Second-order parameter estimation

This work provides a general framework for the design of second-order blind estimators without adopting anyapproximation about the observation statistics or the a prioridistribution of the parameters. The proposed solution is obtainedminimizing the estimator variance subject to some constraints onthe estimator bias. The resulting optimal estimator is found todepend on the observation fourth-order moments that can be calculatedanalytically from the known signal model. Unfortunately,in most cases, the performance of this estimator is severely limitedby the residual bias inherent to nonlinear estimation problems.To overcome this limitation, the second-order minimum varianceunbiased estimator is deduced from the general solution by assumingaccurate prior information on the vector of parameters.This small-error approximation is adopted to design iterativeestimators or trackers. It is shown that the associated varianceconstitutes the lower bound for the variance of any unbiasedestimator based on the sample covariance matrix.The paper formulation is then applied to track the angle-of-arrival(AoA) of multiple digitally-modulated sources by means ofa uniform linear array. The optimal second-order tracker is comparedwith the classical maximum likelihood (ML) blind methodsthat are shown to be quadratic in the observed data as well. Simulationshave confirmed that the discrete nature of the transmittedsymbols can be exploited to improve considerably the discriminationof near sources in medium-to-high SNR scenarios.

Monte Carlo Methods in Parameter Estimation of Nonlinear Models

Yksi keskeisimmistä tehtävistä matemaattisten mallien tilastollisessa analyysissä on mallien tuntemattomien parametrien estimointi. Tässä diplomityössä ollaan kiinnostuneita tuntemattomien parametrien jakaumista ja niiden muodostamiseen sopivista numeerisista menetelmistä, etenkin tapauksissa, joissa malli on epälineaarinen parametrien suhteen. Erilaisten numeeristen menetelmien osalta pääpaino on Markovin ketju Monte Carlo -menetelmissä (MCMC). Nämä laskentaintensiiviset menetelmät ovat viime aikoina kasvattaneet suosiotaan lähinnä kasvaneen laskentatehon vuoksi. Sekä Markovin ketjujen että Monte Carlo -simuloinnin teoriaa on esitelty työssä siinä määrin, että menetelmien toimivuus saadaan perusteltua. Viime aikoina kehitetyistä menetelmistä tarkastellaan etenkin adaptiivisia MCMC menetelmiä. Työn lähestymistapa on käytännönläheinen ja erilaisia MCMC -menetelmien toteutukseen liittyviä asioita korostetaan. Työn empiirisessä osuudessa tarkastellaan viiden esimerkkimallin tuntemattomien parametrien jakaumaa käyttäen hyväksi teoriaosassa esitettyjä menetelmiä. Mallit kuvaavat kemiallisia reaktioita ja kuvataan tavallisina differentiaaliyhtälöryhminä. Mallit on kerätty kemisteiltä Lappeenrannan teknillisestä yliopistosta ja Åbo Akademista, Turusta.

Particle Size Analysis of Pharmaceutical Powders by Laser Diffraction

Raaka-aineen hiukkaskoko on lääkekehityksessä keskeinen materiaaliparametri. Lääkeaineen partikkelikoko vaikuttaa moneen lääketuotteen tärkeään ominaisuuteen, esimerkiksi lääkkeen biologiseen hyväksikäytettävyyteen. Tässä diplomityössä keskityttiin jauhemaisten lääkeaineiden hiukkaskoon määrittämiseen laserdiffraktiomenetelmällä. Menetelmä perustuu siihen, että partikkeleista sironneen valon intensiteetin sirontakulmajakauma on riippuvainen partikkelien kokojakaumasta. Työn kirjallisuusosassa esiteltiin laserdiffraktiomenetelmän teoriaa. PIDS (Polarization Intensity Differential Scattering) tekniikka, jota voidaan käyttää laserdiffraktion yhteydessä, on myös kuvattu kirjallisuusosassa. Muihin menetelmiin perustuvista analyysimenetelmistä tutustuttiin mikroskopiaan sekä aerodynaamisen lentoajan määrittämiseen perustuvaan menetelmään. Kirjallisuusosassa esiteltiin myös partikkelikoon yleisimpiä esitystapoja. Työn kokeellisen osan tarkoituksena oli kehittää ja validoida laserdiffraktioon perustuva partikkelikoon määritysmenetelmä tietylle lääkeaineelle. Menetelmäkehitys tehtiin käyttäen Beckman Coulter LS 13 320 laserdiffraktoria. Laite mahdollistaa PIDS-tekniikan käytön laserdiffraktiotekniikan ohella. Menetelmäkehitys aloitettiin arvioimalla, että kyseinen lääkeaine soveltuu parhaiten määritettäväksi nesteeseen dispergoituna. Liukoisuuden perusteella väliaineeksi valittiin tällä lääkeaineella kyllästetty vesiliuos. Dispergointiaineen sekä ultraäänihauteen käyttö havaittiin tarpeelliseksi dispergoidessa kyseistä lääkeainetta kylläiseen vesiliuokseen. Lopuksi sekoitusnopeus näytteensyöttöyksikössä säädettiin sopivaksi. Validointivaiheessa kehitetyn menetelmän todettiin soveltuvan hyvin kyseiselle lääkeaineelle ja tulosten todettiin olevan oikeellisia sekä toistettavia. Menetelmä ei myöskään ollut herkkä pienille häiriöille.

Discrepancy between Visual Acuity and Microperimetry in AMD Patients: Visual Acuity Appears as an Inadequate Parameter to Test Macular Function.

BACKGROUND: Best corrected visual acuity (BCVA) of 0.8 or above in AMD patients can sometimes correspond to poor macular function inducing a serious visual handicap. Microperimetry can be used to objectivize this difference. PATIENTS AND METHODS: A retrospective study was undertaken on 233 files of AMD patients of whom 82 had had a microperimetry. BCVA was compared with microperimetry performance. All examinations were performed in an identical setting by the same team of 3 persons. RESULTS: Among the 82 patients included, 32 (39.0%) had a BCVA equal to or above 0.8 even though their microperimetry performance was lower than 200/560 db. 10 of them (12.2% of total) had an even poorer microperimetry below 120/560 db indicating poor macular function. CONCLUSIONS: More than a third of the AMD patients had a bad or very bad microperimetry performance in parallel with a good visual acuity. Microperimetry is a valuable tool to assess and follow real macular function in AMD patients when visual acuity alone can be misleading.

Protein loop compaction and the origin of the effect of arginine and glutamic acid mixtures on solubility, stability and transient oligomerization of proteins

Addition of a 50 mM mixture of l-arginine and l-glutamic acid (RE) is extensively used to improve protein solubility and stability, although the origin of the effect is not well understood. We present Small Angle X-ray Scattering (SAXS) and Nuclear Magnetic Resonance (NMR) results showing that RE induces protein compaction by collapsing flexible loops on the protein core. This is suggested to be a general mechanism preventing aggregation and improving resistance to proteases and to originate from the polyelectrolyte nature of RE. Molecular polyelectrolyte mixtures are expected to display long range correlation effects according to dressed interaction site theory. We hypothesize that perturbation of the RE solution by dissolved proteins is proportional to the volume occupied by the protein. As a consequence, loop collapse, minimizing the effective protein volume, is favored in the presence of RE.

Radiographic adenoid evaluation: proposal of an objective parameter

Objective The objective of the present study was to evaluate current radiographic parameters designed to investigate adenoid hypertrophy and nasopharyngeal obstruction, and to present an alternative radiographic assessment method. Materials and Methods In order to do so, children (4 to14 years old) who presented with nasal obstruction or oral breathing complaints were submitted to cavum radiographic examination. One hundred and twenty records were evaluated according to quantitative radiographic parameters, and data were correlated with a gold-standard videonasopharyngoscopic study, in relation to the percentage of choanal obstruction. Subsequently, a regression analysis was performed in order to create an original model so the percentage of the choanal obstruction could be predicted. Results The quantitative parameters demonstrated moderate, if not weak correlation with the real percentage of choanal obstruction. The regression model (110.119*A/N) demonstrated a satisfactory ability to “predict” the actual percentage of choanal obstruction. Conclusion Since current adenoid quantitative radiographic parameters present limitations, the model presented by the present study might be considered as an alternative assessment method in cases where videonasopharyngoscopic evaluation is unavailable.

Supercritical CO2 recovery of caffeine from green coffee oil: new experimental solubility data and modeling

The caffeine solubility in supercritical CO2 was studied by assessing the effects of pressure and temperature on the extraction of green coffee oil (GCO). The Peng-Robinson¹ equation of state was used to correlate the solubility of caffeine with a thermodynamic model and two mixing rules were evaluated: the classical mixing rule of van der Waals with two adjustable parameters (PR-VDW) and a density dependent one, proposed by Mohamed and Holder² with two (PR-MH, two parameters adjusted to the attractive term) and three (PR-MH3 two parameters adjusted to the attractive and one to the repulsive term) adjustable parameters. The best results were obtained with the mixing rule of Mohamed and Holder² with three parameters.

Thermodynamic study of the solubility of sodium naproxen in some ethanol + water mixtures

By using the van't Hoff and Gibbs equations the apparent thermodynamic functions Gibbs energy, enthalpy, and entropy of solution for sodium naproxen in ethanol + water cosolvent mixtures, were evaluated from solubility data determined at temperatures from (278.15 to 308.15) K. The drug solubility was greatest in neat water and lowest in neat ethanol at all the temperatures studied. By means of non-linear enthalpy-entropy compensation analysis, it follows that the dissolution process of this drug in ethanol-rich mixtures is entropy-driven, whereas, in water-rich mixtures the process is enthalpy-driven.

Improving the solubility of the antichagasic drug benznidazole through formation of inclusion complexes with cyclodextrins

This study describes unpublished research on improving the solubility of benznidazole by the formation of an inclusion complex. The cyclodextrins selected were αCD, βCD, γCD, HPβCD, RMβCD and SBβCD. All complexes were obtained in solution, presenting 1:1 stoichiometry according to the phase solubility diagram. The highest association constants were obtained with RMβCD and SBβCD, being selected for attainment of solid state complexes. These were characterized using XRD, SEM and dissolution test. The data obtained suggest the formation of complexes and indicate that these may provide a promising alternative way of developing solid doses of drug with suitable biopharmaceutical properties.

Thermodynamic study of the solubility of triclocarban in ethanol + propylene glycol mixtures

By using the van't Hoff and Gibbs equations the apparent thermodynamic functions Gibbs energy, enthalpy, and entropy of solution for triclocarban in ethanol + propylene glycol mixtures were evaluated from solubility data determined at temperatures from (293.15 to 313.15) K. The drug solubility was greatest in the mixture with 0.60 in mass fraction of ethanol and lowest in neat propylene glycol at almost all the temperatures studied. Non-linear enthalpy-entropy compensation is found indicating apparently different mechanisms of the solution process according to the mixtures composition.

Test Campaign Parameter Editor for a Graphical TTCN-3 Development Environment

This paper presents the design for a graphical parameter editor for Testing and Test Control Notation 3 (TTCN-3) test suites. This work was done in the context of OpenTTCN IDE, a TTCN-3 development environment built on top of the Eclipse platform. The design presented relies on an additional parameter editing tab added to the launch configurations for test campaigns. This parameter editing tab shows the list of editable parameters and allows opening editing components for the different parameters. Each TTCN-3 primitive type will have a specific editing component providing tools to ease modification of values of that type.

Differential Evolution approach and parameter estimation of chaotic

Parameter estimation still remains a challenge in many important applications. There is a need to develop methods that utilize achievements in modern computational systems with growing capabilities. Owing to this fact different kinds of Evolutionary Algorithms are becoming an especially perspective field of research. The main aim of this thesis is to explore theoretical aspects of a specific type of Evolutionary Algorithms class, the Differential Evolution (DE) method, and implement this algorithm as codes capable to solve a large range of problems. Matlab, a numerical computing environment provided by MathWorks inc., has been utilized for this purpose. Our implementation empirically demonstrates the benefits of a stochastic optimizers with respect to deterministic optimizers in case of stochastic and chaotic problems. Furthermore, the advanced features of Differential Evolution are discussed as well as taken into account in the Matlab realization. Test "toycase" examples are presented in order to show advantages and disadvantages caused by additional aspects involved in extensions of the basic algorithm. Another aim of this paper is to apply the DE approach to the parameter estimation problem of the system exhibiting chaotic behavior, where the well-known Lorenz system with specific set of parameter values is taken as an example. Finally, the DE approach for estimation of chaotic dynamics is compared to the Ensemble prediction and parameter estimation system (EPPES) approach which was recently proposed as a possible solution for similar problems.