Computer Model

The lattice Boltzmann method is an important technique for the numerical solution of partial differential equations because it has nearly ideal scalability on parallel computers for many applications. However, to achieve the scalability and speed potential of the lattice Boltzmann technique, the issues of data reusability in cache-based computer architectures must be addressed. Utilizing the two-dimensional diffusion equation, T t = µ(T xx + T yy), this paper examines cache optimization for the lattice Boltzmann method in both serial and parallel implementations. In this study, speedups due to cache optimization were found to be 1.9-2.5 for the serial implementation and 3.6-3.8 for the parallel case in which the domain decomposition was optimized for stride-one access. In the parallel non-cached implementation, the method of domain decomposition (horizontal or vertical) used for parallelization did not significantly affect the compute time. In contrast, the cache-based implementation of the lattice Boltzmann method was significantly faster when the domain decomposition was optimized for stride-one access. Additionally, the cache-optimized lattice Boltzmann method in which the domain decomposition was optimized for stride-one access displayed superlinear scalability on all problem sizes as the number of processors was increased.

On the basis of Eu's generalized hydrodynamics, a computational model is developed for the numerical simulation of rarefied and microscale diatomic gas flows. The rotational nonequilibrium effect is taken into account by introducing excess normal stress associated with the bulk viscosity of the gas. The computational model for diatomic gases reduces to the model for monatomic gases in the limit of vanishing bulk viscosity. The thermodynamically consistent computational model is applied to the one-dimensional shock wave structure and the two-dimensional hypersonic rarefied flow around a blunt body in order to demonstrate its capability and validate the numerical results. The general properties of the constitutive equations are also presented through a simple analysis. The numerical results show that the new generalized hydrodynamic computational model yields the solutions in qualitative agreement with experimental data and DSMC results in the case of the problems studied.

In this paper we examine the different formulations of Gillespie’s stochastic simulation algorithm (SSA) [D. Gillespie, J. Phys. Chem. 81, 2340 (1977)] with respect to computational efficiency, and propose an optimization to improve the efficiency of the direct method. Based on careful timing studies and an analysis of the time-consuming operations, we conclude that for most practical problems the optimized direct method is the most efficient formulation of SSA. This is in contrast to the widely held belief that Gibson and Bruck’s next reaction method [M. Gibson and J. Bruck, J. Phys. Chem. A 104, 1876 (2000)] is the best way to implement the SSA for large systems. Our analysis explains the source of the discrepancy.

Consciousness is a key feature of mammalian cognition and revealing its underlying mechanisms is one of the most important scientific challenges for the 21st century. In this article I review how computational and theoretical approaches can facilitate a transition from correlation to explanation in consciousness science. I describe progress towards identifying 'explanatory correlates' underlying four fundamental properties characterizing most if not all conscious experiences: (i) the coexistence of segregation and integration in conscious scenes, (ii) the emergence of a subjective first-person perspective, (iii) the presence of affective conscious contents, either transiently (emotion) or as a background (mood) and (iv) experiences of intention and agency that are characteristic of voluntary action. I also discuss how synthetic approaches can shed additional light on possible functions of consciousness, the role of embodiment in consciousness, and the plausibility of constructing a conscious artefact. Keywords Consciousness Á Explanatory correlate Á Causal density Á Complexity Á Perspectivalness Á Emotion Á Volition Á Computational model Á Selfhood Á Emergence Invited article for inaugural issue of Cognitive Computation.

Consciousness is a key feature of mammalian cognition and revealing its underlying mechanisms is one of the most important scientific challenges for the 21st century. In this article I review how computational and theoretical approaches can facilitate a transition from correlation to explanation in consciousness science. I describe progress towards identifying 'explanatory correlates' underlying four fundamental properties characterizing most if not all conscious experiences: (i) the coexistence of segregation and integration in conscious scenes, (ii) the emergence of a subjective first-person perspective, (iii) the presence of affective conscious contents, either transiently (emotion) or as a background (mood) and (iv) experiences of intention and agency that are characteristic of voluntary action. I also discuss how synthetic approaches can shed additional light on possible functions of consciousness, the role of embodiment in consciousness, and the plausibility of constructing a conscious artefact. Keywords Consciousness Á Explanatory correlate Á Causal density Á Complexity Á Perspectivalness Á Emotion Á Volition Á Computational model Á Selfhood Á Emergence Invited article for inaugural issue of Cognitive Computation.

Background: Because BRCA gene mutation testing is costly, occasionally uninformative, and frequently associated with ethical and legal issues, careful patient selection is required prior to testing. Estimation of BRCA gene mutation probability is an important component of pretest counseling, but the accuracy of these estimates is currently unknown. We measured the performance of eight cancer risk counselors and of a computer model, BRCAPRO, at identifying families likely to carry a BRCA gene mutation. Methods: Eight cancer risk counselors and the computer model BRCAPRO estimated BRCA gene mutation probabilities for 148 pedigrees selected from an initial sample of 272 pedigrees. The final sample was limited to pedigrees with a proband affected by breast or ovarian cancer and BRCA1 and BRCA2 gene sequencing results unequivocally reported as negative or positive for a deleterious mutation. Sensitivity, specificity, negative predictive value, positive predictive value, and areas under receiver operator characteristics (ROC) curves were calculated for each risk counselor and for BRCAPRO. All statistical tests were two sided. Results: Using a greater-than-10% BRCA gene mutation probability threshold, the median sensitivity for identifying mutation carriers was 94% (range = 81% to 98%) for the eight risk counselors and 92% (range = 91% to 92%) for BRCAPRO. Median specificity at this threshold was 16% (range = 6% to 34%) for the risk counselors and 32% (range = 30% to 34%) for BRCAPRO (P = .04). Median area under the ROC curves was 0.671 for the risk counselors (range = 0.620 to 0.717) and 0.712 (range = 0.706 to 0.720) for BRCAPRO (P = .04). There was a slight, but not statistically significant, improvement in all counselor performance measures when BRCAPRO-assigned gene mutation probability information was included with the pedigrees. Conclusions: Sensitivity for identifying BRCA gene mutation carriers is similar for experienced risk counselors and the computer model BRCAPRO. Because the computer model consistently demonstrated superior specificity, overall discrimination between BRCA gene mutation carriers and BRCA gene mutation noncarriers was slightly better for BRCAPRO. [

Laser spark phenomena are studied in air and ammonia-oxygen mixtures by the use of a two-dimensional, axially-symmetric, time-accurate computational fluid dynamic model. The initial laser spark temperature distribution is generated to simulate a post-breakdown profile that is consistent with theoretical, experimental, and computational investigations for a nominal 10-ns optical breakdown laser pulse. Thermodynamic properties of various species are extended to

The findings in this report are not to be construed as an official Department of the Army position unless so designated by other authorized documents. The contents of this report are not to be used for advertising, publication, or promotional purposes. Citation of trade names does not constitute an official endorsement or approval of the use of such commercial products.

In this paper, I analyze how the auditory system works when exposed to different kinds of music components, such as melodies, harmonies, the mere successions of sounds, and the ordinary simultaneities of sounds. I will claim that, while melodies and harmonies are perceivable, the mere successions of sounds and the ordinary simultaneities of sounds are processed at the cognitive level. This conclusion is based on the analysis of how the auditory system employs primitive grouping, schema-based grouping, and cognitive schema-based grouping when ordering the auditory landscape by the identification and categorization of meaningful musical streams.

Depressions impose a huge burden on both the patient suffering from a depression as well as society in general. In order to make interventions for a depressed patient during a therapy more personalized and effective, a supporting personal software agent can be useful. Such an agent should then have a good idea of the current state of the person. A computational model for human mood regulation and depression has been developed in previous work, but in order for the agent to give optimal support during an intervention, it should also have knowledge on the precise functioning of the intervention in relation with the mood regulation and depression. This paper therefore presents computational models for these interventions for different types of therapy. Simulation results are presented showing that the mood regulation and depression indeed follow the expected patterns when applying these therapies. The intervention models have been evaluated for a variety of patient types by simulation experiments and formal verification.

Background: Compared with static imaging, dynamic emission computed tomographic imaging with compartment modeling can quantify in vivo physiologic processes, providing useful information about molecular disease processes. Dynamic imaging involves estimation of kinetic rate parameters. For multi-compartment models, kinetic parameter estimation can be computationally demanding and problematic with local minima. Methods: This paper offers a new perspective to the compartment model fitting problem where Fourier linear system theory is applied to derive closed-form formulas for estimating kinetic parameters for the two-compartment model. The proposed Fourier domain estimation method provides a unique solution, and offers very different noise response as compared to traditional non-linear chi-squared minimization techniques. Results: The unique feature of the proposed Fourier domain method is that only low frequency components are used for kinetic parameter estimation, where the DC (i.e., the zero frequency) component in the data is treated as the most important information, and high frequency components that tend to be corrupted by statistical noise are discarded. Computer simulations show that the proposed method is robust without having to specify the initial condition. The resultant solution can be fine tuned using the traditional iterative method. Conclusions: The proposed Fourier-domain estimation method has closed-form formulas. The proposed Fourier-domain curve-fitting method does not require an initial condition, it minimizes a quadratic objective function and a closed-form solution can be obtained. The noise is easier to control, simply by discarding the high frequency components, and emphasizing the DC component.

The parameters of a given ͑chaotic͒ dynamical model are estimated from scalar time series by adapting a computer model until it synchronizes with the given data. This parameter identification method is applied to numerically generated and experimental data from Chua's circuit. ͓S1063-651X͑96͒12912-3͔

In this paper, we describe a concatenative synthesis sys- tem which was first designed for a realistic synthesis of melodic phrases. It has since been augmented to become an experimental TTS (Text-to-Speech) synthesizer. To- day, it is able to realize hybrid synthesis involving speech segments and musical excerpts coming from any record- ing imported in its database. The system can also synthe- size sentences with different voices, sentences with mu- sical sounds, melodic phrases with speech segments and generate compositional material from specific intonation patterns using a prosodic pattern extractor.

A dvanced combustion research is essential to designing more efficient engines. Nextgeneration engines will operate in nonconventional, mixed-mode, and turbulent conditions. Combustion processes in such an environment, combined with new physical and chemical fuel properties, feature complicated interactions that are poorly understood at a fundamental level. Recently, Sandia National Laboratories scientists have instrumented their simulations with particles to capture and better understand the turbulent dynamics in combustion processes. So, how to analyze and visualize these particles' temporal behaviors from different aspects is critical to understanding combustion. When visualizing a large number of moving particles, we confront two main issues. The first is what properties of the particle data to visualize; the other is how to deal with the large data. To conduct a comprehensive study of particle behaviors, a visualization system must be able to present the temporal

A computational model of pricing and profitability in the Queensland sugar industry is applied to a comparative analysis of likely alternative industry structures that may arise in the wake of industry fefonn. Implementation of proposals suggested by the sugar industry review working party and in some of the submissions to it are also examined. The model is a simple static optimisation model of the trade in sugarcane in a local mill area. Numerical results are presented to compare prices and profitability for both a representative mill and growers in a monopsony situation. a contestable market. and under the current institutional arrangement. The results indicate that although deregulation has the potential to lead to improved welfare for both growers and the mills. this will only be the case if mills price competitively, i.e. in the contestable market case where the threat of competition from neighbouring and competing mills is sufficient to force the incumbent mill to pay for cane at a competitive price to prevent the entry of potential competitors.

The relationship between equilibrium convergence to a uniform quality distribution and price is investigated in the Q-model, a self-organizing, evolutionary computational matching model of a fixed-price post-secondary higher education system created by ...

This paper describes the application of eight statistical and machine-learning methods to derive computer models for predicting mortality of hospital patients with pneumonia from their finadings at initial presentation. The eight models were each constructed based on 9847 patient cases and they were each evaluated on 4352 additional cases. The primary evaluation metric was the error in predicted survival as a function of the fraction of patients predicted to survive. This metric is useful in assessing a model's potential to assist a clinician in deciding whether to treat a given patient in the hospital or at home.

Analytical and numerical solutions are presented, describing dynamics and fracture of composite metal-fabric armour penetrated by small projectiles (bullets and fragments). Comparison of one-dimensional and spatial axisymmetric models for nonlinear dynamics of a ply is conducted and their capabilities for practical calculations are discussed. A computer model for spatial dynamics of composite armour is described as a basis for a calculation tool specially designed to simulate penetration processes in actual metal/fabrics shields. Residual parameters of the projectile after perforation of the primary metal armour are obtained on the basis of experimental data processing and energy considerations. Comparison of calculation results with test data for actual steel-kevlar shields produced by the Israeli Military Industries Co. shows sufficient applicability of the tool.

The International Institute for Applied Systems Analysis has undertaken a study of the use of risk analysis in siting liquefied energy gas facilities in four countries: the Federal Republic of Germany, the Netherlands, the United Kingdom, and the United States. The work on which the present paper is based was part of this larger study. The authors of this paper have devised a descriptive framework for the issues raised by siting large-scale technological facilities, and have illustrated its concepts by applying them to an LNG siting process in California. They also suggest ways of using analytical methods to improve both the interaction process among the interested parties and the outcome of the siting debate. Their ideas are in the spirit of the research that IIASA is presently carrying out on the role of analysts in the policymaking process. Thus, this paper not only contributes to the Institute's work on the problems of risk but also has somewhat broader implications.

Potassium ion (K +) kinetics in intra and extracellular compartments during hemodialysis was studied by means of a double-pool computer model which included potassium-dependent active transport (Na-K-ATPase pump) in thirty-four patients (21M/13F; aged 66 ± 22 years old, dry weight 68 ± 18 kg, height 160 ± 15 cm) on renal replacement therapy with thrice weekly 4 hour double-needle hemodialysis. Each patient was studied during acetate free biofiltration (AFB) with a constant K + dialysate concentration (K CONST therapy) and with a timevarying (profiled) K + dialysate concentration (K PROF therapy). The two therapies induced different levels of K + plasma concentration (K CONST : 3.6±0.8 vs. K PROF : 4.0±0.7 mmol/L, time-averaged values, p<0.01). The computer model was tuned to accurately fit plasmatic K + measured in the course of K CONST and K PROF therapies and was then used to simulate the kinetics of intra and extracellular K +. Model-based analysis showed that almost all the K + removal in the first 90 minutes of dialysis was mainly derived from the extracellular compartment. The different K + time course in the dialysate and the consequently different Na-K pump activity resulted in a different sharing of removed potassium mass at the end of dialysis: 55±17% from the extracellular compartment in K + PROF vs. 41±14% in K + CONST. These results suggest that the Na-K pump plays a major role in K + apportionment between extracellular and intracellular compartments, and potassium dialysate concentration strongly influences pump activity. For this reason the computer-model here presented may represent a useful tool to quantitatively assess the impact of dialysate potassium on K + kinetics in intra and extracellular compartments and to design dialysate potassium content tailored to the patient's needs.

Several mutations of the gene encoding for the cardiac sodium channel (SCN5A) are associated with Congenital Brugada syndrome (BrS), but the assessment of their functional consequences with the experimental models is biased by technical limitations. To overcome such limitations we used a novel approach combining in vitro data and computer modeling. The Y1795H mutation of SCN5A was evaluated. A Markovian model capable to reproduce the kinetics of both wild type (WT) and mutant channels was incorporated into the Luo-Rudy comprehensive model of ventricular cells. Here presented results highlight the high sensitivity of simulated AP of virtual transgenic cells to the maximum conductance assigned to the sodium current in mutant channel model. A value of about 10000 S/F allows the reproduction of coherent action potentials in WT and mutant cells.

A computer model of pressure response to hemodialysis-induced hypovolemia is reported. Heart rate and hematocrit, measured in the course of hemodialysis, are imposed as computer model inputs and the model computes the arterial pressure response after tuning model parameters representative of patient's cardiovascular reactivity. Computer model reproduced with good accuracy experimental data (arterial pressure, cardiac output and total peripherical resistance). Parameter identification over successive sessions of the same patients revealed satisfactory reliability, providing a physiological interpretative key to patient's hemodynamic behavior during hemodialysis.

A new method of rapid pharmacophore fingerprinting (PharmPrint method) has been developed. A basis set of 10 549 three-point pharmacophores has been constructed by enumerating several distance ranges and pharmacophoric features. Software has been developed to assign pharmacophoric types to atoms in chemical structures, generate multiple conformations, and construct the binary fingerprint according to the pharmacophores that result. The fingerprint is used as a descriptor for developing a quantitative structureactivity relationship (QSAR) model using partial least squares. An example is given using sets of ligands for the estrogen receptor (ER). The result is compared with previously published results on the same data to show the superiority of a full 3D, conformationally flexible approach. The QSAR model can be readily interpreted in structural/chemical terms. Further examples are given using binary activity data and some of our novel in-house compounds, which show the value of the model when crossing compound classes.

We introduce a variational principle suitable for the computational modeling of crystalline materials. We consider a class of materials that are described by non-quasiconvex variational integrals. We are further focused on equlibria of such materials that have non-attainment structure, i.e., Dirichlet boundary conditions prohibit these variational integrals from attaining their infima. Consequently, the equilibrium is described by probablity distributions. The new variational principle provides the possibility to use standard optimization tools to achieve stochastic equilibrium states starting from given initial deterministic states. 1I NTRODUCTION Recently, there has been a great deal of research into the modeling and use of so-called Smart Materials. These materials have the ability to undergo internal physical transformations, which may be used to do work in ways and places that traditional engineering materials cannot. Such new materials include composites, ceramics, liquid crystals, biomaterials, ferromagnetics and shape memory alloys. Advances in micro-machines, damping mechanisms, high-resolution displays and superconductors are a few of the applications for which they are being designed. These materials are singled out by their unique ability to undergo a temperature dependent crystalline phase transformation, known as the Martensitic Transformation. At higher temperatures Shape Memory Alloys exhibit a stiff, cubic crystalline lattice structure known as the Austenitic phase. In lower temperatures, these alloys change to exhibit a more easily deformable tetragonal lattice structure, having many crystallographically equivalent states. The reason for the name comes from the process where, if one begins by establishing a reference configuration in the Austenitic phase, then cools

We consider a class of alloys and ceramics with equilibria described by non-attainable infima of non-quasiconvex variational integrals. Such situations frequently arise when atomic lattice structure plays an important role at the mesoscopic continuum level. We prove that standard variational approaches associated with gradient based relaxation of non-quasiconvex integrals in Banach or Hilbert spaces are not capable of generating relaxing sequences for problems with non-attainable structure. We introduce a variational principle suitable for the computational purposes of approaching non-attainable infima of variational integrals. We demonstrate that this principle is suitable for direct calculations of the Young Measures on a computational example in one dimension. The new variational principle provides the possibility to approximate crystalline microstructures using a Fokker-Planck equation at the meso-scale. We provide an example of such a construction.

Through a mathematical and computational model of the physical behavior of shape memory alloy wires, this study shows that localized heating and cooling of such materials provide an effective means of damping vibrational energy. The thermally induced pseudo-elastic behavior of a shape memory wire is modeled using a continuum thermodynamic model and solved computationally as described by the authors in [23]. Computational experiments confirm that up to 80% of an initial shock of vibrational energy can be eliminated at the onset of a thermally-induced phase transformation through the use of spatially-distributed transformation regions along the length of a shape memory alloy wire.

This paper introduces a system that simulates the transition from the one-word stage to the two-word stage in child language production. Two-word descriptions are syntactically generated and compete against one-word descriptions from the outset. Two-word descriptions ...

A computational model has been used to infer rules governing dendritic growth of layer 2 / 3 associative pyramidal neurons in a rat model of foetal alcohol syndrome. Basal dendrites were studied in adult rats exposed to ethanol during the first postnatal week. Results suggest that ethanol exposure during early postnatal life affects mainly the branching of dendrites rather than their elongation.

Microtubules (MTs) are cytoskeletal polymers that exhibit dynamic instability, the random alternation between growth and shrinkage. MT dynamic instability plays an essential role in cell development, division, and motility. To investigate dynamic instability, simulation models have been widely used. However, conditions under which the concentration of free tubulin fluctuates as a result of growing or shrinking MTs have not been studied before. Such conditions can arise, for example, in small compartments, such as neuronal growth cones. Here we investigate by means of computational modeling how concentration fluctuations caused by growing and shrinking MTs affect dynamic instability. We show that these fluctuations shorten MT growth and shrinkage times and change their distributions from exponential to non-exponential, gamma-like. Gamma-like distributions of MT growth and shrinkage times, which allow optimal stochastic searching by MTs, have been observed in various cell types and are believed to require structural changes in the MT during growth or shrinkage. Our results, however, show that these distributions can already arise as a result of fluctuations in the concentration of free tubulin due to growing and shrinking MTs. Such fluctuations are possible not only in small compartments but also when tubulin diffusion is slow or when many MTs (de)polymerize synchronously. Volume and all other factors that influence these fluctuations can affect MT dynamic instability and, consequently, the processes that depend on it, such as neuronal growth cone behavior and cell motility in general.

We present a reinforcement learning model of gaze following that learns to incorporate eye cues in a developmental trajectory similar to that found in infants: older infants follow gaze more frequently when both the caregiver's eyes and head are turned than when only her head is turned. Similarly, infants learn to follow gaze less when the caregiver's eyes are closed than when her eyes are open. The model works through the maximization of visual reward, and not by representing an estimate of the other person's attentional state, as would be expected by adherents of a mentalist interpretation of gaze following. Within the debate about the age of onset in the use of eye cues for gaze following, we hypothesize that eye cues have an effect as soon as the infant learns to follow gaze, but at first it might be small and therefore difficult to measure. Finally, we propose this learning approach for modeling other aspects of theory of mind.

Background. The optimal closure technique of median sternotomy remains controversial. The objective of this study was to analyze the structural response of the separated sternum using computer-based numerical discretization techniques, such as finite element methods. Methods. Thoracic computer tomographic scans (2.5-mm slices) were segmented, analyzed by image processing techniques, and transferred into a three-dimensional finite element model. In a first approach a linear elastic material model was used; neglecting nonlinear and damage effects of the bones. The influence of muscles and tendons was disregarded. Nonlinear contact conditions were applied between the two sternal parts and between fixation wires and sternum. The structural response of this model was investigated under normal breathing and asymmetric leaning on one side of the chest. Displacement and stress response of the segmented sternum were compared regarding two different closure techniques (single loop, figure-of-eight). Results. The obtained results revealed that for the normal breathing load case the single loop technique is capable of clamping the sternum sufficiently, assuming that the wires are prestressed. For asymmetric loading conditions, such as leaning on one side of the chest, the figure-of-eight loop can substantially reduce the relative longitudinal displacement between the two parts compared with the single loop. Conclusions. The application of numerical simulation techniques using complex computer models enabled the determination of structural behavior of the chest regarding the influence of different closure techniques. They allowed easy and fast modifications and therefore, in contrast to a real physical model, in-depth parameter studies.

An examination of how widely distributed and specialized activities of the brain are flexibly and effectively coordinated. A fundamental shift is occurring in neuroscience and related disciplines. In the past, researchers focused on functional specialization of the brain, discovering complex processing strategies based on convergence and divergence in slowly adapting anatomical architectures. Yet for the brain to cope with ever-changing and unpredictable circumstances, it needs strategies with richer interactive short-term dynamics. Recent research has revealed ways in which the brain effectively coordinates widely distributed and specialized activities to meet the needs of the moment. This book explores these findings, examining the functions, mechanisms, and manifestations of distributed dynamical coordination in the brain and mind across different species and levels of organization. The book identifies three basic functions of dynamic coordination: contextual disambiguation, dyna...

Formal Methods has been proven to improve software quality and provide a method of systematic software construction. However, it has yet to gain widespread acceptance in the software industry. In this paper we look at the benefits to be derived from the use of Formal Methods and examine the obstacles to widespread acceptance. We also introduce the Equivalent Transformation Language (ETL)-A formal specification language that we feel can help to overcome some of these obstacles. We explain how this can be done by first examining the mathematical foundation of the ETL and then demonstrate the capabilities of ETL by systematically constructing an ETL specification for the cell automaton "Life". Finally, we discuss the benefits of using ETL as a formal specification language.

This review covers the methods of computer simulation of protein interactions taking part in photosynthetic electron transport reactions. A direct multiparticle simulation method that simulates reactions describing interactions of ensembles of molecules in the heterogeneous interior of a cell is developed. In the models, protein molecules move according to the laws of Brownian dynamics, mutually orient themselves in the electrical field, and form complexes in the 3D scene. The method allows us to visualize the processes of molecule interactions and to calculate the rate constants for protein complex formation reactions in the solution and in the photosynthetic membrane. Three-dimensional multiparticle computer models for simulating the complex formation kinetics for plastocyanin with photosystem I and cytochrome bf complex, and ferredoxin with photosystem I and ferredoxin:NADP +-reductase are considered. Effects of ionic strength are featured for wild type and mutant proteins. The computer multiparticle models describe nonmonotonic dependences of complex formation rates on the ionic strength as the result of long-range electrostatic interactions.

We designed 3D multiparticle computer models to simulate diffusion and interactions of spinach plastocyanin and ferredoxin with plant photosystem 1 in a solution. Using these models we studied kinetic characteristics of plastocyanin-photosystem 1 and ferredoxin-photosystem 1 complex formation at a variety of ionic strength values. The computer multiparticle models demonstrate non-monotonic dependences of complex formation rates on the ionic strength as the result of long-range electrostatic interactions. Our calculations show that the decrease in the association second-order rate constant at low values of the ionic strength is caused by the protein pairs spending more time in "wrong" orientations which do not satisfy the docking conditions and so do not form the final complex capable of the electron transfer.

Several theoretical models have been proposed in the past for predicting the basic mechanical properties of thermally point bonded nonwovens from structural features of the constituents. However, the role of bond geometry, distribution and related fiber properties were not taken into account. We have developed a mechanics based model to help understand the behavior of point bonded materials as a

Learning affordances can be defined as learning action potentials, ie, learning that an object exhibiting certain regularities offers the possibility of performing a particular action. We propose a method to endow an agent with the capability of acquiring this knowledge by ...

In this paper, the seismic performance of reinforced concrete moment resisting frames coupled with a floor containing precast-prestressed units is examined. Mechanisms associated with the beam strength enhancement arising from plastic hinges and floor interactions are described. A computational model is set up to predict the response of a 3D frame containing precast-prestressed floor units with cast-in-situ concrete topping. This model contains newly developed plastic hinge elements which account for flexural, shear and elongation response of plastic hinges in beams subjected to inelastic rotation and varying axial load levels. To allow for floor interaction with the beam plastic hinges, the model uses axial strut-and-tie elements to represent the linking slab between the longitudinal beams and the first precast unit. Analysis using this model shows good agreement with the experimental results indicating that the model can be used to analyse the seismic performance of RC frames containing precast-prestressed flooring systems.

Population balances for simultaneous coagulation and breakage (and their analogs, e.g., polymerization and depolymerization) are employed in describing many systems (e.g., aerosols, powders and polymers), and many unit operations including reactors, crystallizers and size reduction=enlargement equipment. The population balance equations for homogeneous coagulation rate, power-law breakage rate and self-similar daughter particles are solved in moment form under a polynomial interpolative closure rule. Limiting steady-state analytical approximations for the distribution function of the very small particles are incorporated into basis sets enabling reconstruction of the distributions from their moments utilizing a nonlinear regression technique.

The paper presents an important part of the results of the OECD/NEA benchmark transient ‘Switching off one main circulation pump at nominal power’ analyzed by the coupled system code ATHLET-KIKO3D. The benchmark includes a set of input data for the NPP Kalinin-3 (VVER-1000) and consists of three exercises such as point kinetics plant simulation, boundary condition problem for coupled 3-D neutronics/core T-H response evaluation and a best-estimate coupled code plant transient modeling. Some observations and comparisons with measured data for integral reactor parameters are discussed. Special attention is paid on the modelling and comparisons performed for the control rod movement and the reactor power history. Of primary interest are the comparisons done for the local incore parameters –SPND signals at 7 layers of some fuel assemblies. An important step is done for the future performing of uncertainty analysis in the frame of the OECD/NEA activities.

The dynamic core behavior of the High Performance Light Water Reactor (HPLWR), which is a Generation IV light water reactor concept, operated at a supercritical pressure of 25 MPa with a core outlet temperature of 500°C, was investigated in case of Reactivity Initiated Accidents (RIA) events. Before the analyses, the heat transfer correlations and properties of the supercritical water, built into the ATHLET code, were verified by using the Kirillov and the Pismenny single channel thermal hydraulic measurements. The presented results of the performed analyses are reporting about significant perturbation of the power distribution. In comparison to PWRs, delayed and more effective moderator feedback was obtained. The acceptance criteria are not fulfilled in all cases, which points out the importance of the RIA analyses. On the basis of the analyses sufficient countermeasures can be applied in the future to fulfill the acceptance criteria.

To investigate the role of the posterior thalamus in controlling voluntary and visually triggered eye movements and ocular fixation. Methods: The latency to initiate saccades to peripheral targets (visually triggered) and in response to verbal commands (voluntary) was measured in three patients with unilateral lesions of the posterior thalamus, in normal controls, and in neurological controls with Parkinson's disease. On half the trials a fixation point offset simultaneously with target onset, and on half it remained visible. Results: Offset of the fixation point simultaneous with target onset decreased saccade latency for both voluntary and visually triggered eye movements in controls, but only for voluntary saccades in patients with thalamic lesions. Conclusions: These findings suggest that separate neural systems control fixation when making voluntary and visually triggered eye movements, and that the thalamus is involved in the control of fixation for visually triggered but not for voluntary saccades.

In this work we present a new modelling paradigm for computing the complete failure of metal frames by combining the stress-resultant beam model and the shell model. The shell model is used to compute the material parameters that are needed by an inelastic stress-resultant beam model; therefore, we consider the shell model as the meso-scale model and the beam model as the macro-scale model. The shell model takes into account elastoplasticity with strain-hardening and strain-softening, as well as geometrical nonlinearity (including local buckling of a part of a beam). By using results of the shell model, the stress-resultant inelastic beam model is derived that takes into account elastoplasticity with hardening, as well as softening effects (of material and geometric type). The beam softening effects are numerically modelled in a localized failure point by using beam finite element with embedded discontinuity. The original feature of the proposed multi-scale (i.e. shell-beam) computational model is its ability to incorporate both material and geometrical instability contributions into the stress-resultant beam model softening response. Several representative numerical simulations are presented to illustrate a very satisfying performance of the proposed approach.

A technical team from Australia, Europe and the United States has been assembled to plan and conduct the research needed to provide a technology base for far-side crash protection. To date the findings are as follows: (1) in the USA and Australia there are large opportunities for far-side injury reduction, especially if safety features could mitigate injuries in both far-side planar impacts and far-side rollovers, (2) the IIHS test barrier offers considerable promise as a suitable test device to induce the damage that is representative of farside crashes that produce injury, but the test speed should be higher for far-side crashes than for nearside crashes, (3) a modified MADYMO human facet model was validated for use in evaluating far-side countermeasures, (4) either the THOR-NT or the WorldSID dummy would be a satisfactory test device for assessing far-side protection, but would require minor modifications such as changing in the location of the chest instrumentation and (5) injury criteria and risk functions for use with WorldSID in far-side crashes have been documented.

Emotions are an integral part of human decision making. It follows that emotions should take part in the decision process towards the design of more realistic artificial agents. Three psychological models for emotions are examined and a corresponding algorithm is developed for each depicting its process. A generalized multi-agent model is designed to demonstrate the implementation of each of the three methods. An agent thus represents a human capable of exhibiting emotional state in response to an arbitrary emotionally charged event of varying impact.

Bursting pacemaker neurons in the pre-B otzinger complex (pBC) were modeled in the Hodgkin-Huxley style. The single neuron model included rapidly inactivating sodium, persistent sodium, and delayed-rectiÿer potassium currents. The kinetics of the rapidly inactivating and persistent sodium channels was modeled using experimental data obtained from whole-cell patch clamp recordings from pBC neurons in vitro. Our computational study focused on the conditions that could provide the generation of endogenous bursting activity in single pacemaker neurons and neural populations and on the speciÿc roles of voltage-gated potassium and persistent sodium currents in triggering or suppression of endogenous population oscillations in the pBC.