Dynamic Distribution Simulation Model Objects Based on Knowledge

This paper presents the process of load balancing in simulation system Triad.Net, the architecture of load balancing subsystem. The main features of static and dynamic load balancing are discussed and new approach, controlled dynamic load balancing, needed for regular mapping of simulation model on the network of computers is proposed. The paper considers linguistic constructions of Triad language for different load balancing algorithms description.

Distributed generation modelling for unbalanced three-phase power flow calculations in smart grids

Distributed Generators (DG) are generally modeled as PQ or PV buses in power flow studies. But in order to integrate DG units into the distribution systems and control the reactive power injection it is necessary to know the operation mode and the type of connection to the system. This paper presents a single-phase and a three-phase mathematical model to integrate DG in power flow calculations in distribution systems, especially suited for Smart Grid calculations. If the DG is in PV mode, each step of the power flow algorithm calculates the reactive power injection from the DG to the system to keep the voltage in the bus in a predefined level, if the DG is in PQ mode, the power injection is considered as a negative load. The method is tested on two well known test system, presenting single-phase results on 85 bus system, and three-phase results in the IEEE 34 bus test system. © 2011 IEEE.

Ligand K-edge X-ray absorption spectroscopy and DFT calculations on [Fe3S4]0,+ clusters: delocalization, redox, and effect of the protein environment

Ligand K-edge XAS of an [Fe3S4]0 model complex is reported. The pre-edge can be resolved into contributions from the í2Ssulfide, í3Ssulfide, and Sthiolate ligands. The average ligand-metal bond covalencies obtained from these pre-edges are further distributed between Fe3+ and Fe2.5+ components using DFT calculations. The bridging ligand covalency in the [Fe2S2]+ subsite of the [Fe3S4]0 cluster is found to be significantly lower than its value in a reduced [Fe2S2] cluster (38% vs 61%, respectively). This lowered bridging ligand covalency reduces the superexchange coupling parameter J relative to its value in a reduced [Fe2S2]+ site (-146 cm-1 vs -360 cm-1, respectively). This decrease in J, along with estimates of the double exchange parameter B and vibronic coupling parameter ì2/k-, leads to an S ) 2 delocalized ground state in the [Fe3S4]0 cluster. The S K-edge XAS of the protein ferredoxin II (Fd II) from the D. gigas active site shows a decrease in covalency compared to the model complex, in the same oxidation state, which correlates with the number of H-bonding interactions to specific sulfur ligands present in the active site. The changes in ligand-metal bond covalencies upon redox compared with DFT calculations indicate that the redox reaction involves a two-electron change (one-electron ionization plus a spin change of a second electron) with significant electronic relaxation. The presence of the redox inactive Fe3+ center is found to decrease the barrier of the redox process in the [Fe3S4] cluster due to its strong antiferromagnetic coupling with the redox active Fe2S2 subsite.

Distributed water ingress and water potential measurements using fibre optics

We report on a distributed moisture detection scheme which uses a cable design based on waterswellable hydrogel polymers. The cable modulates the loss characteristic of light guided within a multi-mode optical fibre in response to relative water potentials in the surrounding environment. Interrogation of the cable using conventional optical time-domain reflectometry (OTDR) instruments allows water ingress points to be identified and located with a spatial resolution of 50 cm. The system has been tested in a simulated tendon duct grouting experiment as a means of mapping the extent of fill along the duct during the grouting process. Voided regions were detected and identified to within 50 cm. A series of salt solutions has been used to determine the sensor behaviour over a range of water potentials. These experiments predict that measurements of soil moisture content can be made over the range 0 to – 1500 kPa. Preliminary data on soil measurements have shown that the sensor can detect water pressure changes with a resolution of 45 kPa. Applications for the sensor include quality assurance of grouting procedures, verification of waterproofing barriers and soil moisture content determination (for load-bearing calculations).

Realistic calculations of carbon-based disordered systems

Carbon nanotubes rank amongst potential candidates for a new family of nanoscopic devices, in particular for sensing applications. At the same time that defects in carbon nanotubes act as binding sites for foreign species, our current level of control over the fabrication process does not allow one to specifically choose where these binding sites will actually be positioned. In this work we present a theoretical framework for accurately calculating the electronic and transport properties of long disordered carbon nanotubes containing a large number of binding sites randomly distributed along a sample. This method combines the accuracy and functionality of ab initio density functional theory to determine the electronic structure with a recursive Green`s functions method. We apply this methodology on the problem of nitrogen-rich carbon nanotubes, first considering different types of defects and then demonstrating how our simulations can help in the field of sensor design by allowing one to compute the transport properties of realistic nanotube devices containing a large number of randomly distributed binding sites.

Ab-initio calculations for a realistic sensor: A study of CO sensors based on nitrogen-rich carbon nanotubes

The use of nanoscale low-dimensional systems could boost the sensitivity of gas sensors. In this work we simulate a nanoscopic sensor based on carbon nanotubes with a large number of binding sites using ab initio density functional electronic structure calculations coupled to the Non-Equilibrium Green's Function formalism. We present a recipe where the adsorption process is studied followed by conductance calculations of a single defect system and of more realistic disordered system considering different coverages of molecules as one would expect experimentally. We found that the sensitivity of the disordered system is enhanced by a factor of 5 when compared to the single defect one. Finally, our results from the atomistic electronic transport are used as input to a simple model that connects them to experimental parameters such as temperature and partial gas pressure, providing a procedure for simulating a realistic nanoscopic gas sensor. Using this methodology we show that nitrogen-rich carbon nanotubes could work at room temperature with extremely high sensitivity. Copyright 2012 Author(s). This article is distributed under a Creative Commons Attribution 3.0 Unported License. [http://dx.doi.org/10.1063/1.4739280]

Bayesian Hierarchical Distributed Lag Models for Summer Ozone Exposure and Cardio-Respiratory Mortality

In this paper, we develop Bayesian hierarchical distributed lag models for estimating associations between daily variations in summer ozone levels and daily variations in cardiovascular and respiratory (CVDRESP) mortality counts for 19 U.S. large cities included in the National Morbidity Mortality Air Pollution Study (NMMAPS) for the period 1987 - 1994. At the first stage, we define a semi-parametric distributed lag Poisson regression model to estimate city-specific relative rates of CVDRESP associated with short-term exposure to summer ozone. At the second stage, we specify a class of distributions for the true city-specific relative rates to estimate an overall effect by taking into account the variability within and across cities. We perform the calculations with respect to several random effects distributions (normal, t-student, and mixture of normal), thus relaxing the common assumption of a two-stage normal-normal hierarchical model. We assess the sensitivity of the results to: 1) lag structure for ozone exposure; 2) degree of adjustment for long-term trends; 3) inclusion of other pollutants in the model;4) heat waves; 5) random effects distributions; and 6) prior hyperparameters. On average across cities, we found that a 10ppb increase in summer ozone level for every day in the previous week is associated with 1.25 percent increase in CVDRESP mortality (95% posterior regions: 0.47, 2.03). The relative rate estimates are also positive and statistically significant at lags 0, 1, and 2. We found that associations between summer ozone and CVDRESP mortality are sensitive to the confounding adjustment for PM_10, but are robust to: 1) the adjustment for long-term trends, other gaseous pollutants (NO_2, SO_2, and CO); 2) the distributional assumptions at the second stage of the hierarchical model; and 3) the prior distributions on all unknown parameters. Bayesian hierarchical distributed lag models and their application to the NMMAPS data allow us estimation of an acute health effect associated with exposure to ambient air pollution in the last few days on average across several locations. The application of these methods and the systematic assessment of the sensitivity of findings to model assumptions provide important epidemiological evidence for future air quality regulations.

Hough Transform recursive evaluation using Distributed Arithmetic

Paper submitted to the IFIP International Conference on Very Large Scale Integration (VLSI-SOC), Darmstadt, Germany, 2003.

Airplane design; a textbook of airplane layout and stress analysis calculations with particular emphasis on economics of design.

"First three editions comprising 2400 copies were published between Dec. 1934 and June 1939."

Graphs of calculations of energy deposition and air fluorescence from radiation produced by a nuclear explosion in space /

"Part of this work done under ARPA Order 631, Program Code No. 5820."

Message passing for distributed optimisation of power allocation with renewable resources

The increase in renewable energy generators introduced into the electricity grid is putting pressure on its stability and management as predictions of renewable energy sources cannot be accurate or fully controlled. This, with the additional pressure of fluctuations in demand, presents a problem more complex than the current methods of controlling electricity distribution were designed for. A global approximate and distributed optimisation method for power allocation that accommodates uncertainties and volatility is suggested and analysed. It is based on a probabilistic method known as message passing [1], which has deep links to statistical physics methodology. This principled method of optimisation is based on local calculations and inherently accommodates uncertainties; it is of modest computational complexity and provides good approximate solutions.We consider uncertainty and fluctuations drawn from a Gaussian distribution and incorporate them into the message-passing algorithm. We see the effect that increasing uncertainty has on the transmission cost and how the placement of volatile nodes within a grid, such as renewable generators or consumers, effects it.

Mesh partitioning and load balancing for distributed memory parallel systems

A method is outlined for optimising graph partitions which arise in mapping unstructured mesh calculations to parallel computers. The method employs a relative gain iterative technique to both evenly balance the workload and minimise the number and volume of interprocessor communications. A parallel graph reduction technique is also briefly described and can be used to give a global perspective to the optimisation. The algorithms work efficiently in parallel as well as sequentially and when combined with a fast direct partitioning technique (such as the Greedy algorithm) to give an initial partition, the resulting two-stage process proves itself to be both a powerful and flexible solution to the static graph-partitioning problem. Experiments indicate that the resulting parallel code can provide high quality partitions, independent of the initial partition, within a few seconds. The algorithms can also be used for dynamic load-balancing, reusing existing partitions and in this case the procedures are much faster than static techniques, provide partitions of similar or higher quality and, in comparison, involve the migration of a fraction of the data.

Core-valence Correlation Effects On Ir Calculations: The Bf3 And Bcl3 Cases.

The first theoretical results of core-valence correlation effects are presented for the infrared wavenumbers and intensities of the BF3 and BCl3 molecules, using (double- and triple-zeta) Dunning core-valence basis sets at the CCSD(T) level. The results are compared with those calculated in the frozen core approximation with standard Dunning basis sets at the same correlation level and with the experimental values. The general conclusion is that the effect of core-valence correlation is, for infrared wavenumbers and intensities, smaller than the effect of adding augmented diffuse functions to the basis set, e.g., cc-pVTZ to aug-cc-pVTZ. Moreover, the trends observed in the data are mainly related to the augmented functions rather than the core-valence functions added to the basis set. The results obtained here confirm previous studies pointing out the large descrepancy between the theoretical and experimental intensities of the stretching mode for BCl3.

CYP2C19 and ABCB1 gene polymorphisms are differently distributed according to ethnicity in the Brazilian general population

Background: Recent studies have reported the clinical importance of CYP2C19 and ABCB1 polymorphisms in an individualized approach to clopidogrel treatment. The aims of this study were to evaluate the frequencies of CYP2C19 and ABCB1 polymorphisms and to identify the clopidogrel-predicted metabolic phenotypes according to ethnic groups in a sample of individuals representative of a highly admixtured population. Methods: One hundred and eighty-three Amerindians and 1,029 subjects of the general population of 4 regions of the country were included. Genotypes for the ABCB1c.C3435T (rs1045642), CYP2C19*2 (rs4244285), CYP2C19*3 (rs4986893), CYP2C19*4 (rs28399504), CYP2C19*5 (rs56337013), and CYP2C19*17 (rs12248560) polymorphisms were detected by polymerase chain reaction followed by high resolution melting analysis. The CYP2C19*3, CYP2C19*4 and CYP2C19*5 variants were genotyped in a subsample of subjects (300 samples randomly selected). Results: The CYP2C19*3 and CYP2C19*5 variant alleles were not detected and the CYP2C19*4 variant allele presented a frequency of 0.3%. The allelic frequencies for the ABCB1c.C3435T, CYP2C19*2 and CYP2C19*17 polymorphisms were differently distributed according to ethnicity: Amerindian (51.4%, 10.4%, 15.8%); Caucasian descent (43.2%, 16.9%, 18.0%); Mulatto (35.9%, 16.5%, 21.3%); and African descent (32.8%, 20.2%, 26.3%) individuals, respectively. As a result, self-referred ethnicity was able to predict significantly different clopidogrel-predicted metabolic phenotypes prevalence even for a highly admixtured population. Conclusion: Our findings indicate the existence of inter-ethnic differences in the ABCB1 and CYP2C19 variant allele frequencies in the Brazilian general population plus Amerindians. This information could help in stratifying individuals from this population regarding clopidogrel-predicted metabolic phenotypes and design more cost-effective programs towards individualization of clopidogrel therapy.

The Brain as a Distributed Intelligent Processing System: An EEG Study

Background: Various neuroimaging studies, both structural and functional, have provided support for the proposal that a distributed brain network is likely to be the neural basis of intelligence. The theory of Distributed Intelligent Processing Systems (DIPS), first developed in the field of Artificial Intelligence, was proposed to adequately model distributed neural intelligent processing. In addition, the neural efficiency hypothesis suggests that individuals with higher intelligence display more focused cortical activation during cognitive performance, resulting in lower total brain activation when compared with individuals who have lower intelligence. This may be understood as a property of the DIPS. Methodology and Principal Findings: In our study, a new EEG brain mapping technique, based on the neural efficiency hypothesis and the notion of the brain as a Distributed Intelligence Processing System, was used to investigate the correlations between IQ evaluated with WAIS (Whechsler Adult Intelligence Scale) and WISC (Wechsler Intelligence Scale for Children), and the brain activity associated with visual and verbal processing, in order to test the validity of a distributed neural basis for intelligence. Conclusion: The present results support these claims and the neural efficiency hypothesis.