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  • Articles  (80,956)
  • American Association for the Advancement of Science  (79,538)
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  • 1
    Publication Date: 2013-09-16
    Description: One-dimensional second-order hyperbolic telegraph equation was formulated using Ohm’s law and solved by a recent and reliable semianalytic method, namely, the reduced differential transform method (RDTM). Using this method, it is possible to find the exact solution or a closed approximate solution of a differential equation. Three numerical examples have been carried out in order to check the effectiveness, the accuracy, and convergence of the method. The RDTM is a powerful mathematical technique for solving wide range of problems arising in science and engineering fields.
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  • 2
    Publication Date: 2013-10-02
    Description: Surface roughness is considered as the quality index of the machine parts. Many diverse techniques have been applied in modelling metal cutting processes. Previous studies have revealed that artificial intelligence techniques are novel soft computing methods which fit the solution of nonlinear and complex problems like metal cutting processes. The present study used adaptive neurofuzzy inference system for the purpose of predicting the surface roughness when end milling Ti6Al4V alloy with coated (PVD) and uncoated cutting tools under dry cutting conditions. Real experimental results have been used for training and testing of ANFIS models, and the best model was selected based on minimum root mean square error. A generalized bell-shaped function has been adopted as a membership function for the modelling process, and its numbers were changed from 2 to 5. The findings provided evidence of the capability of ANFIS in modelling surface roughness in end milling process and obtainment of good matching between experimental and predicted results.
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  • 3
    Publication Date: 2013-10-03
    Description: Empirical evidence created a commonly accepted understanding that synchronisation and stability of material flows impact its productivity. This crucial link between synchronous and stable material flows by time and quantity to create a supply chain with the highest throughput rates is at the heart of lean thinking. Although this supply chain triangle has generally been acknowledged over many years, it is necessary to reach a finer understanding of these dynamics. Therefore, we will develop and study supply chains with the help of fluid dynamics. A multistage, continuous material flow is modelled through a conservation law for material density. Unlike similar approaches, our model is not based on some quasi steady-state assumptions about the stochastic behaviour of the involved supply chain but rather on a simple deterministic rule for material flow density. These models allow us to take into account the nonlinear, dynamical interactions of different supply chain echelons and to test synchronised and stable flow with respect to its potential impacts. Numerical simulations verify that the model is able to simulate transient supply chain phenomena. Moreover, a quantification method relating to the fundamental link between synchronisation, stability, and productivity of supply chains has been found.
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  • 4
    Publication Date: 2013-04-09
    Description: Obtaining unique oligos from an EST database is a problem of great importance in bioinformatics, particularly in the discovery of new genes and the mapping of the human genome. Many algorithms have been developed to find unique oligos, many of which are much less time consuming than the traditional brute force approach. An algorithm was presented by Zheng et al. (2004) which finds the solution of the unique oligos search problem efficiently. We implement this algorithm as well as several new algorithms based on some theorems included in this paper. We demonstrate how, with these new algorithms, we can obtain unique oligos much faster than with previous ones. We parallelize these new algorithms to further improve the time of finding unique oligos. All algorithms are run on ESTs obtained from a Barley EST database.
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  • 5
    Publication Date: 2013-09-13
    Description: Extensive research has been devoted to economic production quantity (EPQ) problem. However, no attention has been paid to problems where unit production and set-up costs must be considered as functions of production rate. In this paper, we address the problem of determining the optimal production quantity and rate of production in which unit production and set-up costs are assumed to be continuous functions of production rate. Based on the traditional economic production quantity (EPQ) formula, the cost function associated with this model is proved to be nonconvex and a procedure is proposed to solve this problem. Finally, utility of the model is presented using some numerical examples and the results are analyzed.
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  • 6
    Publication Date: 2014-12-16
    Description: Diabetic retinopathy is the leading cause of blindness worldwide. It is caused by the abnormal growth of the retinal blood vessels. Plasminogen activator inhibitor1 (PAI1) is the key growth factor and the inhibition of PAI1 can reduce the angiogenesis. In this study, currently available inhibitors are taken and tested for the toxicity, binding affinity, and bioactivities of the compounds by in silico approach. Five toxic free inhibitors were identified, among which N-acetyl-D-glucosamine shows the significant binding affinity and two of the molecules are having the better bioactivity properties. The molecular optimization of 2-(acetylamino)-2-deoxy-A-D-glucopyranose and alpha-L-fucose can be used for the treatment of diabetic retinopathy.
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  • 7
    Publication Date: 2011-06-15
    Description: One of the main methods to reduce the production costs is waste recycling which is the most important challenge for the future. Cotton wastes collected from ginning process have desirable properties which could be used during spinning process. The purpose of this study was to develop predictive models of breaking strength and mass irregularity (CVm%) of cotton waste rotor-spun yarns containing cotton waste collected from ginning process by using the artificial neural network trained with backpropagation algorithm. Artificial neural network models have been developed based on rotor diameter, rotor speed, navel type, opener roller speed, ginning waste proportion and yarn linear density as input parameters. The parameters of artificial neural network model, namely, learning, and momentum rate, number of hidden layers and number of hidden processing elements (neurons) were optimized to get the best predictive models. The findings showed that the breaking strength and mass irregularity of rotor spun yarns could be predicted satisfactorily by artificial neural network. The maximum error in predicting the breaking strength and mass irregularity of testing data was 8.34% and 6.65%, respectively.
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  • 8
    Publication Date: 2011-06-14
    Description: The aim of the current research is to propose a new generation of automated guided vehicle systems for alleviating the collision states in material handling systems where the automated guided vehicles movements are allowed to be both unidirectional and bidirectional. The objective function is to maximize the average annual profit in an FMS system using a simulation method. Despite several researches done in this field, this criterion has been studied rarely. The current study includes some new changes in AGV design for preventing some common problems such as congestions and deadlocks based on real profits/costs analysis in a flexible manufacturing system. For this reason, some experiments have been carried out to study the effects of several empty vehicle dispatching rules on average annual profit. The results show that the proposed framework is efficient and robust enough for industrial environments.
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  • 9
    Publication Date: 2011-06-29
    Description: Cerebral aneurysms are local expansions of blood vessel walls in the brain blood system. The rupture of an aneurysm is a very severe event associated with a high rate of mortality. When cerebral aneurysms are detected, clinicians need to decide if operation is required. The risk of aneurysm rupture is then compared to the risks associated with the medical intervention. In the present paper, a probabilistic framework for a mechanically based rupture risk assessment of cerebral aneurysms is proposed. The method is based on the assumption that the strength of aneurysmal tissues can be described by a statistical distribution. A structural analysis of the aneurysm in question is performed, and the maximum stress experienced by the aneurysm is compared to the strength distribution. The proposed model was compared with clinical results for ruptured aneurysms in terms of rupture density and accumulated rupture risk as a function of aneurysm size. The model was able to reproduce the clinical results well. The proposed framework may potentially be used under in vivo conditions to predict the risk of rupture for diagnosed aneurysms.
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  • 10
    Publication Date: 2011-08-04
    Description: Kamaniskeg Lake is a long, narrow, and deep small lake located in the northern part of Ontario, Canada. The goals of this paper were to examine various options to improve the water quality in the northern part of the lake by altering the local hydraulic flow conditions. Towards this end, a preliminary screening suggested that the flow circulation could be increased around a central island (Mask Island) in the northern part of the lake by opening up an existing causeway connecting the mainland and central island. Three-dimensional (3D) hydraulic and transport models were adopted in this paper to investigate the hydraulic conditions under various wind forces and causeway structures. The modelling results show that opening the causeway in a few places is unlikely to generate a large flow circulation around the central island. Full circulation only appears to be possible if the causeway is fully removed and a strong wind blows in a favourable direction. The possible reasons for existing water quality variations at the intake of a local WTP (water treatment plant) are also explored in the paper.
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  • 11
    Publication Date: 2011-08-10
    Description: Numerical simulation of the arc-flow interaction in high-voltage circuit breakers requires a radiation model capable of handling high-temperature participating thermal plasmas. The modeling of the radiative transfer plays a critical role in the overall accuracy of such CFD simulations. As a result of the increase of computational power, CPU intensive methods based on the radiative transfer equation, leading to more accurate results, are now becoming attractive alternatives to current approximate models. In this paper, the predictive capabilities of the finite volume method (RTE-FVM) and the P1 model are investigated. A systematic comparison between these two models and analytical solutions are presented for a variety of relevant test cases. Two implementations of each approach are compared, and a critical evaluation is presented.
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  • 12
    Publication Date: 2011-10-10
    Description: This is the continuation of our research on development of a fully nonlinear, dynamically consistent, numerical ship motion model (DiSSEL). In this paper we report our results on modeling ship maneuvering in arbitrary seaway that is one of the most challenging and important problems in seakeeping. In our modeling, we developed an adaptive algorithm to maintain dynamical balances numerically as the encounter frequencies (the wave frequencies as measured on the ship) varying with the ship maneuvering state. The key of this new algorithm is to evaluate the encounter frequency variation differently in the physical domain and in the frequency domain, thus effectively eliminating possible numerical dynamical imbalances. We have tested this algorithm with several well-documented maneuvering experiments, and our results agree very well with experimental data. In particular, the numerical time series of roll and pitch motions and the numerical ship tracks (i.e., surge, sway, and yaw) are nearly identical to those of experiments.
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  • 13
    Publication Date: 2011-10-12
    Description: Healthcare currently consumes 17% of the U.S. Gross Domestic Product and is expected to reach 20% within the coming decade. Confronted with such high costs, sharp demand, and limited capacity, many hospitals now are vying for shorter lengths of stay and are transferring services from inpatient to outpatient facilities. This paper seeks to develop a methodology for constructing effective outpatient appointment scheduling systems. The objective of these appointment systems is to minimize the average total cost function describing total costs incurred by patient waiting and by staff idle time and overtime. In the paper, we will establish that the average total cost function exhibits a unimodal curve. The lowest point of the curve essentially means the lowest average total cost. We will next develop a simulation-based heuristic algorithm for finding an outpatient schedule near the lowest point. In the paper, we present numerical examples using the heuristic based upon a set of predetermined unit costs. Specifically, we find the near optimal interappointment times for schedules, where there are two and three patients in each block, respectively. The current work does not consider possible no shows and walk-ins. Future work will undertake these issues.
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  • 14
    Publication Date: 2011-12-06
    Description: Cutting operations using blades can arise in a number of industries, for example, food processing industry, in which cheese, fruit and vegetable, even meat, are involved. Certain questions will rise during these works, such as “why pressing-and-slicing cuts use less force than pressing-only cuts” and “how is the influence of the blade cutting-edge on force”. To answer these questions, this research developed a mathematical expression of the cutting stress tensor. Based on the analysis of the stress tensor on the contact surface, the influence of the blade edge-shape and slicing angle on the resultant cutting force were formulated and discussed. These formulations were further verified using experimental results by robotic cutting of potatoes. Through studying the change of the cutting force, the optimal slicing angle can be obtained in terms of maximum feeding distance and minimum cutting force. Based on the blade sharpness properties and the specific materials, the required cutting force can be predicted. These formulation and experimental results explained the basic theory of blade cutting fracture and further provided the support to optimize the cutting mechanism design and to develop the force control algorithms for the automation of blade cutting operations.
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  • 15
    Publication Date: 2012-03-16
    Description: A new efficient heuristic algorithm has been developed for the dynamic facility layout problem with budget constraint (DFLPB) using optimization via simulation technique. The heuristic integrates integer programming and discrete event simulation to address DFLPB. In the proposed algorithm, the nonlinear model of the DFLP has been changed to a pure integer programming (PIP) model. Then, the optimal solution of the PIP model has been used in a simulation model that has been designed in a similar manner as the DFLP for determining the probability of assigning a facility to a location. After a sufficient number of runs, the simulation model obtains near optimum solutions. Finally, to test the performance of the algorithm, several test problems have been taken from the literature and solved. The results show that the proposed algorithm is more efficient in terms of speed and accuracy than other heuristic algorithms presented in previous works.
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  • 16
    Publication Date: 2012-12-21
    Description: Flickermeter is a common name for a system that measures the obnoxiousness of flicker caused by voltage fluctuations. The output of flickermeter is a value of short-term flicker severity indicator, . This paper presents the results of the numerical simulations that reconstruct the processing of flickermeter in frequency domain. With the use of standard test signals, the characteristics of flickermeter were determined for the case of amplitude modulation of input signal, frequency modulation of input signal, and for input signal with interharmonic component. For the needs of simulative research, elements of standard IEC flickermeter signal chain as well as test signal source and tools for acquisition, archiving, and presentation of the obtained results were modeled. The results were presented with a set of charts, and the specific fragments of the charts were pointed out and commented on. Some examples of the influence of input signal’s bandwidth limitation on the flickermeter measurement result were presented for the case of AM and FM modulation. In addition, the diagrams that enable the evaluation of flickermeter’s linearity were also presented.
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  • 17
    Publication Date: 2013-02-21
    Description: The long-range interactions, required to the accurate predictions of tertiary structures of β-sheet-containing proteins, are still difficult to simulate. To remedy this problem and to facilitate β-sheet structure predictions, many efforts have been made by computational methods. However, known efforts on β-sheets mainly focus on interresidue contacts or amino acid partners. In this study, to go one step further, we studied β-sheets on the strand level, in which a statistical analysis was made on the terminal extensions of paired β-strands. In most cases, the two paired β-strands have different lengths, and terminal extensions exist. The terminal extensions are the extended part of the paired strands besides the common paired part. However, we found that the best pairing required a terminal alignment, and β-strands tend to pair to make bigger common parts. As a result, 96.97%  of β-strand pairs have a ratio of 25% of the paired common part to the whole length. Also 94.26% and 95.98%  of β-strand pairs have a ratio of 40% of the paired common part to the length of the two β-strands, respectively. Interstrand register predictions by searching interacting β-strands from several alternative offsets should comply with this rule to reduce the computational searching space to improve the performances of algorithms.
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  • 18
    Publication Date: 2013-02-21
    Description: Solving some mathematical problems such as NP-complete problems by conventional silicon-based computers is problematic and takes so long time. DNA computing is an alternative method of computing which uses DNA molecules for computing purposes. DNA computers have massive degrees of parallel processing capability. The massive parallel processing characteristic of DNA computers is of particular interest in solving NP-complete and hard combinatorial problems. NP-complete problems such as knapsack problem and other hard combinatorial problems can be easily solved by DNA computers in a very short period of time comparing to conventional silicon-based computers. Sticker-based DNA computing is one of the methods of DNA computing. In this paper, the sticker based DNA computing was used for solving the 0/1 knapsack problem. At first, a biomolecular solution space was constructed by using appropriate DNA memory complexes. Then, by the application of a sticker-based parallel algorithm using biological operations, knapsack problem was resolved in polynomial time.
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  • 19
    Publication Date: 2013-02-21
    Description: In this paper we present a new ab initio approach for constructing an unrooted dendrogram using protein clusters, an approach that has the potential for estimating relationships among several thousands of species based on their putative proteomes. We employ an open-source software program called pClust that was developed for use in metagenomic studies. Sequence alignment is performed by pClust using the Smith-Waterman algorithm, which is known to give optimal alignment and, hence, greater accuracy than BLAST-based methods. Protein clusters generated by pClust are used to create protein profiles for each species in the dendrogram, these profiles forming a correlation filter library for use with a new taxon. To augment the dendrogram with a new taxon, a protein profile for the taxon is created using BLASTp, and this new taxon is placed into a position within the dendrogram corresponding to the highest correlation with profiles in the correlation filter library. This work was initiated because of our interest in plasmids, and each step is illustrated using proteomes from Gram-negative bacterial plasmids. Proteomes for 527 plasmids were used to generate the dendrogram, and to demonstrate the utility of the insertion algorithm twelve recently sequenced pAKD plasmids were used to augment the dendrogram.
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  • 20
    Publication Date: 2013-02-21
    Description: Modeling the multiagents cooperative systems inspired from biological self-organized systems in the context of swarm model has been under great considerations especially in the field of the cooperation of multi robots. These models are trying to optimize the behavior of artificial multiagent systems by introducing a consensus, which is a mathematical model between the agents as an intelligence property for each member of the swarm set. The application of this novel approach in the modeling of nonintelligent multi agents systems in the field of cohesion and cluster formation of nanoparticles in nanofluids has been investigated in this study. This goal can be obtained by applying the basic swarm model for agents that are more mechanistic by considering their physical properties such as their mass, diameter, as well as the physical properties of the flow. Clustering in nanofluids is one of the major issues in the study of its effects on heat transfer. Study of the cluster formation dynamics in nanofluids using the swarm model can be useful in controlling the size and formation time of the clusters as well as designing appropriate microchannels, which the nanoparticles are plunged into.
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  • 21
    Publication Date: 2012-11-15
    Description: B-cell epitope prediction aims to aid the design of peptide-based immunogens (e.g., vaccines) for eliciting antipeptide antibodies that protect against disease, but such antibodies fail to confer protection and even promote disease if they bind with low affinity. Hence, the Immune Epitope Database (IEDB) was searched to obtain published thermodynamic and kinetic data on binding interactions of antipeptide antibodies. The data suggest that the affinity of the antibodies for their immunizing peptides appears to be limited in a manner consistent with previously proposed kinetic constraints on affinity maturation in vivo and that cross-reaction of the antibodies with proteins tends to occur with lower affinity than the corresponding reaction of the antibodies with their immunizing peptides. These observations better inform B-cell epitope prediction to avoid overestimating the affinity for both active and passive immunization; whereas active immunization is subject to limitations of affinity maturation in vivo and of the capacity to accumulate endogenous antibodies, passive immunization may transcend such limitations, possibly with the aid of artificial affinity-selection processes and of protein engineering. Additionally, protein disorder warrants further investigation as a possible supplementary criterion for B-cell epitope prediction, where such disorder obviates thermodynamically unfavorable protein structural adjustments in cross-reactions between antipeptide antibodies and proteins.
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  • 22
    Publication Date: 2013-03-07
    Description: The problems of modeling and intervention of biological phenomena have captured the interest of many researchers in the past few decades. The aim of the therapeutic intervention strategies is to move an undesirable state of a diseased network towards a more desirable one. Such an objective can be achieved by the application of drugs to act on some genes/metabolites that experience the undesirable behavior. For the purpose of design and analysis of intervention strategies, mathematical models that can capture the complex dynamics of the biological systems are needed. S-systems, which offer a good compromise between accuracy and mathematical flexibility, are a promising framework for modeling the dynamical behavior of biological phenomena. Due to the complex nonlinear dynamics of the biological phenomena represented by S-systems, nonlinear intervention schemes are needed to cope with the complexity of the nonlinear S-system models. Here, we present an intervention technique based on feedback linearization for biological phenomena modeled by S-systems. This technique is based on perfect knowledge of the S-system model. The proposed intervention technique is applied to the glycolytic-glycogenolytic pathway, and simulation results presented demonstrate the effectiveness of the proposed technique.
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  • 23
    Publication Date: 2013-03-07
    Description: The world has widely changed in terms of communicating, acquiring, and storing information. Hundreds of millions of people are involved in information retrieval tasks on a daily basis, in particular while using a Web search engine or searching their e-mail, making such field the dominant form of information access, overtaking traditional database-style searching. How to handle this huge amount of information has now become a challenging issue. In this paper, after recalling the main topics concerning information retrieval, we present a survey on the main works on literature retrieval and mining in bioinformatics. While claiming that information retrieval approaches are useful in bioinformatics tasks, we discuss some challenges aimed at showing the effectiveness of these approaches applied therein.
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  • 24
    Publication Date: 2012-10-14
    Description: Trypanosoma brucei is a protozoan parasite of major of interest in discovering new genes for drug targets. This parasite alternates its life cycle between the mammal host(s) (bloodstream form) and the insect vector (procyclic form), with two divergent glucose metabolism amenable to in vitro culture. While the metabolic network of the bloodstream forms has been well characterized, the flux distribution between the different branches of the glucose metabolic network in the procyclic form has not been addressed so far. We present a computational analysis (called Metaboflux) that exploits the metabolic topology of the procyclic form, and allows the incorporation of multipurpose experimental data to increase the biological relevance of the model. The alternatives resulting from the structural complexity of networks are formulated as an optimization problem solved by a metaheuristic where experimental data are modeled in a multiobjective function. Our results show that the current metabolic model is in agreement with experimental data and confirms the observed high metabolic flexibility of glucose metabolism. In addition, Metaboflux offers a rational explanation for the high flexibility in the ratio between final products from glucose metabolism, thsat is, flux redistribution through the malic enzyme steps.
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  • 25
    Publication Date: 2012-10-03
    Description: The world production of crude oil is about 3 billion tons per year. The overall objective of the model in present study is supporting the decision makers in planning and conducting preventive and emergency interventions. The conservative equation for the slick dynamics was derived from layer-averaged Navier-Stokes (LNS) equations, averaged over the slick thickness. Eulerian approach is applied across the model, based on nonlinear shallow water Reynolds-averaged Navier-Stokes (RANS) equations. Depth-integrated standard k-ε turbulence schemes have been included in the model. Wetting and drying fronts of intertidal zone and moving boundary are treated within the numerical model. A highly accurate algorithm based on a fourth-degree accurate shape function has been used through an alternating-direction implicit (ADI) scheme which separates the operators into locally one-dimensional (LOD) components. The solution has been achieved by the application of KPENTA algorithm for the set of the flow equations which constitutes a pentadiagonal matrix. Hydrodynamic model was validated for a channel with a sudden expansion in width. For validation of oil spill model, predicted results are compared with experimental data from a physical modeling of oil spill in a laboratory wave basin under controlled conditions.
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  • 26
    Publication Date: 2012-10-04
    Description: Based on the DC motor speed response measurement under a step voltage input, important motor parameters such as the electrical time constant, the mechanical time constant, and the friction can be estimated. A power series expansion of the motor speed response is presented, whose coefficients are related to the motor parameters. These coefficients can be easily computed using existing curve fitting methods. Experimental results are presented to demonstrate the application of this approach. In these experiments, the approach was readily implemented and gave more accurate estimates than conventional methods.
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  • 27
    Publication Date: 2012-10-16
    Description: This paper presents a comparative analysis between the practical results of pig iron die-type part casting and the results reached by simulation. The insert was made of polystyrene, and the casting was downward vertical. As after the part casting and heat treatment cracks were observed in the part, it became necessary to locate and identify these fissures and to establish some measures for eliminating the casting defects and for locating them. The research method was the comparisons of defects identified through verifications, measurements, and metallographic analyses applied to the cast part with the results of some criteria specific to simulation after simulating the casting process. In order to verify the compatibility between reality and simulation, we then simulated the part casting respecting the real conditions in which it was cast. By visualising certain sections of the cast part during solidification, relevant details occur about the possible evolution of defects. The simulation software was AnyCasting, the measurements were done through nondestructive methods.
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  • 28
    Publication Date: 2012-10-18
    Description: The projective integration method based on the Galerkin-free framework with the assistance of proper orthogonal decomposition (POD) is presented in this paper. The present method is applied to simulate two-dimensional incompressible fluid flows past the NACA0012 airfoil problem. The approach consists of using high-accuracy direct numerical simulations over short time intervals, from which POD modes are extracted for approximating the dynamics of the primary variables. The solution is then projected with larger time steps using any standard time integrator, without the need to recompute it from the governing equations. This is called the online projective integration method. The results by the projective integration method are in good agreement with the full scale simulation with less computational needs. We also study the individual function of each POD mode used in the projective integration method. It is found that the first POD mode can capture basic flow behaviors but the overall dynamic is rather inaccurate. The second and the third POD modes assist the first mode by correcting magnitudes and phases of vorticity fields. However, adding the fifth POD mode in the model leads to some incorrect results in phase-shift forms for both drag and lift coefficients. This suggests the optimal number of POD modes to use in the projective integration method.
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  • 29
    Publication Date: 2012-10-25
    Description: A glazing façade subjected to blast loads has a structural behaviour that strongly differs from the typical response of a glazing system subjected to ordinary loads. Consequently, sophisticated modelling techniques are required to identify correctly its criticalities. The paper investigates the behaviour of a cable-supported façade subjected to high-level blast loading. Nonlinear dynamic analyses are performed in ABAQUS/Explicit using a sophisticated FE-model (M01), calibrated to dynamic experimental and numerical results. The structural effects of the total design blast impulse, as well as only its positive phase, are analyzed. At the same time, the possible cracking of glass panels is taken into account, since this phenomenon could modify the response of the entire façade. Finally, deep investigations are dedicated to the bearing cables, since subjecting them to elevated axial forces and their collapse could compromise the integrity of the cladding wall. Based on results of previous studies, frictional devices differently applied at their ends are presented to improve the response of the façade under the impact of a high-level explosion. Structural effects of various solutions are highlighted through dynamic simulations. Single vertical devices, if appropriately calibrated, allow reducing significantly the axial forces in cables, and lightly the tensile stresses in glass panes.
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  • 30
    Publication Date: 2013-02-09
    Description: Modeling the multiagents cooperative systems inspired from biological self-organized systems in the context of swarm model has been under great considerations especially in the field of the cooperation of multi robots. These models are trying to optimize the behavior of artificial multiagent systems by introducing a consensus, which is a mathematical model between the agents as an intelligence property for each member of the swarm set. The application of this novel approach in the modeling of nonintelligent multi agents systems in the field of cohesion and cluster formation of nanoparticles in nanofluids has been investigated in this study. This goal can be obtained by applying the basic swarm model for agents that are more mechanistic by considering their physical properties such as their mass, diameter, as well as the physical properties of the flow. Clustering in nanofluids is one of the major issues in the study of its effects on heat transfer. Study of the cluster formation dynamics in nanofluids using the swarm model can be useful in controlling the size and formation time of the clusters as well as designing appropriate microchannels, which the nanoparticles are plunged into.
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  • 31
    Publication Date: 2013-02-19
    Description: Solving some mathematical problems such as NP-complete problems by conventional silicon-based computers is problematic and takes so long time. DNA computing is an alternative method of computing which uses DNA molecules for computing purposes. DNA computers have massive degrees of parallel processing capability. The massive parallel processing characteristic of DNA computers is of particular interest in solving NP-complete and hard combinatorial problems. NP-complete problems such as knapsack problem and other hard combinatorial problems can be easily solved by DNA computers in a very short period of time comparing to conventional silicon-based computers. Sticker-based DNA computing is one of the methods of DNA computing. In this paper, the sticker based DNA computing was used for solving the 0/1 knapsack problem. At first, a biomolecular solution space was constructed by using appropriate DNA memory complexes. Then, by the application of a sticker-based parallel algorithm using biological operations, knapsack problem was resolved in polynomial time.
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  • 32
    Publication Date: 2012-09-03
    Description: Numerical studies have been performed to visualize vortical flow structures emerged from jet cross-flow interactions. A single square jet issuing perpendicularly into a cross-flow was simulated first, followed by two additional scenarios, that is, inclined square jet at angles of 30° and 60° and round and elliptic jets at an angle of 90°, respectively. The simulation considers a jet to cross-flow velocity ratio of 2.5 and a Reynolds number of 225, based on the free-stream flow quantities and the jet exit width in case of square jet or minor axis length in case of elliptic jet. For the single square jet, the vortical flow structures simulated are in good qualitative agreement with the findings by other researchers. Further analysis reveals that the jet penetrates deeper into the cross-flow field for the normal jet, and the decrease of the jet inclination angle weakens the cross-flow entrainment in the near-wake region. For both noncircular and circular jet hole shapes, the flow field in the vicinity of the jet exit has been dominated by large-scale dynamic flow structures and it was found that the elliptic jet hole geometry has maximum “lifted-off” effect among three hole configurations studied. This finding is also in good qualitative agreement with existing experimental observations.
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  • 33
    Publication Date: 2012-07-21
    Description: The nucleotide sequences complexity in chromosome 3 of Caenorhabditis elegans (C. elegans) is studied. The complexity of these sequences is compared with some random sequences. Moreover, by using some parameters related to complexity such as fractal dimension and frequency, indicator matrix is given a first classification of sequences of C. elegans. In particular, the sequences with highest and lowest fractal value are singled out. It is shown that the intrinsic nature of the low fractal dimension sequences has many common features with the random sequences.
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  • 34
    Publication Date: 2012-06-21
    Description: Treatment of bipolar disorder with lithium therapy during pregnancy is a medical challenge. Bipolar disorder is more prevalent in women and its onset is often concurrent with peak reproductive age. Treatment typically involves administration of the element lithium, which has been classified as a class D drug (legal to use during pregnancy, but may cause birth defects) and is one of only thirty known teratogenic drugs. There is no clear recommendation in the literature on the maximum acceptable dosage regimen for pregnant, bipolar women. We recommend a maximum dosage regimen based on a physiologically based pharmacokinetic (PBPK) model. The model simulates the concentration of lithium in the organs and tissues of a pregnant woman and her fetus. First, we modeled time-dependent lithium concentration profiles resulting from lithium therapy known to have caused birth defects. Next, we identified maximum and average fetal lithium concentrations during treatment. Then, we developed a lithium therapy regimen to maximize the concentration of lithium in the mother’s brain, while maintaining the fetal concentration low enough to reduce the risk of birth defects. This maximum dosage regimen suggested by the model was 400 mg lithium three times per day.
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  • 35
    Publication Date: 2012-06-21
    Description: The pairwise comparison of RNA secondary structures is a fundamental problem, with direct application in mining databases for annotating putative noncoding RNA candidates in newly sequenced genomes. An increasing number of software tools are available for comparing RNA secondary structures, based on different models (such as ordered trees or forests, arc annotated sequences, and multilevel trees) and computational principles (edit distance, alignment). We describe here the website BRASERO that offers tools for evaluating such software tools on real and synthetic datasets.
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  • 36
    Publication Date: 2012-06-21
    Description: The wide coverage and biological relevance of the Gene Ontology (GO), confirmed through its successful use in protein function prediction, have led to the growth in its popularity. In order to exploit the extent of biological knowledge that GO offers in describing genes or groups of genes, there is a need for an efficient, scalable similarity measure for GO terms and GO-annotated proteins. While several GO similarity measures exist, none adequately addresses all issues surrounding the design and usage of the ontology. We introduce a new metric for measuring the distance between two GO terms using the intrinsic topology of the GO-DAG, thus enabling the measurement of functional similarities between proteins based on their GO annotations. We assess the performance of this metric using a ROC analysis on human protein-protein interaction datasets and correlation coefficient analysis on the selected set of protein pairs from the CESSM online tool. This metric achieves good performance compared to the existing annotation-based GO measures. We used this new metric to assess functional similarity between orthologues, and show that it is effective at determining whether orthologues are annotated with similar functions and identifying cases where annotation is inconsistent between orthologues.
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  • 37
    Publication Date: 2012-06-21
    Description: The first step of HIV-1 infection involves interaction between the viral glycoprotein gp120 and the human cellular receptor CD4. Inhibition of the gp120-CD4 interaction represents an attractive strategy to block HIV-1 infection. In an attempt to explore the known lack of affinity of murine CD4 to gp120, we have investigated peptides presenting the putative gp120-binding site of murine CD4 (mCD4). Molecular modeling indicates that mCD4 protein cannot bind gp120 due to steric clashes, while the larger conformational flexibility of mCD4 peptides allows an interaction. This finding is confirmed by experimental binding assays, which also evidenced specificity of the peptide-gp120 interaction. Molecular dynamics simulations indicate that the mCD4-peptide stably interacts with gp120 via an intermolecular β-sheet, while an important salt-bridge formed by a C-terminal lysine is lost. Fixation of the C-terminus by introducing a disulfide bridge between the N- and C-termini of the peptide significantly enhanced the affinity to gp120.
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  • 38
    Publication Date: 2012-06-21
    Description: Various enzyme identification protocols involving homology transfer by sequence-sequence or profile-sequence comparisons have been devised which utilise Swiss-Prot sequences associated with EC numbers as the training set. A profile HMM constructed for a particular EC number might select sequences which perform a different enzymatic function due to the presence of certain fold-specific residues which are conserved in enzymes sharing a common fold. We describe a protocol, ModEnzA (HMM-ModE Enzyme Annotation), which generates profile HMMs highly specific at a functional level as defined by the EC numbers by incorporating information from negative training sequences. We enrich the training dataset by mining sequences from the NCBI Non-Redundant database for increased sensitivity. We compare our method with other enzyme identification methods, both for assigning EC numbers to a genome as well as identifying protein sequences associated with an enzymatic activity. We report a sensitivity of 88% and specificity of 95% in identifying EC numbers and annotating enzymatic sequences from the E. coli genome which is higher than any other method. With the next-generation sequencing methods producing a huge amount of sequence data, the development and use of fully automated yet accurate protocols such as ModEnzA is warranted for rapid annotation of newly sequenced genomes and metagenomic sequences.
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  • 39
    Publication Date: 2012-06-21
    Description: The advent of high-throughput sequencing technologies constituted a major advance in genomic studies, offering new prospects in a wide range of applications.We propose a rigorous and flexible algorithmic solution to mapping SOLiD color-space reads to a reference genome. The solution relies on an advanced method of seed design that uses a faithful probabilistic model of read matches and, on the other hand, a novel seeding principle especially adapted to read mapping. Our method can handle both lossy and lossless frameworks and is able to distinguish, at the level of seed design, between SNPs and reading errors. We illustrate our approach by several seed designs and demonstrate their efficiency.
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  • 40
    Publication Date: 2012-06-21
    Description: We represent proteins by amino acid interaction networks. This is a graph whose vertices are the proteins amino acids and whose edges are the interactions between them. Once we have compared this type of graphs to the general model of scale-free networks, we analyze the existence of nodes which highly interact, the hubs. We describe these nodes taking into account their position in the primary structure to study their apparition frequency in the folded proteins. Finally, we observe that their interaction level is a consequence of the general rules which govern the folding process.
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  • 41
    Publication Date: 2012-06-21
    Description: High-throughput “omics” technologies bring new opportunities for biological and biomedical researchers to ask complex questions and gain new scientific insights. However, the voluminous, complex, and context-dependent data being maintained in heterogeneous and distributed environments plus the lack of well-defined data standard and standardized nomenclature imposes a major challenge which requires advanced computational methods and bioinformatics infrastructures for integration, mining, visualization, and comparative analysis to facilitate data-driven hypothesis generation and biological knowledge discovery. In this paper, we present the challenges in high-throughput “omics” data integration and analysis, introduce a protein-centric approach for systems integration of large and heterogeneous high-throughput “omics” data including microarray, mass spectrometry, protein sequence, protein structure, and protein interaction data, and use scientific case study to illustrate how one can use varied “omics” data from different laboratories to make useful connections that could lead to new biological knowledge.
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  • 42
    Publication Date: 2012-06-21
    Description: Detection of discriminating patterns in gene expression data can be accomplished by using various methods of statistical learning. It has been proposed that sample pooling in this context would have negative effects; however, pooling cannot always be avoided. We propose a simulation framework to explicitly investigate the parameters of patterns, experimental design, noise, and choice of method in order to find out which effects on classification performance are to be expected. We use a two-group classification task and simulated gene expression data with independent differentially expressed genes as well as bivariate linear patterns and the combination of both. Our results show a clear increase of prediction error with pool size. For pooled training sets powered partial least squares discriminant analysis outperforms discriminance analysis, random forests, and support vector machines with linear or radial kernel for two of three simulated scenarios. The proposed simulation approach can be implemented to systematically investigate a number of additional scenarios of practical interest.
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  • 43
    Publication Date: 2012-06-21
    Description: Understanding of the three-dimensional structures of proteins that interact with carbohydrates covalently (glycoproteins) as well as noncovalently (protein-carbohydrate complexes) is essential to many biological processes and plays a significant role in normal and disease-associated functions. It is important to have a central repository of knowledge available about these protein-carbohydrate complexes as well as preprocessed data of predicted structures. This can be significantly enhanced by tools de novo which can predict carbohydrate-binding sites for proteins in the absence of structure of experimentally known binding site. PROCARB is an open-access database comprising three independently working components, namely, (i) Core PROCARB module, consisting of three-dimensional structures of protein-carbohydrate complexes taken from Protein Data Bank (PDB), (ii) Homology Models module, consisting of manually developed three-dimensional models of N-linked and O-linked glycoproteins of unknown three-dimensional structure, and (iii) CBS-Pred prediction module, consisting of web servers to predict carbohydrate-binding sites using single sequence or server-generated PSSM. Several precomputed structural and functional properties of complexes are also included in the database for quick analysis. In particular, information about function, secondary structure, solvent accessibility, hydrogen bonds and literature reference, and so forth, is included. In addition, each protein in the database is mapped to Uniprot, Pfam, PDB, and so forth.
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  • 44
    Publication Date: 2012-09-13
    Description: This paper presents a precise macromodel of a signal-phase meter, which allows continuous phase measurement during simulation. It has been developed as a support tool during the design process of a signal-conditioning circuit for incremental position encoders. The development of a signal conditioning circuit requires precise measurements of small signal phases, amplitudes and offsets using the analog/digital circuit simulator. The phase measurement cannot be performed directly with a simulator, therefore an appropriate macro-model is needed for a circuit simulator. The structure of the signal-phase meter is based on the conventional signal-phase measuring method and is intended for the measuring of a cosine-signal phase with a known frequency. It recommends that the time variations of an input signal’s parameters (amplitude, phase, frequency, and offset voltage) are slow and small as possible. Rapid change of a signal’s parameters decreases the simulation result’s accuracy. A macro-model’s precision mainly depends on the chosen parameters for the macro-model and for the simulation. We show that with the proposed meter’s model, the phase angle can be measured with an accuracy of more than ±0,02%.
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  • 45
    Publication Date: 2012-09-14
    Description: Reliable identification of copy number aberrations (CNA) from comparative genomic hybridization data would be improved by the availability of a generalised method for processing large datasets. To this end, we developed swatCGH, a data analysis framework and region detection heuristic for computational grids. swatCGH analyses sequentially displaced (sliding) windows of neighbouring probes and applies adaptive thresholds of varying stringency to identify the 10% of each chromosome that contains the most frequently occurring CNAs. We used the method to analyse a published dataset, comparing data preprocessed using four different DNA segmentation algorithms, and two methods for prioritising the detected CNAs. The consolidated list of the most commonly detected aberrations confirmed the value of swatCGH as a simplified high-throughput method for identifying biologically significant CNA regions of interest.
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  • 46
    Publication Date: 2012-09-14
    Description: This paper presents an optimal regulator for depth control simulation of an autonomous underwater vehicle (AUV) using a new approach of decentralized system environment called open control platform (OCP). Simulation results are presented to demonstrate performance of the proposed method.
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  • 47
    Publication Date: 2012-09-13
    Description: A turbocharger unit for diesel engine is often equipped with a built-in online water washing system and its performance is not always satisfactory because of efficiency declination due to deposit accumulated on blade surfaces not being washed away. In this study, a systematic approach of using experimental measurements and computational fluid dynamics (CFD) is adopted to analyse liquid/gas two-phase flow associated with a turbocharger water washing system, in order to understand the underlying flow physics. A medium-sized diesel engine turbocharger configuration is chosen for this purpose. Experiments are focussed on blade surface temperature measurements, while CFD modelling with a coupled Eulerian/Lagrangian method is used for capturing the complex gas/liquid two-phase flow behaviours inside the induction duct and the blade passage. It was found that numerical predictions are in a good agreement with experimental data in terms of temperature distributions of the blade leading edge region and water coverage over the blade ring. Other flow features such as the water droplet trajectories and the particle size distributions are also explored and analysed in further details, and they are useful for understanding the deposit removal mechanism.
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  • 48
    Publication Date: 2012-09-13
    Description: This paper presents a survey of methods and techniques developed for the solution of the continuous gas-lift optimization problem over the last two decades. These range from isolated single-well analysis all the way to real-time multivariate optimization schemes encompassing all wells in a field. While some methods are clearly limited due to their neglect of treating the effects of inter-dependent wells with common flow lines, other methods are limited due to the efficacy and quality of the solution obtained when dealing with large-scale networks comprising hundreds of difficult to produce wells. The aim of this paper is to provide an insight into the approaches developed and to highlight the challenges that remain.
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  • 49
    Publication Date: 2012-09-11
    Description: Constraint-based metabolic models are currently the most comprehensive system-wide models of cellular metabolism. Several challenges arise when building an in silico constraint-based model of an organism that need to be addressed before flux balance analysis (FBA) can be applied for simulations. An algorithm called FBA-Gap is presented here that aids the construction of a working model based on plausible modifications to a given list of reactions that are known to occur in the organism. When applied to a working model, the algorithm gives a hypothesis concerning a minimal medium for sustaining the cell in culture. The utility of the algorithm is demonstrated in creating a new model organism and is applied to four existing working models for generating hypotheses about culture media. In modifying a partial metabolic reconstruction so that biomass may be produced using FBA, the proposed method is more efficient than a previously proposed method in that fewer new reactions are added to complete the model. The proposed method is also more accurate than other approaches in that only biologically plausible reactions and exchange reactions are used.
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  • 50
    Publication Date: 2012-09-14
    Description: Power system network can undergo outages during which there may be a partial or total blackout in the system. In that condition, transmission of power through the optimal path is an important problem in the process of reconfiguration of power system components. For a given set of generation, load pair, there could be many possible paths to transmit the power. The optimal path needs to consider the shortest path (minimum losses), capacity of the transmission line, voltage stability, priority of loads, and power balance between the generation and demand. In this paper, the Bellman Ford Algorithm (BFA) is applied to find out the optimal path and also the several alternative paths by considering all the constraints. In order to demonstrate the capability of BFA, it has been applied to a practical 230 kV network. This restorative path search guidance tool is quite efficient in finding the optimal and also the alternate paths for transmitting the power from a generating station to demand.
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  • 51
    Publication Date: 2012-06-21
    Description: Supertree methods allow to reconstruct large phylogenetic trees by combining smaller trees with overlapping leaf sets into one, more comprehensive supertree. The most commonly used supertree method, matrix representation with parsimony (MRP), produces accurate supertrees but is rather slow due to the underlying hard optimization problem. In this paper, we present an extensive simulation study comparing the performance of MRP and the polynomial supertree methods MinCut Supertree, Modified MinCut Supertree, Build-with-distances, PhySIC, PhySIC_IST, and super distance matrix. We consider both quality and resolution of the reconstructed supertrees. Our findings illustrate the tradeoff between accuracy and running time in supertree construction, as well as the pros and cons of voting- and veto-based supertree approaches. Based on our results, we make some general suggestions for supertree methods yet to come.
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  • 52
    Publication Date: 2012-06-21
    Description: Biochemical systems biology augments more traditional disciplines, such as genomics, biochemistry and molecular biology, by championing (i) mathematical and computational modeling; (ii) the application of traditional engineering practices in the analysis of biochemical systems; and in the past decade increasingly (iii) the use of near-comprehensive data sets derived from ‘omics platform technologies, in particular “downstream” technologies relative to genome sequencing, including transcriptomics, proteomics and metabolomics. The future progress in understanding biological principles will increasingly depend on the development of temporal and spatial analytical techniques that will provide high-resolution data for systems analyses. To date, particularly successful were strategies involving (a) quantitative measurements of cellular components at the mRNA, protein and metabolite levels, as well as in vivo metabolic reaction rates, (b) development of mathematical models that integrate biochemical knowledge with the information generated by high-throughput experiments, and (c) applications to microbial organisms. The inevitable role bioinformatics plays in modern systems biology puts mathematical and computational sciences as an equal partner to analytical and experimental biology. Furthermore, mathematical and computational models are expected to become increasingly prevalent representations of our knowledge about specific biochemical systems.
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  • 53
    Publication Date: 2012-06-21
    Description: An important objective in systems biology is to infer gene regulatory networks from postgenomic data, and dynamic Bayesian networks have been widely applied as a popular tool to this end. The standard approach for nondiscretised data is restricted to a linear model and a homogeneous Markov chain. Recently, various generalisations based on changepoint processes and free allocation mixture models have been proposed. The former aim to relax the homogeneity assumption, whereas the latter are more flexible and, in principle, more adequate for modelling nonlinear processes. In our paper, we compare both paradigms and discuss theoretical shortcomings of the latter approach. We show that a model based on the changepoint process yields systematically better results than the free allocation model when inferring nonstationary gene regulatory processes from simulated gene expression time series. We further cross-compare the performance of both models on three biological systems: macrophages challenged with viral infection, circadian regulation in Arabidopsis thaliana, and morphogenesis in Drosophila melanogaster.
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  • 54
    Publication Date: 2012-06-21
    Description: Background. Delivery of full doses of adjuvant chemotherapy on schedule is key to optimal breast cancer outcomes. Neutropenia is a serious complication of chemotherapy and a common barrier to this goal, leading to dose reductions or delays in treatment. While past research has observed correlations between complete blood count data and neutropenic events, a reliable method of classifying breast cancer patients into low- and high-risk groups remains elusive. Patients and Methods. Thirty-five patients receiving adjuvant chemotherapy for early-stage breast cancer under the care of a single oncologist are examined in this study. FOS-3NN stratifies patient risk based on complete blood count data after the first cycle of treatment. All classifications are independent of breast cancer subtype and clinical markers, with risk level determined by the kinetics of patient blood count response to the first cycle of treatment. Results. In an independent test set of patients unseen by FOS-3NN, 19 out of 21 patients were correctly classified (Fisher’s exact test probability P<0.00023 [2 tailed], Matthews’ correlation coefficient +0.83). Conclusions. We have developed a model that accurately predicts neutropenic events in a population treated with adjuvant chemotherapy in the first cycle of a 6-cycle treatment.
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  • 55
    Publication Date: 2012-06-21
    Description: Bioinformatics, for its very nature, is devoted to a set of targets that constantly evolve. Training is probably the best response to the constant need for the acquisition of bioinformatics skills. It is interesting to assess the effects of training in the different sets of researchers that make use of it. While training bench experimentalists in the life sciences, we have observed instances of changes in their attitudes in research that, if well exploited, can have beneficial impacts in the dialogue with professional bioinformaticians and influence the conduction of the research itself.
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  • 56
    Publication Date: 2012-06-21
    Description: For high-resolution tandem mass spectra, the determination of monoisotopic masses of fragment ions plays a key role in the subsequent peptide and protein identification. In this paper, we present a new algorithm for deisotoping the bottom-up spectra. Isotopic-cluster graphs are constructed to describe the relationship between all possible isotopic clusters. Based on the relationship in isotopic-cluster graphs, each possible isotopic cluster is assessed with a score function, which is built by combining nonintensity and intensity features of fragment ions. The non-intensity features are used to prevent fragment ions with low intensity from being removed. Dynamic programming is adopted to find the highest score path with the most reliable isotopic clusters. The experimental results have shown that the average Mascot scores and F-scores of identified peptides from spectra processed by our deisotoping method are greater than those by YADA and MS-Deconv software.
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  • 57
    Publication Date: 2012-06-21
    Description: Technological developments in large-scale biological experiments, coupled with bioinformatics tools, have opened the doors to computational approaches for the global analysis of whole genomes. This has provided the opportunity to look at genes within their context in the cell. The integration of vast amounts of data generated by these technologies provides a strategy for identifying potential drug targets within microbial pathogens, the causative agents of infectious diseases. As proteins are druggable targets, functional interaction networks between proteins are used to identify proteins essential to the survival, growth, and virulence of these microbial pathogens. Here we have integrated functional genomics data to generate functional interaction networks between Mycobacterium tuberculosis proteins and carried out computational analyses to dissect the functional interaction network produced for identifying drug targets using network topological properties. This study has provided the opportunity to expand the range of potential drug targets and to move towards optimal target-based strategies.
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  • 58
    Publication Date: 2012-06-21
    Description: Typically, next-generation resequencing projects produce large lists of variants. NovelSNPer is a software tool that permits fast and efficient processing of such output lists. In a first step, NovelSNPer determines if a variant represents a known variant or a previously unknown variant. In a second step, each variant is classified into one of 15 SNP classes or 19 InDel classes. Beside the classes used by Ensembl, we introduce POTENTIAL_START_GAINED and START_LOST as new functional classes and present a classification scheme for InDels. NovelSNPer is based upon the gene structure information stored in Ensembl. It processes two million SNPs in six hours. The tool can be used online or downloaded.
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  • 59
    Publication Date: 2012-06-21
    Description: Propidium Iodide is a fluorochrome that is used to measure the DNA content of individual cells, taken from solid tissues, with a flow cytometer. Compensation for spectral cross-over of this fluorochrome still leads to compensation results that are depending on operator experience. We present a data-driven compensation (DDC) algorithm that is designed to automatically compensate combined DNA phenotype flow cytometry acquisitions. The generated compensation values of the DDC algorithm are validated by comparison with manually determined compensation values. The results show that (1) compensation of two-color flow cytometry leads to comparable results using either manual compensation or the DDC method; (2) DDC can calculate sample-specific compensation trace lines; (3) the effects of two different approaches to calculate compensation values can be visualized within one sample. We conclude that the DDC algorithm contributes to the standardization of compensation for spectral cross-over in flow cytometry of solid tissues.
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  • 60
    Publication Date: 2012-06-21
    Description: Understanding mechanisms of protein flexibility is of great importance to structural biology. The ability to detect similarities between proteins and their patterns is vital in discovering new information about unknown protein functions. A Distance Constraint Model (DCM) provides a means to generate a variety of flexibility measures based on a given protein structure. Although information about mechanical properties of flexibility is critical for understanding protein function for a given protein, the question of whether certain characteristics are shared across homologous proteins is difficult to assess. For a proper assessment, a quantified measure of similarity is necessary. This paper begins to explore image processing techniques to quantify similarities in signals and images that characterize protein flexibility. The dataset considered here consists of three different families of proteins, with three proteins in each family. The similarities and differences found within flexibility measures across homologous proteins do not align with sequence-based evolutionary methods.
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  • 61
    Publication Date: 2012-06-21
    Description: Carbohydrate-binding proteins are proteins that can interact with sugar chains but do not modify them. They are involved in many physiological functions, and we have developed a method for predicting them from their amino acid sequences. Our method is based on support vector machines (SVMs). We first clarified the definition of carbohydrate-binding proteins and then constructed positive and negative datasets with which the SVMs were trained. By applying the leave-one-out test to these datasets, our method delivered 0.92 of the area under the receiver operating characteristic (ROC) curve. We also examined two amino acid grouping methods that enable effective learning of sequence patterns and evaluated the performance of these methods. When we applied our method in combination with the homology-based prediction method to the annotated human genome database, H-invDB, we found that the true positive rate of prediction was improved.
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  • 62
    Publication Date: 2012-06-21
    Description: Identifying the various gene expression response patterns is a challenging issue in expression microarray time-course experiments. Due to heterogeneity in the regulatory reaction among thousands of genes tested, it is impossible to manually characterize a parametric form for each of the time-course pattern in a gene by gene manner. We introduce a growth curve model with fractional polynomials to automatically capture the various time-dependent expression patterns and meanwhile efficiently handle missing values due to incomplete observations. For each gene, our procedure compares the performances among fractional polynomial models with power terms from a set of fixed values that offer a wide range of curve shapes and suggests a best fitting model. After a limited simulation study, the model has been applied to our human in vivo irritated epidermis data with missing observations to investigate time-dependent transcriptional responses to a chemical irritant. Our method was able to identify the various nonlinear time-course expression trajectories. The integration of growth curves with fractional polynomials provides a flexible way to model different time-course patterns together with model selection and significant gene identification strategies that can be applied in microarray-based time-course gene expression experiments with missing observations.
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  • 63
    Publication Date: 2012-06-21
    Description: Computational design of novel proteins with well-defined functions is an ongoing topic in computational biology. In this work, we generated and optimized a new synthetic fusion protein using an evolutionary approach. The optimization was guided by directed evolution based on hydrophobicity scores, molecular weight, and secondary structure predictions. Several methods were used to refine the models built from the resulting sequences. We have successfully combined two unrelated naturally occurring binding sites, the immunoglobin Fc-binding site of the Z domain and the DNA-binding motif of MyoD bHLH, into a novel stable protein.
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  • 64
    Publication Date: 2012-06-21
    Description: We present a comprehensive study of cytogenetic alterations that occur during the progression of clear cell renal cell carcinoma (ccRCC). We used high-density high-throughput Affymetrix 100 K SNP arrays to obtain the whole genome SNP copy number information from 71 pretreatment tissue samples with RCC tumors; of those, 42 samples were of human ccRCC subtype. We analyzed patterns of cytogenetic loss and gain from different RCC subtypes and in particular, different stages and grades of ccRCC tumors, using a novel algorithm that we have designed. Based on patterns of cytogenetic alterations in chromosomal regions with frequent losses and gains, we inferred the involvement of candidate genes from these regions in ccRCC tumorigenesis and development. We then proposed a new model of ccRCC tumorigenesis and progression. Our study serves as a comprehensive overview of cytogenetic alterations in a collection of 572 ccRCC tumors from diversified studies and should facilitate the search for specific genes associated with the disease.
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  • 65
    Publication Date: 2012-07-09
    Description: A robust tracking controller for robot manipulators measuring only the angular positions and considering model uncertainties is presented. It is considered that the model is uncertain; that is, the system parameters, nonlinear terms, external perturbations, and the friction effects in each robot joint are considered unknown. The controller is composed by two parts, a linearizing-like control feedback and a high-gain estimator. The main idea is to lump the uncertain terms into a new state which represents the dynamics of the uncertainties. This new state is then estimated in order to be compensated. In this way the resulting controller is robust. A numerical example for a RR robot manipulator is provided, in order to corroborate the results.
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  • 66
    Publication Date: 2012-06-21
    Description: Machine learning was applied to a challenging and biologically significant protein classification problem: the prediction of avonoid UGT acceptor regioselectivity from primary sequence. Novel indices characterizing graphical models of residues were proposed and found to be widely distributed among existing amino acid indices and to cluster residues appropriately. UGT subsequences biochemically linked to regioselectivity were modeled as sets of index sequences. Several learning techniques incorporating these UGT models were compared with classifications based on standard sequence alignment scores. These techniques included an application of time series distance functions to protein classification. Time series distances defined on the index sequences were used in nearest neighbor and support vector machine classifiers. Additionally, Bayesian neural network classifiers were applied to the index sequences. The experiments identified improvements over the nearest neighbor and support vector machine classifications relying on standard alignment similarity scores, as well as strong correlations between specific subsequences and regioselectivities.
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  • 67
    Publication Date: 2012-06-21
    Description: Peptides fold on a time scale that is much smaller than the time required for synthesis, whence all proteins potentially fold cotranslationally to some degree (followed by additional folding events after release from the ribosome). In this paper, in three different ways, we find that cotranslational folding success is associated with higher hydrophobicity at the N-terminus than at the C-terminus. First, we fold simple HP models on a square lattice and observe that HP sequences that fold better cotranslationally than from a fully extended state exhibit a positive difference (N−C) in terminus hydrophobicity. Second, we examine real proteins using a previously established measure of potential cotranslationality known as ALR (Average Logarithmic Ratio of the extent of previous contacts) and again find a correlation with the difference in terminus hydrophobicity. Finally, we use the cotranslational protein structure prediction program SAINT and again find that such an approach to folding is more successful for proteins with higher N-terminus than C-terminus hydrophobicity. All results indicate that cotranslational folding is promoted in part by a hydrophobic start and a less hydrophobic finish to the sequence.
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  • 68
    Publication Date: 2012-06-29
    Description: Gene alterations are a major component of the landscape of tumor genomes. To assess the significance of these alterations in the development of prostate cancer, it is necessary to identify these alterations and analyze them from systems biology perspective. Here, we present a new method (EigFusion) for predicting outlier genes with potential gene rearrangement. EigFusion demonstrated excellent performance in identifying outlier genes with potential rearrangement by testing it to synthetic and real data to evaluate performance. EigFusion was able to identify previously unrecognized genes such as FABP5 and KCNH8 and confirmed their association with primary and metastatic prostate samples while confirmed the metastatic specificity for other genes such as PAH, TOP2A, and SPINK1. We performed protein network based approaches to analyze the network context of potential rearranged genes. Functional gene rearrangement Modules are constructed by integrating functional protein networks. Rearranged genes showed to be highly connected to well-known altered genes in cancer such as AR, RB1, MYC, and BRCA1. Finally, using clinical outcome data of prostate cancer patients, potential rearranged genes demonstrated significant association with prostate cancer specific death.
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  • 69
    Publication Date: 2012-06-29
    Description: In the present study, artificial neural network is used to model the relationship between NOx emissions and operating parameters of a direct injection diesel engine. To provide data for training and testing the network, a 6-inline-cylinder, four-stroke, diesel test engine is used and tested for various engine speeds, mass fuel injection rates, and intake air temperatures. 80% of a total of 144 obtained experimental data is employed for training process. In addition, 10% of the data (randomly selected) is used for network validation and the remaining data is employed for testing the accuracy of the network. The mean square error function is used for evaluating the performance of the network. The results show that the artificial neural network can efficiently be used to predict NOx emissions from the tested engine with about 10% error.
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  • 70
    Publication Date: 2012-06-21
    Description: Biological functionality arises from the complex interactions of simple components. Emerging behaviour is difficult to recognize with verbal models alone, and mathematical approaches are important. Even few interacting components can give rise to a wide range of different responses, that is, sustained, transient, oscillatory, switch-like responses, depending on the values of the model parameters. A quantitative comparison of model predictions and experiments is therefore important to distinguish between competing hypotheses and to judge whether a certain regulatory behaviour is at all possible and plausible given the observed type and strengths of interactions and the speed of reactions. Here I will review a detailed model for the transcription factor σF, a regulator of cell differentiation during sporulation in Bacillus subtilis. I will focus in particular on the type of conclusions that can be drawn from detailed, carefully validated models of biological signaling networks. For most systems, such detailed experimental information is currently not available, but accumulating biochemical data through technical advances are likely to enable the detailed modelling of an increasing number of pathways. A major challenge will be the linking of such detailed models and their integration into a multiscale framework to enable their analysis in a larger biological context.
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  • 71
    Publication Date: 2012-06-21
    Description: The GenSensor Suite consists of four web tools for elucidating relationships among genes and proteins. GenPath results show which biochemical, regulatory, or other gene set categories are over- or under-represented in an input list compared to a background list. All common gene sets are available for searching in GenPath, plus some specialized sets. Users can add custom background lists. GenInteract builds an interaction gene list from a single gene input and then analyzes this in GenPath. GenPubMed uses a PubMed query to identify a list of PubMed IDs, from which a gene list is extracted and queried in GenPath. GenViewer allows the user to query one gene set against another in GenPath. GenPath results are presented with relevant P- and q-values in an uncluttered, fully linked, and integrated table. Users can easily copy this table and paste it directly into a spreadsheet or document.
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  • 72
    Publication Date: 2012-06-21
    Description: Wet laboratory mutagenesis to determine enzyme activity changes is expensive and time consuming. This paper expands on standard one-shot learning by proposing an incremental transductive method (T2bRF) for the prediction of enzyme mutant activity during mutagenesis using Delaunay tessellation and 4-body statistical potentials for representation. Incremental learning is in tune with both eScience and actual experimentation, as it accounts for cumulative annotation effects of enzyme mutant activity over time. The experimental results reported, using cross-validation, show that overall the incremental transductive method proposed, using random forest as base classifier, yields better results compared to one-shot learning methods. T2bRF is shown to yield 90% on T4 and LAC (and 86% on HIV-1). This is significantly better than state-of-the-art competing methods, whose performance yield is at 80% or less using the same datasets.
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  • 73
    Publication Date: 2012-06-21
    Description: Identification of regulatory molecules in signaling pathways is critical for understanding cellular behavior. Given the complexity of the transcriptional gene network, the relationship between molecular expression and phenotype is difficult to determine using reductionist experimental methods. Computational models provide the means to characterize regulatory mechanisms and predict phenotype in the context of gene networks. Integrating gene expression data with phenotypic data in transcriptional network models enables systematic identification of critical molecules in a biological network. We developed an approach based on fuzzy logic to model cell budding in Saccharomyces cerevisiae using time series expression microarray data of the cell cycle. Cell budding is a phenotype of viable cells undergoing division. Predicted interactions between gene expression and phenotype reflected known biological relationships. Dynamic simulation analysis reproduced the behavior of the yeast cell cycle and accurately identified genes and interactions which are essential for cell viability.
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  • 74
    Publication Date: 2012-06-07
    Description: We have modeled a new (Q, r) inventory system which involves a single product, a supplier, and a retailer with customer differentiation under continuous review inventory policy. The supplier provides the retailer with all requirements, and the retailer sells products to the customers. The supplying process is randomly subject to disruptions. Partial backordering is applied when a stock out occurs, and customer can select either to leave the system without purchasing or to backorder products. The customers are categorized into two main classes regarding to their backordering probabilities. The main contribution of this paper is including the customer differentiation in the inventory model. We used simulation technique to verify the impact of supply disruptions and customer differentiation and carried out sensitivity analysis. To test the performance of the model, we have compared our model to one from the latest related research. As the results show, the average of total annual cost of the (Q, r) inventory system is lower than that of the previously developed models such as (r, T) inventory systems.
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  • 75
    Publication Date: 2012-04-23
    Description: This paper deals with the initial modeling of water salinity and its diffusion into the lakes during lock operation on the Panama Canal. A hybrid operational model was implemented using the AnyLogic software simulation environment. This was accomplished by generating an operational discrete-event simulation model and a continuous simulation model based on differential equations, which modeled the salinity diffusion in the lakes. This paper presents that unique application and includes the effective integration of lock operations and its impact on the environment.
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  • 76
    Publication Date: 2012-04-23
    Description: A mathematical modelling of a continuous review stochastic inventory system with a single server is carried out in this work. We assume that demand time points form a Poisson process. The life time of each item is assumed to have exponential distribution. We assume (s,S) ordering policy to replenish stock with random lead time. The server goes for a vacation of an exponentially distributed duration at the time of stock depletion and may take subsequent vacation depending on the stock position. The customer who arrives during the stock-out period or during the server vacation is offered a choice of joining a pool which is of finite capacity or leaving the system. The demands in the pool are selected one by one by the server only when the inventory level is above s, with interval time between any two successive selections distributed as exponential with parameter depending on the number of customers in the pool. The joint probability distribution of the inventory level and the number of customers in the pool is obtained in the steady-state case. Various system performance measures in the steady state are derived, and the long-run total expected cost rate is calculated.
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  • 77
    Publication Date: 2012-05-10
    Description: This paper presents a MATLAB based user friendly software tool called as PV.MY for optimal sizing of photovoltaic (PV) systems. The software has the capabilities of predicting the metrological variables such as solar energy, ambient temperature and wind speed using artificial neural network (ANN), optimizes the PV module/ array tilt angle, optimizes the inverter size and calculate optimal capacities of PV array, battery, wind turbine and diesel generator in hybrid PV systems. The ANN based model for metrological prediction uses four meteorological variables, namely, sun shine ratio, day number and location coordinates. As for PV system sizing, iterative methods are used for determining the optimal sizing of three types of PV systems, which are standalone PV system, hybrid PV/wind system and hybrid PV/diesel generator system. The loss of load probability (LLP) technique is used for optimization in which the energy sources capacities are the variables to be optimized considering very low LLP. As for determining the optimal PV panels tilt angle and inverter size, the Liu and Jordan model for solar energy incident on a tilt surface is used in optimizing the monthly tilt angle, while a model for inverter efficiency curve is used in the optimization of inverter size.
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  • 78
    Publication Date: 2011-11-18
    Description: We motivate our study by simulating the particle transport of a thin film deposition process done by PVD (physical vapor deposition) processes. In this paper we present a new model taken into account a self-consistent electrostatic-particle in cell model with low density Argon plasma. The collision model are based of Monte Carlo simulations is discussed for DC sputtering in lower pressure regimes. In order to simulate transport phenomena within sputtering processes realistically, a spatial and temporal knowledge of the plasma density and electrostatic field configuration is needed. Due to relatively low plasma densities, continuum fluid equations are not applicable. We propose instead a Particle-in-cell (PIC) method, which allows the study of plasma behavior by computing the trajectories of finite-size particles under the action of an external and self-consistent electric field defined in a grid of points.
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  • 79
    Publication Date: 2011-11-16
    Description: The experiments and finite element simulations of composite laminate with stitching are carried out. Firstly, the monotonous tensile experiments with and without stitching are conducted to investigate the influence of stitch reinforcement on the composite laminate. Secondly, the finite element method (FEM) is employed to simulate the tensile process of specimens, and the link element is introduced to simulate the stitching. The experiment results shows that the stitching has little influence on the damage load under monotonous tensile load, while there is a significant influence on the changing of strain. The FEM results are consistent with the experiment results, which means that the link element can be used to study the stitching of the composite laminate. The simulation results also show that the distributions of strain are changed obviously due to the existence of the stitching. Research results have a significant role on the design of the composite structures with and without stitching.
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  • 80
    Publication Date: 2011-11-25
    Description: This paper reveals mathematical models of the simplest Mamdani PI/PD controllers which employ two fuzzy sets (N: negative and P: positive) on the universe of discourse (UoD) of each of two input variables (displacement and velocity) and three fuzzy sets (N: negative, Z: zero, and P: positive) on the UoD of output variable (control output in the case of PD, and incremental control output in the case of PI). The basic constituents of these models are algebraic product/minimum AND, bounded sum/algebraic sum/maximum OR, algebraic product inference, three linear fuzzy control rules, and Center of Sums (CoS) defuzzification. Properties of all these models are investigated. It is shown that all these controllers are different nonlinear PI/PD controllers with their proportional and derivative gains changing with the inputs. The proposed models are significant and useful to control community as they are completely new and qualitatively different from those reported in the literature.
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  • 81
    Publication Date: 2011-11-29
    Description: When a cavitated body moves in shallow water, both flexible free surface and rigid bottom wall will produce great influence on the cavity pattern and hydrodynamics to change the motion attitude and stability of the body. In this paper, a single-fluid multiphase flow method coupled with a natural cavitation model was employed to study the effects of two kinds of boundaries on the natural cavitating flow around a two-dimensional symmetry wedge in shallow water. Within the range of the cavitation number for computation (0.05 ~ 2.04), the cavity pattern would be divided into three types, namely, stable type, transition type and wake-vortex type. The shape of the free surface is fairly similar to that of the cavity's upper surface with well right-and-left symmetry. However, when the immersion depth and the cavitation number are decreasing, the symmetry of the cavity shape is destroyed due to the influence of bottom wall effects. When the cavitation number is less than about 0.1, with the immersion depth going down, free surface effects exerts a stronger influence on the drag coefficient of this 2D wedge, whereas wall effects bring a stronger influence on the lift coefficient.
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  • 82
    Publication Date: 2011-11-30
    Description: The main aim of this work is to show that such a powerful optimizing tool like evolutionary algorithms (EAs) can be in reality used for the simulation and optimization of a nonlinear system. A nonlinear mathematical model is required to describe the dynamic behaviour of batch process; this justifies the use of evolutionary method of the EAs to deal with this process. Four algorithms from the field of artificial intelligent—differential evolution (DE), self-organizing migrating algorithm (SOMA), genetic algorithm (GA), and simulated annealing (SA)—are used in this investigation. The results show that EAs are used successfully in the process optimization.
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  • 83
    Publication Date: 2011-11-18
    Description: Because of the complicated energy conversion process, ultrasonic motor has remarkable nonlinearity. Therefore, it is difficult to achieve accurate speed control of ultrasonic motor. In general, a good model is the foundation of the accurate control effect. Because of the remarkable non-linearity of ultrasonic motor, the model should also be nonlinear. In this paper, the two-input and one-output steady-state model of ultrasonic motor system is worked out using fuzzy reasoning modeling method. Comparison between experimental data and calculated data of the model prove that the model can well simulate the nonlinear relationship among the amplitude of driving voltage, frequency, and rotating speed.
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  • 84
    Publication Date: 2011-10-19
    Description: It is reasonable to expect that, when two nominally flat rough surfaces are brought into contact by an applied resultant force, they must support, in addition to the compressive load, an induced moment. The existence of a net applied moment would imply noneven distribution of contact force so that there are more asperities in contact over one region of the nominal area. In this paper, we consider the contact between two rectangular rough surfaces that provide normal and tangential contact force as well as contact moment to counteract the net moment imposed by the applied forces. The surfaces are permitted to develop slight angular misalignment, and thereby contact moment is derived. Through this scheme, it is possible to also define elastic contribution to friction since the half-plane tangential contact force on one side of an asperity is no longer balanced by the half-plane tangential force component on the opposite side. The elastic friction force, however, is shown to be of a much smaller order than the contact normal force. Approximate closed-form equations are found for contact force and moment for the contact of rough surfaces.
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  • 85
    Publication Date: 2011-11-03
    Description: A computable model of grasping and manipulation of a 3D rigid object with arbitrary smooth surfaces by multiple robot fingers with smooth fingertip surfaces is derived under rolling contact constraints between surfaces. Geometrical conditions of pure rolling contacts are described through the moving-frame coordinates at each rolling contact point under the postulates: (1) two surfaces share a common single contact point without any mutual penetration and a common tangent plane at the contact point and (2) each path length of running of the contact point on the robot fingertip surface and the object surface is equal. It is shown that a set of Euler-Lagrange equations of motion of the fingers-object system can be derived by introducing Lagrange multipliers corresponding to geometric conditions of contacts. A set of 1st-order differential equations governing rotational motions of each fingertip and the object and updating arc-length parameters should be accompanied with the Euler-Lagrange equations. Further more, nonholonomic constraints arising from twisting between the two normal axes to each tangent plane are rewritten into a set of Frenet-Serre equations with a geometrically given normal curvature and a motion-induced geodesic curvature.
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  • 86
    Publication Date: 2011-11-04
    Description: An improved preconditioning is proposed for viscous flow computations in rotating and nonrotating frames at arbitrary Mach numbers. The key to the current method is the use of both free stream Mach number and rotating Mach number to construct a preconditioning matrix, which is applied to the compressible governing equations written in terms of primitive variables. A Fourier analysis is conducted that reveals the efficacy of the modified preconditioning. Numerical approximations for the convective and diffusive fluxes are detailed based on the preconditioned system of equations. A set of boundary conditions using characteristic variables are described for internal and external flow computations. Numerical validations are performed on four realistic viscous flows in both fixed and rotating frames. The results indicated that the modified preconditioning has a superior performance compared to the original method to predict flows from extremely low to supersonic Mach numbers.
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  • 87
    Publication Date: 2011-09-09
    Description: This paper develops a GA ANFIS controller design method for temperature control in plastic extrusion system. Temperature control of plastic extrusion system suffers problems related to longer settling time, couple effects, large time constants, and undesirable overshoot. The system is generally nonlinear and the temperature of the plastic extrusion system may vary over a wide range of disturbances. The system is designed with three controllers. The proposed GA ANFIS controller is the most powerful approach to retrieve the adaptiveness in the case of nonlinear system. In this research the control methods are simulated using simulink. Relatively the methodology and efficiency of the proposed method are compared with those of the traditional methods and the results obtained from GA ANFIS controller give improved performance in terms of time domain specification, set point tracking, and disturbance rejection with optimum stability.
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  • 88
    Publication Date: 2011-11-04
    Description: The objective of this paper is to present a short research about the overall broadband penetration in Greece. In this research, a new empirical deterministic model is proposed for the short-term forecast of the cumulative broadband adoption. The fitting performance of the model is compared with some widely used diffusion models for the cumulative adoption of new telecommunication products, namely, Logistic, Gompertz, Flexible Logistic (FLOG), Box-Cox, Richards, and Bass models. The fitting process is done with broadband penetration official data for Greece. In conclusion, comparing these models with the empirical model, it could be argued that the latter yields well enough statistics indicators for fitting and forecasting performance. It also stresses the need for further research and performance analysis of the model in other more mature broadband markets.
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  • 89
    Publication Date: 2011-10-16
    Description: To include user interactions in simulations of product use, the most common approach is to couple human subjects to simulation models, using hardware interfaces to close the simulation-control loop. Testing with virtual human models could offer a low-cost addition to evaluation with human subjects. This paper explores the possibilities for coupling human and artefact models to achieve fully software-based interaction simulations. We have critically reviewed existing partial solutions to simulate or execute control (both human control and product-embedded control) and compared solutions from literature with a proof-of-concept we have recently developed. Our concept closes all loops, but it does not rely on validated algorithms to predict human decision making and low-level human motor control. For low-level control, validated solutions are available from other approaches. For human decision making, however, validated algorithms exist only to predict the timing but not the reasoning behind it. To identify decision-making schemes beyond what designers can conjecture, testing with human subjects remains indispensable.
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  • 90
    Publication Date: 2011-10-27
    Description: We examine a simulation model for polymer extrusion filters and determine its sensitivity to filter parameters. The simulator is a three-dimensional, time-dependent discretization of a coupled system of nonlinear partial differential equations used to model fluid flow and debris transport, along with statistical relationships that define debris distributions and retention probabilities. The flow of polymer fluid, and suspended debris particles, is tracked to determine how well a filter performs and how long it operates before clogging. A filter may have multiple layers, characterized by thickness, porosity, and average pore diameter. In this work, the thickness of each layer is fixed, while the porosities and pore diameters vary for a two-layer and three-layer study. The effects of porosity and average pore diameter on the measures of filter quality are calculated. For the three layer model, these effects are tested for statistical significance using analysis of variance. Furthermore, the effects of each pair of interacting parameters are considered. This allows the detection of complexity, where in changing two aspects of a filter together may generate results substantially different from what occurs when those same aspects change separately. The principal findings indicate that the first layer of a filter is the most important.
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  • 91
    Publication Date: 2011-03-04
    Description: Packet scheduling has drawn a great deal of attention in the field of wireless networks as it plays an important role in distributing shared resources in a network. The process involves allocating the bandwidth among users and determining their transmission order. In this paper an uplink (UL) scheduling algorithm for the Mobile Worldwide Interoperability for Microwave Access (WiMAX) network based on the cyclic polling model is proposed. The model in this study consists of five queues (UGS, ertPS, rtPS, nrtPS, and BE) visited by a single server. A threshold policy is imposed to the nrtPS queue to ensure that the delay constraint of real time traffic (UGS, ertPS, and rtPS) is not violated making this approach original in comparison to the existing contributions. A mathematical model is formulated for the weighted sum of the mean waiting time of each individual queues based on the pseudo-conservation law. The results of the analysis are useful in obtaining or testing approximation for individual mean waiting time especially when queues are asymmetric (where each queue may have different stochastic characteristic such as arrival rate and service time distribution) and when their number is large (more than 2 queues).
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  • 92
    Publication Date: 2011-03-01
    Description: Coupled equations between wind and saltating particles are presented for a stable wind blowing over an infinite plane bed and the equations are solved for a simplified particle-bed impact process. The calculated results show that the saltating snow particles strongly affect the velocity distribution of the wind, causing a deviation from a logarithmically distributed wind velocity profile. The average height and length of saltating snow particle trajectories exponentially increase as the friction velocity increases; the ejected snow number flux and the streamwise snow transport rate also increase as the friction velocity increases.
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  • 93
    Publication Date: 2011-03-01
    Description: This paper deals with usage of an alternative tool for symbolic regression—analytic programming which is able to solve various problems from the symbolic domain, as well as genetic programming and grammatical evolution. This paper describes a setting of an optimal trajectory for a robot (originally designed as an artificial ant on Santa Fe trail) solved by means of analytic programming. Firstly, main principles of analytic programming are described and explained. The second part shows how analytic programming was used for the application of finding a suitable trajectory step by step. Because analytic programming needs evolutionary algorithms for its run, three evolutionary algorithms were used—self-organizing migrating algorithm, differential evolution, and simulated annealing—to show that anyone can be used. The total number of simulations was 150 and results show that the first two used algorithms were more successful than not so robust simulated annealing.
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  • 94
    Publication Date: 2011-03-01
    Description: A 3D dynamic computer model for the movement of the head-neck complex is presented. It incorporates anatomically correct information about the diverse elements forming the system. The skeleton is considered as a set of interconnected rigid 3D bodies following the Newton-Euler laws of movement. The muscles are modeled using Enderle's linear model, which shows equivalent dynamic characteristics to Loeb's virtual muscle model. The soft tissues, namely, the ligaments, intervertebral disks, and facet joints, are modeled considering their physiological roles and dynamics. In contrast with other head and neck models developed for safety research, the model is aimed to study the neural control of the complex during fast eye and head movements, such as saccades and gaze shifts. In particular, the time-optimal hypothesis and the feedback control ones are discussed.
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  • 95
    Publication Date: 2011-03-01
    Description: This paper presents the topology of operating DC-DC buck converter in boost mode for extra-high-voltage applications. Traditional DC-DC boost converters are used in high-voltage applications, but they are not economical due to the limited output voltage, efficiency and they require two sensors with complex control algorithm. Moreover, due to the effect of parasitic elements the output voltage and power transfer efficiency of DC-DC converters are limited. These limitations are overcome by using the voltage lift technique, opens a good way to improve the performance characteristics of DC-DC converter. The technique is applied to DC-DC converter and a simplified control algorithm in this paper. The performance of the controller is studied for both line and load disturbances. These converters perform positive DC-DC voltage increasing conversion with high power density, high efficiency, low cost in simple structure, small ripples, and wide range of control. Simulation results along theoretical analysis are provided to verify its performance.
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  • 96
    Publication Date: 2011-03-01
    Description: Better understanding of stresses and flow characteristics in the human airways is very important for many clinical applications such as aerosol drug therapy, inhalation toxicology, and airway remodeling process. The bifurcation geometry of airway generations 3 to 5 based on the ICRP tracheobronchial model was chosen to analyze the flow characteristics and stresses during inhalation. A computational model was developed to investigate the airway tissue flexibility effect on stresses and flow characteristics in the airways. The finite-element method with the fluid-structure interaction analysis was employed to investigate the transient responses of the flow characteristics and stresses in the airways during inhalation. The simulation results showed that tissue flexibility affected the maximum airflow velocity, airway pressure, and wall shear stress about 2%, 7%, and 6%, respectively. The simulation results also showed that the differences between the orthotropic and isotropic material models on the airway stresses were in the ranges of 25–52%. The results from the present study suggest that it is very important to incorporate the orthotropic tissue properties into a computational model for studying flow characteristics and stresses in the airways.
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  • 97
    Publication Date: 2011-03-01
    Description: To date, most speech synthesis techniques have relied upon the representation of the vocal tract by some form of filter, a typical example being linear predictive coding (LPC). This paper describes the development of a physiologically realistic model of the vocal tract using the well-established technique of transmission line modelling (TLM). This technique is based on the principle of wave scattering at transmission line segment boundaries and may be used in one, two, or three dimensions. This work uses this technique to model the vocal tract using a one-dimensional transmission line. A six-port scattering node is applied in the region separating the pharyngeal, oral, and the nasal parts of the vocal tract.
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  • 98
    Publication Date: 2011-03-01
    Description: A case study of open-source (OS) development of the computational research software MFIX, used for multiphase computational fluid dynamics simulations, is presented here. The verification and validation steps required for constructing modern computational software and the advantages of OS development in those steps are discussed. The infrastructure used for enabling the OS development of MFIX is described. The impact of OS development on computational research and education in gas-solids flow, as well as the dissemination of information to other areas such as geophysical and volcanology research, is demonstrated. This study shows that the advantages of OS development were realized in the case of MFIX: verification by many users, which enhances software quality; the use of software as a means for accumulating and exchanging information; the facilitation of peer review of the results of computational research.
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  • 99
    Publication Date: 2011-03-01
    Description: A new genetic algorithm (GA) methodology, Bipopulation-Based Genetic Algorithm with Enhanced Interval Search (BGAwEIS), is introduced and used to optimize the design of truss structures with various complexities. The results of BGAwEIS are compared with those obtained by the sequential genetic algorithm (SGA) utilizing a single population, a multipopulation-based genetic algorithm (MPGA) proposed for this study and other existing approaches presented in literature. This study has two goals: outlining BGAwEIS's fundamentals and evaluating the performances of BGAwEIS and MPGA. Consequently, it is demonstrated that MPGA shows a better performance than SGA taking advantage of multiple populations, but BGAwEIS explores promising solution regions more efficiently than MPGA by exploiting the feasible solutions. The performance of BGAwEIS is confirmed by better quality degree of its optimal designations compared to algorithms proposed here and described in literature.
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  • 100
    Publication Date: 2011-03-01
    Description: Pick up-dispatching problem together with delivery-dispatching problem of a multiple-load automated guided vehicle (AGV) system have been studied. By mixing different pick up-dispatching rules, several control strategies (alternatives) have been generated and the best control strategy has been determined considering some important criteria such as System Throughput (ST), Mean Flow Time of Parts (MFTP), Mean Tardiness of Parts (MFTP), AGV Idle Time (AGVIT), AGV Travel Full (AGVTF), AGV Travel Empty (AGVTE), AGV Load Time (AGVLT), AGV Unload Time (AGVUT), Mean Queue Length (MQL) and Mean Queue Waiting (MQW). For ranking the control strategies, a new framework based on MADM methods including fuzzy MADM and TOPSIS method were developed. Then several simulation experiments which had been based on a flow path layout to find the results were conducted. Finally, by using TOPSIS method, the control strategies were ranked. Furthermore, a similar approach was used for determining the optimal fleet size. The main contribution of this paper is developing a new approach combining the top managers' views in selecting the best control strategy for AGV systems while trying to optimize the fleet size at the mean time by combining MADM, MCDM and simulation methods.
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