Adsorption of Sodium Dodecyl Sulfate on Ge Substrate: The Effect of a Low-Polarity Solvent

This paper describes the adsorption of sodium dodecyl sulfate (SDS) molecules in a low polar solvent on Ge substrate by using Fourier transform infrared-attenuated total reflection (FTIR-ATR) spectroscopy and atomic force microscopy (AFM). The maximum SDS amount adsorbed is (5.0 +/- 0.3) x 10(14) molecules cm(-2) in CHCl3, while with the use of CCl4 as subphase the ability of SDS adsorbed is 48% lower. AFM images show that depositions are highly disordered over the interface, and it was possible to establish that the size of the SDS deposition is around 30-40 nm over the Ge surface. A complete description of the infrared spectroscopic bands for the head and tail groups in the SDS molecule is also provided.

Polynomial and Poisson dependence in free Poisson algebras and free Poisson fields

We prove that any two Poisson dependent elements in a free Poisson algebra and a free Poisson field of characteristic zero are algebraically dependent, thus answering positively a question from Makar-Limanov and Umirbaev (2007) [8]. We apply this result to give a new proof of the tameness of automorphisms for free Poisson algebras of rank two (see Makar-Limanov and Umirbaev (2011) [9], Makar-Limanov et al. (2009) [10]). (C) 2011 Elsevier Inc. All rights reserved.

Bagging k-dependence probabilistic networks: An alternative powerful fraud detection tool

Fraud is a global problem that has required more attention due to an accentuated expansion of modern technology and communication. When statistical techniques are used to detect fraud, whether a fraud detection model is accurate enough in order to provide correct classification of the case as a fraudulent or legitimate is a critical factor. In this context, the concept of bootstrap aggregating (bagging) arises. The basic idea is to generate multiple classifiers by obtaining the predicted values from the adjusted models to several replicated datasets and then combining them into a single predictive classification in order to improve the classification accuracy. In this paper, for the first time, we aim to present a pioneer study of the performance of the discrete and continuous k-dependence probabilistic networks within the context of bagging predictors classification. Via a large simulation study and various real datasets, we discovered that the probabilistic networks are a strong modeling option with high predictive capacity and with a high increment using the bagging procedure when compared to traditional techniques. (C) 2012 Elsevier Ltd. All rights reserved.

Degree of multicollinearity and variables involved in linear dependence in additive-dominant models

The objective of this work was to assess the degree of multicollinearity and to identify the variables involved in linear dependence relations in additive-dominant models. Data of birth weight (n=141,567), yearling weight (n=58,124), and scrotal circumference (n=20,371) of Montana Tropical composite cattle were used. Diagnosis of multicollinearity was based on the variance inflation factor (VIF) and on the evaluation of the condition indexes and eigenvalues from the correlation matrix among explanatory variables. The first model studied (RM) included the fixed effect of dam age class at calving and the covariates associated to the direct and maternal additive and non-additive effects. The second model (R) included all the effects of the RM model except the maternal additive effects. Multicollinearity was detected in both models for all traits considered, with VIF values of 1.03 - 70.20 for RM and 1.03 - 60.70 for R. Collinearity increased with the increase of variables in the model and the decrease in the number of observations, and it was classified as weak, with condition index values between 10.00 and 26.77. In general, the variables associated with additive and non-additive effects were involved in multicollinearity, partially due to the natural connection between these covariables as fractions of the biological types in breed composition.

Molecular origin of charge traps in polyfluorene-based semiconductors

The comprehensive control of morphology and structure is of extreme importance in semiconducting polymers when used as active layers in optoelectronic devices. In the work reported here, a systematic investigation of the structural and dynamical properties of poly(9,9-di-n-octyl-fluorene-alt-benzothiadiazole), known as F8BT, and their correlation with electrical properties is presented when the material is used as an active layer in optoelectronic devices. By means of X-ray diffraction, one observes that in thick layer films (thickness of about 4 μm) grown by drop-cast deposition, a solvent induced crystalline phase exists which evolves to a stable phase as the temperature is raised. This was not observed in thin films (thickness of about 250 nm) prepared by spin-coating within the investigated temperature range. By modeling the current-voltages characteristics of both thick and thin film devices, important information on the influence of crystallization on the trapping states could be drawn. Furthermore, the temperature dependence of the charge carrier mobility was found to be closely related to that of the molecular relaxation processes. The understanding of the nature of such molecular relaxations, measured by solid-state nuclear magnetic resonance methods, allows one to understand the importance of molecular relaxations and microstructure changes on the trap states of the system.

Measurement and model calculation of the temperature dependence of ligand-to-metal energy transfer rates in lanthanide complexes

Temperature dependent transient curves of excited levels of a model Eu3+ complex have been measured for the first time. A coincidence between the temperature dependent rise time of the 5D0 emitting level and decay time of the 5D1 excited level in the [Eu(tta)3(H2O)2] complex has been found, which unambiguously proves the T1→5D1→5D0 sensitization pathway. A theoretical approach for the temperature dependent energy transfer rates has been successfully applied to the rationalization of the experimental data.

Analyzing the dependence structure of microarray data: a copula–based approach

The main aim of this Ph.D. dissertation is the study of clustering dependent data by means of copula functions with particular emphasis on microarray data. Copula functions are a popular multivariate modeling tool in each field where the multivariate dependence is of great interest and their use in clustering has not been still investigated. The first part of this work contains the review of the literature of clustering methods, copula functions and microarray experiments. The attention focuses on the K–means (Hartigan, 1975; Hartigan and Wong, 1979), the hierarchical (Everitt, 1974) and the model–based (Fraley and Raftery, 1998, 1999, 2000, 2007) clustering techniques because their performance is compared. Then, the probabilistic interpretation of the Sklar’s theorem (Sklar’s, 1959), the estimation methods for copulas like the Inference for Margins (Joe and Xu, 1996) and the Archimedean and Elliptical copula families are presented. In the end, applications of clustering methods and copulas to the genetic and microarray experiments are highlighted. The second part contains the original contribution proposed. A simulation study is performed in order to evaluate the performance of the K–means and the hierarchical bottom–up clustering methods in identifying clusters according to the dependence structure of the data generating process. Different simulations are performed by varying different conditions (e.g., the kind of margins (distinct, overlapping and nested) and the value of the dependence parameter ) and the results are evaluated by means of different measures of performance. In light of the simulation results and of the limits of the two investigated clustering methods, a new clustering algorithm based on copula functions (‘CoClust’ in brief) is proposed. The basic idea, the iterative procedure of the CoClust and the description of the written R functions with their output are given. The CoClust algorithm is tested on simulated data (by varying the number of clusters, the copula models, the dependence parameter value and the degree of overlap of margins) and is compared with the performance of model–based clustering by using different measures of performance, like the percentage of well–identified number of clusters and the not rejection percentage of H0 on . It is shown that the CoClust algorithm allows to overcome all observed limits of the other investigated clustering techniques and is able to identify clusters according to the dependence structure of the data independently of the degree of overlap of margins and the strength of the dependence. The CoClust uses a criterion based on the maximized log–likelihood function of the copula and can virtually account for any possible dependence relationship between observations. Many peculiar characteristics are shown for the CoClust, e.g. its capability of identifying the true number of clusters and the fact that it does not require a starting classification. Finally, the CoClust algorithm is applied to the real microarray data of Hedenfalk et al. (2001) both to the gene expressions observed in three different cancer samples and to the columns (tumor samples) of the whole data matrix.

A partial dependence factorial analysis to deal with selection bias in observational studis

This thesis presents a creative and practical approach to dealing with the problem of selection bias. Selection bias may be the most important vexing problem in program evaluation or in any line of research that attempts to assert causality. Some of the greatest minds in economics and statistics have scrutinized the problem of selection bias, with the resulting approaches – Rubin’s Potential Outcome Approach(Rosenbaum and Rubin,1983; Rubin, 1991,2001,2004) or Heckman’s Selection model (Heckman, 1979) – being widely accepted and used as the best fixes. These solutions to the bias that arises in particular from self selection are imperfect, and many researchers, when feasible, reserve their strongest causal inference for data from experimental rather than observational studies. The innovative aspect of this thesis is to propose a data transformation that allows measuring and testing in an automatic and multivariate way the presence of selection bias. The approach involves the construction of a multi-dimensional conditional space of the X matrix in which the bias associated with the treatment assignment has been eliminated. Specifically, we propose the use of a partial dependence analysis of the X-space as a tool for investigating the dependence relationship between a set of observable pre-treatment categorical covariates X and a treatment indicator variable T, in order to obtain a measure of bias according to their dependence structure. The measure of selection bias is then expressed in terms of inertia due to the dependence between X and T that has been eliminated. Given the measure of selection bias, we propose a multivariate test of imbalance in order to check if the detected bias is significant, by using the asymptotical distribution of inertia due to T (Estadella et al. 2005) , and by preserving the multivariate nature of data. Further, we propose the use of a clustering procedure as a tool to find groups of comparable units on which estimate local causal effects, and the use of the multivariate test of imbalance as a stopping rule in choosing the best cluster solution set. The method is non parametric, it does not call for modeling the data, based on some underlying theory or assumption about the selection process, but instead it calls for using the existing variability within the data and letting the data to speak. The idea of proposing this multivariate approach to measure selection bias and test balance comes from the consideration that in applied research all aspects of multivariate balance, not represented in the univariate variable- by-variable summaries, are ignored. The first part contains an introduction to evaluation methods as part of public and private decision process and a review of the literature of evaluation methods. The attention is focused on Rubin Potential Outcome Approach, matching methods, and briefly on Heckman’s Selection Model. The second part focuses on some resulting limitations of conventional methods, with particular attention to the problem of how testing in the correct way balancing. The third part contains the original contribution proposed , a simulation study that allows to check the performance of the method for a given dependence setting and an application to a real data set. Finally, we discuss, conclude and explain our future perspectives.

Isospin dependence of the Ar+Ni fusion-evaporation cross section

The fundamental goal of this thesis is the determination of the isospin dependence of the Ar+Ni fusion-evaporation cross section. Three Ar isotope beams, with energies of about 13AMeV, have been accelerated and impinged onto isotopically enriched Ni targets, in order to produce Pd nuclei, with mass number varying from 92 to 104. The measurements have been performed by the high performance 4pi detector INDRA, coupled with the magnetic spectrometer VAMOS. Even if the results are very preliminary, the obtained fusion-evaporation cross sections behaviour gives a hint at the possible isospin dependence of the fusion-evaporation cross sections.

Herstellung, Struktur und Polymerisation neuer Cyclodextrin-komplexierter (Meth)acrylate und radikalische Polymerisation neuer Monomere zur Steuerung rheologischer Eigenschaften

Zusammenfassung In der vorliegenden Arbeit wurden Polymerisationseigenschaften hydrophober Monomere untersucht, die mittels methyliertem b-Cyclodextrin (me-b-CD) als Wirt/Gast-Komplexe homogen in die wäßrige Phase überführt wurden. Mit diesem Verfahren steht eine neue Variante der Polymerisation hydrophober Monomere in Wasser zur Verfügung.Die Charakterisierung der Monomer/CD-Komplexe erfolgte mittels Röntgenstrukturanalyse und 1H-NMR-Spektroskopie: steigende Größe der Gast-Komponente erhöht die Wechselwirkungen zum CD. Zur Untersuchung der Polymerisationsreaktion wurden Copolymerisationsparameter von Komplexen und Übertragungskonstanten von Mercaptoverbindungen bei Polymerisationen von Komplexen ermittelt. In Abhängigkeit der Größe der Gastkomponente und ihrer Wasserlöslichkeit resultieren unterschiedliche Reaktivitäten relativ zu Polymerisationen unkomplexierter Reaktanden in organisch-wäßriger Lösung. Außerdem wurden Copolymerisationen zwischen hydrophoben, me-b-CD-komplexierten Monomeren und wasserlöslichen Monomeren untersucht wie z.B. N-Isopropylacrylamid oder Natrium-4-(acrylamido)phenyldiazosulfonat, dessen Copolymerisation mit Styrol bislang nicht möglich war. Eine weitere Aufgabe war die Herstellung wasserstoffbrückenbindender Polymere. Hierzu wurden assoziationsfähige Monomere hergestellt und mit Methylmethacrylat copolymerisiert. Lösungen der Copolymere wurden rheologisch untersucht. Die Lösungen besitzen hohe Nullscherviskositäten bei 20°C und sind strukturviskos. Die Untersuchung der Temperaturabhängigkeit der Nullscherviskositäten ergab insbesondere bei der Lösung von Poly(N-(methacryl-2-ethyl)-N'-(3-amino-(1,2,4-triazol-2-yl))harnstoff-co-methylmethacrylat) bei niedrigen Temperaturen eine hohe Fließaktivierungsenergie, die zu höheren Temperaturen sank. Die komplexe Viskosität dieser Lösung fiel mit zunehmender Temperatur zunächst ab, stieg dann wieder an und sank erneut. Mittels DSC-Messungen konnten Phasenübergänge für dieses Fließverhalten verantwortlich gemacht werden. Außerdem kann Poly(N-(methacryl-2-ethyl)-N'-(3-amino-(1,2,4-triazol-2-yl))harnstoff-co-methylmethacrylat) thermisch vernetzen.

Phasenverhalten von Polyethylen in Mischsystemen

Die vorliegende Arbeit beschäftigt sich mit dem Phasenverhalten von Polyethylen (PE) in nicht-reaktiven und in reaktiven Systemen. Von drei eng verteilten Polyethylenen (Mw = 6,4, 82 bzw. 380 kg/mol) in n-Hexan sowie für das System 2,2-Dimethylbutan / PE 82 wurde die Entmischung in Abhängigkeit von der Zusammensetzung, dem Druck und der Temperatur experimentell bestimmt. Die Modellierung der Trübungskurven erfolgte nach der Theorie von Sanchez und Lacombe. Dieser Ansatz beschreibt die Ergebnisse qualitativ und kann in einem engen Temperatur- und Druckbereich für gegebenes Molekulargewicht die kritische Temperatur und den kritischen Druck quantitativ vorhersagen. Durch Extrapolation der kritischen Temperatur der verschiedenen Lösungen von PE in n-Hexan auf unendliches Molekulargewicht nach Shultz-Flory wurde im Druckbereich von 20 bis 100 bar und im Temperaturbereich von 130 bis 200 °C eine Grenzlinie bestimmt. Diese Linie trennt unabhängig vom Molekulargewicht des Polymers und der Zusammensetzung der Mischung das Zweiphasengebiet vom homogenen Bereich. Im Fall des Mischlösungsmittels n-Hexan / 2,2-Dimethylbutan wurde für eine annähernd kritische Polymerkonzentration die Abhängigkeit der Entmischungsbedingungen von der Zusammensetzung untersucht. Durch einfache Erweiterung der Sanchez-Lacombe-Theorie und Einführen eines Fitparameters konnte das ternäre System beschrieben werden. An einer breit verteilten PE-Probe wurden Experimente zur Fraktionierung von PE in n-Hexan durchgeführt. Die Analyse der in den koexistenten Phasen enthaltenen Polymere lieferte Informationen über die Konzentration und die Molekulargewichtsverteilung des PE in diesen Phasen sowie die kritische Zusammensetzung der Mischung. Von verschiedenen PE-Lösungen (Mw = 0,5 kg/mol) wurde die polymerisationsinduzierte Phasenseparation in Isobornylmethacrylat mit und ohne Vernetzer untersucht. Mit 15 Gew.-% PE und in Abwesenheit von Vernetzer findet die Entmischung erst bei hohen Umsätzen statt. Die Charakterisierung der resultierenden Proben zeigte, dass sich etwas mehr als 5 Gew.-% PE im Polyisobornylmethacrylat lösen. Die Glasübergangstemperaturen der Polymermischungen steigen mit steigender Vernetzer- und sinkender Polyethylenkonzentration. Bei Proben mit 15 Gew.-% PE zeigte sich folgendes: 5 Gew.-% Vernetzer führen zu großen PE-Bereichen (150 - 200 nm) in der Matrix und der Kristallinitätsgrad ist gering. Bei der Polymermischung mit 10 Gew.-% Vernetzer bilden sich sehr kleine Polyethylenkristalle (< 80 nm) und der Kristallinitätsgrad ist hoch. Ohne Vernetzer hängt der Kristallinitätsgrad - wie bei reinem PE - von der Abkühlrate ab, mit Vernetzer ist er von ihr unabhängig.

Mathematical Modeling to Investigate Antiarrhythmic Drug Side Effects: Rate-Dependence Role in Ionic Currents and Action Potentials Shape in the O’Hara Model

Sudden cardiac death due to ventricular arrhythmia is one of the leading causes of mortality in the world. In the last decades, it has proven that anti-arrhythmic drugs, which prolong the refractory period by means of prolongation of the cardiac action potential duration (APD), play a good role in preventing of relevant human arrhythmias. However, it has long been observed that the “class III antiarrhythmic effect” diminish at faster heart rates and that this phenomenon represent a big weakness, since it is the precise situation when arrhythmias are most prone to occur. It is well known that mathematical modeling is a useful tool for investigating cardiac cell behavior. In the last 60 years, a multitude of cardiac models has been created; from the pioneering work of Hodgkin and Huxley (1952), who first described the ionic currents of the squid giant axon quantitatively, mathematical modeling has made great strides. The O’Hara model, that I employed in this research work, is one of the modern computational models of ventricular myocyte, a new generation began in 1991 with ventricular cell model by Noble et al. Successful of these models is that you can generate novel predictions, suggest experiments and provide a quantitative understanding of underlying mechanism. Obviously, the drawback is that they remain simple models, they don’t represent the real system. The overall goal of this research is to give an additional tool, through mathematical modeling, to understand the behavior of the main ionic currents involved during the action potential (AP), especially underlining the differences between slower and faster heart rates. In particular to evaluate the rate-dependence role on the action potential duration, to implement a new method for interpreting ionic currents behavior after a perturbation effect and to verify the validity of the work proposed by Antonio Zaza using an injected current as a perturbing effect.

Synthesis and application of new ion-tagged ligands and organocatalysts

We report the synthesis and application of some ion-tagged catalysts in organometallic catalysis and organocatalysis. With the installation of an ionic group on the backbone of a known catalyst, two main effects are generally obtained. i) a modification of the solubility of the catalyst: if judicious choice of the ion pair is made, the ion-tag can confer to the catalyst a solubility profile suitable for catalyst recycling. ii) the ionic group can play a non-innocent role in the process considered: if stabilizing interaction between the ionic group and the developing charges in the transition state are established, the reaction can speed up. We describe the use of ion-tagged diphenylprolinol as Zn ligand. The chiral ligand grafted onto an ionic liquid (IL) was recycled 10 times with no loss of reactivity and selectivity, when it was employed in the first example of enantioselective addition of ZnEt2 to aldehydes in ILs. An ammonium-tagged phosphine displayed the capability to stabilize Pd catalysts for the Suzuki reaction in ILs. The ionic phase was recycled 6 times with no detectable loss of activity and very low Pd leaching in the organic phase. This catalytic system was also employed for the functionalization of the challenging substrate 5,11-dibromotetracene. In the field of organocatalysis, we prepared two ion-tagged derivatives of the McMillan imidazolidinone. The results of the asymmetric Diels-Alder reaction between trans-cinnamaldehyde and cyclopentadiene exhibited great dependence on the position and nature of the ionic group. Finally, when O-TMS-diphenylprolinol was tagged with an imidazolium ion, exploiting a silyl ether linker, an efficient catalyst for the asymmetric addition of aldehydes to nitroolefins was achieved. The catalyst displayed enhanced reactivity and the same high level of selectivity of the untagged parent catalyst and it could be employed in a wide range of reaction conditions, included use of water as solvent.

Measurement of the helicity dependence of deuteron photodisintegration for photon energies below 450 MeV

In 1998 a pilot experiment was carried out to study the helicity dependence of photoreaction cross sections using circularly polarized real photons on longitudinally polarized deuterons in a deuterated butanol target. The knowledge of these cross sections is required to test the validity of the Gerasimov-Drell-Hearn sum rule on the deuteron and the neutron. The focus of this thesis is on the results for the differential and total cross sections for the photodisintegration reaction for various photon energies in the range from 200 to 450 MeV using data taken with the detector system DAPHNE. The current understanding of the NN interaction as represented by the calculations by M. Schwamb could be confirmed within the given uncertainties. In addition, the detector DAPHNE has been prepared for the main experiment in 2003. The according work is presented together with results of the quality-test measurements of the renewed detector components.