We propose and study the collective behavior of a model of networked signaling objects that incorporates several ingredients of real-life systems. These ingredients include spatial inhomogeneity with grouping of signaling objects, signal attenuation with distance, and delayed and impulsive coupling between non-identical signaling objects. Depending on the coupling strength and/or time-delay effect, the model exhibits completely, partially, and locally collective signaling behavior. In particular, a correlated signaling (CS) behavior is observed in which there exist time durations when nearly a constant fraction of oscillators in the system are in the signaling state. These time durations are much longer than the duration of a spike when a single oscillator signals, and they are separated by regular intervals in which nearly all oscillators are silent. Such CS behavior is similar to that observed in biological systems such as fireflies, cicadas, crickets, and frogs. The robustness of the CS behavior against noise is also studied. It is found that properly adjusting the coupling strength and noise level could enhance the correlated behavior.

In vivo bioluminescence imaging of cell differentiation in biomaterials: a platform for scaffold development.

PubMed

Bagó, Juli R; Aguilar, Elisabeth; Alieva, Maria; Soler-Botija, Carolina; Vila, Olaia F; Claros, Silvia; Andrades, José A; Becerra, José; Rubio, Nuria; Blanco, Jerónimo

2013-03-01

In vivo testing is a mandatory last step in scaffold development. Agile longitudinal noninvasive real-time monitoring of stem cell behavior in biomaterials implanted in live animals should facilitate the development of scaffolds for tissue engineering. We report on a noninvasive bioluminescence imaging (BLI) procedure for simultaneous monitoring of changes in the expression of multiple genes to evaluate scaffold performance in vivo. Adipose tissue-derived stromal mensenchymal cells were dually labeled with Renilla red fluorescent protein and firefly green fluorescent protein chimeric reporters regulated by cytomegalovirus and tissue-specific promoters, respectively. Labeled cells were induced to differentiate in vitro and in vivo, by seeding in demineralized bone matrices (DBMs) and monitored by BLI. Imaging results were validated by RT-polymerase chain reaction and histological procedures. The proposed approach improves molecular imaging and measurement of changes in gene expression of cells implanted in live animals. This procedure, applicable to the simultaneous analysis of multiple genes from cells seeded in DBMs, should facilitate engineering of scaffolds for tissue repair.

In Vivo Bioluminescence Imaging of Cell Differentiation in Biomaterials: A Platform for Scaffold Development

PubMed Central

Bagó, Juli R.; Aguilar, Elisabeth; Alieva, Maria; Soler-Botija, Carolina; Vila, Olaia F.; Claros, Silvia; Andrades, José A.; Becerra, José; Rubio, Nuria

2013-01-01

In vivo testing is a mandatory last step in scaffold development. Agile longitudinal noninvasive real-time monitoring of stem cell behavior in biomaterials implanted in live animals should facilitate the development of scaffolds for tissue engineering. We report on a noninvasive bioluminescence imaging (BLI) procedure for simultaneous monitoring of changes in the expression of multiple genes to evaluate scaffold performance in vivo. Adipose tissue-derived stromal mensenchymal cells were dually labeled with Renilla red fluorescent protein and firefly green fluorescent protein chimeric reporters regulated by cytomegalovirus and tissue-specific promoters, respectively. Labeled cells were induced to differentiate in vitro and in vivo, by seeding in demineralized bone matrices (DBMs) and monitored by BLI. Imaging results were validated by RT-polymerase chain reaction and histological procedures. The proposed approach improves molecular imaging and measurement of changes in gene expression of cells implanted in live animals. This procedure, applicable to the simultaneous analysis of multiple genes from cells seeded in DBMs, should facilitate engineering of scaffolds for tissue repair. PMID:23013334

Establishment of a luciferase assay-based screening system: Fumitremorgin C selectively inhibits cellular proliferation of immortalized astrocytes expressing an active form of AKT

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

Wang Lei; Sasai, Ken; Akagi, Tsuyoshi

2008-08-29

The AKT pathway is frequently activated in glioblastoma, and as such, inhibitors of this pathway could prove very useful as anti-glioblastoma therapies. Here we established immortalized astrocytes expressing Renilla luciferase as well as those expressing both an active form of AKT and firefly luciferase. Since both luciferase activities represent the numbers of corresponding cell lines, novel inhibitors of the AKT pathway can be identified by treating co-cultures containing the two types of luciferase-expressing cells with individual compounds. Indeed, such a screening system succeeded in identifying fumitremorgin C as an efficient inhibitor of the AKT pathway, which was further confirmed bymore » the ability of fumitremorgin C to selectively inhibit the growth of immortalized astrocytes expressing an active form of AKT. The present study proposes a broadly applicable approach for identifying therapeutic agents that target the pathways and/or molecules responsible for cancer development.« less

Community detection in complex networks by using membrane algorithm

NASA Astrophysics Data System (ADS)

Liu, Chuang; Fan, Linan; Liu, Zhou; Dai, Xiang; Xu, Jiamei; Chang, Baoren

Community detection in complex networks is a key problem of network analysis. In this paper, a new membrane algorithm is proposed to solve the community detection in complex networks. The proposed algorithm is based on membrane systems, which consists of objects, reaction rules, and a membrane structure. Each object represents a candidate partition of a complex network, and the quality of objects is evaluated according to network modularity. The reaction rules include evolutionary rules and communication rules. Evolutionary rules are responsible for improving the quality of objects, which employ the differential evolutionary algorithm to evolve objects. Communication rules implement the information exchanged among membranes. Finally, the proposed algorithm is evaluated on synthetic, real-world networks with real partitions known and the large-scaled networks with real partitions unknown. The experimental results indicate the superior performance of the proposed algorithm in comparison with other experimental algorithms.

A parallel approximate string matching under Levenshtein distance on graphics processing units using warp-shuffle operations

PubMed Central

Ho, ThienLuan; Oh, Seung-Rohk

2017-01-01

Approximate string matching with k-differences has a number of practical applications, ranging from pattern recognition to computational biology. This paper proposes an efficient memory-access algorithm for parallel approximate string matching with k-differences on Graphics Processing Units (GPUs). In the proposed algorithm, all threads in the same GPUs warp share data using warp-shuffle operation instead of accessing the shared memory. Moreover, we implement the proposed algorithm by exploiting the memory structure of GPUs to optimize its performance. Experiment results for real DNA packages revealed that the performance of the proposed algorithm and its implementation archived up to 122.64 and 1.53 times compared to that of sequential algorithm on CPU and previous parallel approximate string matching algorithm on GPUs, respectively. PMID:29016700

Adaptive power allocation schemes based on IAFS algorithm for OFDM-based cognitive radio systems

NASA Astrophysics Data System (ADS)

Zhang, Shuying; Zhao, Xiaohui; Liang, Cong; Ding, Xu

2017-01-01

In cognitive radio (CR) systems, reasonable power allocation can increase transmission rate of CR users or secondary users (SUs) as much as possible and at the same time insure normal communication among primary users (PUs). This study proposes an optimal power allocation scheme for the OFDM-based CR system with one SU influenced by multiple PU interference constraints. This scheme is based on an improved artificial fish swarm (IAFS) algorithm in combination with the advantage of conventional artificial fish swarm (ASF) algorithm and particle swarm optimisation (PSO) algorithm. In performance comparison of IAFS algorithm with other intelligent algorithms by simulations, the superiority of the IAFS algorithm is illustrated; this superiority results in better performance of our proposed scheme than that of the power allocation algorithms proposed by the previous studies in the same scenario. Furthermore, our proposed scheme can obtain higher transmission data rate under the multiple PU interference constraints and the total power constraint of SU than that of the other mentioned works.

FIVQ algorithm for interference hyper-spectral image compression

NASA Astrophysics Data System (ADS)

Wen, Jia; Ma, Caiwen; Zhao, Junsuo

2014-07-01

Based on the improved vector quantization (IVQ) algorithm [1] which was proposed in 2012, this paper proposes a further improved vector quantization (FIVQ) algorithm for LASIS (Large Aperture Static Imaging Spectrometer) interference hyper-spectral image compression. To get better image quality, IVQ algorithm takes both the mean values and the VQ indices as the encoding rules. Although IVQ algorithm can improve both the bit rate and the image quality, it still can be further improved in order to get much lower bit rate for the LASIS interference pattern with the special optical characteristics based on the pushing and sweeping in LASIS imaging principle. In the proposed algorithm FIVQ, the neighborhood of the encoding blocks of the interference pattern image, which are using the mean value rules, will be checked whether they have the same mean value as the current processing block. Experiments show the proposed algorithm FIVQ can get lower bit rate compared to that of the IVQ algorithm for the LASIS interference hyper-spectral sequences.

Novel and efficient tag SNPs selection algorithms.

PubMed

Chen, Wen-Pei; Hung, Che-Lun; Tsai, Suh-Jen Jane; Lin, Yaw-Ling

2014-01-01

SNPs are the most abundant forms of genetic variations amongst species; the association studies between complex diseases and SNPs or haplotypes have received great attention. However, these studies are restricted by the cost of genotyping all SNPs; thus, it is necessary to find smaller subsets, or tag SNPs, representing the rest of the SNPs. In fact, the existing tag SNP selection algorithms are notoriously time-consuming. An efficient algorithm for tag SNP selection was presented, which was applied to analyze the HapMap YRI data. The experimental results show that the proposed algorithm can achieve better performance than the existing tag SNP selection algorithms; in most cases, this proposed algorithm is at least ten times faster than the existing methods. In many cases, when the redundant ratio of the block is high, the proposed algorithm can even be thousands times faster than the previously known methods. Tools and web services for haplotype block analysis integrated by hadoop MapReduce framework are also developed using the proposed algorithm as computation kernels.

Sequential and Mixed Genetic Algorithm and Learning Automata (SGALA, MGALA) for Feature Selection in QSAR

PubMed Central

MotieGhader, Habib; Gharaghani, Sajjad; Masoudi-Sobhanzadeh, Yosef; Masoudi-Nejad, Ali

2017-01-01

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as GA, PSO, ACO and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR feature selection are proposed. SGALA algorithm uses advantages of Genetic algorithm and Learning Automata sequentially and the MGALA algorithm uses advantages of Genetic Algorithm and Learning Automata simultaneously. We applied our proposed algorithms to select the minimum possible number of features from three different datasets and also we observed that the MGALA and SGALA algorithms had the best outcome independently and in average compared to other feature selection algorithms. Through comparison of our proposed algorithms, we deduced that the rate of convergence to optimal result in MGALA and SGALA algorithms were better than the rate of GA, ACO, PSO and LA algorithms. In the end, the results of GA, ACO, PSO, LA, SGALA, and MGALA algorithms were applied as the input of LS-SVR model and the results from LS-SVR models showed that the LS-SVR model had more predictive ability with the input from SGALA and MGALA algorithms than the input from all other mentioned algorithms. Therefore, the results have corroborated that not only is the predictive efficiency of proposed algorithms better, but their rate of convergence is also superior to the all other mentioned algorithms. PMID:28979308

Sequential and Mixed Genetic Algorithm and Learning Automata (SGALA, MGALA) for Feature Selection in QSAR.

PubMed

MotieGhader, Habib; Gharaghani, Sajjad; Masoudi-Sobhanzadeh, Yosef; Masoudi-Nejad, Ali

2017-01-01

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as GA, PSO, ACO and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR feature selection are proposed. SGALA algorithm uses advantages of Genetic algorithm and Learning Automata sequentially and the MGALA algorithm uses advantages of Genetic Algorithm and Learning Automata simultaneously. We applied our proposed algorithms to select the minimum possible number of features from three different datasets and also we observed that the MGALA and SGALA algorithms had the best outcome independently and in average compared to other feature selection algorithms. Through comparison of our proposed algorithms, we deduced that the rate of convergence to optimal result in MGALA and SGALA algorithms were better than the rate of GA, ACO, PSO and LA algorithms. In the end, the results of GA, ACO, PSO, LA, SGALA, and MGALA algorithms were applied as the input of LS-SVR model and the results from LS-SVR models showed that the LS-SVR model had more predictive ability with the input from SGALA and MGALA algorithms than the input from all other mentioned algorithms. Therefore, the results have corroborated that not only is the predictive efficiency of proposed algorithms better, but their rate of convergence is also superior to the all other mentioned algorithms.

Range image registration based on hash map and moth-flame optimization

NASA Astrophysics Data System (ADS)

Zou, Li; Ge, Baozhen; Chen, Lei

2018-03-01

Over the past decade, evolutionary algorithms (EAs) have been introduced to solve range image registration problems because of their robustness and high precision. However, EA-based range image registration algorithms are time-consuming. To reduce the computational time, an EA-based range image registration algorithm using hash map and moth-flame optimization is proposed. In this registration algorithm, a hash map is used to avoid over-exploitation in registration process. Additionally, we present a search equation that is better at exploration and a restart mechanism to avoid being trapped in local minima. We compare the proposed registration algorithm with the registration algorithms using moth-flame optimization and several state-of-the-art EA-based registration algorithms. The experimental results show that the proposed algorithm has a lower computational cost than other algorithms and achieves similar registration precision.

The global Minmax k-means algorithm.

PubMed

Wang, Xiaoyan; Bai, Yanping

2016-01-01

The global k -means algorithm is an incremental approach to clustering that dynamically adds one cluster center at a time through a deterministic global search procedure from suitable initial positions, and employs k -means to minimize the sum of the intra-cluster variances. However the global k -means algorithm sometimes results singleton clusters and the initial positions sometimes are bad, after a bad initialization, poor local optimal can be easily obtained by k -means algorithm. In this paper, we modified the global k -means algorithm to eliminate the singleton clusters at first, and then we apply MinMax k -means clustering error method to global k -means algorithm to overcome the effect of bad initialization, proposed the global Minmax k -means algorithm. The proposed clustering method is tested on some popular data sets and compared to the k -means algorithm, the global k -means algorithm and the MinMax k -means algorithm. The experiment results show our proposed algorithm outperforms other algorithms mentioned in the paper.

Automatic arrival time detection for earthquakes based on Modified Laplacian of Gaussian filter

NASA Astrophysics Data System (ADS)

Saad, Omar M.; Shalaby, Ahmed; Samy, Lotfy; Sayed, Mohammed S.

2018-04-01

Precise identification of onset time for an earthquake is imperative in the right figuring of earthquake's location and different parameters that are utilized for building seismic catalogues. P-wave arrival detection of weak events or micro-earthquakes cannot be precisely determined due to background noise. In this paper, we propose a novel approach based on Modified Laplacian of Gaussian (MLoG) filter to detect the onset time even in the presence of very weak signal-to-noise ratios (SNRs). The proposed algorithm utilizes a denoising-filter algorithm to smooth the background noise. In the proposed algorithm, we employ the MLoG mask to filter the seismic data. Afterward, we apply a Dual-threshold comparator to detect the onset time of the event. The results show that the proposed algorithm can detect the onset time for micro-earthquakes accurately, with SNR of -12 dB. The proposed algorithm achieves an onset time picking accuracy of 93% with a standard deviation error of 0.10 s for 407 field seismic waveforms. Also, we compare the results with short and long time average algorithm (STA/LTA) and the Akaike Information Criterion (AIC), and the proposed algorithm outperforms them.

Distributed convex optimisation with event-triggered communication in networked systems

NASA Astrophysics Data System (ADS)

Liu, Jiayun; Chen, Weisheng

2016-12-01

This paper studies the distributed convex optimisation problem over directed networks. Motivated by practical considerations, we propose a novel distributed zero-gradient-sum optimisation algorithm with event-triggered communication. Therefore, communication and control updates just occur at discrete instants when some predefined condition satisfies. Thus, compared with the time-driven distributed optimisation algorithms, the proposed algorithm has the advantages of less energy consumption and less communication cost. Based on Lyapunov approaches, we show that the proposed algorithm makes the system states asymptotically converge to the solution of the problem exponentially fast and the Zeno behaviour is excluded. Finally, simulation example is given to illustrate the effectiveness of the proposed algorithm.

An improved NAS-RIF algorithm for image restoration

NASA Astrophysics Data System (ADS)

Gao, Weizhe; Zou, Jianhua; Xu, Rong; Liu, Changhai; Li, Hengnian

2016-10-01

Space optical images are inevitably degraded by atmospheric turbulence, error of the optical system and motion. In order to get the true image, a novel nonnegativity and support constants recursive inverse filtering (NAS-RIF) algorithm is proposed to restore the degraded image. Firstly the image noise is weaken by Contourlet denoising algorithm. Secondly, the reliable object support region estimation is used to accelerate the algorithm convergence. We introduce the optimal threshold segmentation technology to improve the object support region. Finally, an object construction limit and the logarithm function are added to enhance algorithm stability. Experimental results demonstrate that, the proposed algorithm can increase the PSNR, and improve the quality of the restored images. The convergence speed of the proposed algorithm is faster than that of the original NAS-RIF algorithm.

Apriori Versions Based on MapReduce for Mining Frequent Patterns on Big Data.

PubMed

Luna, Jose Maria; Padillo, Francisco; Pechenizkiy, Mykola; Ventura, Sebastian

2017-09-27

Pattern mining is one of the most important tasks to extract meaningful and useful information from raw data. This task aims to extract item-sets that represent any type of homogeneity and regularity in data. Although many efficient algorithms have been developed in this regard, the growing interest in data has caused the performance of existing pattern mining techniques to be dropped. The goal of this paper is to propose new efficient pattern mining algorithms to work in big data. To this aim, a series of algorithms based on the MapReduce framework and the Hadoop open-source implementation have been proposed. The proposed algorithms can be divided into three main groups. First, two algorithms [Apriori MapReduce (AprioriMR) and iterative AprioriMR] with no pruning strategy are proposed, which extract any existing item-set in data. Second, two algorithms (space pruning AprioriMR and top AprioriMR) that prune the search space by means of the well-known anti-monotone property are proposed. Finally, a last algorithm (maximal AprioriMR) is also proposed for mining condensed representations of frequent patterns. To test the performance of the proposed algorithms, a varied collection of big data datasets have been considered, comprising up to 3 · 10#x00B9;⁸ transactions and more than 5 million of distinct single-items. The experimental stage includes comparisons against highly efficient and well-known pattern mining algorithms. Results reveal the interest of applying MapReduce versions when complex problems are considered, and also the unsuitability of this paradigm when dealing with small data.

A Novel Color Image Encryption Algorithm Based on Quantum Chaos Sequence

NASA Astrophysics Data System (ADS)

Liu, Hui; Jin, Cong

2017-03-01

In this paper, a novel algorithm of image encryption based on quantum chaotic is proposed. The keystreams are generated by the two-dimensional logistic map as initial conditions and parameters. And then general Arnold scrambling algorithm with keys is exploited to permute the pixels of color components. In diffusion process, a novel encryption algorithm, folding algorithm, is proposed to modify the value of diffused pixels. In order to get the high randomness and complexity, the two-dimensional logistic map and quantum chaotic map are coupled with nearest-neighboring coupled-map lattices. Theoretical analyses and computer simulations confirm that the proposed algorithm has high level of security.

Damage severity assessment in wind turbine blade laboratory model through fuzzy finite element model updating

NASA Astrophysics Data System (ADS)

Turnbull, Heather; Omenzetter, Piotr

2017-04-01

The recent shift towards development of clean, sustainable energy sources has provided a new challenge in terms of structural safety and reliability: with aging, manufacturing defects, harsh environmental and operational conditions, and extreme events such as lightning strikes wind turbines can become damaged resulting in production losses and environmental degradation. To monitor the current structural state of the turbine, structural health monitoring (SHM) techniques would be beneficial. Physics based SHM in the form of calibration of a finite element model (FEMs) by inverse techniques is adopted in this research. Fuzzy finite element model updating (FFEMU) techniques for damage severity assessment of a small-scale wind turbine blade are discussed and implemented. The main advantage is the ability of FFEMU to account in a simple way for uncertainty within the problem of model updating. Uncertainty quantification techniques, such as fuzzy sets, enable a convenient mathematical representation of the various uncertainties. Experimental frequencies obtained from modal analysis on a small-scale wind turbine blade were described by fuzzy numbers to model measurement uncertainty. During this investigation, damage severity estimation was investigated through addition of small masses of varying magnitude to the trailing edge of the structure. This structural modification, intended to be in lieu of damage, enabled non-destructive experimental simulation of structural change. A numerical model was constructed with multiple variable additional masses simulated upon the blades trailing edge and used as updating parameters. Objective functions for updating were constructed and minimized using both particle swarm optimization algorithm and firefly algorithm. FFEMU was able to obtain a prediction of baseline material properties of the blade whilst also successfully predicting, with sufficient accuracy, a larger magnitude of structural alteration and its location.

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling

PubMed Central

Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

2015-01-01

An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems. PMID:25961028

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling.

PubMed

Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

2015-01-01

An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

A weighted information criterion for multiple minor components and its adaptive extraction algorithms.

PubMed

Gao, Yingbin; Kong, Xiangyu; Zhang, Huihui; Hou, Li'an

2017-05-01

Minor component (MC) plays an important role in signal processing and data analysis, so it is a valuable work to develop MC extraction algorithms. Based on the concepts of weighted subspace and optimum theory, a weighted information criterion is proposed for searching the optimum solution of a linear neural network. This information criterion exhibits a unique global minimum attained if and only if the state matrix is composed of the desired MCs of an autocorrelation matrix of an input signal. By using gradient ascent method and recursive least square (RLS) method, two algorithms are developed for multiple MCs extraction. The global convergences of the proposed algorithms are also analyzed by the Lyapunov method. The proposed algorithms can extract the multiple MCs in parallel and has advantage in dealing with high dimension matrices. Since the weighted matrix does not require an accurate value, it facilitates the system design of the proposed algorithms for practical applications. The speed and computation advantages of the proposed algorithms are verified through simulations. Copyright © 2017 Elsevier Ltd. All rights reserved.

A new algorithm for distorted fingerprints matching based on normalized fuzzy similarity measure.

PubMed

Chen, Xinjian; Tian, Jie; Yang, Xin

2006-03-01

Coping with nonlinear distortions in fingerprint matching is a challenging task. This paper proposes a novel algorithm, normalized fuzzy similarity measure (NFSM), to deal with the nonlinear distortions. The proposed algorithm has two main steps. First, the template and input fingerprints were aligned. In this process, the local topological structure matching was introduced to improve the robustness of global alignment. Second, the method NFSM was introduced to compute the similarity between the template and input fingerprints. The proposed algorithm was evaluated on fingerprints databases of FVC2004. Experimental results confirm that NFSM is a reliable and effective algorithm for fingerprint matching with nonliner distortions. The algorithm gives considerably higher matching scores compared to conventional matching algorithms for the deformed fingerprints.

SDIA: A dynamic situation driven information fusion algorithm for cloud environment

NASA Astrophysics Data System (ADS)

Guo, Shuhang; Wang, Tong; Wang, Jian

2017-09-01

Information fusion is an important issue in information integration domain. In order to form an extensive information fusion technology under the complex and diverse situations, a new information fusion algorithm is proposed. Firstly, a fuzzy evaluation model of tag utility was proposed that can be used to count the tag entropy. Secondly, a ubiquitous situation tag tree model is proposed to define multidimensional structure of information situation. Thirdly, the similarity matching between the situation models is classified into three types: the tree inclusion, the tree embedding, and the tree compatibility. Next, in order to reduce the time complexity of the tree compatible matching algorithm, a fast and ordered tree matching algorithm is proposed based on the node entropy, which is used to support the information fusion by ubiquitous situation. Since the algorithm revolve from the graph theory of disordered tree matching algorithm, it can improve the information fusion present recall rate and precision rate in the situation. The information fusion algorithm is compared with the star and the random tree matching algorithm, and the difference between the three algorithms is analyzed in the view of isomorphism, which proves the innovation and applicability of the algorithm.

A new effective operator for the hybrid algorithm for solving global optimisation problems

NASA Astrophysics Data System (ADS)

Duc, Le Anh; Li, Kenli; Nguyen, Tien Trong; Yen, Vu Minh; Truong, Tung Khac

2018-04-01

Hybrid algorithms have been recently used to solve complex single-objective optimisation problems. The ultimate goal is to find an optimised global solution by using these algorithms. Based on the existing algorithms (HP_CRO, PSO, RCCRO), this study proposes a new hybrid algorithm called MPC (Mean-PSO-CRO), which utilises a new Mean-Search Operator. By employing this new operator, the proposed algorithm improves the search ability on areas of the solution space that the other operators of previous algorithms do not explore. Specifically, the Mean-Search Operator helps find the better solutions in comparison with other algorithms. Moreover, the authors have proposed two parameters for balancing local and global search and between various types of local search, as well. In addition, three versions of this operator, which use different constraints, are introduced. The experimental results on 23 benchmark functions, which are used in previous works, show that our framework can find better optimal or close-to-optimal solutions with faster convergence speed for most of the benchmark functions, especially the high-dimensional functions. Thus, the proposed algorithm is more effective in solving single-objective optimisation problems than the other existing algorithms.

Wavelength converter placement for different RWA algorithms in wavelength-routed all-optical networks

NASA Astrophysics Data System (ADS)

Chu, Xiaowen; Li, Bo; Chlamtac, Imrich

2002-07-01

Sparse wavelength conversion and appropriate routing and wavelength assignment (RWA) algorithms are the two key factors in improving the blocking performance in wavelength-routed all-optical networks. It has been shown that the optimal placement of a limited number of wavelength converters in an arbitrary mesh network is an NP complete problem. There have been various heuristic algorithms proposed in the literature, in which most of them assume that a static routing and random wavelength assignment RWA algorithm is employed. However, the existing work shows that fixed-alternate routing and dynamic routing RWA algorithms can achieve much better blocking performance. Our study in this paper further demonstrates that the wavelength converter placement and RWA algorithms are closely related in the sense that a well designed wavelength converter placement mechanism for a particular RWA algorithm might not work well with a different RWA algorithm. Therefore, the wavelength converter placement and the RWA have to be considered jointly. The objective of this paper is to investigate the wavelength converter placement problem under fixed-alternate routing algorithm and least-loaded routing algorithm. Under the fixed-alternate routing algorithm, we propose a heuristic algorithm called Minimum Blocking Probability First (MBPF) algorithm for wavelength converter placement. Under the least-loaded routing algorithm, we propose a heuristic converter placement algorithm called Weighted Maximum Segment Length (WMSL) algorithm. The objective of the converter placement algorithm is to minimize the overall blocking probability. Extensive simulation studies have been carried out over three typical mesh networks, including the 14-node NSFNET, 19-node EON and 38-node CTNET. We observe that the proposed algorithms not only outperform existing wavelength converter placement algorithms by a large margin, but they also can achieve almost the same performance comparing with full wavelength conversion under the same RWA algorithm.

Adaptive cockroach swarm algorithm

NASA Astrophysics Data System (ADS)

Obagbuwa, Ibidun C.; Abidoye, Ademola P.

2017-07-01

An adaptive cockroach swarm optimization (ACSO) algorithm is proposed in this paper to strengthen the existing cockroach swarm optimization (CSO) algorithm. The ruthless component of CSO algorithm is modified by the employment of blend crossover predator-prey evolution method which helps algorithm prevent any possible population collapse, maintain population diversity and create adaptive search in each iteration. The performance of the proposed algorithm on 16 global optimization benchmark function problems was evaluated and compared with the existing CSO, cuckoo search, differential evolution, particle swarm optimization and artificial bee colony algorithms.

Novel angle estimation for bistatic MIMO radar using an improved MUSIC

NASA Astrophysics Data System (ADS)

Li, Jianfeng; Zhang, Xiaofei; Chen, Han

2014-09-01

In this article, we study the problem of angle estimation for bistatic multiple-input multiple-output (MIMO) radar and propose an improved multiple signal classification (MUSIC) algorithm for joint direction of departure (DOD) and direction of arrival (DOA) estimation. The proposed algorithm obtains initial estimations of angles obtained from the signal subspace and uses the local one-dimensional peak searches to achieve the joint estimations of DOD and DOA. The angle estimation performance of the proposed algorithm is better than that of estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm, and is almost the same as that of two-dimensional MUSIC. Furthermore, the proposed algorithm can be suitable for irregular array geometry, obtain automatically paired DOD and DOA estimations, and avoid two-dimensional peak searching. The simulation results verify the effectiveness and improvement of the algorithm.

A fast iterative recursive least squares algorithm for Wiener model identification of highly nonlinear systems.

PubMed

Kazemi, Mahdi; Arefi, Mohammad Mehdi

2017-03-01

In this paper, an online identification algorithm is presented for nonlinear systems in the presence of output colored noise. The proposed method is based on extended recursive least squares (ERLS) algorithm, where the identified system is in polynomial Wiener form. To this end, an unknown intermediate signal is estimated by using an inner iterative algorithm. The iterative recursive algorithm adaptively modifies the vector of parameters of the presented Wiener model when the system parameters vary. In addition, to increase the robustness of the proposed method against variations, a robust RLS algorithm is applied to the model. Simulation results are provided to show the effectiveness of the proposed approach. Results confirm that the proposed method has fast convergence rate with robust characteristics, which increases the efficiency of the proposed model and identification approach. For instance, the FIT criterion will be achieved 92% in CSTR process where about 400 data is used. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Fast template matching with polynomials.

PubMed

Omachi, Shinichiro; Omachi, Masako

2007-08-01

Template matching is widely used for many applications in image and signal processing. This paper proposes a novel template matching algorithm, called algebraic template matching. Given a template and an input image, algebraic template matching efficiently calculates similarities between the template and the partial images of the input image, for various widths and heights. The partial image most similar to the template image is detected from the input image for any location, width, and height. In the proposed algorithm, a polynomial that approximates the template image is used to match the input image instead of the template image. The proposed algorithm is effective especially when the width and height of the template image differ from the partial image to be matched. An algorithm using the Legendre polynomial is proposed for efficient approximation of the template image. This algorithm not only reduces computational costs, but also improves the quality of the approximated image. It is shown theoretically and experimentally that the computational cost of the proposed algorithm is much smaller than the existing methods.

Hue-preserving and saturation-improved color histogram equalization algorithm.

PubMed

Song, Ki Sun; Kang, Hee; Kang, Moon Gi

2016-06-01

In this paper, an algorithm is proposed to improve contrast and saturation without color degradation. The local histogram equalization (HE) method offers better performance than the global HE method, whereas the local HE method sometimes produces undesirable results due to the block-based processing. The proposed contrast-enhancement (CE) algorithm reflects the characteristics of the global HE method in the local HE method to avoid the artifacts, while global and local contrasts are enhanced. There are two ways to apply the proposed CE algorithm to color images. One is luminance processing methods, and the other one is each channel processing methods. However, these ways incur excessive or reduced saturation and color degradation problems. The proposed algorithm solves these problems by using channel adaptive equalization and similarity of ratios between the channels. Experimental results show that the proposed algorithm enhances contrast and saturation while preserving the hue and producing better performance than existing methods in terms of objective evaluation metrics.

Array signal recovery algorithm for a single-RF-channel DBF array

NASA Astrophysics Data System (ADS)

Zhang, Duo; Wu, Wen; Fang, Da Gang

2016-12-01

An array signal recovery algorithm based on sparse signal reconstruction theory is proposed for a single-RF-channel digital beamforming (DBF) array. A single-RF-channel antenna array is a low-cost antenna array in which signals are obtained from all antenna elements by only one microwave digital receiver. The spatially parallel array signals are converted into time-sequence signals, which are then sampled by the system. The proposed algorithm uses these time-sequence samples to recover the original parallel array signals by exploiting the second-order sparse structure of the array signals. Additionally, an optimization method based on the artificial bee colony (ABC) algorithm is proposed to improve the reconstruction performance. Using the proposed algorithm, the motion compensation problem for the single-RF-channel DBF array can be solved effectively, and the angle and Doppler information for the target can be simultaneously estimated. The effectiveness of the proposed algorithms is demonstrated by the results of numerical simulations.

Evolutionary Fuzzy Block-Matching-Based Camera Raw Image Denoising.

PubMed

Yang, Chin-Chang; Guo, Shu-Mei; Tsai, Jason Sheng-Hong

2017-09-01

An evolutionary fuzzy block-matching-based image denoising algorithm is proposed to remove noise from a camera raw image. Recently, a variance stabilization transform is widely used to stabilize the noise variance, so that a Gaussian denoising algorithm can be used to remove the signal-dependent noise in camera sensors. However, in the stabilized domain, the existed denoising algorithm may blur too much detail. To provide a better estimate of the noise-free signal, a new block-matching approach is proposed to find similar blocks by the use of a type-2 fuzzy logic system (FLS). Then, these similar blocks are averaged with the weightings which are determined by the FLS. Finally, an efficient differential evolution is used to further improve the performance of the proposed denoising algorithm. The experimental results show that the proposed denoising algorithm effectively improves the performance of image denoising. Furthermore, the average performance of the proposed method is better than those of two state-of-the-art image denoising algorithms in subjective and objective measures.

Long-term surface EMG monitoring using K-means clustering and compressive sensing

NASA Astrophysics Data System (ADS)

Balouchestani, Mohammadreza; Krishnan, Sridhar

2015-05-01

In this work, we present an advanced K-means clustering algorithm based on Compressed Sensing theory (CS) in combination with the K-Singular Value Decomposition (K-SVD) method for Clustering of long-term recording of surface Electromyography (sEMG) signals. The long-term monitoring of sEMG signals aims at recording of the electrical activity produced by muscles which are very useful procedure for treatment and diagnostic purposes as well as for detection of various pathologies. The proposed algorithm is examined for three scenarios of sEMG signals including healthy person (sEMG-Healthy), a patient with myopathy (sEMG-Myopathy), and a patient with neuropathy (sEMG-Neuropathr), respectively. The proposed algorithm can easily scan large sEMG datasets of long-term sEMG recording. We test the proposed algorithm with Principal Component Analysis (PCA) and Linear Correlation Coefficient (LCC) dimensionality reduction methods. Then, the output of the proposed algorithm is fed to K-Nearest Neighbours (K-NN) and Probabilistic Neural Network (PNN) classifiers in order to calclute the clustering performance. The proposed algorithm achieves a classification accuracy of 99.22%. This ability allows reducing 17% of Average Classification Error (ACE), 9% of Training Error (TE), and 18% of Root Mean Square Error (RMSE). The proposed algorithm also reduces 14% clustering energy consumption compared to the existing K-Means clustering algorithm.

Research on target tracking algorithm based on spatio-temporal context

NASA Astrophysics Data System (ADS)

Li, Baiping; Xu, Sanmei; Kang, Hongjuan

2017-07-01

In this paper, a novel target tracking algorithm based on spatio-temporal context is proposed. During the tracking process, the camera shaking or occlusion may lead to the failure of tracking. The proposed algorithm can solve this problem effectively. The method use the spatio-temporal context algorithm as the main research object. We get the first frame's target region via mouse. Then the spatio-temporal context algorithm is used to get the tracking targets of the sequence of frames. During this process a similarity measure function based on perceptual hash algorithm is used to judge the tracking results. If tracking failed, reset the initial value of Mean Shift algorithm for the subsequent target tracking. Experiment results show that the proposed algorithm can achieve real-time and stable tracking when camera shaking or target occlusion.

Incoherent beam combining based on the momentum SPGD algorithm

NASA Astrophysics Data System (ADS)

Yang, Guoqing; Liu, Lisheng; Jiang, Zhenhua; Guo, Jin; Wang, Tingfeng

2018-05-01

Incoherent beam combining (ICBC) technology is one of the most promising ways to achieve high-energy, near-diffraction laser output. In this paper, the momentum method is proposed as a modification of the stochastic parallel gradient descent (SPGD) algorithm. The momentum method can improve the speed of convergence of the combining system efficiently. The analytical method is employed to interpret the principle of the momentum method. Furthermore, the proposed algorithm is testified through simulations as well as experiments. The results of the simulations and the experiments show that the proposed algorithm not only accelerates the speed of the iteration, but also keeps the stability of the combining process. Therefore the feasibility of the proposed algorithm in the beam combining system is testified.

Approximated affine projection algorithm for feedback cancellation in hearing aids.

PubMed

Lee, Sangmin; Kim, In-Young; Park, Young-Cheol

2007-09-01

We propose an approximated affine projection (AP) algorithm for feedback cancellation in hearing aids. It is based on the conventional approach using the Gauss-Seidel (GS) iteration, but provides more stable convergence behaviour even with small step sizes. In the proposed algorithm, a residue of the weighted error vector, instead of the current error sample, is used to provide stable convergence. A new learning rate control scheme is also applied to the proposed algorithm to prevent signal cancellation and system instability. The new scheme determines step size in proportion to the prediction factor of the input, so that adaptation is inhibited whenever tone-like signals are present in the input. Simulation results verified the efficiency of the proposed algorithm.

Classification of Parkinson's disease utilizing multi-edit nearest-neighbor and ensemble learning algorithms with speech samples.

PubMed

Zhang, He-Hua; Yang, Liuyang; Liu, Yuchuan; Wang, Pin; Yin, Jun; Li, Yongming; Qiu, Mingguo; Zhu, Xueru; Yan, Fang

2016-11-16

The use of speech based data in the classification of Parkinson disease (PD) has been shown to provide an effect, non-invasive mode of classification in recent years. Thus, there has been an increased interest in speech pattern analysis methods applicable to Parkinsonism for building predictive tele-diagnosis and tele-monitoring models. One of the obstacles in optimizing classifications is to reduce noise within the collected speech samples, thus ensuring better classification accuracy and stability. While the currently used methods are effect, the ability to invoke instance selection has been seldomly examined. In this study, a PD classification algorithm was proposed and examined that combines a multi-edit-nearest-neighbor (MENN) algorithm and an ensemble learning algorithm. First, the MENN algorithm is applied for selecting optimal training speech samples iteratively, thereby obtaining samples with high separability. Next, an ensemble learning algorithm, random forest (RF) or decorrelated neural network ensembles (DNNE), is used to generate trained samples from the collected training samples. Lastly, the trained ensemble learning algorithms are applied to the test samples for PD classification. This proposed method was examined using a more recently deposited public datasets and compared against other currently used algorithms for validation. Experimental results showed that the proposed algorithm obtained the highest degree of improved classification accuracy (29.44%) compared with the other algorithm that was examined. Furthermore, the MENN algorithm alone was found to improve classification accuracy by as much as 45.72%. Moreover, the proposed algorithm was found to exhibit a higher stability, particularly when combining the MENN and RF algorithms. This study showed that the proposed method could improve PD classification when using speech data and can be applied to future studies seeking to improve PD classification methods.

A scalable and practical one-pass clustering algorithm for recommender system

NASA Astrophysics Data System (ADS)

Khalid, Asra; Ghazanfar, Mustansar Ali; Azam, Awais; Alahmari, Saad Ali

2015-12-01

KMeans clustering-based recommendation algorithms have been proposed claiming to increase the scalability of recommender systems. One potential drawback of these algorithms is that they perform training offline and hence cannot accommodate the incremental updates with the arrival of new data, making them unsuitable for the dynamic environments. From this line of research, a new clustering algorithm called One-Pass is proposed, which is a simple, fast, and accurate. We show empirically that the proposed algorithm outperforms K-Means in terms of recommendation and training time while maintaining a good level of accuracy.

Fast perceptual image hash based on cascade algorithm

NASA Astrophysics Data System (ADS)

Ruchay, Alexey; Kober, Vitaly; Yavtushenko, Evgeniya

2017-09-01

In this paper, we propose a perceptual image hash algorithm based on cascade algorithm, which can be applied in image authentication, retrieval, and indexing. Image perceptual hash uses for image retrieval in sense of human perception against distortions caused by compression, noise, common signal processing and geometrical modifications. The main disadvantage of perceptual hash is high time expenses. In the proposed cascade algorithm of image retrieval initializes with short hashes, and then a full hash is applied to the processed results. Computer simulation results show that the proposed hash algorithm yields a good performance in terms of robustness, discriminability, and time expenses.

A Self Adaptive Differential Evolution Algorithm for Global Optimization

NASA Astrophysics Data System (ADS)

Kumar, Pravesh; Pant, Millie

This paper presents a new Differential Evolution algorithm based on hybridization of adaptive control parameters and trigonometric mutation. First we propose a self adaptive DE named ADE where choice of control parameter F and Cr is not fixed at some constant value but is taken iteratively. The proposed algorithm is further modified by applying trigonometric mutation in it and the corresponding algorithm is named as ATDE. The performance of ATDE is evaluated on the set of 8 benchmark functions and the results are compared with the classical DE algorithm in terms of average fitness function value, number of function evaluations, convergence time and success rate. The numerical result shows the competence of the proposed algorithm.

Greedy Algorithms for Nonnegativity-Constrained Simultaneous Sparse Recovery

PubMed Central

Kim, Daeun; Haldar, Justin P.

2016-01-01

This work proposes a family of greedy algorithms to jointly reconstruct a set of vectors that are (i) nonnegative and (ii) simultaneously sparse with a shared support set. The proposed algorithms generalize previous approaches that were designed to impose these constraints individually. Similar to previous greedy algorithms for sparse recovery, the proposed algorithms iteratively identify promising support indices. In contrast to previous approaches, the support index selection procedure has been adapted to prioritize indices that are consistent with both the nonnegativity and shared support constraints. Empirical results demonstrate for the first time that the combined use of simultaneous sparsity and nonnegativity constraints can substantially improve recovery performance relative to existing greedy algorithms that impose less signal structure. PMID:26973368

Fast ℓ1-regularized space-time adaptive processing using alternating direction method of multipliers

NASA Astrophysics Data System (ADS)

Qin, Lilong; Wu, Manqing; Wang, Xuan; Dong, Zhen

2017-04-01

Motivated by the sparsity of filter coefficients in full-dimension space-time adaptive processing (STAP) algorithms, this paper proposes a fast ℓ1-regularized STAP algorithm based on the alternating direction method of multipliers to accelerate the convergence and reduce the calculations. The proposed algorithm uses a splitting variable to obtain an equivalent optimization formulation, which is addressed with an augmented Lagrangian method. Using the alternating recursive algorithm, the method can rapidly result in a low minimum mean-square error without a large number of calculations. Through theoretical analysis and experimental verification, we demonstrate that the proposed algorithm provides a better output signal-to-clutter-noise ratio performance than other algorithms.

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.

Visual saliency-based fast intracoding algorithm for high efficiency video coding

NASA Astrophysics Data System (ADS)

Zhou, Xin; Shi, Guangming; Zhou, Wei; Duan, Zhemin

2017-01-01

Intraprediction has been significantly improved in high efficiency video coding over H.264/AVC with quad-tree-based coding unit (CU) structure from size 64×64 to 8×8 and more prediction modes. However, these techniques cause a dramatic increase in computational complexity. An intracoding algorithm is proposed that consists of perceptual fast CU size decision algorithm and fast intraprediction mode decision algorithm. First, based on the visual saliency detection, an adaptive and fast CU size decision method is proposed to alleviate intraencoding complexity. Furthermore, a fast intraprediction mode decision algorithm with step halving rough mode decision method and early modes pruning algorithm is presented to selectively check the potential modes and effectively reduce the complexity of computation. Experimental results show that our proposed fast method reduces the computational complexity of the current HM to about 57% in encoding time with only 0.37% increases in BD rate. Meanwhile, the proposed fast algorithm has reasonable peak signal-to-noise ratio losses and nearly the same subjective perceptual quality.

A Large-Scale Multi-Hop Localization Algorithm Based on Regularized Extreme Learning for Wireless Networks.

PubMed

Zheng, Wei; Yan, Xiaoyong; Zhao, Wei; Qian, Chengshan

2017-12-20

A novel large-scale multi-hop localization algorithm based on regularized extreme learning is proposed in this paper. The large-scale multi-hop localization problem is formulated as a learning problem. Unlike other similar localization algorithms, the proposed algorithm overcomes the shortcoming of the traditional algorithms which are only applicable to an isotropic network, therefore has a strong adaptability to the complex deployment environment. The proposed algorithm is composed of three stages: data acquisition, modeling and location estimation. In data acquisition stage, the training information between nodes of the given network is collected. In modeling stage, the model among the hop-counts and the physical distances between nodes is constructed using regularized extreme learning. In location estimation stage, each node finds its specific location in a distributed manner. Theoretical analysis and several experiments show that the proposed algorithm can adapt to the different topological environments with low computational cost. Furthermore, high accuracy can be achieved by this method without setting complex parameters.

Computationally efficient algorithm for high sampling-frequency operation of active noise control

NASA Astrophysics Data System (ADS)

Rout, Nirmal Kumar; Das, Debi Prasad; Panda, Ganapati

2015-05-01

In high sampling-frequency operation of active noise control (ANC) system the length of the secondary path estimate and the ANC filter are very long. This increases the computational complexity of the conventional filtered-x least mean square (FXLMS) algorithm. To reduce the computational complexity of long order ANC system using FXLMS algorithm, frequency domain block ANC algorithms have been proposed in past. These full block frequency domain ANC algorithms are associated with some disadvantages such as large block delay, quantization error due to computation of large size transforms and implementation difficulties in existing low-end DSP hardware. To overcome these shortcomings, the partitioned block ANC algorithm is newly proposed where the long length filters in ANC are divided into a number of equal partitions and suitably assembled to perform the FXLMS algorithm in the frequency domain. The complexity of this proposed frequency domain partitioned block FXLMS (FPBFXLMS) algorithm is quite reduced compared to the conventional FXLMS algorithm. It is further reduced by merging one fast Fourier transform (FFT)-inverse fast Fourier transform (IFFT) combination to derive the reduced structure FPBFXLMS (RFPBFXLMS) algorithm. Computational complexity analysis for different orders of filter and partition size are presented. Systematic computer simulations are carried out for both the proposed partitioned block ANC algorithms to show its accuracy compared to the time domain FXLMS algorithm.

Iterative algorithm for joint zero diagonalization with application in blind source separation.

PubMed

Zhang, Wei-Tao; Lou, Shun-Tian

2011-07-01

A new iterative algorithm for the nonunitary joint zero diagonalization of a set of matrices is proposed for blind source separation applications. On one hand, since the zero diagonalizer of the proposed algorithm is constructed iteratively by successive multiplications of an invertible matrix, the singular solutions that occur in the existing nonunitary iterative algorithms are naturally avoided. On the other hand, compared to the algebraic method for joint zero diagonalization, the proposed algorithm requires fewer matrices to be zero diagonalized to yield even better performance. The extension of the algorithm to the complex and nonsquare mixing cases is also addressed. Numerical simulations on both synthetic data and blind source separation using time-frequency distributions illustrate the performance of the algorithm and provide a comparison to the leading joint zero diagonalization schemes.

Personalized recommendation via unbalance full-connectivity inference

NASA Astrophysics Data System (ADS)

Ma, Wenping; Ren, Chen; Wu, Yue; Wang, Shanfeng; Feng, Xiang

2017-10-01

Recommender systems play an important role to help us to find useful information. They are widely used by most e-commerce web sites to push the potential items to individual user according to purchase history. Network-based recommendation algorithms are popular and effective in recommendation, which use two types of elements to represent users and items respectively. In this paper, based on consistence-based inference (CBI) algorithm, we propose a novel network-based algorithm, in which users and items are recognized with no difference. The proposed algorithm also uses information diffusion to find the relationship between users and items. Different from traditional network-based recommendation algorithms, information diffusion initializes from users and items, respectively. Experiments show that the proposed algorithm is effective compared with traditional network-based recommendation algorithms.

An enhanced fast scanning algorithm for image segmentation

NASA Astrophysics Data System (ADS)

Ismael, Ahmed Naser; Yusof, Yuhanis binti

2015-12-01

Segmentation is an essential and important process that separates an image into regions that have similar characteristics or features. This will transform the image for a better image analysis and evaluation. An important benefit of segmentation is the identification of region of interest in a particular image. Various algorithms have been proposed for image segmentation and this includes the Fast Scanning algorithm which has been employed on food, sport and medical images. It scans all pixels in the image and cluster each pixel according to the upper and left neighbor pixels. The clustering process in Fast Scanning algorithm is performed by merging pixels with similar neighbor based on an identified threshold. Such an approach will lead to a weak reliability and shape matching of the produced segments. This paper proposes an adaptive threshold function to be used in the clustering process of the Fast Scanning algorithm. This function used the gray'value in the image's pixels and variance Also, the level of the image that is more the threshold are converted into intensity values between 0 and 1, and other values are converted into intensity values zero. The proposed enhanced Fast Scanning algorithm is realized on images of the public and private transportation in Iraq. Evaluation is later made by comparing the produced images of proposed algorithm and the standard Fast Scanning algorithm. The results showed that proposed algorithm is faster in terms the time from standard fast scanning.

A Modified Differential Coherent Bit Synchronization Algorithm for BeiDou Weak Signals with Large Frequency Deviation.

PubMed

Han, Zhifeng; Liu, Jianye; Li, Rongbing; Zeng, Qinghua; Wang, Yi

2017-07-04

BeiDou system navigation messages are modulated with a secondary NH (Neumann-Hoffman) code of 1 kbps, where frequent bit transitions limit the coherent integration time to 1 millisecond. Therefore, a bit synchronization algorithm is necessary to obtain bit edges and NH code phases. In order to realize bit synchronization for BeiDou weak signals with large frequency deviation, a bit synchronization algorithm based on differential coherent and maximum likelihood is proposed. Firstly, a differential coherent approach is used to remove the effect of frequency deviation, and the differential delay time is set to be a multiple of bit cycle to remove the influence of NH code. Secondly, the maximum likelihood function detection is used to improve the detection probability of weak signals. Finally, Monte Carlo simulations are conducted to analyze the detection performance of the proposed algorithm compared with a traditional algorithm under the CN0s of 20~40 dB-Hz and different frequency deviations. The results show that the proposed algorithm outperforms the traditional method with a frequency deviation of 50 Hz. This algorithm can remove the effect of BeiDou NH code effectively and weaken the influence of frequency deviation. To confirm the feasibility of the proposed algorithm, real data tests are conducted. The proposed algorithm is suitable for BeiDou weak signal bit synchronization with large frequency deviation.

A robust firearm identification algorithm of forensic ballistics specimens

NASA Astrophysics Data System (ADS)

Chuan, Z. L.; Jemain, A. A.; Liong, C.-Y.; Ghani, N. A. M.; Tan, L. K.

2017-09-01

There are several inherent difficulties in the existing firearm identification algorithms, include requiring the physical interpretation and time consuming. Therefore, the aim of this study is to propose a robust algorithm for a firearm identification based on extracting a set of informative features from the segmented region of interest (ROI) using the simulated noisy center-firing pin impression images. The proposed algorithm comprises Laplacian sharpening filter, clustering-based threshold selection, unweighted least square estimator, and segment a square ROI from the noisy images. A total of 250 simulated noisy images collected from five different pistols of the same make, model and caliber are used to evaluate the robustness of the proposed algorithm. This study found that the proposed algorithm is able to perform the identical task on the noisy images with noise levels as high as 70%, while maintaining a firearm identification accuracy rate of over 90%.

Temperature - Emissivity Separation Assessment in a Sub-Urban Scenario

NASA Astrophysics Data System (ADS)

Moscadelli, M.; Diani, M.; Corsini, G.

2017-10-01

In this paper, a methodology that aims at evaluating the effectiveness of different TES strategies is presented. The methodology takes into account the specific material of interest in the monitored scenario, sensor characteristics, and errors in the atmospheric compensation step. The methodology is proposed in order to predict and analyse algorithms performances during the planning of a remote sensing mission, aimed to discover specific materials of interest in the monitored scenario. As case study, the proposed methodology is applied to a real airborne data set of a suburban scenario. In order to perform the TES problem, three state-of-the-art algorithms, and a recently proposed one, are investigated: Temperature-Emissivity Separation '98 (TES-98) algorithm, Stepwise Refining TES (SRTES) algorithm, Linear piecewise TES (LTES) algorithm, and Optimized Smoothing TES (OSTES) algorithm. At the end, the accuracy obtained with real data, and the ones predicted by means of the proposed methodology are compared and discussed.

Active impulsive noise control using maximum correntropy with adaptive kernel size

NASA Astrophysics Data System (ADS)

Lu, Lu; Zhao, Haiquan

2017-03-01

The active noise control (ANC) based on the principle of superposition is an attractive method to attenuate the noise signals. However, the impulsive noise in the ANC systems will degrade the performance of the controller. In this paper, a filtered-x recursive maximum correntropy (FxRMC) algorithm is proposed based on the maximum correntropy criterion (MCC) to reduce the effect of outliers. The proposed FxRMC algorithm does not requires any priori information of the noise characteristics and outperforms the filtered-x least mean square (FxLMS) algorithm for impulsive noise. Meanwhile, in order to adjust the kernel size of FxRMC algorithm online, a recursive approach is proposed through taking into account the past estimates of error signals over a sliding window. Simulation and experimental results in the context of active impulsive noise control demonstrate that the proposed algorithms achieve much better performance than the existing algorithms in various noise environments.

Maneuver Algorithm for Bearings-Only Target Tracking with Acceleration and Field of View Constraints

NASA Astrophysics Data System (ADS)

Roh, Heekun; Shim, Sang-Wook; Tahk, Min-Jea

2018-05-01

This paper proposes a maneuver algorithm for the agent performing target tracking with bearing angle information only. The goal of the agent is to estimate the target position and velocity based only on the bearing angle data. The methods of bearings-only target state estimation are outlined. The nature of bearings-only target tracking problem is then addressed. Based on the insight from above-mentioned properties, the maneuver algorithm for the agent is suggested. The proposed algorithm is composed of a nonlinear, hysteresis guidance law and the estimation accuracy assessment criteria based on the theory of Cramer-Rao bound. The proposed guidance law generates lateral acceleration command based on current field of view angle. The accuracy criteria supply the expected estimation variance, which acts as a terminal criterion for the proposed algorithm. The aforementioned algorithm is verified with a two-dimensional simulation.

Short-term Power Load Forecasting Based on Balanced KNN

NASA Astrophysics Data System (ADS)

Lv, Xianlong; Cheng, Xingong; YanShuang; Tang, Yan-mei

2018-03-01

To improve the accuracy of load forecasting, a short-term load forecasting model based on balanced KNN algorithm is proposed; According to the load characteristics, the historical data of massive power load are divided into scenes by the K-means algorithm; In view of unbalanced load scenes, the balanced KNN algorithm is proposed to classify the scene accurately; The local weighted linear regression algorithm is used to fitting and predict the load; Adopting the Apache Hadoop programming framework of cloud computing, the proposed algorithm model is parallelized and improved to enhance its ability of dealing with massive and high-dimension data. The analysis of the household electricity consumption data for a residential district is done by 23-nodes cloud computing cluster, and experimental results show that the load forecasting accuracy and execution time by the proposed model are the better than those of traditional forecasting algorithm.

Detecting community structure via the maximal sub-graphs and belonging degrees in complex networks

NASA Astrophysics Data System (ADS)

Cui, Yaozu; Wang, Xingyuan; Eustace, Justine

2014-12-01

Community structure is a common phenomenon in complex networks, and it has been shown that some communities in complex networks often overlap each other. So in this paper we propose a new algorithm to detect overlapping community structure in complex networks. To identify the overlapping community structure, our algorithm firstly extracts fully connected sub-graphs which are maximal sub-graphs from original networks. Then two maximal sub-graphs having the key pair-vertices can be merged into a new larger sub-graph using some belonging degree functions. Furthermore we extend the modularity function to evaluate the proposed algorithm. In addition, overlapping nodes between communities are founded successfully. Finally we report the comparison between the modularity and the computational complexity of the proposed algorithm with some other existing algorithms. The experimental results show that the proposed algorithm gives satisfactory results.

An Efficient Conflict Detection Algorithm for Packet Filters

NASA Astrophysics Data System (ADS)

Lee, Chun-Liang; Lin, Guan-Yu; Chen, Yaw-Chung

Packet classification is essential for supporting advanced network services such as firewalls, quality-of-service (QoS), virtual private networks (VPN), and policy-based routing. The rules that routers use to classify packets are called packet filters. If two or more filters overlap, a conflict occurs and leads to ambiguity in packet classification. This study proposes an algorithm that can efficiently detect and resolve filter conflicts using tuple based search. The time complexity of the proposed algorithm is O(nW+s), and the space complexity is O(nW), where n is the number of filters, W is the number of bits in a header field, and s is the number of conflicts. This study uses the synthetic filter databases generated by ClassBench to evaluate the proposed algorithm. Simulation results show that the proposed algorithm can achieve better performance than existing conflict detection algorithms both in time and space, particularly for databases with large numbers of conflicts.

Asynchronous Incremental Stochastic Dual Descent Algorithm for Network Resource Allocation

NASA Astrophysics Data System (ADS)

Bedi, Amrit Singh; Rajawat, Ketan

2018-05-01

Stochastic network optimization problems entail finding resource allocation policies that are optimum on an average but must be designed in an online fashion. Such problems are ubiquitous in communication networks, where resources such as energy and bandwidth are divided among nodes to satisfy certain long-term objectives. This paper proposes an asynchronous incremental dual decent resource allocation algorithm that utilizes delayed stochastic {gradients} for carrying out its updates. The proposed algorithm is well-suited to heterogeneous networks as it allows the computationally-challenged or energy-starved nodes to, at times, postpone the updates. The asymptotic analysis of the proposed algorithm is carried out, establishing dual convergence under both, constant and diminishing step sizes. It is also shown that with constant step size, the proposed resource allocation policy is asymptotically near-optimal. An application involving multi-cell coordinated beamforming is detailed, demonstrating the usefulness of the proposed algorithm.

Heterogeneous Tensor Decomposition for Clustering via Manifold Optimization.

PubMed

Sun, Yanfeng; Gao, Junbin; Hong, Xia; Mishra, Bamdev; Yin, Baocai

2016-03-01

Tensor clustering is an important tool that exploits intrinsically rich structures in real-world multiarray or Tensor datasets. Often in dealing with those datasets, standard practice is to use subspace clustering that is based on vectorizing multiarray data. However, vectorization of tensorial data does not exploit complete structure information. In this paper, we propose a subspace clustering algorithm without adopting any vectorization process. Our approach is based on a novel heterogeneous Tucker decomposition model taking into account cluster membership information. We propose a new clustering algorithm that alternates between different modes of the proposed heterogeneous tensor model. All but the last mode have closed-form updates. Updating the last mode reduces to optimizing over the multinomial manifold for which we investigate second order Riemannian geometry and propose a trust-region algorithm. Numerical experiments show that our proposed algorithm compete effectively with state-of-the-art clustering algorithms that are based on tensor factorization.

Liposomes as protective capsules for active silica sol-gel biocomposite synthesis.

PubMed

Li, Ye; Yip, Wai Tak

2005-09-21

Using liposome to shield an enzyme from hostile chemical environments during the sol-gel formation process has resulted in a novel approach to synthesizing silica sol-gel biocomposite materials. By reporting the encapsulation of horseradish peroxidase and firefly luciferase, we demonstrate that this new protocol can produce silica biocomposites that are more active than trapping the enzymes directly into hydrogels.

Method of detecting and counting bacteria in body fluids

NASA Technical Reports Server (NTRS)

Chappelle, E. W.; Picciolo, G. L. (Inventor)

1973-01-01

A novel method is reported for determining bacterial levels in urine samples, which method depends on the quantitative determination of bacterial adenosine triphosphate (ATP) in the presence of non-bacterial ATP. After the removal of non-bacterial ATP, the bacterial ATP is released by cell rupture and is measured by an enzymatic bioluminescent assay using an enzyme obtained from the firefly.

Firefly

DTIC Science & Technology

2012-05-29

Hunter College has completed work on baseline measurements of relaxation times for pentacene at various temperatures in order to determine optimal...temperatures for measuring relaxation rate as a function of doping. We have also repeated these measurements on pentacene samples at 2 different...P3HT using a time-lag method. 2 Technical Accomplishments This Period Relaxation Measurements on Pentacene . As described initially in the 1Q

QPSO-Based Adaptive DNA Computing Algorithm

PubMed Central

Karakose, Mehmet; Cigdem, Ugur

2013-01-01

DNA (deoxyribonucleic acid) computing that is a new computation model based on DNA molecules for information storage has been increasingly used for optimization and data analysis in recent years. However, DNA computing algorithm has some limitations in terms of convergence speed, adaptability, and effectiveness. In this paper, a new approach for improvement of DNA computing is proposed. This new approach aims to perform DNA computing algorithm with adaptive parameters towards the desired goal using quantum-behaved particle swarm optimization (QPSO). Some contributions provided by the proposed QPSO based on adaptive DNA computing algorithm are as follows: (1) parameters of population size, crossover rate, maximum number of operations, enzyme and virus mutation rate, and fitness function of DNA computing algorithm are simultaneously tuned for adaptive process, (2) adaptive algorithm is performed using QPSO algorithm for goal-driven progress, faster operation, and flexibility in data, and (3) numerical realization of DNA computing algorithm with proposed approach is implemented in system identification. Two experiments with different systems were carried out to evaluate the performance of the proposed approach with comparative results. Experimental results obtained with Matlab and FPGA demonstrate ability to provide effective optimization, considerable convergence speed, and high accuracy according to DNA computing algorithm. PMID:23935409

Unmitigated numerical solution to the diffraction term in the parabolic nonlinear ultrasound wave equation.

PubMed

Hasani, Mojtaba H; Gharibzadeh, Shahriar; Farjami, Yaghoub; Tavakkoli, Jahan

2013-09-01

Various numerical algorithms have been developed to solve the Khokhlov-Kuznetsov-Zabolotskaya (KZK) parabolic nonlinear wave equation. In this work, a generalized time-domain numerical algorithm is proposed to solve the diffraction term of the KZK equation. This algorithm solves the transverse Laplacian operator of the KZK equation in three-dimensional (3D) Cartesian coordinates using a finite-difference method based on the five-point implicit backward finite difference and the five-point Crank-Nicolson finite difference discretization techniques. This leads to a more uniform discretization of the Laplacian operator which in turn results in fewer calculation gridding nodes without compromising accuracy in the diffraction term. In addition, a new empirical algorithm based on the LU decomposition technique is proposed to solve the system of linear equations obtained from this discretization. The proposed empirical algorithm improves the calculation speed and memory usage, while the order of computational complexity remains linear in calculation of the diffraction term in the KZK equation. For evaluating the accuracy of the proposed algorithm, two previously published algorithms are used as comparison references: the conventional 2D Texas code and its generalization for 3D geometries. The results show that the accuracy/efficiency performance of the proposed algorithm is comparable with the established time-domain methods.

An arrhythmia classification algorithm using a dedicated wavelet adapted to different subjects.

PubMed

Kim, Jinkwon; Min, Se Dong; Lee, Myoungho

2011-06-27

Numerous studies have been conducted regarding a heartbeat classification algorithm over the past several decades. However, many algorithms have also been studied to acquire robust performance, as biosignals have a large amount of variation among individuals. Various methods have been proposed to reduce the differences coming from personal characteristics, but these expand the differences caused by arrhythmia. In this paper, an arrhythmia classification algorithm using a dedicated wavelet adapted to individual subjects is proposed. We reduced the performance variation using dedicated wavelets, as in the ECG morphologies of the subjects. The proposed algorithm utilizes morphological filtering and a continuous wavelet transform with a dedicated wavelet. A principal component analysis and linear discriminant analysis were utilized to compress the morphological data transformed by the dedicated wavelets. An extreme learning machine was used as a classifier in the proposed algorithm. A performance evaluation was conducted with the MIT-BIH arrhythmia database. The results showed a high sensitivity of 97.51%, specificity of 85.07%, accuracy of 97.94%, and a positive predictive value of 97.26%. The proposed algorithm achieves better accuracy than other state-of-the-art algorithms with no intrasubject between the training and evaluation datasets. And it significantly reduces the amount of intervention needed by physicians.

An arrhythmia classification algorithm using a dedicated wavelet adapted to different subjects

PubMed Central

2011-01-01

Background Numerous studies have been conducted regarding a heartbeat classification algorithm over the past several decades. However, many algorithms have also been studied to acquire robust performance, as biosignals have a large amount of variation among individuals. Various methods have been proposed to reduce the differences coming from personal characteristics, but these expand the differences caused by arrhythmia. Methods In this paper, an arrhythmia classification algorithm using a dedicated wavelet adapted to individual subjects is proposed. We reduced the performance variation using dedicated wavelets, as in the ECG morphologies of the subjects. The proposed algorithm utilizes morphological filtering and a continuous wavelet transform with a dedicated wavelet. A principal component analysis and linear discriminant analysis were utilized to compress the morphological data transformed by the dedicated wavelets. An extreme learning machine was used as a classifier in the proposed algorithm. Results A performance evaluation was conducted with the MIT-BIH arrhythmia database. The results showed a high sensitivity of 97.51%, specificity of 85.07%, accuracy of 97.94%, and a positive predictive value of 97.26%. Conclusions The proposed algorithm achieves better accuracy than other state-of-the-art algorithms with no intrasubject between the training and evaluation datasets. And it significantly reduces the amount of intervention needed by physicians. PMID:21707989

Optical imaging of Renilla luciferase, synthetic Renilla luciferase, and firefly luciferase reporter gene expression in living mice.

PubMed

Bhaumik, S; Lewis, X Z; Gambhir, S S

2004-01-01

We have recently demonstrated that Renilla luciferase (Rluc) is a promising bioluminescence reporter gene that can be used for noninvasive optical imaging of reporter gene expression in living mice, with the aid of a cooled charged couple device (CCD) camera. In the current study, we explore the expression of a novel synthetic Renilla luciferase reporter gene (hRluc) in living mice, which has previously been reported to be a more sensitive reporter than native Rluc in mammalian cells. We explore the strategies of simultaneous imaging of both Renilla luciferase enzyme (RL) and synthetic Renilla luciferase enzyme (hRL):coelenterazine (substrate for RL/hRL) in the same living mouse. We also demonstrate that hRL:coelenterazine can yield a higher signal when compared to Firefly luciferase enzyme (FL): D-Luciferin, both in cell culture studies and when imaged from cells at the surface and from lungs of living mice. These studies demonstrate that hRluc should be a useful primary reporter gene with high sensitivity when used alone or in conjunction with other bioluminescence reporter genes for imaging in living rodents. (c) 2004 Society of Photo-Optical Instrumentation Engineers.

A homogeneous biochemiluminescent assay for detection of influenza

NASA Astrophysics Data System (ADS)

Hui, Kwok Min; Li, Xiao Jing; Pan, Lu; Li, X. J.

2015-05-01

Current methods of rapid detection of influenza are based on detection of the nucleic acids or antigens of influenza viruses. Since influenza viruses constantly mutate leading to appearance of new strains or variants of viruses, these detection methods are susceptible to genetic changes in influenza viruses. Type A and B influenza viruses contain neuraminidase, an essential enzyme for virus replication which enables progeny influenza viruses leave the host cells to infect new cells. Here we describe an assay method, the homogeneous biochemiluminescent assay (HBA), for rapid detection of influenza by detecting viral neuraminidase activity. The assay mimics the light production process of a firefly: a viral neuraminidase specific substrate containing a luciferin moiety is cleaved in the presence of influenza virus to release luciferin, which becomes a substrate to firefly luciferase in a light production system. All reagents can be formulated in a single reaction mix so that the assay involves only one manual step, i.e., sample addition. Presence of Type A or B influenza virus in the sample leads to production of strong, stable and easily detectable light signal, which lasts for hours. Thus, this influenza virus assay is suitable for use in point-of-care settings.

FT-IR, FT-Raman spectra and DFT calculations of melaminium perchlorate monohydrate.

PubMed

Kanagathara, N; Marchewka, M K; Drozd, M; Renganathan, N G; Gunasekaran, S; Anbalagan, G

2013-08-01

Melaminium perchlorate monohydrate (MPM), an organic material has been synthesized by slow solvent evaporation method at room temperature. Powder X-ray diffraction analysis confirms that MPM crystal belongs to triclinic system with space group P-1. FTIR and FT Raman spectra are recorded at room temperature. Functional group assignment has been made for the melaminium cations and perchlorate anions. Vibrational spectra have also been discussed on the basis of quantum chemical density functional theory (DFT) calculations using Firefly (PC GAMESS) version 7.1 G. Vibrational frequencies are calculated and scaled values are compared with experimental values. The assignment of the bands has been made on the basis of the calculated PED. The Mulliken charges, HOMO-LUMO orbital energies are analyzed directly from Firefly program log files and graphically illustrated. HOMO-LUMO energy gap and other related molecular properties are also calculated. The theoretically constructed FT-IR and FT-Raman spectra of MPM coincide with the experimental one. The chemical structure of the compound has been established by (1)H and (13)C NMR spectra. No detectable signal was observed during powder test for second harmonic generation. Copyright © 2013 Elsevier B.V. All rights reserved.

Development of a new metal artifact reduction algorithm by using an edge preserving method for CBCT imaging

NASA Astrophysics Data System (ADS)

Kim, Juhye; Nam, Haewon; Lee, Rena

2015-07-01

CT (computed tomography) images, metal materials such as tooth supplements or surgical clips can cause metal artifact and degrade image quality. In severe cases, this may lead to misdiagnosis. In this research, we developed a new MAR (metal artifact reduction) algorithm by using an edge preserving filter and the MATLAB program (Mathworks, version R2012a). The proposed algorithm consists of 6 steps: image reconstruction from projection data, metal segmentation, forward projection, interpolation, applied edge preserving smoothing filter, and new image reconstruction. For an evaluation of the proposed algorithm, we obtained both numerical simulation data and data for a Rando phantom. In the numerical simulation data, four metal regions were added into the Shepp Logan phantom for metal artifacts. The projection data of the metal-inserted Rando phantom were obtained by using a prototype CBCT scanner manufactured by medical engineering and medical physics (MEMP) laboratory research group in medical science at Ewha Womans University. After these had been adopted the proposed algorithm was performed, and the result were compared with the original image (with metal artifact without correction) and with a corrected image based on linear interpolation. Both visual and quantitative evaluations were done. Compared with the original image with metal artifacts and with the image corrected by using linear interpolation, both the numerical and the experimental phantom data demonstrated that the proposed algorithm reduced the metal artifact. In conclusion, the evaluation in this research showed that the proposed algorithm outperformed the interpolation based MAR algorithm. If an optimization and a stability evaluation of the proposed algorithm can be performed, the developed algorithm is expected to be an effective tool for eliminating metal artifacts even in commercial CT systems.

Gaussian diffusion sinogram inpainting for X-ray CT metal artifact reduction.

PubMed

Peng, Chengtao; Qiu, Bensheng; Li, Ming; Guan, Yihui; Zhang, Cheng; Wu, Zhongyi; Zheng, Jian

2017-01-05

Metal objects implanted in the bodies of patients usually generate severe streaking artifacts in reconstructed images of X-ray computed tomography, which degrade the image quality and affect the diagnosis of disease. Therefore, it is essential to reduce these artifacts to meet the clinical demands. In this work, we propose a Gaussian diffusion sinogram inpainting metal artifact reduction algorithm based on prior images to reduce these artifacts for fan-beam computed tomography reconstruction. In this algorithm, prior information that originated from a tissue-classified prior image is used for the inpainting of metal-corrupted projections, and it is incorporated into a Gaussian diffusion function. The prior knowledge is particularly designed to locate the diffusion position and improve the sparsity of the subtraction sinogram, which is obtained by subtracting the prior sinogram of the metal regions from the original sinogram. The sinogram inpainting algorithm is implemented through an approach of diffusing prior energy and is then solved by gradient descent. The performance of the proposed metal artifact reduction algorithm is compared with two conventional metal artifact reduction algorithms, namely the interpolation metal artifact reduction algorithm and normalized metal artifact reduction algorithm. The experimental datasets used included both simulated and clinical datasets. By evaluating the results subjectively, the proposed metal artifact reduction algorithm causes fewer secondary artifacts than the two conventional metal artifact reduction algorithms, which lead to severe secondary artifacts resulting from impertinent interpolation and normalization. Additionally, the objective evaluation shows the proposed approach has the smallest normalized mean absolute deviation and the highest signal-to-noise ratio, indicating that the proposed method has produced the image with the best quality. No matter for the simulated datasets or the clinical datasets, the proposed algorithm has reduced the metal artifacts apparently.

A novel artificial immune clonal selection classification and rule mining with swarm learning model

NASA Astrophysics Data System (ADS)

Al-Sheshtawi, Khaled A.; Abdul-Kader, Hatem M.; Elsisi, Ashraf B.

2013-06-01

Metaheuristic optimisation algorithms have become popular choice for solving complex problems. By integrating Artificial Immune clonal selection algorithm (CSA) and particle swarm optimisation (PSO) algorithm, a novel hybrid Clonal Selection Classification and Rule Mining with Swarm Learning Algorithm (CS2) is proposed. The main goal of the approach is to exploit and explore the parallel computation merit of Clonal Selection and the speed and self-organisation merits of Particle Swarm by sharing information between clonal selection population and particle swarm. Hence, we employed the advantages of PSO to improve the mutation mechanism of the artificial immune CSA and to mine classification rules within datasets. Consequently, our proposed algorithm required less training time and memory cells in comparison to other AIS algorithms. In this paper, classification rule mining has been modelled as a miltiobjective optimisation problem with predictive accuracy. The multiobjective approach is intended to allow the PSO algorithm to return an approximation to the accuracy and comprehensibility border, containing solutions that are spread across the border. We compared our proposed algorithm classification accuracy CS2 with five commonly used CSAs, namely: AIRS1, AIRS2, AIRS-Parallel, CLONALG, and CSCA using eight benchmark datasets. We also compared our proposed algorithm classification accuracy CS2 with other five methods, namely: Naïve Bayes, SVM, MLP, CART, and RFB. The results show that the proposed algorithm is comparable to the 10 studied algorithms. As a result, the hybridisation, built of CSA and PSO, can develop respective merit, compensate opponent defect, and make search-optimal effect and speed better.

The serial message-passing schedule for LDPC decoding algorithms

NASA Astrophysics Data System (ADS)

Liu, Mingshan; Liu, Shanshan; Zhou, Yuan; Jiang, Xue

2015-12-01

The conventional message-passing schedule for LDPC decoding algorithms is the so-called flooding schedule. It has the disadvantage that the updated messages cannot be used until next iteration, thus reducing the convergence speed . In this case, the Layered Decoding algorithm (LBP) based on serial message-passing schedule is proposed. In this paper the decoding principle of LBP algorithm is briefly introduced, and then proposed its two improved algorithms, the grouped serial decoding algorithm (Grouped LBP) and the semi-serial decoding algorithm .They can improve LBP algorithm's decoding speed while maintaining a good decoding performance.

CURE-SMOTE algorithm and hybrid algorithm for feature selection and parameter optimization based on random forests.

PubMed

Ma, Li; Fan, Suohai

2017-03-14

The random forests algorithm is a type of classifier with prominent universality, a wide application range, and robustness for avoiding overfitting. But there are still some drawbacks to random forests. Therefore, to improve the performance of random forests, this paper seeks to improve imbalanced data processing, feature selection and parameter optimization. We propose the CURE-SMOTE algorithm for the imbalanced data classification problem. Experiments on imbalanced UCI data reveal that the combination of Clustering Using Representatives (CURE) enhances the original synthetic minority oversampling technique (SMOTE) algorithms effectively compared with the classification results on the original data using random sampling, Borderline-SMOTE1, safe-level SMOTE, C-SMOTE, and k-means-SMOTE. Additionally, the hybrid RF (random forests) algorithm has been proposed for feature selection and parameter optimization, which uses the minimum out of bag (OOB) data error as its objective function. Simulation results on binary and higher-dimensional data indicate that the proposed hybrid RF algorithms, hybrid genetic-random forests algorithm, hybrid particle swarm-random forests algorithm and hybrid fish swarm-random forests algorithm can achieve the minimum OOB error and show the best generalization ability. The training set produced from the proposed CURE-SMOTE algorithm is closer to the original data distribution because it contains minimal noise. Thus, better classification results are produced from this feasible and effective algorithm. Moreover, the hybrid algorithm's F-value, G-mean, AUC and OOB scores demonstrate that they surpass the performance of the original RF algorithm. Hence, this hybrid algorithm provides a new way to perform feature selection and parameter optimization.

A flocking algorithm for multi-agent systems with connectivity preservation under hybrid metric-topological interactions.

PubMed

He, Chenlong; Feng, Zuren; Ren, Zhigang

2018-01-01

In this paper, we propose a connectivity-preserving flocking algorithm for multi-agent systems in which the neighbor set of each agent is determined by the hybrid metric-topological distance so that the interaction topology can be represented as the range-limited Delaunay graph, which combines the properties of the commonly used disk graph and Delaunay graph. As a result, the proposed flocking algorithm has the following advantages over the existing ones. First, range-limited Delaunay graph is sparser than the disk graph so that the information exchange among agents is reduced significantly. Second, some links irrelevant to the connectivity can be dynamically deleted during the evolution of the system. Thus, the proposed flocking algorithm is more flexible than existing algorithms, where links are not allowed to be disconnected once they are created. Finally, the multi-agent system spontaneously generates a regular quasi-lattice formation without imposing the constraint on the ratio of the sensing range of the agent to the desired distance between two adjacent agents. With the interaction topology induced by the hybrid distance, the proposed flocking algorithm can still be implemented in a distributed manner. We prove that the proposed flocking algorithm can steer the multi-agent system to a stable flocking motion, provided the initial interaction topology of multi-agent systems is connected and the hysteresis in link addition is smaller than a derived upper bound. The correctness and effectiveness of the proposed algorithm are verified by extensive numerical simulations, where the flocking algorithms based on the disk and Delaunay graph are compared.

A flocking algorithm for multi-agent systems with connectivity preservation under hybrid metric-topological interactions

PubMed Central

Feng, Zuren; Ren, Zhigang

2018-01-01

In this paper, we propose a connectivity-preserving flocking algorithm for multi-agent systems in which the neighbor set of each agent is determined by the hybrid metric-topological distance so that the interaction topology can be represented as the range-limited Delaunay graph, which combines the properties of the commonly used disk graph and Delaunay graph. As a result, the proposed flocking algorithm has the following advantages over the existing ones. First, range-limited Delaunay graph is sparser than the disk graph so that the information exchange among agents is reduced significantly. Second, some links irrelevant to the connectivity can be dynamically deleted during the evolution of the system. Thus, the proposed flocking algorithm is more flexible than existing algorithms, where links are not allowed to be disconnected once they are created. Finally, the multi-agent system spontaneously generates a regular quasi-lattice formation without imposing the constraint on the ratio of the sensing range of the agent to the desired distance between two adjacent agents. With the interaction topology induced by the hybrid distance, the proposed flocking algorithm can still be implemented in a distributed manner. We prove that the proposed flocking algorithm can steer the multi-agent system to a stable flocking motion, provided the initial interaction topology of multi-agent systems is connected and the hysteresis in link addition is smaller than a derived upper bound. The correctness and effectiveness of the proposed algorithm are verified by extensive numerical simulations, where the flocking algorithms based on the disk and Delaunay graph are compared. PMID:29462217

Time-frequency analysis-based time-windowing algorithm for the inverse synthetic aperture radar imaging of ships

NASA Astrophysics Data System (ADS)

Zhou, Peng; Zhang, Xi; Sun, Weifeng; Dai, Yongshou; Wan, Yong

2018-01-01

An algorithm based on time-frequency analysis is proposed to select an imaging time window for the inverse synthetic aperture radar imaging of ships. An appropriate range bin is selected to perform the time-frequency analysis after radial motion compensation. The selected range bin is that with the maximum mean amplitude among the range bins whose echoes are confirmed to be contributed by a dominant scatter. The criterion for judging whether the echoes of a range bin are contributed by a dominant scatter is key to the proposed algorithm and is therefore described in detail. When the first range bin that satisfies the judgment criterion is found, a sequence composed of the frequencies that have the largest amplitudes in every moment's time-frequency spectrum corresponding to this range bin is employed to calculate the length and the center moment of the optimal imaging time window. Experiments performed with simulation data and real data show the effectiveness of the proposed algorithm, and comparisons between the proposed algorithm and the image contrast-based algorithm (ICBA) are provided. Similar image contrast and lower entropy are acquired using the proposed algorithm as compared with those values when using the ICBA.

Two New PRP Conjugate Gradient Algorithms for Minimization Optimization Models.

PubMed

Yuan, Gonglin; Duan, Xiabin; Liu, Wenjie; Wang, Xiaoliang; Cui, Zengru; Sheng, Zhou

2015-01-01

Two new PRP conjugate Algorithms are proposed in this paper based on two modified PRP conjugate gradient methods: the first algorithm is proposed for solving unconstrained optimization problems, and the second algorithm is proposed for solving nonlinear equations. The first method contains two aspects of information: function value and gradient value. The two methods both possess some good properties, as follows: 1) βk ≥ 0 2) the search direction has the trust region property without the use of any line search method 3) the search direction has sufficient descent property without the use of any line search method. Under some suitable conditions, we establish the global convergence of the two algorithms. We conduct numerical experiments to evaluate our algorithms. The numerical results indicate that the first algorithm is effective and competitive for solving unconstrained optimization problems and that the second algorithm is effective for solving large-scale nonlinear equations.

Two New PRP Conjugate Gradient Algorithms for Minimization Optimization Models

PubMed Central

Yuan, Gonglin; Duan, Xiabin; Liu, Wenjie; Wang, Xiaoliang; Cui, Zengru; Sheng, Zhou

2015-01-01

Two new PRP conjugate Algorithms are proposed in this paper based on two modified PRP conjugate gradient methods: the first algorithm is proposed for solving unconstrained optimization problems, and the second algorithm is proposed for solving nonlinear equations. The first method contains two aspects of information: function value and gradient value. The two methods both possess some good properties, as follows: 1)β k ≥ 0 2) the search direction has the trust region property without the use of any line search method 3) the search direction has sufficient descent property without the use of any line search method. Under some suitable conditions, we establish the global convergence of the two algorithms. We conduct numerical experiments to evaluate our algorithms. The numerical results indicate that the first algorithm is effective and competitive for solving unconstrained optimization problems and that the second algorithm is effective for solving large-scale nonlinear equations. PMID:26502409

Wavelet compression of multichannel ECG data by enhanced set partitioning in hierarchical trees algorithm.

PubMed

Sharifahmadian, Ershad

2006-01-01

The set partitioning in hierarchical trees (SPIHT) algorithm is very effective and computationally simple technique for image and signal compression. Here the author modified the algorithm which provides even better performance than the SPIHT algorithm. The enhanced set partitioning in hierarchical trees (ESPIHT) algorithm has performance faster than the SPIHT algorithm. In addition, the proposed algorithm reduces the number of bits in a bit stream which is stored or transmitted. I applied it to compression of multichannel ECG data. Also, I presented a specific procedure based on the modified algorithm for more efficient compression of multichannel ECG data. This method employed on selected records from the MIT-BIH arrhythmia database. According to experiments, the proposed method attained the significant results regarding compression of multichannel ECG data. Furthermore, in order to compress one signal which is stored for a long time, the proposed multichannel compression method can be utilized efficiently.

A proximity algorithm accelerated by Gauss-Seidel iterations for L1/TV denoising models

NASA Astrophysics Data System (ADS)

Li, Qia; Micchelli, Charles A.; Shen, Lixin; Xu, Yuesheng

2012-09-01

Our goal in this paper is to improve the computational performance of the proximity algorithms for the L1/TV denoising model. This leads us to a new characterization of all solutions to the L1/TV model via fixed-point equations expressed in terms of the proximity operators. Based upon this observation we develop an algorithm for solving the model and establish its convergence. Furthermore, we demonstrate that the proposed algorithm can be accelerated through the use of the componentwise Gauss-Seidel iteration so that the CPU time consumed is significantly reduced. Numerical experiments using the proposed algorithm for impulsive noise removal are included, with a comparison to three recently developed algorithms. The numerical results show that while the proposed algorithm enjoys a high quality of the restored images, as the other three known algorithms do, it performs significantly better in terms of computational efficiency measured in the CPU time consumed.

Beamspace dual signal space projection (bDSSP): a method for selective detection of deep sources in MEG measurements.

PubMed

Sekihara, Kensuke; Adachi, Yoshiaki; Kubota, Hiroshi K; Cai, Chang; Nagarajan, Srikantan S

2018-06-01

Magnetoencephalography (MEG) has a well-recognized weakness at detecting deeper brain activities. This paper proposes a novel algorithm for selective detection of deep sources by suppressing interference signals from superficial sources in MEG measurements. The proposed algorithm combines the beamspace preprocessing method with the dual signal space projection (DSSP) interference suppression method. A prerequisite of the proposed algorithm is prior knowledge of the location of the deep sources. The proposed algorithm first derives the basis vectors that span a local region just covering the locations of the deep sources. It then estimates the time-domain signal subspace of the superficial sources by using the projector composed of these basis vectors. Signals from the deep sources are extracted by projecting the row space of the data matrix onto the direction orthogonal to the signal subspace of the superficial sources. Compared with the previously proposed beamspace signal space separation (SSS) method, the proposed algorithm is capable of suppressing much stronger interference from superficial sources. This capability is demonstrated in our computer simulation as well as experiments using phantom data. The proposed bDSSP algorithm can be a powerful tool in studies of physiological functions of midbrain and deep brain structures.

Beamspace dual signal space projection (bDSSP): a method for selective detection of deep sources in MEG measurements

NASA Astrophysics Data System (ADS)

Sekihara, Kensuke; Adachi, Yoshiaki; Kubota, Hiroshi K.; Cai, Chang; Nagarajan, Srikantan S.

2018-06-01

Objective. Magnetoencephalography (MEG) has a well-recognized weakness at detecting deeper brain activities. This paper proposes a novel algorithm for selective detection of deep sources by suppressing interference signals from superficial sources in MEG measurements. Approach. The proposed algorithm combines the beamspace preprocessing method with the dual signal space projection (DSSP) interference suppression method. A prerequisite of the proposed algorithm is prior knowledge of the location of the deep sources. The proposed algorithm first derives the basis vectors that span a local region just covering the locations of the deep sources. It then estimates the time-domain signal subspace of the superficial sources by using the projector composed of these basis vectors. Signals from the deep sources are extracted by projecting the row space of the data matrix onto the direction orthogonal to the signal subspace of the superficial sources. Main results. Compared with the previously proposed beamspace signal space separation (SSS) method, the proposed algorithm is capable of suppressing much stronger interference from superficial sources. This capability is demonstrated in our computer simulation as well as experiments using phantom data. Significance. The proposed bDSSP algorithm can be a powerful tool in studies of physiological functions of midbrain and deep brain structures.

Development of a Tool for an Efficient Calibration of CORSIM Models

DOT National Transportation Integrated Search

2014-08-01

This project proposes a Memetic Algorithm (MA) for the calibration of microscopic traffic flow simulation models. The proposed MA includes a combination of genetic and simulated annealing algorithms. The genetic algorithm performs the exploration of ...

On an adaptive preconditioned Crank-Nicolson MCMC algorithm for infinite dimensional Bayesian inference

NASA Astrophysics Data System (ADS)

Hu, Zixi; Yao, Zhewei; Li, Jinglai

2017-03-01

Many scientific and engineering problems require to perform Bayesian inference for unknowns of infinite dimension. In such problems, many standard Markov Chain Monte Carlo (MCMC) algorithms become arbitrary slow under the mesh refinement, which is referred to as being dimension dependent. To this end, a family of dimensional independent MCMC algorithms, known as the preconditioned Crank-Nicolson (pCN) methods, were proposed to sample the infinite dimensional parameters. In this work we develop an adaptive version of the pCN algorithm, where the covariance operator of the proposal distribution is adjusted based on sampling history to improve the simulation efficiency. We show that the proposed algorithm satisfies an important ergodicity condition under some mild assumptions. Finally we provide numerical examples to demonstrate the performance of the proposed method.

[Formula: see text]-regularized recursive total least squares based sparse system identification for the error-in-variables.

PubMed

Lim, Jun-Seok; Pang, Hee-Suk

2016-01-01

In this paper an [Formula: see text]-regularized recursive total least squares (RTLS) algorithm is considered for the sparse system identification. Although recursive least squares (RLS) has been successfully applied in sparse system identification, the estimation performance in RLS based algorithms becomes worse, when both input and output are contaminated by noise (the error-in-variables problem). We proposed an algorithm to handle the error-in-variables problem. The proposed [Formula: see text]-RTLS algorithm is an RLS like iteration using the [Formula: see text] regularization. The proposed algorithm not only gives excellent performance but also reduces the required complexity through the effective inversion matrix handling. Simulations demonstrate the superiority of the proposed [Formula: see text]-regularized RTLS for the sparse system identification setting.

Integrating image quality in 2nu-SVM biometric match score fusion.

PubMed

Vatsa, Mayank; Singh, Richa; Noore, Afzel

2007-10-01

This paper proposes an intelligent 2nu-support vector machine based match score fusion algorithm to improve the performance of face and iris recognition by integrating the quality of images. The proposed algorithm applies redundant discrete wavelet transform to evaluate the underlying linear and non-linear features present in the image. A composite quality score is computed to determine the extent of smoothness, sharpness, noise, and other pertinent features present in each subband of the image. The match score and the corresponding quality score of an image are fused using 2nu-support vector machine to improve the verification performance. The proposed algorithm is experimentally validated using the FERET face database and the CASIA iris database. The verification performance and statistical evaluation show that the proposed algorithm outperforms existing fusion algorithms.

a Threshold-Free Filtering Algorithm for Airborne LIDAR Point Clouds Based on Expectation-Maximization

NASA Astrophysics Data System (ADS)

Hui, Z.; Cheng, P.; Ziggah, Y. Y.; Nie, Y.

2018-04-01

Filtering is a key step for most applications of airborne LiDAR point clouds. Although lots of filtering algorithms have been put forward in recent years, most of them suffer from parameters setting or thresholds adjusting, which will be time-consuming and reduce the degree of automation of the algorithm. To overcome this problem, this paper proposed a threshold-free filtering algorithm based on expectation-maximization. The proposed algorithm is developed based on an assumption that point clouds are seen as a mixture of Gaussian models. The separation of ground points and non-ground points from point clouds can be replaced as a separation of a mixed Gaussian model. Expectation-maximization (EM) is applied for realizing the separation. EM is used to calculate maximum likelihood estimates of the mixture parameters. Using the estimated parameters, the likelihoods of each point belonging to ground or object can be computed. After several iterations, point clouds can be labelled as the component with a larger likelihood. Furthermore, intensity information was also utilized to optimize the filtering results acquired using the EM method. The proposed algorithm was tested using two different datasets used in practice. Experimental results showed that the proposed method can filter non-ground points effectively. To quantitatively evaluate the proposed method, this paper adopted the dataset provided by the ISPRS for the test. The proposed algorithm can obtain a 4.48 % total error which is much lower than most of the eight classical filtering algorithms reported by the ISPRS.

A joint equalization algorithm in high speed communication systems

NASA Astrophysics Data System (ADS)

Hao, Xin; Lin, Changxing; Wang, Zhaohui; Cheng, Binbin; Deng, Xianjin

2018-02-01

This paper presents a joint equalization algorithm in high speed communication systems. This algorithm takes the advantages of traditional equalization algorithms to use pre-equalization and post-equalization. The pre-equalization algorithm takes the advantage of CMA algorithm, which is not sensitive to the frequency offset. Pre-equalization is located before the carrier recovery loop in order to make the carrier recovery loop a better performance and overcome most of the frequency offset. The post-equalization takes the advantage of MMA algorithm in order to overcome the residual frequency offset. This paper analyzes the advantages and disadvantages of several equalization algorithms in the first place, and then simulates the proposed joint equalization algorithm in Matlab platform. The simulation results shows the constellation diagrams and the bit error rate curve, both these results show that the proposed joint equalization algorithm is better than the traditional algorithms. The residual frequency offset is shown directly in the constellation diagrams. When SNR is 14dB， the bit error rate of the simulated system with the proposed joint equalization algorithm is 103 times better than CMA algorithm, 77 times better than MMA equalization, and 9 times better than CMA-MMA equalization.

Corner detection and sorting method based on improved Harris algorithm in camera calibration

NASA Astrophysics Data System (ADS)

Xiao, Ying; Wang, Yonghong; Dan, Xizuo; Huang, Anqi; Hu, Yue; Yang, Lianxiang

2016-11-01

In traditional Harris corner detection algorithm, the appropriate threshold which is used to eliminate false corners is selected manually. In order to detect corners automatically, an improved algorithm which combines Harris and circular boundary theory of corners is proposed in this paper. After detecting accurate corner coordinates by using Harris algorithm and Forstner algorithm, false corners within chessboard pattern of the calibration plate can be eliminated automatically by using circular boundary theory. Moreover, a corner sorting method based on an improved calibration plate is proposed to eliminate false background corners and sort remaining corners in order. Experiment results show that the proposed algorithms can eliminate all false corners and sort remaining corners correctly and automatically.

Medical image reconstruction algorithm based on the geometric information between sensor detector and ROI

NASA Astrophysics Data System (ADS)

Ham, Woonchul; Song, Chulgyu; Lee, Kangsan; Roh, Seungkuk

2016-05-01

In this paper, we propose a new image reconstruction algorithm considering the geometric information of acoustic sources and senor detector and review the two-step reconstruction algorithm which was previously proposed based on the geometrical information of ROI(region of interest) considering the finite size of acoustic sensor element. In a new image reconstruction algorithm, not only mathematical analysis is very simple but also its software implementation is very easy because we don't need to use the FFT. We verify the effectiveness of the proposed reconstruction algorithm by showing the simulation results by using Matlab k-wave toolkit.

A Gradient Taguchi Method for Engineering Optimization

NASA Astrophysics Data System (ADS)

Hwang, Shun-Fa; Wu, Jen-Chih; He, Rong-Song

2017-10-01

To balance the robustness and the convergence speed of optimization, a novel hybrid algorithm consisting of Taguchi method and the steepest descent method is proposed in this work. Taguchi method using orthogonal arrays could quickly find the optimum combination of the levels of various factors, even when the number of level and/or factor is quite large. This algorithm is applied to the inverse determination of elastic constants of three composite plates by combining numerical method and vibration testing. For these problems, the proposed algorithm could find better elastic constants in less computation cost. Therefore, the proposed algorithm has nice robustness and fast convergence speed as compared to some hybrid genetic algorithms.

A street rubbish detection algorithm based on Sift and RCNN

NASA Astrophysics Data System (ADS)

Yu, XiPeng; Chen, Zhong; Zhang, Shuo; Zhang, Ting

2018-02-01

This paper presents a street rubbish detection algorithm based on image registration with Sift feature and RCNN. Firstly, obtain the rubbish region proposal on the real-time street image and set up the CNN convolution neural network trained by the rubbish samples set consists of rubbish and non-rubbish images; Secondly, for every clean street image, obtain the Sift feature and do image registration with the real-time street image to obtain the differential image, the differential image filters a lot of background information, obtain the rubbish region proposal rect where the rubbish may appear on the differential image by the selective search algorithm. Then, the CNN model is used to detect the image pixel data in each of the region proposal on the real-time street image. According to the output vector of the CNN, it is judged whether the rubbish is in the region proposal or not. If it is rubbish, the region proposal on the real-time street image is marked. This algorithm avoids the large number of false detection caused by the detection on the whole image because the CNN is used to identify the image only in the region proposal on the real-time street image that may appear rubbish. Different from the traditional object detection algorithm based on the region proposal, the region proposal is obtained on the differential image not whole real-time street image, and the number of the invalid region proposal is greatly reduced. The algorithm has the high mean average precision (mAP).

A polarized low-coherence interferometry demodulation algorithm by recovering the absolute phase of a selected monochromatic frequency.

PubMed

Jiang, Junfeng; Wang, Shaohua; Liu, Tiegen; Liu, Kun; Yin, Jinde; Meng, Xiange; Zhang, Yimo; Wang, Shuang; Qin, Zunqi; Wu, Fan; Li, Dingjie

2012-07-30

A demodulation algorithm based on absolute phase recovery of a selected monochromatic frequency is proposed for optical fiber Fabry-Perot pressure sensing system. The algorithm uses Fourier transform to get the relative phase and intercept of the unwrapped phase-frequency linear fit curve to identify its interference-order, which are then used to recover the absolute phase. A simplified mathematical model of the polarized low-coherence interference fringes was established to illustrate the principle of the proposed algorithm. Phase unwrapping and the selection of monochromatic frequency were discussed in detail. Pressure measurement experiment was carried out to verify the effectiveness of the proposed algorithm. Results showed that the demodulation precision by our algorithm could reach up to 0.15kPa, which has been improved by 13 times comparing with phase slope based algorithm.

A novel minimum cost maximum power algorithm for future smart home energy management.

PubMed

Singaravelan, A; Kowsalya, M

2017-11-01

With the latest development of smart grid technology, the energy management system can be efficiently implemented at consumer premises. In this paper, an energy management system with wireless communication and smart meter are designed for scheduling the electric home appliances efficiently with an aim of reducing the cost and peak demand. For an efficient scheduling scheme, the appliances are classified into two types: uninterruptible and interruptible appliances. The problem formulation was constructed based on the practical constraints that make the proposed algorithm cope up with the real-time situation. The formulated problem was identified as Mixed Integer Linear Programming (MILP) problem, so this problem was solved by a step-wise approach. This paper proposes a novel Minimum Cost Maximum Power (MCMP) algorithm to solve the formulated problem. The proposed algorithm was simulated with input data available in the existing method. For validating the proposed MCMP algorithm, results were compared with the existing method. The compared results prove that the proposed algorithm efficiently reduces the consumer electricity consumption cost and peak demand to optimum level with 100% task completion without sacrificing the consumer comfort.

A novel symbiotic organisms search algorithm for congestion management in deregulated environment

NASA Astrophysics Data System (ADS)

Verma, Sumit; Saha, Subhodip; Mukherjee, V.

2017-01-01

In today's competitive electricity market, managing transmission congestion in deregulated power system has created challenges for independent system operators to operate the transmission lines reliably within the limits. This paper proposes a new meta-heuristic algorithm, called as symbiotic organisms search (SOS) algorithm, for congestion management (CM) problem in pool based electricity market by real power rescheduling of generators. Inspired by interactions among organisms in ecosystem, SOS algorithm is a recent population based algorithm which does not require any algorithm specific control parameters unlike other algorithms. Various security constraints such as load bus voltage and line loading are taken into account while dealing with the CM problem. In this paper, the proposed SOS algorithm is applied on modified IEEE 30- and 57-bus test power system for the solution of CM problem. The results, thus, obtained are compared to those reported in the recent state-of-the-art literature. The efficacy of the proposed SOS algorithm for obtaining the higher quality solution is also established.

A novel symbiotic organisms search algorithm for congestion management in deregulated environment

NASA Astrophysics Data System (ADS)

Verma, Sumit; Saha, Subhodip; Mukherjee, V.

2017-01-01

In today's competitive electricity market, managing transmission congestion in deregulated power system has created challenges for independent system operators to operate the transmission lines reliably within the limits. This paper proposes a new meta-heuristic algorithm, called as symbiotic organisms search (SOS) algorithm, for congestion management (CM) problem in pool-based electricity market by real power rescheduling of generators. Inspired by interactions among organisms in ecosystem, SOS algorithm is a recent population-based algorithm which does not require any algorithm specific control parameters unlike other algorithms. Various security constraints such as load bus voltage and line loading are taken into account while dealing with the CM problem. In this paper, the proposed SOS algorithm is applied on modified IEEE 30- and 57-bus test power system for the solution of CM problem. The results, thus, obtained are compared to those reported in the recent state-of-the-art literature. The efficacy of the proposed SOS algorithm for obtaining the higher quality solution is also established.

A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation

PubMed Central

Jiang, Chen; Zhang, Shu-Bi; Zhang, Qiu-Zhao

2016-01-01

The Kalman filter is an optimal estimator with numerous applications in technology, especially in systems with Gaussian distributed noise. Moreover, the adaptive Kalman filtering algorithms, based on the Kalman filter, can control the influence of dynamic model errors. In contrast to the adaptive Kalman filtering algorithms, the H-infinity filter is able to address the interference of the stochastic model by minimization of the worst-case estimation error. In this paper, a novel adaptive H-infinity filtering algorithm, which integrates the adaptive Kalman filter and the H-infinity filter in order to perform a comprehensive filtering algorithm, is presented. In the proposed algorithm, a robust estimation method is employed to control the influence of outliers. In order to verify the proposed algorithm, experiments with real data of the Global Positioning System (GPS) and Inertial Navigation System (INS) integrated navigation, were conducted. The experimental results have shown that the proposed algorithm has multiple advantages compared to the other filtering algorithms. PMID:27999361

A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation.

PubMed

Jiang, Chen; Zhang, Shu-Bi; Zhang, Qiu-Zhao

2016-12-19

The Kalman filter is an optimal estimator with numerous applications in technology, especially in systems with Gaussian distributed noise. Moreover, the adaptive Kalman filtering algorithms, based on the Kalman filter, can control the influence of dynamic model errors. In contrast to the adaptive Kalman filtering algorithms, the H-infinity filter is able to address the interference of the stochastic model by minimization of the worst-case estimation error. In this paper, a novel adaptive H-infinity filtering algorithm, which integrates the adaptive Kalman filter and the H-infinity filter in order to perform a comprehensive filtering algorithm, is presented. In the proposed algorithm, a robust estimation method is employed to control the influence of outliers. In order to verify the proposed algorithm, experiments with real data of the Global Positioning System (GPS) and Inertial Navigation System (INS) integrated navigation, were conducted. The experimental results have shown that the proposed algorithm has multiple advantages compared to the other filtering algorithms.

Minimalist ensemble algorithms for genome-wide protein localization prediction.

PubMed

Lin, Jhih-Rong; Mondal, Ananda Mohan; Liu, Rong; Hu, Jianjun

2012-07-03

Computational prediction of protein subcellular localization can greatly help to elucidate its functions. Despite the existence of dozens of protein localization prediction algorithms, the prediction accuracy and coverage are still low. Several ensemble algorithms have been proposed to improve the prediction performance, which usually include as many as 10 or more individual localization algorithms. However, their performance is still limited by the running complexity and redundancy among individual prediction algorithms. This paper proposed a novel method for rational design of minimalist ensemble algorithms for practical genome-wide protein subcellular localization prediction. The algorithm is based on combining a feature selection based filter and a logistic regression classifier. Using a novel concept of contribution scores, we analyzed issues of algorithm redundancy, consensus mistakes, and algorithm complementarity in designing ensemble algorithms. We applied the proposed minimalist logistic regression (LR) ensemble algorithm to two genome-wide datasets of Yeast and Human and compared its performance with current ensemble algorithms. Experimental results showed that the minimalist ensemble algorithm can achieve high prediction accuracy with only 1/3 to 1/2 of individual predictors of current ensemble algorithms, which greatly reduces computational complexity and running time. It was found that the high performance ensemble algorithms are usually composed of the predictors that together cover most of available features. Compared to the best individual predictor, our ensemble algorithm improved the prediction accuracy from AUC score of 0.558 to 0.707 for the Yeast dataset and from 0.628 to 0.646 for the Human dataset. Compared with popular weighted voting based ensemble algorithms, our classifier-based ensemble algorithms achieved much better performance without suffering from inclusion of too many individual predictors. We proposed a method for rational design of minimalist ensemble algorithms using feature selection and classifiers. The proposed minimalist ensemble algorithm based on logistic regression can achieve equal or better prediction performance while using only half or one-third of individual predictors compared to other ensemble algorithms. The results also suggested that meta-predictors that take advantage of a variety of features by combining individual predictors tend to achieve the best performance. The LR ensemble server and related benchmark datasets are available at http://mleg.cse.sc.edu/LRensemble/cgi-bin/predict.cgi.

Minimalist ensemble algorithms for genome-wide protein localization prediction

PubMed Central

2012-01-01

Background Computational prediction of protein subcellular localization can greatly help to elucidate its functions. Despite the existence of dozens of protein localization prediction algorithms, the prediction accuracy and coverage are still low. Several ensemble algorithms have been proposed to improve the prediction performance, which usually include as many as 10 or more individual localization algorithms. However, their performance is still limited by the running complexity and redundancy among individual prediction algorithms. Results This paper proposed a novel method for rational design of minimalist ensemble algorithms for practical genome-wide protein subcellular localization prediction. The algorithm is based on combining a feature selection based filter and a logistic regression classifier. Using a novel concept of contribution scores, we analyzed issues of algorithm redundancy, consensus mistakes, and algorithm complementarity in designing ensemble algorithms. We applied the proposed minimalist logistic regression (LR) ensemble algorithm to two genome-wide datasets of Yeast and Human and compared its performance with current ensemble algorithms. Experimental results showed that the minimalist ensemble algorithm can achieve high prediction accuracy with only 1/3 to 1/2 of individual predictors of current ensemble algorithms, which greatly reduces computational complexity and running time. It was found that the high performance ensemble algorithms are usually composed of the predictors that together cover most of available features. Compared to the best individual predictor, our ensemble algorithm improved the prediction accuracy from AUC score of 0.558 to 0.707 for the Yeast dataset and from 0.628 to 0.646 for the Human dataset. Compared with popular weighted voting based ensemble algorithms, our classifier-based ensemble algorithms achieved much better performance without suffering from inclusion of too many individual predictors. Conclusions We proposed a method for rational design of minimalist ensemble algorithms using feature selection and classifiers. The proposed minimalist ensemble algorithm based on logistic regression can achieve equal or better prediction performance while using only half or one-third of individual predictors compared to other ensemble algorithms. The results also suggested that meta-predictors that take advantage of a variety of features by combining individual predictors tend to achieve the best performance. The LR ensemble server and related benchmark datasets are available at http://mleg.cse.sc.edu/LRensemble/cgi-bin/predict.cgi. PMID:22759391

An enhanced deterministic K-Means clustering algorithm for cancer subtype prediction from gene expression data.

PubMed

Nidheesh, N; Abdul Nazeer, K A; Ameer, P M

2017-12-01

Clustering algorithms with steps involving randomness usually give different results on different executions for the same dataset. This non-deterministic nature of algorithms such as the K-Means clustering algorithm limits their applicability in areas such as cancer subtype prediction using gene expression data. It is hard to sensibly compare the results of such algorithms with those of other algorithms. The non-deterministic nature of K-Means is due to its random selection of data points as initial centroids. We propose an improved, density based version of K-Means, which involves a novel and systematic method for selecting initial centroids. The key idea of the algorithm is to select data points which belong to dense regions and which are adequately separated in feature space as the initial centroids. We compared the proposed algorithm to a set of eleven widely used single clustering algorithms and a prominent ensemble clustering algorithm which is being used for cancer data classification, based on the performances on a set of datasets comprising ten cancer gene expression datasets. The proposed algorithm has shown better overall performance than the others. There is a pressing need in the Biomedical domain for simple, easy-to-use and more accurate Machine Learning tools for cancer subtype prediction. The proposed algorithm is simple, easy-to-use and gives stable results. Moreover, it provides comparatively better predictions of cancer subtypes from gene expression data. Copyright © 2017 Elsevier Ltd. All rights reserved.

Clustering algorithm for determining community structure in large networks

NASA Astrophysics Data System (ADS)

Pujol, Josep M.; Béjar, Javier; Delgado, Jordi

2006-07-01

We propose an algorithm to find the community structure in complex networks based on the combination of spectral analysis and modularity optimization. The clustering produced by our algorithm is as accurate as the best algorithms on the literature of modularity optimization; however, the main asset of the algorithm is its efficiency. The best match for our algorithm is Newman’s fast algorithm, which is the reference algorithm for clustering in large networks due to its efficiency. When both algorithms are compared, our algorithm outperforms the fast algorithm both in efficiency and accuracy of the clustering, in terms of modularity. Thus, the results suggest that the proposed algorithm is a good choice to analyze the community structure of medium and large networks in the range of tens and hundreds of thousand vertices.

Finding all solutions of nonlinear equations using the dual simplex method

NASA Astrophysics Data System (ADS)

Yamamura, Kiyotaka; Fujioka, Tsuyoshi

2003-03-01

Recently, an efficient algorithm has been proposed for finding all solutions of systems of nonlinear equations using linear programming. This algorithm is based on a simple test (termed the LP test) for nonexistence of a solution to a system of nonlinear equations using the dual simplex method. In this letter, an improved version of the LP test algorithm is proposed. By numerical examples, it is shown that the proposed algorithm could find all solutions of a system of 300 nonlinear equations in practical computation time.

Solving the multiple-set split equality common fixed-point problem of firmly quasi-nonexpansive operators.

PubMed

Zhao, Jing; Zong, Haili

2018-01-01

In this paper, we propose parallel and cyclic iterative algorithms for solving the multiple-set split equality common fixed-point problem of firmly quasi-nonexpansive operators. We also combine the process of cyclic and parallel iterative methods and propose two mixed iterative algorithms. Our several algorithms do not need any prior information about the operator norms. Under mild assumptions, we prove weak convergence of the proposed iterative sequences in Hilbert spaces. As applications, we obtain several iterative algorithms to solve the multiple-set split equality problem.

Compressive Sensing of Foot Gait Signals and Its Application for the Estimation of Clinically Relevant Time Series.

PubMed

Pant, Jeevan K; Krishnan, Sridhar

2016-07-01

A new signal reconstruction algorithm for compressive sensing based on the minimization of a pseudonorm which promotes block-sparse structure on the first-order difference of the signal is proposed. Involved optimization is carried out by using a sequential version of Fletcher-Reeves' conjugate-gradient algorithm, and the line search is based on Banach's fixed-point theorem. The algorithm is suitable for the reconstruction of foot gait signals which admit block-sparse structure on the first-order difference. An additional algorithm for the estimation of stride-interval, swing-interval, and stance-interval time series from the reconstructed foot gait signals is also proposed. This algorithm is based on finding zero crossing indices of the foot gait signal and using the resulting indices for the computation of time series. Extensive simulation results demonstrate that the proposed signal reconstruction algorithm yields improved signal-to-noise ratio and requires significantly reduced computational effort relative to several competing algorithms over a wide range of compression ratio. For a compression ratio in the range from 88% to 94%, the proposed algorithm is found to offer improved accuracy for the estimation of clinically relevant time-series parameters, namely, the mean value, variance, and spectral index of stride-interval, stance-interval, and swing-interval time series, relative to its nearest competitor algorithm. The improvement in performance for compression ratio as high as 94% indicates that the proposed algorithms would be useful for designing compressive sensing-based systems for long-term telemonitoring of human gait signals.

The Orthogonally Partitioned EM Algorithm: Extending the EM Algorithm for Algorithmic Stability and Bias Correction Due to Imperfect Data.

PubMed

Regier, Michael D; Moodie, Erica E M

2016-05-01

We propose an extension of the EM algorithm that exploits the common assumption of unique parameterization, corrects for biases due to missing data and measurement error, converges for the specified model when standard implementation of the EM algorithm has a low probability of convergence, and reduces a potentially complex algorithm into a sequence of smaller, simpler, self-contained EM algorithms. We use the theory surrounding the EM algorithm to derive the theoretical results of our proposal, showing that an optimal solution over the parameter space is obtained. A simulation study is used to explore the finite sample properties of the proposed extension when there is missing data and measurement error. We observe that partitioning the EM algorithm into simpler steps may provide better bias reduction in the estimation of model parameters. The ability to breakdown a complicated problem in to a series of simpler, more accessible problems will permit a broader implementation of the EM algorithm, permit the use of software packages that now implement and/or automate the EM algorithm, and make the EM algorithm more accessible to a wider and more general audience.

The cascaded moving k-means and fuzzy c-means clustering algorithms for unsupervised segmentation of malaria images

NASA Astrophysics Data System (ADS)

Abdul-Nasir, Aimi Salihah; Mashor, Mohd Yusoff; Halim, Nurul Hazwani Abd; Mohamed, Zeehaida

2015-05-01

Malaria is a life-threatening parasitic infectious disease that corresponds for nearly one million deaths each year. Due to the requirement of prompt and accurate diagnosis of malaria, the current study has proposed an unsupervised pixel segmentation based on clustering algorithm in order to obtain the fully segmented red blood cells (RBCs) infected with malaria parasites based on the thin blood smear images of P. vivax species. In order to obtain the segmented infected cell, the malaria images are first enhanced by using modified global contrast stretching technique. Then, an unsupervised segmentation technique based on clustering algorithm has been applied on the intensity component of malaria image in order to segment the infected cell from its blood cells background. In this study, cascaded moving k-means (MKM) and fuzzy c-means (FCM) clustering algorithms has been proposed for malaria slide image segmentation. After that, median filter algorithm has been applied to smooth the image as well as to remove any unwanted regions such as small background pixels from the image. Finally, seeded region growing area extraction algorithm has been applied in order to remove large unwanted regions that are still appeared on the image due to their size in which cannot be cleaned by using median filter. The effectiveness of the proposed cascaded MKM and FCM clustering algorithms has been analyzed qualitatively and quantitatively by comparing the proposed cascaded clustering algorithm with MKM and FCM clustering algorithms. Overall, the results indicate that segmentation using the proposed cascaded clustering algorithm has produced the best segmentation performances by achieving acceptable sensitivity as well as high specificity and accuracy values compared to the segmentation results provided by MKM and FCM algorithms.

A community detection algorithm based on structural similarity

NASA Astrophysics Data System (ADS)

Guo, Xuchao; Hao, Xia; Liu, Yaqiong; Zhang, Li; Wang, Lu

2017-09-01

In order to further improve the efficiency and accuracy of community detection algorithm, a new algorithm named SSTCA (the community detection algorithm based on structural similarity with threshold) is proposed. In this algorithm, the structural similarities are taken as the weights of edges, and the threshold k is considered to remove multiple edges whose weights are less than the threshold, and improve the computational efficiency. Tests were done on the Zachary’s network, Dolphins’ social network and Football dataset by the proposed algorithm, and compared with GN and SSNCA algorithm. The results show that the new algorithm is superior to other algorithms in accuracy for the dense networks and the operating efficiency is improved obviously.

Replication and Comparison of the Newly Proposed ADOS-2, Module 4 Algorithm in ASD without ID: A Multi-Site Study

ERIC Educational Resources Information Center

Pugliese, Cara E.; Kenworthy, Lauren; Bal, Vanessa Hus; Wallace, Gregory L.; Yerys, Benjamin E.; Maddox, Brenna B.; White, Susan W.; Popal, Haroon; Armour, Anna Chelsea; Miller, Judith; Herrington, John D.; Schultz, Robert T.; Martin, Alex; Anthony, Laura Gutermuth

2015-01-01

Recent updates have been proposed to the Autism Diagnostic Observation Schedule-2 Module 4 diagnostic algorithm. This new algorithm, however, has not yet been validated in an independent sample without intellectual disability (ID). This multi-site study compared the original and revised algorithms in individuals with ASD without ID. The revised…

Phase retrieval via incremental truncated amplitude flow algorithm

NASA Astrophysics Data System (ADS)

Zhang, Quanbing; Wang, Zhifa; Wang, Linjie; Cheng, Shichao

2017-10-01

This paper considers the phase retrieval problem of recovering the unknown signal from the given quadratic measurements. A phase retrieval algorithm based on Incremental Truncated Amplitude Flow (ITAF) which combines the ITWF algorithm and the TAF algorithm is proposed. The proposed ITAF algorithm enhances the initialization by performing both of the truncation methods used in ITWF and TAF respectively, and improves the performance in the gradient stage by applying the incremental method proposed in ITWF to the loop stage of TAF. Moreover, the original sampling vector and measurements are preprocessed before initialization according to the variance of the sensing matrix. Simulation experiments verified the feasibility and validity of the proposed ITAF algorithm. The experimental results show that it can obtain higher success rate and faster convergence speed compared with other algorithms. Especially, for the noiseless random Gaussian signals, ITAF can recover any real-valued signal accurately from the magnitude measurements whose number is about 2.5 times of the signal length, which is close to the theoretic limit (about 2 times of the signal length). And it usually converges to the optimal solution within 20 iterations which is much less than the state-of-the-art algorithms.

Seismic noise attenuation using an online subspace tracking algorithm

NASA Astrophysics Data System (ADS)

Zhou, Yatong; Li, Shuhua; Zhang, Dong; Chen, Yangkang

2018-02-01

We propose a new low-rank based noise attenuation method using an efficient algorithm for tracking subspaces from highly corrupted seismic observations. The subspace tracking algorithm requires only basic linear algebraic manipulations. The algorithm is derived by analysing incremental gradient descent on the Grassmannian manifold of subspaces. When the multidimensional seismic data are mapped to a low-rank space, the subspace tracking algorithm can be directly applied to the input low-rank matrix to estimate the useful signals. Since the subspace tracking algorithm is an online algorithm, it is more robust to random noise than traditional truncated singular value decomposition (TSVD) based subspace tracking algorithm. Compared with the state-of-the-art algorithms, the proposed denoising method can obtain better performance. More specifically, the proposed method outperforms the TSVD-based singular spectrum analysis method in causing less residual noise and also in saving half of the computational cost. Several synthetic and field data examples with different levels of complexities demonstrate the effectiveness and robustness of the presented algorithm in rejecting different types of noise including random noise, spiky noise, blending noise, and coherent noise.

A hybrid CS-SA intelligent approach to solve uncertain dynamic facility layout problems considering dependency of demands

NASA Astrophysics Data System (ADS)

Moslemipour, Ghorbanali

2018-07-01

This paper aims at proposing a quadratic assignment-based mathematical model to deal with the stochastic dynamic facility layout problem. In this problem, product demands are assumed to be dependent normally distributed random variables with known probability density function and covariance that change from period to period at random. To solve the proposed model, a novel hybrid intelligent algorithm is proposed by combining the simulated annealing and clonal selection algorithms. The proposed model and the hybrid algorithm are verified and validated using design of experiment and benchmark methods. The results show that the hybrid algorithm has an outstanding performance from both solution quality and computational time points of view. Besides, the proposed model can be used in both of the stochastic and deterministic situations.

A robust embedded vision system feasible white balance algorithm

NASA Astrophysics Data System (ADS)

Wang, Yuan; Yu, Feihong

2018-01-01

White balance is a very important part of the color image processing pipeline. In order to meet the need of efficiency and accuracy in embedded machine vision processing system, an efficient and robust white balance algorithm combining several classical ones is proposed. The proposed algorithm mainly has three parts. Firstly, in order to guarantee higher efficiency, an initial parameter calculated from the statistics of R, G and B components from raw data is used to initialize the following iterative method. After that, the bilinear interpolation algorithm is utilized to implement demosaicing procedure. Finally, an adaptive step adjustable scheme is introduced to ensure the controllability and robustness of the algorithm. In order to verify the proposed algorithm's performance on embedded vision system, a smart camera based on IMX6 DualLite, IMX291 and XC6130 is designed. Extensive experiments on a large amount of images under different color temperatures and exposure conditions illustrate that the proposed white balance algorithm avoids color deviation problem effectively, achieves a good balance between efficiency and quality, and is suitable for embedded machine vision processing system.

Training radial basis function networks for wind speed prediction using PSO enhanced differential search optimizer

PubMed Central

2018-01-01

This paper presents an integrated hybrid optimization algorithm for training the radial basis function neural network (RBF NN). Training of neural networks is still a challenging exercise in machine learning domain. Traditional training algorithms in general suffer and trap in local optima and lead to premature convergence, which makes them ineffective when applied for datasets with diverse features. Training algorithms based on evolutionary computations are becoming popular due to their robust nature in overcoming the drawbacks of the traditional algorithms. Accordingly, this paper proposes a hybrid training procedure with differential search (DS) algorithm functionally integrated with the particle swarm optimization (PSO). To surmount the local trapping of the search procedure, a new population initialization scheme is proposed using Logistic chaotic sequence, which enhances the population diversity and aid the search capability. To demonstrate the effectiveness of the proposed RBF hybrid training algorithm, experimental analysis on publicly available 7 benchmark datasets are performed. Subsequently, experiments were conducted on a practical application case for wind speed prediction to expound the superiority of the proposed RBF training algorithm in terms of prediction accuracy. PMID:29768463

Novel bio-inspired smart control for hazard mitigation of civil structures

NASA Astrophysics Data System (ADS)

Kim, Yeesock; Kim, Changwon; Langari, Reza

2010-11-01

In this paper, a new bio-inspired controller is proposed for vibration mitigation of smart structures subjected to ground disturbances (i.e. earthquakes). The control system is developed through the integration of a brain emotional learning (BEL) algorithm with a proportional-integral-derivative (PID) controller and a semiactive inversion (Inv) algorithm. The BEL algorithm is based on the neurologically inspired computational model of the amygdala and the orbitofrontal cortex. To demonstrate the effectiveness of the proposed hybrid BEL-PID-Inv control algorithm, a seismically excited building structure equipped with a magnetorheological (MR) damper is investigated. The performance of the proposed hybrid BEL-PID-Inv control algorithm is compared with that of passive, PID, linear quadratic Gaussian (LQG), and BEL control systems. In the simulation, the robustness of the hybrid BEL-PID-Inv control algorithm in the presence of modeling uncertainties as well as external disturbances is investigated. It is shown that the proposed hybrid BEL-PID-Inv control algorithm is effective in improving the dynamic responses of seismically excited building structure-MR damper systems.

Training radial basis function networks for wind speed prediction using PSO enhanced differential search optimizer.

PubMed

Rani R, Hannah Jessie; Victoire T, Aruldoss Albert

2018-01-01

This paper presents an integrated hybrid optimization algorithm for training the radial basis function neural network (RBF NN). Training of neural networks is still a challenging exercise in machine learning domain. Traditional training algorithms in general suffer and trap in local optima and lead to premature convergence, which makes them ineffective when applied for datasets with diverse features. Training algorithms based on evolutionary computations are becoming popular due to their robust nature in overcoming the drawbacks of the traditional algorithms. Accordingly, this paper proposes a hybrid training procedure with differential search (DS) algorithm functionally integrated with the particle swarm optimization (PSO). To surmount the local trapping of the search procedure, a new population initialization scheme is proposed using Logistic chaotic sequence, which enhances the population diversity and aid the search capability. To demonstrate the effectiveness of the proposed RBF hybrid training algorithm, experimental analysis on publicly available 7 benchmark datasets are performed. Subsequently, experiments were conducted on a practical application case for wind speed prediction to expound the superiority of the proposed RBF training algorithm in terms of prediction accuracy.

Fast adaptive diamond search algorithm for block-matching motion estimation using spatial correlation

NASA Astrophysics Data System (ADS)

Park, Sang-Gon; Jeong, Dong-Seok

2000-12-01

In this paper, we propose a fast adaptive diamond search algorithm (FADS) for block matching motion estimation. Many fast motion estimation algorithms reduce the computational complexity by the UESA (Unimodal Error Surface Assumption) where the matching error monotonically increases as the search moves away from the global minimum point. Recently, many fast BMAs (Block Matching Algorithms) make use of the fact that global minimum points in real world video sequences are centered at the position of zero motion. But these BMAs, especially in large motion, are easily trapped into the local minima and result in poor matching accuracy. So, we propose a new motion estimation algorithm using the spatial correlation among the neighboring blocks. We move the search origin according to the motion vectors of the spatially neighboring blocks and their MAEs (Mean Absolute Errors). The computer simulation shows that the proposed algorithm has almost the same computational complexity with DS (Diamond Search), but enhances PSNR. Moreover, the proposed algorithm gives almost the same PSNR as that of FS (Full Search), even for the large motion with half the computational load.

Cloud computing-based TagSNP selection algorithm for human genome data.

PubMed

Hung, Che-Lun; Chen, Wen-Pei; Hua, Guan-Jie; Zheng, Huiru; Tsai, Suh-Jen Jane; Lin, Yaw-Ling

2015-01-05

Single nucleotide polymorphisms (SNPs) play a fundamental role in human genetic variation and are used in medical diagnostics, phylogeny construction, and drug design. They provide the highest-resolution genetic fingerprint for identifying disease associations and human features. Haplotypes are regions of linked genetic variants that are closely spaced on the genome and tend to be inherited together. Genetics research has revealed SNPs within certain haplotype blocks that introduce few distinct common haplotypes into most of the population. Haplotype block structures are used in association-based methods to map disease genes. In this paper, we propose an efficient algorithm for identifying haplotype blocks in the genome. In chromosomal haplotype data retrieved from the HapMap project website, the proposed algorithm identified longer haplotype blocks than an existing algorithm. To enhance its performance, we extended the proposed algorithm into a parallel algorithm that copies data in parallel via the Hadoop MapReduce framework. The proposed MapReduce-paralleled combinatorial algorithm performed well on real-world data obtained from the HapMap dataset; the improvement in computational efficiency was proportional to the number of processors used.

Opposition-Based Memetic Algorithm and Hybrid Approach for Sorting Permutations by Reversals.

PubMed

Soncco-Álvarez, José Luis; Muñoz, Daniel M; Ayala-Rincón, Mauricio

2018-02-21

Sorting unsigned permutations by reversals is a difficult problem; indeed, it was proved to be NP-hard by Caprara (1997). Because of its high complexity, many approximation algorithms to compute the minimal reversal distance were proposed until reaching the nowadays best-known theoretical ratio of 1.375. In this article, two memetic algorithms to compute the reversal distance are proposed. The first one uses the technique of opposition-based learning leading to an opposition-based memetic algorithm; the second one improves the previous algorithm by applying the heuristic of two breakpoint elimination leading to a hybrid approach. Several experiments were performed with one-hundred randomly generated permutations, single benchmark permutations, and biological permutations. Results of the experiments showed that the proposed OBMA and Hybrid-OBMA algorithms achieve the best results for practical cases, that is, for permutations of length up to 120. Also, Hybrid-OBMA showed to improve the results of OBMA for permutations greater than or equal to 60. The applicability of our proposed algorithms was checked processing permutations based on biological data, in which case OBMA gave the best average results for all instances.

A multipopulation PSO based memetic algorithm for permutation flow shop scheduling.

PubMed

Liu, Ruochen; Ma, Chenlin; Ma, Wenping; Li, Yangyang

2013-01-01

The permutation flow shop scheduling problem (PFSSP) is part of production scheduling, which belongs to the hardest combinatorial optimization problem. In this paper, a multipopulation particle swarm optimization (PSO) based memetic algorithm (MPSOMA) is proposed in this paper. In the proposed algorithm, the whole particle swarm population is divided into three subpopulations in which each particle evolves itself by the standard PSO and then updates each subpopulation by using different local search schemes such as variable neighborhood search (VNS) and individual improvement scheme (IIS). Then, the best particle of each subpopulation is selected to construct a probabilistic model by using estimation of distribution algorithm (EDA) and three particles are sampled from the probabilistic model to update the worst individual in each subpopulation. The best particle in the entire particle swarm is used to update the global optimal solution. The proposed MPSOMA is compared with two recently proposed algorithms, namely, PSO based memetic algorithm (PSOMA) and hybrid particle swarm optimization with estimation of distribution algorithm (PSOEDA), on 29 well-known PFFSPs taken from OR-library, and the experimental results show that it is an effective approach for the PFFSP.

A nudging data assimilation algorithm for the identification of groundwater pumping

NASA Astrophysics Data System (ADS)

Cheng, Wei-Chen; Kendall, Donald R.; Putti, Mario; Yeh, William W.-G.

2009-08-01

This study develops a nudging data assimilation algorithm for estimating unknown pumping from private wells in an aquifer system using measured data of hydraulic head. The proposed algorithm treats the unknown pumping as an additional sink term in the governing equation of groundwater flow and provides a consistent physical interpretation for pumping rate identification. The algorithm identifies the unknown pumping and, at the same time, reduces the forecast error in hydraulic heads. We apply the proposed algorithm to the Las Posas Groundwater Basin in southern California. We consider the following three pumping scenarios: constant pumping rates, spatially varying pumping rates, and temporally varying pumping rates. We also study the impact of head measurement errors on the proposed algorithm. In the case study we seek to estimate the six unknown pumping rates from private wells using head measurements from four observation wells. The results show an excellent rate of convergence for pumping estimation. The case study demonstrates the applicability, accuracy, and efficiency of the proposed data assimilation algorithm for the identification of unknown pumping in an aquifer system.

A nudging data assimilation algorithm for the identification of groundwater pumping

NASA Astrophysics Data System (ADS)

Cheng, W.; Kendall, D. R.; Putti, M.; Yeh, W. W.

2008-12-01

This study develops a nudging data assimilation algorithm for estimating unknown pumping from private wells in an aquifer system using measurement data of hydraulic head. The proposed algorithm treats the unknown pumping as an additional sink term in the governing equation of groundwater flow and provides a consistently physical interpretation for pumping rate identification. The algorithm identifies unknown pumping and, at the same time, reduces the forecast error in hydraulic heads. We apply the proposed algorithm to the Las Posas Groundwater Basin in southern California. We consider the following three pumping scenarios: constant pumping rate, spatially varying pumping rates, and temporally varying pumping rates. We also study the impact of head measurement errors on the proposed algorithm. In the case study, we seek to estimate the six unknown pumping rates from private wells using head measurements from four observation wells. The results show excellent rate of convergence for pumping estimation. The case study demonstrates the applicability, accuracy, and efficiency of the proposed data assimilation algorithm for the identification of unknown pumping in an aquifer system.

Cloud Computing-Based TagSNP Selection Algorithm for Human Genome Data

PubMed Central

Hung, Che-Lun; Chen, Wen-Pei; Hua, Guan-Jie; Zheng, Huiru; Tsai, Suh-Jen Jane; Lin, Yaw-Ling

2015-01-01

Single nucleotide polymorphisms (SNPs) play a fundamental role in human genetic variation and are used in medical diagnostics, phylogeny construction, and drug design. They provide the highest-resolution genetic fingerprint for identifying disease associations and human features. Haplotypes are regions of linked genetic variants that are closely spaced on the genome and tend to be inherited together. Genetics research has revealed SNPs within certain haplotype blocks that introduce few distinct common haplotypes into most of the population. Haplotype block structures are used in association-based methods to map disease genes. In this paper, we propose an efficient algorithm for identifying haplotype blocks in the genome. In chromosomal haplotype data retrieved from the HapMap project website, the proposed algorithm identified longer haplotype blocks than an existing algorithm. To enhance its performance, we extended the proposed algorithm into a parallel algorithm that copies data in parallel via the Hadoop MapReduce framework. The proposed MapReduce-paralleled combinatorial algorithm performed well on real-world data obtained from the HapMap dataset; the improvement in computational efficiency was proportional to the number of processors used. PMID:25569088