An Error-Localization, Validation and Optimization Tool for Embedded Code Augmentation: an Architecture Oriented Approach

Embedded systems are usually designed for a single or a specified set of tasks. This specificity means the system design as well as its hardware/software development can be highly optimized. Embedded software must meet the requirements such as high reliability operation on resource-constrained platforms, real time constraints and rapid development. This necessitates the adoption of static machine codes analysis tools running on a host machine for the validation and optimization of embedded system codes, which can help meet all of these goals. This could significantly augment the software quality and is still a challenging field.Embedded systems are usually designed for a single or a specified set of tasks. This specificity means the system design as well as its hardware/software development can be highly optimized. Embedded software must meet the requirements such as high reliability operation on resource-constrained platforms, real time constraints and rapid development. This necessitates the adoption of static machine codes analysis tools running on a host machine for the validation and optimization of embedded system codes, which can help meet all of these goals. This could significantly augment the software quality and is still a challenging field.Embedded systems are usually designed for a single or a specified set of tasks. This specificity means the system design as well as its hardware/software development can be highly optimized. Embedded software must meet the requirements such as high reliability operation on resource-constrained platforms, real time constraints and rapid development. This necessitates the adoption of static machine codes analysis tools running on a host machine for the validation and optimization of embedded system codes, which can help meet all of these goals. This could significantly augment the software quality and is still a challenging field.Embedded systems are usually designed for a single or a specified set of tasks. This specificity means the system design as well as its hardware/software development can be highly optimized. Embedded software must meet the requirements such as high reliability operation on resource-constrained platforms, real time constraints and rapid development. This necessitates the adoption of static machine codes analysis tools running on a host machine for the validation and optimization of embedded system codes, which can help meet all of these goals. This could significantly augment the software quality and is still a challenging field.This dissertation contributes to an architecture oriented code validation, error localization and optimization technique assisting the embedded system designer in software debugging, to make it more effective at early detection of software bugs that are otherwise hard to detect, using the static analysis of machine codes. The focus of this work is to develop methods that automatically localize faults as well as optimize the code and thus improve the debugging process as well as quality of the code.Validation is done with the help of rules of inferences formulated for the target processor. The rules govern the occurrence of illegitimate/out of place instructions and code sequences for executing the computational and integrated peripheral functions. The stipulated rules are encoded in propositional logic formulae and their compliance is tested individually in all possible execution paths of the application programs. An incorrect sequence of machine code pattern is identified using slicing techniques on the control flow graph generated from the machine code.An algorithm to assist the compiler to eliminate the redundant bank switching codes and decide on optimum data allocation to banked memory resulting in minimum number of bank switching codes in embedded system software is proposed. A relation matrix and a state transition diagram formed for the active memory bank state transition corresponding to each bank selection instruction is used for the detection of redundant codes. Instances of code redundancy based on the stipulated rules for the target processor are identified.This validation and optimization tool can be integrated to the system development environment. It is a novel approach independent of compiler/assembler, applicable to a wide range of processors once appropriate rules are formulated. Program states are identified mainly with machine code pattern, which drastically reduces the state space creation contributing to an improved state-of-the-art model checking. Though the technique described is general, the implementation is architecture oriented, and hence the feasibility study is conducted on PIC16F87X microcontrollers. The proposed tool will be very useful in steering novices towards correct use of difficult microcontroller features in developing embedded systems.

Optimization of carbon and nitrogen sources and growth factors for the production of an aquaculture probiotic (Pseudomonas MCCB 103) using response surface methodology

Aim: To develop a new medium for enhanced production of biomass of an aquaculture probiotic Pseudomonas MCCB 103 and its antagonistic phenazine compound, pyocyanin. Methods and Results: Carbon and nitrogen sources and growth factors, such as amino acids and vitamins, were screened initially in a mineral medium for the biomass and antagonistic compound of Pseudomonas MCCB 103. The selected ingredients were further optimized using a full-factorial central composite design of the response surface methodology. The medium optimized as per the model for biomass contained mannitol (20 g l)1), glycerol (20 g l)1), sodium chloride (5 g l)1), urea (3Æ3 g l)1) and mineral salts solution (20 ml l)1), and the one optimized for the antagonistic compound contained mannitol (2 g l)1), glycerol (20 g l)1), sodium chloride (5Æ1 g l)1), urea (3Æ6 g l)1) and mineral salts solution (20 ml l)1). Subsequently, the model was validated experimentally with a biomass increase by 19% and fivefold increase of the antagonistic compound. Conclusion: Significant increase in the biomass and antagonistic compound production could be obtained in the new media. Significance and Impact of the Study: Media formulation and optimization are the primary steps involved in bioprocess technology, an attempt not made so far in the production of aquaculture probiotics

Soft Computing Approach for Optimization of siRNA Efficiency Prediction for Post-transcriptional Gene Silencing

Post-transcriptional gene silencing by RNA interference is mediated by small interfering RNA called siRNA. This gene silencing mechanism can be exploited therapeutically to a wide variety of disease-associated targets, especially in AIDS, neurodegenerative diseases, cholesterol and cancer on mice with the hope of extending these approaches to treat humans. Over the recent past, a significant amount of work has been undertaken to understand the gene silencing mediated by exogenous siRNA. The design of efficient exogenous siRNA sequences is challenging because of many issues related to siRNA. While designing efficient siRNA, target mRNAs must be selected such that their corresponding siRNAs are likely to be efficient against that target and unlikely to accidentally silence other transcripts due to sequence similarity. So before doing gene silencing by siRNAs, it is essential to analyze their off-target effects in addition to their inhibition efficiency against a particular target. Hence designing exogenous siRNA with good knock-down efficiency and target specificity is an area of concern to be addressed. Some methods have been developed already by considering both inhibition efficiency and off-target possibility of siRNA against agene. Out of these methods, only a few have achieved good inhibition efficiency, specificity and sensitivity. The main focus of this thesis is to develop computational methods to optimize the efficiency of siRNA in terms of “inhibition capacity and off-target possibility” against target mRNAs with improved efficacy, which may be useful in the area of gene silencing and drug design for tumor development. This study aims to investigate the currently available siRNA prediction approaches and to devise a better computational approach to tackle the problem of siRNA efficacy by inhibition capacity and off-target possibility. The strength and limitations of the available approaches are investigated and taken into consideration for making improved solution. Thus the approaches proposed in this study extend some of the good scoring previous state of the art techniques by incorporating machine learning and statistical approaches and thermodynamic features like whole stacking energy to improve the prediction accuracy, inhibition efficiency, sensitivity and specificity. Here, we propose one Support Vector Machine (SVM) model, and two Artificial Neural Network (ANN) models for siRNA efficiency prediction. In SVM model, the classification property is used to classify whether the siRNA is efficient or inefficient in silencing a target gene. The first ANNmodel, named siRNA Designer, is used for optimizing the inhibition efficiency of siRNA against target genes. The second ANN model, named Optimized siRNA Designer, OpsiD, produces efficient siRNAs with high inhibition efficiency to degrade target genes with improved sensitivity-specificity, and identifies the off-target knockdown possibility of siRNA against non-target genes. The models are trained and tested against a large data set of siRNA sequences. The validations are conducted using Pearson Correlation Coefficient, Mathews Correlation Coefficient, Receiver Operating Characteristic analysis, Accuracy of prediction, Sensitivity and Specificity. It is found that the approach, OpsiD, is capable of predicting the inhibition capacity of siRNA against a target mRNA with improved results over the state of the art techniques. Also we are able to understand the influence of whole stacking energy on efficiency of siRNA. The model is further improved by including the ability to identify the “off-target possibility” of predicted siRNA on non-target genes. Thus the proposed model, OpsiD, can predict optimized siRNA by considering both “inhibition efficiency on target genes and off-target possibility on non-target genes”, with improved inhibition efficiency, specificity and sensitivity. Since we have taken efforts to optimize the siRNA efficacy in terms of “inhibition efficiency and offtarget possibility”, we hope that the risk of “off-target effect” while doing gene silencing in various bioinformatics fields can be overcome to a great extent. These findings may provide new insights into cancer diagnosis, prognosis and therapy by gene silencing. The approach may be found useful for designing exogenous siRNA for therapeutic applications and gene silencing techniques in different areas of bioinformatics.

Micro-electromechanical structural design and optimization of vertical cavity photonic devices with wide continuous tuning

Diese Arbeit umfaßt das elektromechanische Design und die Designoptimierung von weit durchstimmbaren optischen multimembranbasierten Bauelementen, mit vertikal orientierten Kavitäten, basierend auf der Finiten Element Methode (FEM). Ein multimembran InP/Luft Fabry-Pérot optischer Filter wird dargestellt und umfassend analysiert. In dieser Arbeit wird ein systematisches strukturelles Designverfahren dargestellt. Genaue analytische elektromechanischer Modelle für die Bauelemente sind abgeleitet worden. Diese können unschätzbare Werkzeuge sein, um am Anfang der Designphase schnell einen klaren Einblick zur Verfügung zu stellen. Mittels des FEM Programms ist der durch die nicht-lineare Verspannung hervorgerufene versteifende Effekt nachgeforscht und sein Effekt auf die Verlängerung der mechanischen Durchstimmungsstrecke der Bauelemente demonstriert worden. Interessant war auch die Beobachtung, dass die normierte Relation zwischen Ablenkung und Spannung ein unveränderliches Profil hat. Die Deformation der Membranflächen der in dieser Arbeit dargestellten Bauelementformen erwies sich als ein unerwünschter, jedoch manchmal unvermeidbarer Effekt. Es zeigt sich aber, dass die Wahl der Größe der strukturellen Dimensionen den Grad der Membrandeformation im Falle der Aktuation beeinflusst. Diese Arbeit stellt ein elektromechanisches in FEMLAB implementierte quasi-3D Modell, das allgemein für die Modellierung dünner Strukturen angewendet werden kann, dar; und zwar indem man diese als 2D-Objekte betrachtet und die dritte Dimension als eine konstante Größe (z.B. die Schichtdicke) oder eine Größe, welche eine mathematische Funktion ist, annimmt. Diese Annahme verringert drastisch die Berechnungszeit sowie den erforderlichen Arbeitsspeicherbedarf. Weiter ist es für die Nachforschung des Effekts der Skalierung der durchstimmbaren Bauelemente verwendet worden. Eine neuartige Skalierungstechnik wurde abgeleitet und verwendet. Die Ergebnisse belegen, dass das daraus resultierende, skalierte Bauelement fast genau die gleiche mechanische Durchstimmung wie das unskalierte zeigt. Die Einbeziehung des Einflusses von axialen Verspannungen und Gradientenverspannungen in die Berechnungen erforderte die Änderung der Standardimplementierung des 3D Mechanikberechnungsmodus, der mit der benutzten FEM Software geliefert wurde. Die Ergebnisse dieser Studie zeigen einen großen Einfluss der Verspannung auf die Durchstimmungseigenschaften der untersuchten Bauelemente. Ferner stimmten die Ergebnisse der theoretischen Modellrechnung mit den experimentellen Resultaten sehr gut überein.

Optimization-Based Robotic Manipulation for Safe Interaction with Human Operators

This thesis investigates a method for human-robot interaction (HRI) in order to uphold productivity of industrial robots like minimization of the shortest operation time, while ensuring human safety like collision avoidance. For solving such problems an online motion planning approach for robotic manipulators with HRI has been proposed. The approach is based on model predictive control (MPC) with embedded mixed integer programming. The planning strategies of the robotic manipulators mainly considered in the thesis are directly performed in the workspace for easy obstacle representation. The non-convex optimization problem is approximated by a mixed-integer program (MIP). It is further effectively reformulated such that the number of binary variables and the number of feasible integer solutions are drastically decreased. Safety-relevant regions, which are potentially occupied by the human operators, can be generated online by a proposed method based on hidden Markov models. In contrast to previous approaches, which derive predictions based on probability density functions in the form of single points, such as most likely or expected human positions, the proposed method computes safety-relevant subsets of the workspace as a region which is possibly occupied by the human at future instances of time. The method is further enhanced by combining reachability analysis to increase the prediction accuracy. These safety-relevant regions can subsequently serve as safety constraints when the motion is planned by optimization. This way one arrives at motion plans that are safe, i.e. plans that avoid collision with a probability not less than a predefined threshold. The developed methods have been successfully applied to a developed demonstrator, where an industrial robot works in the same space as a human operator. The task of the industrial robot is to drive its end-effector according to a nominal sequence of grippingmotion-releasing operations while no collision with a human arm occurs.

Optimization of Processing Technology for Commercial Drying of Bananas (Matooke)

Summary - Cooking banana is one of the most important crops in Uganda; it is a staple food and source of household income in rural areas. The most common cooking banana is locally called matooke, a Musa sp triploid acuminate genome group (AAA-EAHB). It is perishable and traded in fresh form leading to very high postharvest losses (22-45%). This is attributed to: non-uniform level of harvest maturity, poor handling, bulk transportation and lack of value addition/processing technologies, which are currently the main challenges for trade and export, and diversified utilization of matooke. Drying is one of the oldest technologies employed in processing of agricultural produce. A lot of research has been carried out on drying of fruits and vegetables, but little information is available on matooke. Drying of matooke and milling it to flour extends its shelf-life is an important means to overcome the above challenges. Raw matooke flour is a generic flour developed to improve shelf stability of the fruit and to find alternative uses. It is rich in starch (80 - 85%db) and subsequently has a high potential as a calorie resource base. It possesses good properties for both food and non-food industrial use. Some effort has been done to commercialize the processing of matooke but there is still limited information on its processing into flour. It was imperative to carry out an in-depth study to bridge the following gaps: lack of accurate information on the maturity window within which matooke for processing into flour can be harvested leading to non-uniform quality of matooke flour; there is no information on moisture sorption isotherm for matooke from which the minimum equilibrium moisture content in relation to temperature and relative humidity is obtainable, below which the dry matooke would be microbiologically shelf-stable; and lack of information on drying behavior of matooke and standardized processing parameters for matooke in relation to physicochemical properties of the flour. The main objective of the study was to establish the optimum harvest maturity window and optimize the processing parameters for obtaining standardized microbiologically shelf-stable matooke flour with good starch quality attributes. This research was designed to: i) establish the optimum maturity harvest window within which matooke can be harvested to produce a consistent quality of matooke flour, ii) establish the sorption isotherms for matooke, iii) establish the effect of process parameters on drying characteristics of matooke, iv) optimize the drying process parameters for matooke, v) validate the models of maturity and optimum process parameters and vi) standardize process parameters for commercial processing of matooke. Samples were obtained from a banana plantation at Presidential Initiative on Banana Industrial Development (PIBID), Technology Business Incubation Center (TBI) at Nyaruzunga – Bushenyi in Western Uganda. A completely randomized design (CRD) was employed in selecting the banana stools from which samples for the experiments were picked. The cultivar Mbwazirume which is soft cooking and commonly grown in Bushenyi was selected for the study. The static gravitation method recommended by COST 90 Project (Wolf et al., 1985), was used for determination of moisture sorption isotherms. A research dryer developed for this research. All experiments were carried out in laboratories at TBI. The physiological maturity of matooke cv. mbwazirume at Bushenyi is 21 weeks. The optimum harvest maturity window for commercial processing of matooke flour (Raw Tooke Flour - RTF) at Bushenyi is between 15-21 weeks. The finger weight model is recommended for farmers to estimate harvest maturity for matooke and the combined model of finger weight and pulp peel ratio is recommended for commercial processors. Matooke isotherms exhibited type II curve behavior which is characteristic of foodstuffs. The GAB model best described all the adsorption and desorption moisture isotherms. For commercial processing of matooke, in order to obtain a microbiologically shelf-stable dry product. It is recommended to dry it to moisture content below or equal to 10% (wb). The hysteresis phenomenon was exhibited by the moisture sorption isotherms for matooke. The isoteric heat of sorption for both adsorptions and desorption isotherms increased with decreased moisture content. The total isosteric heat of sorption for matooke: adsorption isotherm ranged from 4,586 – 2,386 kJ/kg and desorption isotherm from 18,194– 2,391 kJ/kg for equilibrium moisture content from 0.3 – 0.01 (db) respectively. The minimum energy required for drying matooke from 80 – 10% (wb) is 8,124 kJ/kg of water removed. Implying that the minimum energy required for drying of 1 kg of fresh matooke from 80 - 10% (wb) is 5,793 kJ. The drying of matooke takes place in three steps: the warm-up and the two falling rate periods. The drying rate constant for all processing parameters ranged from 5,793 kJ and effective diffusivity ranged from 1.5E-10 - 8.27E-10 m2/s. The activation energy (Ea) for matooke was 16.3kJ/mol (1,605 kJ/kg). Comparing the activation energy (Ea) with the net isosteric heat of sorption for desorption isotherm (qst) (1,297.62) at 0.1 (kg water/kg dry matter), indicated that Ea was higher than qst suggesting that moisture molecules travel in liquid form in matooke slices. The total color difference (ΔE*) between the fresh and dry samples, was lowest for effect of thickness of 7 mm, followed by air velocity of 6 m/s, and then drying air temperature at 70˚C. The drying system controlled by set surface product temperature, reduced the drying time by 50% compared to that of a drying system controlled by set air drying temperature. The processing parameters did not have a significant effect on physicochemical and quality attributes, suggesting that any drying air temperature can be used in the initial stages of drying as long as the product temperature does not exceed gelatinization temperature of matooke (72˚C). The optimum processing parameters for single-layer drying of matooke are: thickness = 3 mm, air temperatures 70˚C, dew point temperature 18˚C and air velocity 6 m/s overflow mode. From practical point of view it is recommended that for commercial processing of matooke, to employ multi-layer drying of loading capacity equal or less than 7 kg/m², thickness 3 mm, air temperatures 70˚C, dew point temperature 18˚C and air velocity 6 m/s overflow mode.

Optimization of the Mechanical and Optical Properties of Tunable Optical Sensor Arrays (TOSA) for a Nanospectrometer in the Visible and Near Infrared Spectral Range

Tunable Optical Sensor Arrays (TOSA) based on Fabry-Pérot (FP) filters, for high quality spectroscopic applications in the visible and near infrared spectral range are investigated within this work. The optical performance of the FP filters is improved by using ion beam sputtered niobium pentoxide (Nb2O5) and silicon dioxide (SiO2) Distributed Bragg Reflectors (DBRs) as mirrors. Due to their high refractive index contrast, only a few alternating pairs of Nb2O5 and SiO2 films can achieve DBRs with high reflectivity in a wide spectral range, while ion beam sputter deposition (IBSD) is utilized due to its ability to produce films with high optical purity. However, IBSD films are highly stressed; resulting in stress induced mirror curvature and suspension bending in the free standing filter suspensions of the MEMS (Micro-Electro-Mechanical Systems) FP filters. Stress induced mirror curvature results in filter transmission line degradation, while suspension bending results in high required filter tuning voltages. Moreover, stress induced suspension bending results in higher order mode filter operation which in turn degrades the optical resolution of the filter. Therefore, the deposition process is optimized to achieve both near zero absorption and low residual stress. High energy ion bombardment during film deposition is utilized to reduce the film density, and hence the film compressive stress. Utilizing this technique, the compressive stress of Nb2O5 is reduced by ~43%, while that for SiO2 is reduced by ~40%. Filters fabricated with stress reduced films show curvatures as low as 100 nm for 70 μm mirrors. To reduce the stress induced bending in the free standing filter suspensions, a stress optimized multi-layer suspension design is presented; with a tensile stressed metal sandwiched between two compressively stressed films. The stress in Physical Vapor Deposited (PVD) metals is therefore characterized for use as filter top-electrode and stress compensating layer. Surface micromachining is used to fabricate tunable FP filters in the visible spectral range using the above mentioned design. The upward bending of the suspensions is reduced from several micrometers to less than 100 nm and 250 nm for two different suspension layer combinations. Mechanical tuning of up to 188 nm is obtained by applying 40 V of actuation voltage. Alternatively, a filter line with transmission of 65.5%, Full Width at Half Maximum (FWHM) of 10.5 nm and a stopband of 170 nm (at an output wavelength of 594 nm) is achieved. Numerical model simulations are also performed to study the validity of the stress optimized suspension design for the near infrared spectral range, wherein membrane displacement and suspension deformation due to material residual stress is studied. Two bandpass filter designs based on quarter-wave and non-quarter-wave layers are presented as integral components of the TOSA. With a filter passband of 135 nm and a broad stopband of over 650 nm, high average filter transmission of 88% is achieved inside the passband, while maximum filter transmission of less than 1.6% outside the passband is achieved.

L´onconasa com a model per l´estudi de les bases moleculars de la citotoxicitat de les ribonucleases pancreàtiques. Aplicacions a la construcció de ribonucleases amb activitat antimicrobiana

La primera part d'aquest treball s´ha centrat en la caracterització i optimització del procés d'activació de l´onconasa recombinant per tal d'obtenir l´enzim igual a la forma nativa. Per això, les reaccions d'eliminació de la Met-1 i la ciclació de la Glu1, necessàries per generar el piroglutamic han estat seguides per MALDI-TOF MS. La segona part d´aquest treball s´ha centrat en l´estudi de la contribució del pont disulfur 30-75 de l´onconasa a les seves propietats biològiques. Els resultats suggereixen que el potencial redox del citosol cel·lular podria reduir el pont disulfur 30-75 de l´onconasa salvatge afectant la unió onconasa -inhibidor proteic de ribonucleases. La tercera part ha consistit en la construcció de variants de l´HP-RNasa i onconasa amb activitat bactericida. Per això, s´ha introduït el determinant bactericida (YRWR) descrit per la proteïna catiònica d'eosinòfils en els dos enzims. Els resultats obtinguts han evidenciat que les dues ribonucleases amb el determinant bactericida presenten activitat citotòxica contra bacteris gram-negatius preferentment.

Improvement of strategies for the management of fire blight (Erwinia amylovora). Evaluation and optimization of physical and chemical control methods, and use of decision support systems

El foc bacterià és una malaltia que afecta a plantes de la família de la rosàcies, causada pel bacteri Erwinia amylovora. El seu rang d'hostes inclou arbres fruiters, com la perera, la pomera o el codonyer, i plantes ornamentals de gran interès comercial i econòmic. Actualment, la malaltia s'ha dispersat i es troba àmpliament distribuïda en totes les zones de clima temperat del món. A Espanya, on la malaltia no és endèmica, el foc bacterià es va detectar per primer cop al 1995 al nord del país (Euskadi) i posteriorment, han aparegut varis focus en altres localitzacions, que han estat convenientment eradicats. El control del foc bacterià, és molt poc efectiu en plantes afectades per la malaltia, de manera que es basa en mesures encaminades a evitar la dispersió del patogen, i la introducció de la malaltia en regions no endèmiques. En aquest treball, la termoteràpia ha estat avaluada com a mètode d'eradicació d'E. amylovora de material vegetal de propagació asimptomàtic. S'ha demostrat que la termoteràpia és un mètode viable d'eradicar E. amylovora de material de propagació. Gairebé totes les espècies i varietats de rosàcies mantingudes en condicions d'humitat sobrevivien 7 hores a 45 ºC i més de 3 hores a 50 ºC, mentre que més d'1 hora d'exposició a 50 ºC amb calor seca produïa danys en el material vegetal i reduïa la brotació. Tractaments de 60 min a 45 ºC o 30 min a 50 ºC van ser suficients per reduir la població epífita d'E. amylovora a nivells no detectables (5 x 102 ufc g-1 p.f.) en branques de perera. Els derivats dels fosfonats i el benzotiadiazol són efectius en el control del foc bacterià en perera i pomera, tant en condicions de laboratori, com d'hivernacle i camp. Els inductors de defensa de les plantes redueixen els nivells de malaltia fins al 40-60%. Els intervals de temps mínims per aconseguir el millor control de la malaltia van ser 5 dies pel fosetil-Al, i 7 dies per l'etefon i el benzotiadiazol, i les dosis òptimes pel fosetil-Al i el benzotiadiazol van ser 3.72 g HPO32- L-1 i 150 mg i.a. L-1, respectivament. Es millora l'eficàcia del fosetil-Al i del benzotiadiazol en el control del foc bacterià, quan es combinen amb els antibiòtics a la meitat de la dosi d'aquests últims. Tot i que l'estratègia de barrejar productes és més pràctica i fàcil de dur a terme a camp, que l'estratègia de combinar productes, el millor nivell de control de la malaltia s'aconsegueix amb l'estratègia de combinar productes. Es va analitzar a nivell histològic i ultrastructural l'efecte del benzotiadiazol i dels fosfonats en la interacció Erwinia amylovora-perera. Ni el benzotiadiazol, ni el fosetil-Al, ni l'etefon van induir canvis estructurals en els teixits de perera 7 dies després de la seva aplicació. No obstant, després de la inoculació d'E. amylovora es va observar en plantes tractades amb fosetil-Al i etefon una desorganització estructural cel·lular, mentre que en les plantes tractades amb benzotiadiazol aquestes alteracions tissulars van ser retardades. S'han avaluat dos models (Maryblyt, Cougarblight) en un camp a Espanya afectat per la malaltia, per determinar la precisió de les prediccions. Es van utilitzar dos models per elaborar el mapa de risc, el BRS-Powell combinat i el BIS95 modificat. Els resultats van mostrar dos zones amb elevat i baix risc de la malaltia. Maryblyt i Cougarblight són dos models de fàcil ús, tot i que la seva implementació en programes de maneig de la malaltia requereix que siguin avaluats i validats per un període de temps més llarg i en àrees on la malaltia hi estigui present.

An integrative model of amino acid metabolism in the liver of the lactating dairy cow

The objective of this work was to construct a dynamic model of hepatic amino acid metabolism in the lactating dairy cow that could be parameterized using net flow data from in vivo experiments. The model considers 22 amino acids, ammonia, urea, and 13 energetic metabolites, and was parameterized using a steady-state balance model and two in vivo, net flow experiments conducted with mid-lactation dairy cows. Extracellular flows were derived directly from the observed data. An optimization routine was used to derive nine intracellular flows. The resulting dynamic model was found to be stable across a range of inputs suggesting that it can be perturbed and applied to other physiological states. Although nitrogen was generally in balance, leucine was in slight deficit compared to predicted needs for export protein synthesis, suggesting that an alternative source of leucine (e.g. peptides) was utilized. Simulations of varying glucagon concentrations indicated that an additional 5 mol/d of glucose could be synthesized at the reference substrate concentrations and blood flows. The increased glucose production was supported by increased removal from blood of lactate, glutamate, aspartate, alanine, asparagine, and glutamine. As glucose Output increased, ketone body and acetate release increased while CO2 release declined. The pattern of amino acids appearing in hepatic vein blood was affected by changes in amino acid concentration in portal vein blood, portal blood flow rate and glucagon concentration, with methionine and phenylalanine being the most affected of essential amino acids. Experimental evidence is insufficient to determine whether essential amino acids are affected by varying gluconeogenic demands. (C) 2004 Published by Elsevier Ltd.

RBF equalizer design using directional evolutionary multi-objective optimization

Whilst radial basis function (RBF) equalizers have been employed to combat the linear and nonlinear distortions in modern communication systems, most of them do not take into account the equalizer's generalization capability. In this paper, it is firstly proposed that the. model's generalization capability can be improved by treating the modelling problem as a multi-objective optimization (MOO) problem, with each objective based on one of several training sets. Then, as a modelling application, a new RBF equalizer learning scheme is introduced based on the directional evolutionary MOO (EMOO). Directional EMOO improves the computational efficiency of conventional EMOO, which has been widely applied in solving MOO problems, by explicitly making use of the directional information. Computer simulation demonstrates that the new scheme can be used to derive RBF equalizers with good performance not only on explaining the training samples but on predicting the unseen samples.

Parallel performance and scalability experiments with the Danish Eulerian Model on the EPCC supercomputers

The Danish Eulerian Model (DEM) is a powerful air pollution model, designed to calculate the concentrations of various dangerous species over a large geographical region (e.g. Europe). It takes into account the main physical and chemical processes between these species, the actual meteorological conditions, emissions, etc.. This is a huge computational task and requires significant resources of storage and CPU time. Parallel computing is essential for the efficient practical use of the model. Some efficient parallel versions of the model were created over the past several years. A suitable parallel version of DEM by using the Message Passing Interface library (AIPI) was implemented on two powerful supercomputers of the EPCC - Edinburgh, available via the HPC-Europa programme for transnational access to research infrastructures in EC: a Sun Fire E15K and an IBM HPCx cluster. Although the implementation is in principal, the same for both supercomputers, few modifications had to be done for successful porting of the code on the IBM HPCx cluster. Performance analysis and parallel optimization was done next. Results from bench marking experiments will be presented in this paper. Another set of experiments was carried out in order to investigate the sensitivity of the model to variation of some chemical rate constants in the chemical submodel. Certain modifications of the code were necessary to be done in accordance with this task. The obtained results will be used for further sensitivity analysis Studies by using Monte Carlo simulation.

Selection of funding schemes by a borrowing decision model: a Hong Kong case study

In financial decision-making, a number of mathematical models have been developed for financial management in construction. However, optimizing both qualitative and quantitative factors and the semi-structured nature of construction finance optimization problems are key challenges in solving construction finance decisions. The selection of funding schemes by a modified construction loan acquisition model is solved by an adaptive genetic algorithm (AGA) approach. The basic objectives of the model are to optimize the loan and to minimize the interest payments for all projects. Multiple projects being undertaken by a medium-size construction firm in Hong Kong were used as a real case study to demonstrate the application of the model to the borrowing decision problems. A compromise monthly borrowing schedule was finally achieved. The results indicate that Small and Medium Enterprise (SME) Loan Guarantee Scheme (SGS) was first identified as the source of external financing. Selection of sources of funding can then be made to avoid the possibility of financial problems in the firm by classifying qualitative factors into external, interactive and internal types and taking additional qualitative factors including sovereignty, credit ability and networking into consideration. Thus a more accurate, objective and reliable borrowing decision can be provided for the decision-maker to analyse the financial options.

Use of the statistical properties of the wavelet-transform coefficients for optimization of integration time in Fourier transform spectrometry

We show that an analysis of the mean and variance of discrete wavelet coefficients of coaveraged time-domain interferograms can be used as a specification for determining when to stop coaveraging. We also show that, if a prediction model built in the wavelet domain is used to determine the composition of unknown samples, a stopping criterion for the coaveraging process can be developed with respect to the uncertainty tolerated in the prediction.

Dynamic integrated system optimization and parameter estimation for discrete time optimal control of nonlinear systems

An algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses Dynamic Integrated System Optimization and Parameter Estimation (DISOPE), which achieves the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimization procedure. A version of the algorithm with a linear-quadratic model-based problem, implemented in the C+ + programming language, is developed and applied to illustrative simulation examples. An analysis of the optimality and convergence properties of the algorithm is also presented.