The use of Meteosat satellite data for spatial rainfall estimations and hydrological simulations

Satellite information, in combination with conventional point source measurements, can be a valuable source of information. This thesis is devoted to the spatial estimation of areal rainfall over a region using both the measurements from a dense and sparse network of rain-gauges and images from the meteorological satellites. A primary concern is to study the effects of such satellite assisted rainfall estimates on the performance of rainfall-runoff models. Low-cost image processing systems and peripherals are used to process and manipulate the data. Both secondary as well as primary satellite images were used for analysis. The secondary data was obtained from the in-house satellite receiver and the primary data was obtained from an outside source. Ground truth data was obtained from the local Water Authority. A number of algorithms are presented that combine the satellite and conventional data sources to produce areal rainfall estimates and the results are compared with some of the more traditional methodologies. The results indicate that the satellite cloud information is valuable in the assessment of the spatial distribution of areal rainfall, for both half-hourly as well as daily estimates of rainfall. It is also demonstrated how the performance of the simple multiple regression rainfall-runoff model is improved when satellite cloud information is used as a separate input in addition to rainfall estimates from conventional means. The use of low-cost equipment, from image processing systems to satellite imagery, makes it possible for developing countries to introduce such systems in areas where the benefits are greatest.

Using empirical evidence of variations in worker performance to extend the capabilities of discrete event simulations in manufacturing

Discrete event simulation of manufacturing systems has become widely accepted as an important tool to aid the design of such systems. Often, however, it is applied by practitioners in a manner which largely ignores an important element of industry; namely, the workforce. Workers are usually represented as simple resources, often with deterministic performance values. This approach ignores the potentially large effect that human performance variation can have on a system. A long-term data collection exercise is described with the aim of quantifying the performance variation of workers in a typical automotive assembly plant. The data are presented in a histogram form which is immediately usable in simulations to improve the accuracy of design assessment. The results show levels of skewness and range which are far larger than anticipated by current researchers and practitioners in the field.

Molecular dynamics simulations:bring biomolecular structures alive on a computer

The molecular dynamics (MD) simulations play a very important role in science today. They have been used successfully in binding free-energy calculations and rational design of drugs and vaccines. MD simulations can help visualize and understand structures and dynamics at an atomistic level when combined with molecular graphics programs. The molecular and atomistic properties can be displayed on a computer in a time-dependent way, which opens a road toward a better understanding of the relationship of structure, dynamics, and function. In this chapter, the basics of MD are explained, together with a step-by-step description of setup and running an MD simulation.

Molecular dynamics simulations of the adsorption and diffusion behavior of pure and mixed alkanes in silicalite

The adsorption and diffusion of mixed hydrocarbon components in silicalite have been studied using molecular dynamic simulation methods. We have investigated the effect of molecular loadings and temperature on the diffusional behavior of both pure and mixed alkane components. For binary mixtures with components of similar sizes, molecular diffusional behavior in the channels was noticed to be reversed as loading is increased. This behavior was noticeably absent for components of different sizes in the mixture. Methane molecules in the methane/propane mixture have the highest diffusion coefficients across the entire loading range. Binary mixtures containing ethane molecules prove more difficult to separate compared to other binary components. In the ternary mixture, however, ethane molecules diffuse much faster at 400 K in the channel with a tendency to separate out quickly from other components. © 2005 Elsevier Inc. All rights reserved.

Monte Carlo and molecular dynamics simulations of methane in potassium montmorillonite clay hydrates at elevated pressures and temperatures

The structure and dynamics of methane in hydrated potassium montmorillonite clay have been studied under conditions encountered in sedimentary basin and compared to those of hydrated sodium montmorillonite clay using computer simulation techniques. The simulated systems contain two molecular layers of water and followed gradients of 150 barkm-1 and 30 Kkm-1 up to a maximum burial depth of 6 km. Methane particle is coordinated to about 19 oxygen atoms, with 6 of these coming from the clay surface oxygen. Potassium ions tend to move away from the center towards the clay surface, in contrast to the behavior observed with the hydrated sodium form. The clay surface affinity for methane was found to be higher in the hydrated K-form. Methane diffusion in the two-layer hydrated K-montmorillonite increases from 0.39×10-9 m2s-1 at 280 K to 3.27×10-9 m2s-1 at 460 K compared to 0.36×10-9 m2s-1 at 280 K to 4.26×10-9 m2s-1 at 460 K in Na-montmorillonite hydrate. The distributions of the potassium ions were found to vary in the hydrates when compared to those of sodium form. Water molecules were also found to be very mobile in the potassium clay hydrates compared to sodium clay hydrates. © 2004 Elsevier Inc. All All rights reserved.

Large-scale molecular dynamics simulations of HLA-A*0201 complexed with a tumor-specific antigenic peptide:can the α3 and β2m domains be neglected?

Large-scale massively parallel molecular dynamics (MD) simulations of the human class I major histo-compatibility complex (MHC) protein HLA-A*0201 bound to a decameric tumor-specific antigenic peptide GVY-DGREHTV were performed using a scalable MD code on high-performance computing platforms. Such computational capabilities put us in reach of simulations of various scales and complexities. The supercomputing resources available Large-scale massively parallel molecular dynamics (MD) simulations of the human class I major histocompatibility complex (MHC) protein HLA-A*0201 bound to a decameric tumor-specific antigenic peptide GVYDGREHTV were performed using a scalable MD code on high-performance computing platforms. Such computational capabilities put us in reach of simulations of various scales and complexities. The supercomputing resources available for this study allow us to compare directly differences in the behavior of very large molecular models; in this case, the entire extracellular portion of the peptide–MHC complex vs. the isolated peptide binding domain. Comparison of the results from the partial and the whole system simulations indicates that the peptide is less tightly bound in the partial system than in the whole system. From a detailed study of conformations, solvent-accessible surface area, the nature of the water network structure, and the binding energies, we conclude that, when considering the conformation of the α1–α2 domain, the α3 and β2m domains cannot be neglected. © 2004 Wiley Periodicals, Inc. J Comput Chem 25: 1803–1813, 2004

Using SPICE for power system simulations

Power system simulation software is a useful tool for teaching the fundamentals of power system design and operation. However, existing commercial packages are not ideal for teaching work-based students because of high-cost, complexity of the software and licensing restrictions. This paper describes a set of power systems libraries that have been developed for use with the free, student-edition of a Micro-Cap Spice that overcomes these problems. In addition, these libraries are easily adapted to include power electronic converter based components into the simulation, such as HVDC, FACTS and smart-grid devices, as well as advanced system control functions. These types of technology are set to become more widespread throughout existing power networks, and their inclusion into a power engineering degree course is therefore becoming increasingly important.

Monte Carlo Random Walk Simulations Based on Distributed Order Differential Equations with Applications to Cell Biology

Mathematics Subject Classification: 65C05, 60G50, 39A10, 92C37

Histidine hydrogen bonding in MHC at pH 5 and pH 7 modeled by molecular docking and molecular dynamics simulations

Hydrogen bonds play important roles in maintaining the structure of proteins and in the formation of most biomolecular protein-ligand complexes. All amino acids can act as hydrogen bond donors and acceptors. Among amino acids, Histidine is unique, as it can exist in neutral or positively charged forms within the physiological pH range of 5.0 to 7.0. Histidine can thus interact with other aromatic residues as well as forming hydrogen bonds with polar and charged residues. The ability of His to exchange a proton lies at the heart of many important functional biomolecular interactions, including immunological ones. By using molecular docking and molecular dynamics simulation, we examine the influence of His protonation/deprotonation on peptide binding affinity to MHC class II proteins from locus HLA-DP. Peptide-MHC interaction underlies the adaptive cellular immune response, upon which the next generation of commercially-important vaccines will depend. Consistent with experiment, we find that peptides containing protonated His residues bind better to HLA-DP proteins than those with unprotonated His. Enhanced binding at pH 5.0 is due, in part, to additional hydrogen bonds formed between peptide His+ and DP proteins. In acidic endosomes, protein His79β is predominantly protonated. As a result, the peptide binding cleft narrows in the vicinity of His79β, which stabilizes the peptide - HLA-DP protein complex. © 2014 Bentham Science Publishers.

CO adsorption over Pd nanoparticles:a general framework for IR simulations on nanoparticles

CO vibrational spectra over catalytic nanoparticles under high coverages/pressures are discussed from a DFT perspective. Hybrid B3LYP and PBE DFT calculations of CO chemisorbed over Pd4 and Pd13 nanoclusters, and a 1.1 nm Pd38 nanoparticle, have been performed in order to simulate the corresponding coverage dependent infrared (IR) absorption spectra, and hence provide a quantitative foundation for the interpretation of experimental IR spectra of CO over Pd nanocatalysts. B3LYP simulated IR intensities are used to quantify site occupation numbers through comparison with experimental DRIFTS spectra, allowing an atomistic model of CO surface coverage to be created. DFT adsorption energetics for low CO coverage (θ → 0) suggest the CO binding strength follows the order hollow > bridge > linear, even for dispersion-corrected functionals for sub-nanometre Pd nanoclusters. For a Pd38 nanoparticle, hollow and bridge-bound are energetically similar (hollow ≈ bridge > atop). It is well known that this ordering has not been found at the high coverages used experimentally, wherein atop CO has a much higher population than observed over Pd(111), confirmed by our DRIFTS spectra for Pd nanoparticles supported on a KIT-6 silica, and hence site populations were calculated through a comparison of DFT and spectroscopic data. At high CO coverage (θ = 1), all three adsorbed CO species co-exist on Pd38, and their interdiffusion is thermally feasible at STP. Under such high surface coverages, DFT predicts that bridge-bound CO chains are thermodynamically stable and isoenergetic to an entirely hollow bound Pd/CO system. The Pd38 nanoparticle undergoes a linear (3.5%), isotropic expansion with increasing CO coverage, accompanied by 63 and 30 cm− 1 blue-shifts of hollow and linear bound CO respectively.

Queue Length Simulations in a Finite Single-line Queueing System with Repeated Calls

2000 Mathematics Subject Classification: 60K25.

Szimulációk és érzékenységvizsgálatok a magyar gazdaság egy középméretű makromodelljével = Simulations and sensitivity analyses with a medium-sized macro model of the Hungarian economy

A tanulmányban a Pénzügyminisztérium gazdaságpolitikai főosztálya és az MTA Közgazdaságtudományi Intézete által kifejlesztett középméretű negyedéves makrogazdasági modell segítségével elemezzük a magyar gazdaság legfontosabb mechanizmusait. A modellezés során követett alapelvek és a modell blokkjainak bemutatása után egy forgatókönyv-elemzés keretében vizsgáljuk a makrogazdasági és költségvetési folyamatokat befolyásoló főbb faktorok hatásait. A - tágan értelmezett - "bizonytalansági tényezőket" három csoportba soroljuk: megkülönböztetjük a külső környezet (például árfolyam) változását, a gazdasági szereplők viselkedésében rejlő bizonytalanságokat (például a bérigazodás sebességének vagy a fogyasztássimítás mértékének bizonytalanságát), valamint a gazdaságpolitikai lépéseket (például állami bérek emelését). Megmutatjuk, hogy e kockázatok makrokövetkezményei nem függetlenek egymástól, például egy árfolyamváltozás hatását befolyásolja a bérigazodás sebessége. ______ This paper analyses the most important mechanisms of the Hungarian economy using a medium-sized quarterly macroeconomic model developed jointly by the Economic Policy Department of the Ministry of Finance and the Institute of Economics of the Hungarian Academy of Sciences. After introducing the fundamental principles of modelling and the building blocks of the model investigated, within a scenario analysis, the authors present the effects of the main factors behind the macroeconomic and budgetary processes. The sources of uncertainty - defined in a broad sense - are categorized in three groups: change in the external environment (e.g. the exchange rate), uncertainties in the behav-iour of economic agents (e.g. in speed of wage adjustment or extent of consumption smoothing), and economic policy decisions (e.g. the increase in public sector wages). The macroeconomic consequences of these uncertainties are shown not to be independent of each other. For instance, the effects of an exchange rate shock are influenced by the speed of wage adjustment.

Simulations of Theoretical Ecosystem Growth Model (TEGM) during various climate conditions

Climate change has a great impact on the build and the work of natural ecosystems. Disappearance of some population or growth of the number in some species can be already caused by little change in temperature. A Theoretical Ecosystem Growth Model was investigated in order to examine the effects of various climate patterns on the ecological equilibrium. The answers of the ecosystems which are given to the climate change could be described by means of global climate modelling and dynamic vegetation models. The examination of the operation of the ecosystems is only possible in huge centres on supercomputers because of the number and the complexity of the calculation. The number of the calculation could be decreased to the level of a PC by considering the temperature and the reproduction during the modelling of a theoretical ecosystem and several important theoretical questions could be answered.

Achievement of generic baccalaureate student nurses using computer -assisted instruction simulations during a nursing review course

The use of computer assisted instruction (CAI) simulations as an instructional strategy provides nursing students with a critical thinking approach for evaluating risks and benefits and choosing correct alternatives in "safe" patient care situations. It was hypothesized that using CAI simulations during an upper level nursing review course would have a positive effect on the students' posttest scores. Subjects (n = 36) were senior nursing students enrolled in a nursing review course in an undergraduate baccalaureate program. A limitation of the study was the small sample size. The study employed a modified group experimental design using the t test for independent samples. The group who received the CAI simulations during the physiological system review demonstrated a significant increase (p $<$.01) in the posttest score mean when compared to the lecture-discussion group score mean. There was no significant difference between high and low clinical grade point average (GPA) students in the CAI and lecture-discussion groups and their score means on the posttest. However, score mean differences of the low clinical GPA students showed a greater increase for the CAI group than the lecture-discussion group. There was no significant difference between the groups in their system content subscore means on the exit examination completed three weeks later. It was concluded that CAI simulations are as effective as lecture-discussion in assisting upper level students to process information for clinical decision making. CAI simulations can be considered as an instructional strategy to supplement or replace lecture content during a review course, allowing more efficient use of faculty time. It is recommended that the study be repeated using a larger sample size. Further investigations are recommended in comparing the effectiveness of computer software formats and various instructional strategies for other learning situations and student populations. ^