Open AccessArticle
Artificial Immune Classifier Based on ELLipsoidal Regions (AICELL)
Computation 2017, 5(2), 31; doi:10.3390/computation5020031 -
Abstract
Pattern classification is a central problem in machine learning, with a wide array of applications, and rule-based classifiers are one of the most prominent approaches. Among these classifiers, Incremental Rule Learning algorithms combine the advantages of classic Pittsburg and Michigan approaches, while, on
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Pattern classification is a central problem in machine learning, with a wide array of applications, and rule-based classifiers are one of the most prominent approaches. Among these classifiers, Incremental Rule Learning algorithms combine the advantages of classic Pittsburg and Michigan approaches, while, on the other hand, classifiers using fuzzy membership functions often result in systems with fewer rules and better generalization ability. To discover an optimal set of rules, learning classifier systems have always relied on bio-inspired models, mainly genetic algorithms. In this paper we propose a classification algorithm based on an efficient bio-inspired approach, Artificial Immune Networks. The proposed algorithm encodes the patterns as antigens, and evolves a set of antibodies, representing fuzzy classification rules of ellipsoidal surface, to cover the problem space. The innate immune mechanisms of affinity maturation and diversity preservation are modified and adapted to the classification context, resulting in a classifier that combines the advantages of both incremental rule learning and fuzzy classifier systems. The algorithm is compared to a number of state-of-the-art rule-based classifiers, as well as Support Vector Machines (SVM), producing very satisfying results, particularly in problems with large number of attributes and classes. Full article
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Open AccessArticle
Theoretical Prediction of Electronic Structures and Phonon Dispersion of Ce2XN2 (X = S, Se, and Te) Ternary
Computation 2017, 5(2), 29; doi:10.3390/computation5020029 -
Abstract
A systematic study of structural, electronic, vibrational properties of new ternary dicerium selenide dinitride, Ce2SeN2 and predicted compounds—Ce2SN2 and Ce2TeN2—is performed using first-principles calculations within Perdew–Burke–Ernzerhof functional with Hubbard correction. Our calculated results
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A systematic study of structural, electronic, vibrational properties of new ternary dicerium selenide dinitride, Ce2SeN2 and predicted compounds—Ce2SN2 and Ce2TeN2—is performed using first-principles calculations within Perdew–Burke–Ernzerhof functional with Hubbard correction. Our calculated results for structural parameters nicely agree to the experimental measurements. We predict that all ternary dicerium chalcogenide nitrides are thermodynamically stable. The predicted elastic constants and related mechanical properties demonstrate its profound mechanical stability as well. Moreover, our results show that Ce2XN2 are insulator materials. Trends of the structural parameters, electronic structures, and phonon dispersion are discussed in terms of the characteristics of the Ce (4f) states. Full article
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Open AccessArticle
Levy-Lieb-Based Monte Carlo Study of the Dimensionality Behaviour of the Electronic Kinetic Functional
Computation 2017, 5(2), 30; doi:10.3390/computation5020030 -
Abstract
We consider a gas of interacting electrons in the limit of nearly uniform density and treat the one dimensional (1D), two dimensional (2D) and three dimensional (3D) cases. We focus on the determination of the correlation part of the kinetic functional by employing
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We consider a gas of interacting electrons in the limit of nearly uniform density and treat the one dimensional (1D), two dimensional (2D) and three dimensional (3D) cases. We focus on the determination of the correlation part of the kinetic functional by employing a Monte Carlo sampling technique of electrons in space based on an analytic derivation via the Levy-Lieb constrained search principle. Of particular interest is the question of the behaviour of the functional as one passes from 1D to 3D; according to the basic principles of Density Functional Theory (DFT) the form of the universal functional should be independent of the dimensionality. However, in practice the straightforward use of current approximate functionals in different dimensions is problematic. Here, we show that going from the 3D to the 2D case the functional form is consistent (concave function) but in 1D becomes convex; such a drastic difference is peculiar of 1D electron systems as it is for other quantities. Given the interesting behaviour of the functional, this study represents a basic first-principle approach to the problem and suggests further investigations using highly accurate (though expensive) many-electron computational techniques, such as Quantum Monte Carlo. Full article
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Open AccessArticle
Geometric Derivation of the Stress Tensor of the Homogeneous Electron Gas
Computation 2017, 5(2), 28; doi:10.3390/computation5020028 -
Abstract
The foundation of many approximations in time-dependent density functional theory (TDDFT) lies in the theory of the homogeneous electron gas. However, unlike the ground-state DFT, in which the exchange-correlation potential of the homogeneous electron gas is known exactly via the quantum Monte Carlo
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The foundation of many approximations in time-dependent density functional theory (TDDFT) lies in the theory of the homogeneous electron gas. However, unlike the ground-state DFT, in which the exchange-correlation potential of the homogeneous electron gas is known exactly via the quantum Monte Carlo calculation, the time-dependent or frequency-dependent dynamical potential of the homogeneous electron gas has not been known exactly, due to the absence of a similar variational principle for excited states. In this work, we present a simple geometric derivation of the time-dependent dynamical exchange-correlation potential for the homogeneous system. With this derivation, the dynamical potential can be expressed in terms of the stress tensor, offering an alternative to calculate the bulk and shear moduli, two key input quantities in TDDFT. Full article
Open AccessArticle
Energetic Study of Clusters and Reaction Barrier Heights from Efficient Semilocal Density Functionals
Computation 2017, 5(2), 27; doi:10.3390/computation5020027 -
Abstract
The accurate first-principles prediction of the energetic properties of molecules and clusters from efficient semilocal density functionals is of broad interest. Here we study the performance of a non-empirical Tao-Mo (TM) density functional on binding energies and excitation energies of titanium dioxide and
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The accurate first-principles prediction of the energetic properties of molecules and clusters from efficient semilocal density functionals is of broad interest. Here we study the performance of a non-empirical Tao-Mo (TM) density functional on binding energies and excitation energies of titanium dioxide and water clusters, as well as reaction barrier heights. To make a comparison, a combination of the TM exchange part with the TPSS (Tao–Perdew–Staroverov–Scuseria) correlation functional—called TMTPSS—is also included in this study. Our calculations show that the best binding energies of titanium dioxide are predicted by PBE0 (Perdew–Burke–Ernzerhof hybrid functional), TM, and TMTPSS with nearly the same accuracy, while B3LYP (Beck’s three-parameter exchange part with Lee-Yang-Parr correlation), TPSS, and PBE (Perdew–Burke–Ernzerhof) yield larger mean absolute errors. For excitation energies of titanium and water clusters, PBE0 and B3LYP are the most accurate functionals, outperforming the performance of semilocal functionals due to the nonlocality problem suffered by the latter. Nevertheless, TMTPSS and TM functionals are still good accurate semilocal methods, improving upon the commonly-used TPSS and PBE functionals. We also find that the best reaction barrier heights are predicted by PBE0 and B3LYP, thanks to the nonlocality incorporated into these two hybrid functionals, but TMTPSS and TM are obviously more accurate than SCAN (Strongly Constrained and Appropriately Normed), TPSS, and PBE, suggesting the good performance of TM and TMTPSS for physically different systems and properties. Full article
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Open AccessArticle
Deep Visual Attributes vs. Hand-Crafted Audio Features on Multidomain Speech Emotion Recognition
Computation 2017, 5(2), 26; doi:10.3390/computation5020026 -
Abstract
Emotion recognition from speech may play a crucial role in many applications related to human–computer interaction or understanding the affective state of users in certain tasks, where other modalities such as video or physiological parameters are unavailable. In general, a human’s emotions may
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Emotion recognition from speech may play a crucial role in many applications related to human–computer interaction or understanding the affective state of users in certain tasks, where other modalities such as video or physiological parameters are unavailable. In general, a human’s emotions may be recognized using several modalities such as analyzing facial expressions, speech, physiological parameters (e.g., electroencephalograms, electrocardiograms) etc. However, measuring of these modalities may be difficult, obtrusive or require expensive hardware. In that context, speech may be the best alternative modality in many practical applications. In this work we present an approach that uses a Convolutional Neural Network (CNN) functioning as a visual feature extractor and trained using raw speech information. In contrast to traditional machine learning approaches, CNNs are responsible for identifying the important features of the input thus, making the need of hand-crafted feature engineering optional in many tasks. In this paper no extra features are required other than the spectrogram representations and hand-crafted features were only extracted for validation purposes of our method. Moreover, it does not require any linguistic model and is not specific to any particular language. We compare the proposed approach using cross-language datasets and demonstrate that it is able to provide superior results vs. traditional ones that use hand-crafted features. Full article
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Open AccessArticle
Numerical Simulation of the Laminar Forced Convective Heat Transfer between Two Concentric Cylinders
Computation 2017, 5(2), 25; doi:10.3390/computation5020025 -
Abstract
The dual reciprocity method (DRM) is a highly efficient numerical method of transforming domain integrals arising from the non-homogeneous term of the Poisson equation into equivalent boundary integrals. In this paper, the velocity and temperature fields of laminar forced heat convection in a
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The dual reciprocity method (DRM) is a highly efficient numerical method of transforming domain integrals arising from the non-homogeneous term of the Poisson equation into equivalent boundary integrals. In this paper, the velocity and temperature fields of laminar forced heat convection in a concentric annular tube, with constant heat flux boundary conditions, have been studied using numerical simulations. The DRM has been used to solve the governing equation, which is expressed in the form of a Poisson equation. A test problem is employed to verify the DRM solutions with different boundary element discretizations and numbers of internal points. The results of the numerical simulations are discussed and compared with exact analytical solutions. Good agreement between the numerical results and exact solutions is evident, as the maximum relative errors are less than 5% to 6%, and the R2-values are greater than 0.999 in all cases. These results confirm the effectiveness and accuracy of the proposed numerical model, which is based on the DRM. Full article
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Open AccessFeature PaperArticle
Analyzing the Effect and Performance of Lossy Compression on Aeroacoustic Simulation of Gas Injector
Computation 2017, 5(2), 24; doi:10.3390/computation5020024 -
Abstract
Computational fluid dynamic simulations involve large state data, leading to performance degradation due to data transfer times, while requiring large disk space. To alleviate the situation, an adaptive lossy compression algorithm has been developed, which is based on regions of interest. This algorithm
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Computational fluid dynamic simulations involve large state data, leading to performance degradation due to data transfer times, while requiring large disk space. To alleviate the situation, an adaptive lossy compression algorithm has been developed, which is based on regions of interest. This algorithm uses prediction-based compression and exploits the temporal coherence between subsequent simulation frames. The difference between the actual value and the predicted value is adaptively quantized and encoded. The adaptation is in line with user requirements, that consist of the acceptable inaccuracy, the regions of interest and the required compression throughput. The data compression algorithm was evaluated with simulation data obtained by the discontinuous Galerkin spectral element method. We analyzed the performance, compression ratio and inaccuracy introduced by the lossy compression algorithm. The post processing analysis shows high compression ratios, with reasonable quantization errors. Full article
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Open AccessArticle
Implicit Large Eddy Simulation of Flow in a Micro-Orifice with the Cumulant Lattice Boltzmann Method
Computation 2017, 5(2), 23; doi:10.3390/computation5020023 -
Abstract
A detailed numerical study of turbulent flow through a micro-orifice is presented in this work. The flow becomes turbulent due to the orifice at the considered Reynolds numbers (∼104). The obtained flow rates are in good agreement with the experimental
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A detailed numerical study of turbulent flow through a micro-orifice is presented in this work. The flow becomes turbulent due to the orifice at the considered Reynolds numbers (∼104). The obtained flow rates are in good agreement with the experimental measurements. The discharge coefficient and the pressure loss are presented for two input pressures. The laminar stress and the generated turbulent stresses are investigated in detail, and the location of the vena contracta is quantitatively reproduced. Full article
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Open AccessArticle
Scatter Search Applied to the Inference of a Development Gene Network
Computation 2017, 5(2), 22; doi:10.3390/computation5020022 -
Abstract
Efficient network inference is one of the challenges of current-day biology. Its application to the study of development has seen noteworthy success, yet a multicellular context, tissue growth, and cellular rearrangements impose additional computational costs and prohibit a wide application of current methods.
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Efficient network inference is one of the challenges of current-day biology. Its application to the study of development has seen noteworthy success, yet a multicellular context, tissue growth, and cellular rearrangements impose additional computational costs and prohibit a wide application of current methods. Therefore, reducing computational cost and providing quick feedback at intermediate stages are desirable features for network inference. Here we propose a hybrid approach composed of two stages: exploration with scatter search and exploitation of intermediate solutions with low temperature simulated annealing. We test the approach on the well-understood process of early body plan development in flies, focusing on the gap gene network. We compare the hybrid approach to simulated annealing, a method of network inference with a proven track record. We find that scatter search performs well at exploring parameter space and that low temperature simulated annealing refines the intermediate results into excellent model fits. From this we conclude that for poorly-studied developmental systems, scatter search is a valuable tool for exploration and accelerates the elucidation of gene regulatory networks. Full article
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Open AccessArticle
An Information Technology Framework for the Development of an Embedded Computer System for the Remote and Non-Destructive Study of Sensitive Archaeology Sites
Computation 2017, 5(2), 21; doi:10.3390/computation5020021 -
Abstract
The paper proposes an information technology framework for the development of an embedded remote system for non-destructive observation and study of sensitive archaeological sites. The overall concept and motivation are described. The general hardware layout and software configuration are presented. The paper concentrates
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The paper proposes an information technology framework for the development of an embedded remote system for non-destructive observation and study of sensitive archaeological sites. The overall concept and motivation are described. The general hardware layout and software configuration are presented. The paper concentrates on the implementation of the following informational technology components: (a) a geographically unique identification scheme supporting a global key space for a key-value store; (b) a common method for octree modeling for spatial geometrical models of the archaeological artifacts, and abstract object representation in the global key space; (c) a broadcast of the archaeological information as an Extensible Markup Language (XML) stream over the Web for worldwide availability; and (d) a set of testing methods increasing the fault tolerance of the system. This framework can serve as a foundation for the development of a complete system for remote archaeological exploration of enclosed archaeological sites like buried churches, tombs, and caves. An archaeological site is opened once upon discovery, the embedded computer system is installed inside upon a robotic platform, equipped with sensors, cameras, and actuators, and the intact site is sealed again. Archaeological research is conducted on a multimedia data stream which is sent remotely from the system and conforms to necessary standards for digital archaeology. Full article
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Open AccessArticle
Detecting Perturbed Subpathways towards Mouse Lung Regeneration Following H1N1 Influenza Infection
Computation 2017, 5(2), 20; doi:10.3390/computation5020020 -
Abstract
It has already been established by the systems-level approaches that the future of predictive disease biomarkers will not be sketched by plain lists of genes or proteins or other biological entities but rather integrated entities that consider all underlying component relationships. Towards this
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It has already been established by the systems-level approaches that the future of predictive disease biomarkers will not be sketched by plain lists of genes or proteins or other biological entities but rather integrated entities that consider all underlying component relationships. Towards this orientation, early pathway-based approaches coupled expression data with whole pathway interaction topologies but it was the recent approaches that zoomed into subpathways (local areas of the entire biological pathway) that provided more targeted and context-specific candidate disease biomarkers. Here, we explore the application potential of PerSubs, a graph-based algorithm which identifies differentially activated disease-specific subpathways. PerSubs is applicable both for microarray and RNA-Seq data and utilizes the Kyoto Encyclopedia of Genes and Genomes (KEGG) database as reference for biological pathways. PerSubs operates in two stages: first, identifies differentially expressed genes (or uses any list of disease-related genes) and in second stage, treating each gene of the list as start point, it scans the pathway topology around to build meaningful subpathway topologies. Here, we apply PerSubs to investigate which pathways are perturbed towards mouse lung regeneration following H1N1 influenza infection. Full article
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Open AccessArticle
Esoteric Twist: An Efficient in-Place Streaming Algorithmus for the Lattice Boltzmann Method on Massively Parallel Hardware
Computation 2017, 5(2), 19; doi:10.3390/computation5020019 -
Abstract
We present and analyze the Esoteric Twist algorithm for the Lattice Boltzmann Method. Esoteric Twist is a thread safe in-place streaming method that combines streaming and collision and requires only a single data set. Compared to other in-place streaming techniques, Esoteric Twist minimizes
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We present and analyze the Esoteric Twist algorithm for the Lattice Boltzmann Method. Esoteric Twist is a thread safe in-place streaming method that combines streaming and collision and requires only a single data set. Compared to other in-place streaming techniques, Esoteric Twist minimizes the memory footprint and the memory traffic when indirect addressing is used. Esoteric Twist is particularly suitable for the implementation of the Lattice Boltzmann Method on Graphic Processing Units. Full article
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Open AccessArticle
An Accurate Computational Tool for Performance Estimation of FSO Communication Links over Weak to Strong Atmospheric Turbulent Channels
Computation 2017, 5(1), 18; doi:10.3390/computation5010018 -
Abstract
The terrestrial optical wireless communication links have attracted significant research and commercial worldwide interest over the last few years due to the fact that they offer very high and secure data rate transmission with relatively low installation and operational costs, and without need
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The terrestrial optical wireless communication links have attracted significant research and commercial worldwide interest over the last few years due to the fact that they offer very high and secure data rate transmission with relatively low installation and operational costs, and without need of licensing. However, since the propagation path of the information signal, i.e., the laser beam, is the atmosphere, their effectivity affects the atmospheric conditions strongly in the specific area. Thus, system performance depends significantly on the rain, the fog, the hail, the atmospheric turbulence, etc. Due to the influence of these effects, it is necessary to study, theoretically and numerically, very carefully before the installation of such a communication system. In this work, we present exactly and accurately approximate mathematical expressions for the estimation of the average capacity and the outage probability performance metrics, as functions of the link’s parameters, the transmitted power, the attenuation due to the fog, the ambient noise and the atmospheric turbulence phenomenon. The latter causes the scintillation effect, which results in random and fast fluctuations of the irradiance at the receiver’s end. These fluctuations can be studied accurately with statistical methods. Thus, in this work, we use either the lognormal or the gamma–gamma distribution for weak or moderate to strong turbulence conditions, respectively. Moreover, using the derived mathematical expressions, we design, accomplish and present a computational tool for the estimation of these systems’ performances, while also taking into account the parameter of the link and the atmospheric conditions. Furthermore, in order to increase the accuracy of the presented tool, for the cases where the obtained analytical mathematical expressions are complex, the performance results are verified with the numerical estimation of the appropriate integrals. Finally, using the derived mathematical expression and the presented computational tool, we present the corresponding numerical results, using common parameter values for realistic terrestrial free space optical communication systems. Full article
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Open AccessArticle
Evaluation of Soil-Structure Interaction on the Seismic Response of Liquid Storage Tanks under Earthquake Ground Motions
Computation 2017, 5(1), 17; doi:10.3390/computation5010017 -
Abstract
Soil-structure interaction (SSI) could affect the seismic response of structures. Since liquid storage tanks are vital structures and must continue their operation under severe earthquakes, their seismic behavior should be studied. Accordingly, the seismic response of two types of steel liquid storage tanks
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Soil-structure interaction (SSI) could affect the seismic response of structures. Since liquid storage tanks are vital structures and must continue their operation under severe earthquakes, their seismic behavior should be studied. Accordingly, the seismic response of two types of steel liquid storage tanks (namely, broad and slender, with aspect ratios of height to radius equal to 0.6 and 1.85) founded on half-space soil is scrutinized under different earthquake ground motions. For a better comparison, the six considered ground motions are classified, based on their pulse-like characteristics, into two groups, named far and near fault ground motions. To model the liquid storage tanks, the simplified mass-spring model is used and the liquid is modeled as two lumped masses known as sloshing and impulsive, and the interaction of fluid and structure is considered using two coupled springs and dashpots. The SSI effect, also, is considered using a coupled spring and dashpot. Additionally, four types of soils are used to consider a wide variety of soil properties. To this end, after deriving the equations of motion, MATLAB programming is employed to obtain the time history responses. Results show that although the SSI effect leads to a decrease in the impulsive displacement, overturning moment, and normalized base shear, the sloshing (or convective) displacement is not affected by such effects due to its long period. Full article
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Open AccessArticle
Simplification of Reaction Networks, Confluence and Elementary Modes
Computation 2017, 5(1), 14; doi:10.3390/computation5010014 -
Abstract
Reaction networks can be simplified by eliminating linear intermediate species in partial steadystates. Inthispaper,westudythequestionwhetherthisrewriteprocedureisconfluent,so that for any given reaction network with kinetic constraints, a unique normal form will be obtained independently of the elimination order. We first show that confluence fails for the
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Reaction networks can be simplified by eliminating linear intermediate species in partial steadystates. Inthispaper,westudythequestionwhetherthisrewriteprocedureisconfluent,so that for any given reaction network with kinetic constraints, a unique normal form will be obtained independently of the elimination order. We first show that confluence fails for the elimination of intermediates even without kinetics, if “dependent reactions” introduced by the simplification are not removed. This leads us to revising the simplification algorithm into a variant of the double description method for computing elementary modes, so that it keeps track of kinetic information. Folklore results on elementary modes imply the confluence of the revised simplification algorithm with respect to the network structure, i.e., the structure of fully simplified networks is unique. We show, however, that the kinetic rates assigned to the reactions may not be unique, and provide a biological example where two different simplified networks can be obtained. Finally, we give a criterion on the structure of the initial network that is sufficient to guarantee the confluence of both the structure and the kinetic rates. Full article
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Open AccessArticle
A Hybrid Computation Model to Describe the Progression of Multiple Myeloma and Its Intra-Clonal Heterogeneity
Computation 2017, 5(1), 16; doi:10.3390/computation5010016 -
Abstract
Multiplemyeloma(MM)isageneticallycomplexhematologicalcancerthatischaracterized by proliferation of malignant plasma cells in the bone marrow. MM evolves from the clonal premalignant disorder monoclonal gammopathy of unknown significance (MGUS) by sequential genetic changes involving many different genes, resulting in dysregulated growth of multiple clones of plasma cells. The
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Multiplemyeloma(MM)isageneticallycomplexhematologicalcancerthatischaracterized by proliferation of malignant plasma cells in the bone marrow. MM evolves from the clonal premalignant disorder monoclonal gammopathy of unknown significance (MGUS) by sequential genetic changes involving many different genes, resulting in dysregulated growth of multiple clones of plasma cells. The migration, survival, and proliferation of these clones require the direct and indirect interactions with the non-hematopoietic cells of the bone marrow. We develop a hybrid discrete-continuous model of MM development from the MGUS stage. The discrete aspect of the modelisobservedatthecellularlevel: cellsarerepresentedasindividualobjectswhichmove,interact, divide, and die by apoptosis. Each of these actions is regulated by intracellular and extracellular processes as described by continuous models. The hybrid model consists of the following submodels that have been simplified from the much more complex state of evolving MM: cell motion due to chemotaxis, intracellular regulation of plasma cells, extracellular regulation in the bone marrow, and acquisition of mutations upon cell division. By extending a previous, simpler model in which the extracellular matrix was considered to be uniformly distributed, the new hybrid model provides a more accurate description in which cytokines are produced by the marrow microenvironment and consumed by the myeloma cells. The complex multiple genetic changes in MM cells and the numerous cell-cell and cytokine-mediated interactions between myeloma cells and their marrow microenviroment are simplified in the model such that four related but evolving MM clones can be studied as they compete for dominance in the setting of intraclonal heterogeneity. Full article
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Open AccessFeature PaperArticle
Schrödinger Theory of Electrons in Electromagnetic Fields: New Perspectives
Computation 2017, 5(1), 15; doi:10.3390/computation5010015 -
Abstract
The Schrödinger theory of electrons in an external electromagnetic field is described from the new perspective of the individual electron. The perspective is arrived at via the time-dependent “Quantal Newtonian” law (or differential virial theorem). (The time-independent law, a special case, provides a
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The Schrödinger theory of electrons in an external electromagnetic field is described from the new perspective of the individual electron. The perspective is arrived at via the time-dependent “Quantal Newtonian” law (or differential virial theorem). (The time-independent law, a special case, provides a similar description of stationary-state theory). These laws are in terms of “classical” fields whose sources are quantal expectations of Hermitian operators taken with respect to the wave function. The laws reveal the following physics: (a) in addition to the external field, each electron experiences an internal field whose components are representative of a specific property of the system such as the correlations due to the Pauli exclusion principle and Coulomb repulsion, the electron density, kinetic effects, and an internal magnetic field component. The response of the electron is described by the current density field; (b) the scalar potential energy of an electron is the work done in a conservative field. It is thus path-independent. The conservative field is the sum of the internal and Lorentz fields. Hence, the potential is inherently related to the properties of the system, and its constituent property-related components known. As the sources of the fields are functionals of the wave function, so are the respective fields, and, therefore, the scalar potential is a known functional of the wave function; (c) as such, the system Hamiltonian is a known functional of the wave function. This reveals the intrinsic self-consistent nature of the Schrödinger equation, thereby providing a path for the determination of the exact wave functions and energies of the system; (d) with the Schrödinger equation written in self-consistent form, the Hamiltonian now admits via the Lorentz field a new term that explicitly involves the external magnetic field. The new understandings are explicated for the stationary state case by application to two quantum dots in a magnetostatic field, one in a ground state and the other in an excited state. For the time-dependent case, the evolution of the same states of the quantum dots in both a magnetostatic and a time-dependent electric field is described. In each case, the satisfaction of the corresponding “Quantal Newtonian” law is demonstrated. Full article
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Open AccessArticle
Aerodynamic Performance of a NREL S809 Airfoil in an Air-Sand Particle Two-Phase Flow
Computation 2017, 5(1), 13; doi:10.3390/computation5010013 -
Abstract
This paper opens up a new perspective on the aerodynamic performance of a wind turbine airfoil. More specifically, the paper deals with a steady, incompressible two-phase flow, consisting of air and two different concentrations of sand particles, over an airfoil from the National
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This paper opens up a new perspective on the aerodynamic performance of a wind turbine airfoil. More specifically, the paper deals with a steady, incompressible two-phase flow, consisting of air and two different concentrations of sand particles, over an airfoil from the National Renewable Energy Laboratory, NREL S809. The numerical simulations were performed on turbulence models for aerodynamic operations using commercial computational fluid dynamics (CFD) code. The computational results obtained for the aerodynamic performance of an S809 airfoil at various angles of attack operating at Reynolds numbers of Re = 1 × 106 and Re = 2 × 106 in a dry, dusty environment were compared with existing experimental data on air flow over an S809 airfoil from reliable sources. Notably, a structured mesh consisting of 80,000 cells had already been identified as the most appropriate for numerical simulations. Finally, it was concluded that sand concentration significantly affected the aerodynamic performance of the airfoil; there was an increase in the values of the predicted drag coefficients, as well as a decrease in the values of the predicted lift coefficients caused by increasing concentrations of sand particles. The region around the airfoil was studied by using contours of static pressure and discrete phase model (DPM) concentration. Full article
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Open AccessArticle
Numerical Modelling of Double-Steel Plate Composite Shear Walls
Computation 2017, 5(1), 12; doi:10.3390/computation5010012 -
Abstract
Double-steel plate concrete composite shear walls are being used for nuclear plants and high-rise buildings. They consist of thick concrete walls, exterior steel faceplates serving as reinforcement and shear connectors, which guarantee the composite action between the two different materials. Several researchers have
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Double-steel plate concrete composite shear walls are being used for nuclear plants and high-rise buildings. They consist of thick concrete walls, exterior steel faceplates serving as reinforcement and shear connectors, which guarantee the composite action between the two different materials. Several researchers have used the Finite Element Method to investigate the behaviour of double-steel plate concrete walls. The majority of them model every element explicitly leading to a rather time-consuming solution, which cannot be easily used for design purposes. In the present paper, the main objective is the introduction of a three-dimensional finite element model, which can efficiently predict the overall performance of a double-steel plate concrete wall in terms of accuracy and time saving. At first, empirical formulations and design relations established in current design codes for shear connectors are evaluated. Then, a simplified finite element model is used to investigate the nonlinear response of composite walls. The developed model is validated using results from tests reported in the literature in terms of axial compression and monotonic, cyclic in-plane shear loading. Several finite element modelling issues related to potential convergence problems, loading strategies and computer efficiency are also discussed. The accuracy and simplicity of the proposed model make it suitable for further numerical studies on the shear connection behaviour at the steel-concrete interface. Full article
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