Numerical and analytical approaches to strongly correlated electron systems

In this thesis we consider three different models for strongly correlated electrons, namely a multi-band Hubbard model as well as the spinless Falicov-Kimball model, both with a semi-elliptical density of states in the limit of infinite dimensions d, and the attractive Hubbard model on a square lattice in d=2. In the first part, we study a two-band Hubbard model with unequal bandwidths and anisotropic Hund's rule coupling (J_z-model) in the limit of infinite dimensions within the dynamical mean-field theory (DMFT). Here, the DMFT impurity problem is solved with the use of quantum Monte Carlo (QMC) simulations. Our main result is that the J_z-model describes the occurrence of an orbital-selective Mott transition (OSMT), in contrast to earlier findings. We investigate the model with a high-precision DMFT algorithm, which was developed as part of this thesis and which supplements QMC with a high-frequency expansion of the self-energy. The main advantage of this scheme is the extraordinary accuracy of the numerical solutions, which can be obtained already with moderate computational effort, so that studies of multi-orbital systems within the DMFT+QMC are strongly improved. We also found that a suitably defined Falicov-Kimball (FK) model exhibits an OSMT, revealing the close connection of the Falicov-Kimball physics to the J_z-model in the OSM phase. In the second part of this thesis we study the attractive Hubbard model in two spatial dimensions within second-order self-consistent perturbation theory. This model is considered on a square lattice at finite doping and at low temperatures. Our main result is that the predictions of first-order perturbation theory (Hartree-Fock approximation) are renormalized by a factor of the order of unity even at arbitrarily weak interaction (U->0). The renormalization factor q can be evaluated as a function of the filling n for 00, the q-factor vanishes, signaling the divergence of self-consistent perturbation theory in this limit. Thus we present the first asymptotically exact results at weak-coupling for the negative-U Hubbard model in d=2 at finite doping.

Synthesis of Biologically Active Small Molecules: Different Approaches to Drug Design

In the past years, genome biology had disclosed an ever-growing kind of biological targets that emerged as ideal points for therapeutic intervention. Nevertheless, the number of new chemical entities (NCEs) translated into effective therapies employed in the clinic, still not observed. Innovative strategies in drug discovery combined with different approaches to drug design should be searched for bridge this gap. In this context organic synthetic chemistry had to provide for effective strategies to achieve biologically active small molecules to consider not only as potentially drug candidates, but also as chemical tools to dissect biological systems. In this scenario, during my PhD, inspired by the Biology-oriented Synthesis approach, a small library of hybrid molecules endowed with privileged scaffolds, able to block cell cycle and to induce apoptosis and cell differentiation, merged with natural-like cores were synthesized. A synthetic platform which joined a Domino Knoevenagel-Diels Alder reaction with a Suzuki coupling was performed in order to reach the hybrid compounds. These molecules can represent either antitumor lead candidates, or valuable chemical tools to study molecular pathways in cancer cells. The biological profile expressed by some of these derivatives showed a well defined antiproliferative activity on leukemia Bcr-Abl expressing K562 cell lines. A parallel project regarded the rational design and synthesis of minimally structurally hERG blockers with the purpose of enhancing the SAR studies of a previously synthesized collection. A Target-Oriented Synthesis approach was applied. Combining conventional and microwave heating, the desired final compounds were achieved in good yields and reaction rates. The preliminary biological results of the compounds, showed a potent blocking activity. The obtained small set of hERG blockers, was able to gain more insight the minimal structural requirements for hERG liability, which is mandatory to investigate in order to reduce the risk of potential side effects of new drug candidates.

Methodological approaches to estimate human population exposure to chemical substances

The public awareness that chemical substances are present ubiquitously in the environment, can be assumed through the diet and can exhibit various health effects, is very high in Europe and Italy. National and international institutions are called to provide figures on the magnitude, frequency, and duration of the population exposure to chemicals, including both natural or anthropogenic substances, voluntarily added to consumers’ good or accidentally entering the production chains. This thesis focuses broadly on how human population exposure to chemicals can be estimated, with particular attention to the methodological approaches and specific focus on dietary exposure assessment and biomonitoring. From the results obtained in the different studies collected in this thesis, it has been pointed out that when selecting the approach to use for the estimate of the exposure to chemicals, several different aspects must be taken into account: the nature of the chemical substance, the population of interest, clarify if the objective is to assess chronic or acute exposure, and finally, take into account the quality and quantity of data available in order to specify and quantify the uncertainty of the estimate.

An overview of the objectives of and the approaches to propensity score analyses

The assessment of treatment effects from observational studies may be biased with patients not randomly allocated to the experimental or control group. One way to overcome this conceptual shortcoming in the design of such studies is the use of propensity scores to adjust for differences of the characteristics between patients treated with experimental and control interventions. The propensity score is defined as the probability that a patient received the experimental intervention conditional on pre-treatment characteristics at baseline. Here, we review how propensity scores are estimated and how they can help in adjusting the treatment effect for baseline imbalances. We further discuss how to evaluate adequate overlap of baseline characteristics between patient groups, provide guidelines for variable selection and model building in modelling the propensity score, and review different methods of propensity score adjustments. We conclude that propensity analyses may help in evaluating the comparability of patients in observational studies, and may account for more potential confounding factors than conventional covariate adjustment approaches. However, bias due to unmeasured confounding cannot be corrected for.

TB research at UT-Houston--a review of cord factor: new approaches to drugs, vaccines and the pathogenesis of tuberculosis.

Tuberculosis remains a major threat as drug resistance continues to increase. Pulmonary tuberculosis in adults is responsible for 80% of clinical cases and nearly 100% of transmission of infection. Unfortunately, since we have no animal models of adult type pulmonary tuberculosis, the most important type of disease remains largely out of reach of modern science and many fundamental questions remain unanswered. This paper reviews research dating back to the 1950's providing compelling evidence that cord factor (trehalose 6,6 dimycolate [TDM]) is essential for understanding tuberculosis. However, the original papers by Bloch and Noll were too far ahead of their time to have immediate impact. We can now recognize that the physical and biologic properties of cord factor are unprecedented in science, especially its ability to switch between two sets of biologic activities with changes in conformation. While TDM remains on organisms, it protects them from killing within macrophages, reduces antibiotic effectiveness and inhibits the stimulation of protective immune responses. If it comes off organisms and associates with lipid, TDM becomes a driver of tissue damage and necrosis. Studies emanating from cord factor research have produced (1) a rationale for improving vaccines, (2) an approach to new drugs that overcome natural resistance to antibiotics, (3) models of caseating granulomas that reproduce multiple manifestations of human tuberculosis. (4) evidence that TDM is a key T cell antigen in destructive lesions of tuberculosis, and (5) a new understanding of the pathology and pathogenesis of postprimary tuberculosis that can guide more informative studies of long standing mysteries of tuberculosis.

Three Experimental Approaches to Measure the Social Context Dependence of Prejudice Communication and Discriminatory Behavior

Empirical research on discrimination is faced with crucial problems stemming from the specific character of its object of study. In democratic societies the communication of prejudices and other forms of discriminatory behavior is considered socially undesirable and depends on situational factors such as whether a situation is considered private or whether a discriminatory consensus can be assumed. Regular surveys thus can only offer a blurred picture of the phenomenon. But also survey experiments intended to decrease the social desirability bias (SDB) so far failed in systematically implementing situational variables. This paper introduces three experimental approaches to improve the study of discrimination and other topics of social (un-)desirability. First, we argue in favor of cognitive context framing in surveys in order to operationalize the salience of situational norms. Second, factorial surveys offer a way to take situational contexts and substitute behavior into account. And third, choice experiments – a rather new method in sociology – offer a more valid method of measuring behavioral characteristics compared to simple items in surveys. All three approaches – which may be combined – are easy to implement in large-scale surveys. Results of empirical studies demonstrate the fruitfulness of each of these approaches.

Evaluating knowledge-based approaches to the multilingual extension of a temporal expression normalizer

The extension to new languages is a well known bottleneck for rule-based systems. Considerable human effort, which typically consists in re-writing from scratch huge amounts of rules, is in fact required to transfer the knowledge available to the system from one language to a new one. Provided sufficient annotated data, machine learning algorithms allow to minimize the costs of such knowledge transfer but, up to date, proved to be ineffective for some specific tasks. Among these, the recognition and normalization of temporal expressions still remains out of their reach. Focusing on this task, and still adhering to the rule-based framework, this paper presents a bunch of experiments on the automatic porting to Italian of a system originally developed for Spanish. Different automatic rule translation strategies are evaluated and discussed, providing a comprehensive overview of the challenge.

From community approaches to single-cell genomics: the discovery of ubiquitous hyperhalophilic Bacteroidetes generalists

The microbiota of multi-pond solar salterns around the world has been analyzed using a variety of culture-dependent and molecular techniques. However, studies addressing the dynamic nature of these systems are very scarce. Here we have characterized the temporal variation during 1 year of the microbiota of five ponds with increasing salinity (from 18% to >40%), by means of CARD-FISH and DGGE. Microbial community structure was statistically correlated with several environmental parameters, including ionic composition and meteorological factors, indicating that the microbial community was dynamic as specific phylotypes appeared only at certain times of the year. In addition to total salinity, microbial composition was strongly influenced by temperature and specific ionic composition. Remarkably, DGGE analyses unveiled the presence of most phylotypes previously detected in hypersaline systems using metagenomics and other molecular techniques, such as the very abundant Haloquadratum and Salinibacter representatives or the recently described low GC Actinobacteria and Nanohaloarchaeota. In addition, an uncultured group of Bacteroidetes was present along the whole range of salinity. Database searches indicated a previously unrecognized widespread distribution of this phylotype. Single-cell genome analysis of five members of this group suggested a set of metabolic characteristics that could provide competitive advantages in hypersaline environments, such as polymer degradation capabilities, the presence of retinal-binding light-activated proton pumps and arsenate reduction potential. In addition, the fairly high metagenomic fragment recruitment obtained for these single cells in both the intermediate and hypersaline ponds further confirm the DGGE data and point to the generalist lifestyle of this new Bacteroidetes group.

Using multiple landscape genetic approaches to test the validity of genetic clusters in a species characterized by an isolation-by-distance pattern

Bayesian clustering methods are typically used to identify barriers to gene flow, but they are prone to deduce artificial subdivisions in a study population characterized by an isolation-by-distance pattern (IbD). Here we analysed the landscape genetic structure of a population of wild boars (Sus scrofa) from south-western Germany. Two clustering methods inferred the presence of the same genetic discontinuity. However, the population in question was characterized by a strong IbD pattern. While landscape-resistance modelling failed to identify landscape features that influenced wild boar movement, partial Mantel tests and multiple regression of distance matrices (MRDMs) suggested that the empirically inferred clusters were separated by a genuine barrier. When simulating random lines bisecting the study area, 60% of the unique barriers represented, according to partial Mantel tests and MRDMs, significant obstacles to gene flow. By contrast, the random-lines simulation showed that the boundaries of the inferred empirical clusters corresponded to the most important genetic discontinuity in the study area. Given the degree of habitat fragmentation separating the two empirical partitions, it is likely that the clustering programs correctly identified a barrier to gene flow. The differing results between the work published here and other studies suggest that it will be very difficult to draw general conclusions about habitat permeability in wild boar from individual studies.

Normative approaches to the prevention of alcohol abuse and alcoholism : proceedings of a symposium, April 26-28, 1977, San Diego, California /

Mode of access: Internet.

Political discourse analysis from the point of view of translation studies

Political discourse very often relies on translation. Political Discourse Analysis (PDA), however, has not yet taken full account of the phenomenon of translation. This paper argues that the disciplines of Translation Studies (TS) and PDA can benefit from closer cooperation. It starts by presenting examples of authentic translations of political texts, commenting on them from the point of view of TS. These examples concern political effects caused by specific translation solutions; the processes by which information is transferred via translation to another culture; and the structure and function of equally valid texts in their respective cultures. After a brief survey of the discipline of Translation Studies, the paper concludes with outlining scope for interdisciplinary cooperation between PDA and TS. This is illustrated with reference to an awareness of product features, multilingual texts, process analysis, and the politics of translation.