Regional approaches to e-government initiatives in the Caribbean

This paper examines the potential benefits and challenges of regionally managed e-government development initiatives. It examines the current state of e-government in four Caribbean countries – Barbados, Jamaica, Saint Vincent and the Grenadines, and Trinidad and Tobago – in order to establish a broader understanding of the challenges that face e-government initiatives in the region. It also reviews a number of e-government initiatives that have been undertaken through projects managed at a regional level. Based on this analysis, it presents a set of best practices that are recommended to agencies engaged in the task of coordinating the implementation of regionally-based e-government initiatives.

A critical comparison of different approaches to sediment-quality assessments in the Santos estuarine system in Brazil

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

The beneficial effect of equisetum giganteum L. against candida biofilm formation: new approaches to denture stomatitis

Equisetum giganteum L. (E. giganteum), Equisetaceae, commonly called giant horsetail, is an endemic plant of Central and South America and is used in traditional medicine as diuretic and hemostatic in urinary disorders and in inflammatory conditions among other applications. The chemical composition of the extract EtOH 70% of E. giganteum has shown a clear presence of phenolic compounds derived from caffeic and ferulic acids and flavonoid heterosides derived from quercitin and kaempferol, in addition to styrylpyrones. E. giganteum, mainly at the highest concentrations, showed antimicrobial activity against the relevant microorganisms tested: Escherichia coli, Staphylococcus aureus, and Candida albicans. It also demonstrated antiadherent activity on C. albicans biofilms in an experimental model that is similar to dentures. Moreover, all concentrations tested showed anti-inflammatory activity. The extract did not show cytotoxicity in contact with human cells. These properties might qualify E. giganteum extract to be a promising alternative for the topic treatment and prevention of oral candidiasis and denture stomatitis.

Theoretical approaches to forensic entomology: I. Mathematical model of postfeeding larval dispersal

An overall theoretical approach to model phenomena of interest for forensic entomology is advanced. Efforts are concentrated in identifying biological attributes at the individual, population and community of the arthropod fauna associated with decomposing human corpses and then incorporating these attributes into mathematical models. In particular in this paper a diffusion model of dispersal of post feeding larvae is described for blowflies, which are the most common insects associated with corpses.

Theoretical approaches to liana management: a search for a less harmful method

Lianas can change forest dynamics, slowing down forest regeneration after a perturbation. In these cases, it may be necessary to manage these woody climbers. Our aim was to simulate two management strategies: (1) focusing on abundant liana species and (2) focusing on the largest lianas, and contrast them with the random removal of lianas. We applied mathematical simulations for liana removal in three different vegetation types in southeastern Brazil: a Rainforest, a Seasonal Tropical Forest, and a Woodland Savanna. Using these samples, we performed simulations based on two liana removal procedures and compared them with random removal. We also used regression analysis with quasi-Poisson distribution to test whether larger lianas were aggressive, i.e., if they climbed into many trees. The procedure of cutting larger lianas was as effective as cutting them randomly and proved not to be a good method for liana management. Moreover, most of the lianas climbed into one or two trees, i.e., were not aggressive. Cutting the most abundant lianas proved to be a more effective method than cutting lianas randomly. This method could maintain liana richness and presumably should accelerate forest regeneration.

Chemoenzymatic approaches to obtain chiral-centered selenium compounds

The synthesis of chiral-centered selenium compounds is presented. Enantioselective oxidations of these organoselenium compounds were performed using a wide range of biocatalysts, including Baeyer-Villiger monooxygenases, oxidoreductases-containing Aspergillus terreus and lipase (Cal-B) in the presence of oxidants. Finally, efficient synthesis of enantiopure organoselenium compounds using a kinetic resolution approach mediated by Cal-B was achieved. (C) 2012 Elsevier Ltd. All rights reserved.

The Social City : Middle-way approaches to housing and sub-urban golvernmentality in southern Stockholm, 1900-1945

This dissertation deals with the period bridging the era of extreme housing shortages in Stockholm on the eve of industrialisation and the much admired programmes of housing provision that followed after the second world war, when Stockholm district Vällingby became an example for underground railway-serviced ”new towns”. It is argued that important changes were made in the housing and town planning policy in Stockholm in this period that paved the way for the successful ensuing period. Foremost among these changes was the uniquely developed practice of municipal leaseholding with the help of site leasehold rights (Erbbaurecht). The study is informed by recent developments in Foucauldian social research, which go under the heading ’governmentality’. Developments within urban planning are understood as different solutions to the problem of urban order. To a large extent, urban and housing policies changed during the period from direct interventions into the lives of inhabitants connected to a liberal understanding of housing provision, to the building of a disciplinary city, and the conduct of ’governmental’ power, building on increased activity on behalf of the local state to provide housing and the integration and co-operation of large collectives. Municipal leaseholding was a fundamental means for the implementation of this policy. When the new policies were introduced, they were limited to the outer parts of the city and administered by special administrative bodies. This administrative and spatial separation was largely upheld throughout the period, and represented as the parallel building of a ’social’ outer city, while things in the inner ’mercantile’ city proceeded more or less as before. This separation was founded in a radical difference in land holding policy: while sites in the inner city were privatised and sold at market values, land in the outer city was mostly leasehold land, distributed according to administrative – and thus politically decided – priorities. These differences were also understood and acknowledged by the inhabitants. Thorough studies of the local press and the organisational life of the southern parts of the outer city reveals that the local identity was tightly connected with the representations connected to the different land holding systems. Inhabitants in the south-western parts of the city, which in this period was still largely built on private sites, displayed a spatial understanding built on the contradictions between centre and periphery. The inhabitants living on leaseholding sites, however, showed a clear understanding of their position as members of model communities, tightly connected to the policy of the municipal administration. The organisations on leaseholding sites also displayed a deep co-operation with the administration. As the analyses of election results show, the inhabitants also seemed to have felt a greater degree of integration with the society at large, than people living in other parts of the city. The leaseholding system in Stockholm has persisted until today and has been one of the strongest in the world, although the local neo-liberal politicians are currently disposing it off.

New approaches to open problems in gene expression microarray data

In the past decade, the advent of efficient genome sequencing tools and high-throughput experimental biotechnology has lead to enormous progress in the life science. Among the most important innovations is the microarray tecnology. It allows to quantify the expression for thousands of genes simultaneously by measurin the hybridization from a tissue of interest to probes on a small glass or plastic slide. The characteristics of these data include a fair amount of random noise, a predictor dimension in the thousand, and a sample noise in the dozens. One of the most exciting areas to which microarray technology has been applied is the challenge of deciphering complex disease such as cancer. In these studies, samples are taken from two or more groups of individuals with heterogeneous phenotypes, pathologies, or clinical outcomes. these samples are hybridized to microarrays in an effort to find a small number of genes which are strongly correlated with the group of individuals. Eventhough today methods to analyse the data are welle developed and close to reach a standard organization (through the effort of preposed International project like Microarray Gene Expression Data -MGED- Society [1]) it is not unfrequant to stumble in a clinician's question that do not have a compelling statistical method that could permit to answer it.The contribution of this dissertation in deciphering disease regards the development of new approaches aiming at handle open problems posed by clinicians in handle specific experimental designs. In Chapter 1 starting from a biological necessary introduction, we revise the microarray tecnologies and all the important steps that involve an experiment from the production of the array, to the quality controls ending with preprocessing steps that will be used into the data analysis in the rest of the dissertation. While in Chapter 2 a critical review of standard analysis methods are provided stressing most of problems that In Chapter 3 is introduced a method to adress the issue of unbalanced design of miacroarray experiments. In microarray experiments, experimental design is a crucial starting-point for obtaining reasonable results. In a two-class problem, an equal or similar number of samples it should be collected between the two classes. However in some cases, e.g. rare pathologies, the approach to be taken is less evident. We propose to address this issue by applying a modified version of SAM [2]. MultiSAM consists in a reiterated application of a SAM analysis, comparing the less populated class (LPC) with 1,000 random samplings of the same size from the more populated class (MPC) A list of the differentially expressed genes is generated for each SAM application. After 1,000 reiterations, each single probe given a "score" ranging from 0 to 1,000 based on its recurrence in the 1,000 lists as differentially expressed. The performance of MultiSAM was compared to the performance of SAM and LIMMA [3] over two simulated data sets via beta and exponential distribution. The results of all three algorithms over low- noise data sets seems acceptable However, on a real unbalanced two-channel data set reagardin Chronic Lymphocitic Leukemia, LIMMA finds no significant probe, SAM finds 23 significantly changed probes but cannot separate the two classes, while MultiSAM finds 122 probes with score >300 and separates the data into two clusters by hierarchical clustering. We also report extra-assay validation in terms of differentially expressed genes Although standard algorithms perform well over low-noise simulated data sets, multi-SAM seems to be the only one able to reveal subtle differences in gene expression profiles on real unbalanced data. In Chapter 4 a method to adress similarities evaluation in a three-class prblem by means of Relevance Vector Machine [4] is described. In fact, looking at microarray data in a prognostic and diagnostic clinical framework, not only differences could have a crucial role. In some cases similarities can give useful and, sometimes even more, important information. The goal, given three classes, could be to establish, with a certain level of confidence, if the third one is similar to the first or the second one. In this work we show that Relevance Vector Machine (RVM) [2] could be a possible solutions to the limitation of standard supervised classification. In fact, RVM offers many advantages compared, for example, with his well-known precursor (Support Vector Machine - SVM [3]). Among these advantages, the estimate of posterior probability of class membership represents a key feature to address the similarity issue. This is a highly important, but often overlooked, option of any practical pattern recognition system. We focused on Tumor-Grade-three-class problem, so we have 67 samples of grade I (G1), 54 samples of grade 3 (G3) and 100 samples of grade 2 (G2). The goal is to find a model able to separate G1 from G3, then evaluate the third class G2 as test-set to obtain the probability for samples of G2 to be member of class G1 or class G3. The analysis showed that breast cancer samples of grade II have a molecular profile more similar to breast cancer samples of grade I. Looking at the literature this result have been guessed, but no measure of significance was gived before.

TCAD approaches to multidimensional simulation of advanced semiconductor devices

Technology scaling increasingly emphasizes complexity and non-ideality of the electrical behavior of semiconductor devices and boosts interest on alternatives to the conventional planar MOSFET architecture. TCAD simulation tools are fundamental to the analysis and development of new technology generations. However, the increasing device complexity is reflected in an augmented dimensionality of the problems to be solved. The trade-off between accuracy and computational cost of the simulation is especially influenced by domain discretization: mesh generation is therefore one of the most critical steps and automatic approaches are sought. Moreover, the problem size is further increased by process variations, calling for a statistical representation of the single device through an ensemble of microscopically different instances. The aim of this thesis is to present multi-disciplinary approaches to handle this increasing problem dimensionality in a numerical simulation perspective. The topic of mesh generation is tackled by presenting a new Wavelet-based Adaptive Method (WAM) for the automatic refinement of 2D and 3D domain discretizations. Multiresolution techniques and efficient signal processing algorithms are exploited to increase grid resolution in the domain regions where relevant physical phenomena take place. Moreover, the grid is dynamically adapted to follow solution changes produced by bias variations and quality criteria are imposed on the produced meshes. The further dimensionality increase due to variability in extremely scaled devices is considered with reference to two increasingly critical phenomena, namely line-edge roughness (LER) and random dopant fluctuations (RD). The impact of such phenomena on FinFET devices, which represent a promising alternative to planar CMOS technology, is estimated through 2D and 3D TCAD simulations and statistical tools, taking into account matching performance of single devices as well as basic circuit blocks such as SRAMs. Several process options are compared, including resist- and spacer-defined fin patterning as well as different doping profile definitions. Combining statistical simulations with experimental data, potentialities and shortcomings of the FinFET architecture are analyzed and useful design guidelines are provided, which boost feasibility of this technology for mainstream applications in sub-45 nm generation integrated circuits.

Different approaches to identify markers for meat quality and production traits in pigs: analysis of the transcriptome in post mortem skeletal muscle and investigation of candidate genes

Due to the growing attention of consumers towards their food, improvement of quality of animal products has become one of the main focus of research. To this aim, the application of modern molecular genetics approaches has been proved extremely useful and effective. This innovative drive includes all livestock species productions, including pork. The Italian pig breeding industry is unique because needs heavy pigs slaughtered at about 160 kg for the production of high quality processed products. For this reason, it requires precise meat quality and carcass characteristics. Two aspects have been considered in this thesis: the application of the transcriptome analysis in post mortem pig muscles as a possible method to evaluate meat quality parameters related to the pre mortem status of the animals, including health, nutrition, welfare, and with potential applications for product traceability (chapters 3 and 4); the study of candidate genes for obesity related traits in order to identify markers associated with fatness in pigs that could be applied to improve carcass quality (chapters 5, 6, and 7). Chapter three addresses the first issue from a methodological point of view. When we considered this issue, it was not obvious that post mortem skeletal muscle could be useful for transcriptomic analysis. Therefore we demonstrated that the quality of RNA extracted from skeletal muscle of pigs sampled at different post mortem intervals (20 minutes, 2 hours, 6 hours, and 24 hours) is good for downstream applications. Degradation occurred starting from 48 h post mortem even if at this time it is still possible to use some RNA products. In the fourth chapter, in order to demonstrate the potential use of RNA obtained up to 24 hours post mortem, we present the results of RNA analysis with the Affymetrix microarray platform that made it possible to assess the level of expression of more of 24000 mRNAs. We did not identify any significant differences between the different post mortem times suggesting that this technique could be applied to retrieve information coming from the transcriptome of skeletal muscle samples not collected just after slaughtering. This study represents the first contribution of this kind applied to pork. In the fifth chapter, we investigated as candidate for fat deposition the TBC1D1 [TBC1 (tre-2/USP6, BUB2, cdc16) gene. This gene is involved in mechanisms regulating energy homeostasis in skeletal muscle and is associated with predisposition to obesity in humans. By resequencing a fragment of the TBC1D1 gene we identified three synonymous mutations localized in exon 2 (g.40A>G, g.151C>T, and g.172T>C) and 2 polymorphisms localized in intron 2 (g.219G>A and g.252G>A). One of these polymorphisms (g.219G>A) was genotyped by high resolution melting (HRM) analysis and PCR-RFLP. Moreover, this gene sequence was mapped by radiation hybrid analysis on porcine chromosome 8. The association study was conducted in 756 performance tested pigs of Italian Large White and Italian Duroc breeds. Significant results were obtained for lean meat content, back fat thickness, visible intermuscular fat and ham weight. In chapter six, a second candidate gene (tribbles homolog 3, TRIB3) is analyzed in a study of association with carcass and meat quality traits. The TRIB3 gene is involved in energy metabolism of skeletal muscle and plays a role as suppressor of adipocyte differentiation. We identified two polymorphisms in the first coding exon of the porcine TRIB3 gene, one is a synonymous SNP (c.132T> C), a second is a missense mutation (c.146C> T, p.P49L). The two polymorphisms appear to be in complete linkage disequilibrium between and within breeds. The in silico analysis of the p.P49L substitution suggests that it might have a functional effect. The association study in about 650 pigs indicates that this marker is associated with back fat thickness in Italian Large White and Italian Duroc breeds in two different experimental designs. This polymorphisms is also associated with lactate content of muscle semimembranosus in Italian Large White pigs. Expression analysis indicated that this gene is transcribed in skeletal muscle and adipose tissue as well as in other tissues. In the seventh chapter, we reported the genotyping results for of 677 SNPs in extreme divergent groups of pigs chosen according to the extreme estimated breeding values for back fat thickness. SNPs were identified by resequencing, literature mining and in silico database mining. analysis, data reported in the literature of 60 candidates genes for obesity. Genotyping was carried out using the GoldenGate (Illumina) platform. Of the analyzed SNPs more that 300 were polymorphic in the genotyped population and had minor allele frequency (MAF) >0.05. Of these SNPs, 65 were associated (P<0.10) with back fat thickness. One of the most significant gene marker was the same TBC1D1 SNPs reported in chapter 5, confirming the role of this gene in fat deposition in pig. These results could be important to better define the pig as a model for human obesity other than for marker assisted selection to improve carcass characteristics.

Supramolecular approaches to organized luminescent nanostructures for sensing, labeling and imaging applications

The common thread of this thesis is the will of investigating properties and behavior of assemblies. Groups of objects display peculiar properties, which can be very far from the simple sum of respective components’ properties. This is truer, the smaller is inter-objects distance, i.e. the higher is their density, and the smaller is the container size. “Confinement” is in fact a key concept in many topics explored and here reported. It can be conceived as a spatial limitation, that yet gives origin to unexpected processes and phenomena based on inter-objects communication. Such phenomena eventually result in “non-linear properties”, responsible for the low predictability of large assemblies. Chapter 1 provides two insights on surface chemistry, namely (i) on a supramolecular assembly based on orthogonal forces, and (ii) on selective and sensitive fluorescent sensing in thin polymeric film. In chapters 2 to 4 confinement of molecules plays a major role. Most of the work focuses on FRET within core-shell nanoparticles, investigated both through a simulation model and through experiments. Exciting results of great applicative interest are drawn, such as a method of tuning emission wavelength at constant excitation, and a way of overcoming self-quenching processes by setting up a competitive deactivation channel. We envisage applications of these materials as labels for multiplexing analysis, and in all fields of fluorescence imaging, where brightness coupled with biocompatibility and water solubility is required. Adducts of nanoparticles and molecular photoswitches are investigated in the context of superresolution techniques for fluorescence microscopy. In chapter 5 a method is proposed to prepare a library of functionalized Pluronic F127, which gives access to a twofold “smart” nanomaterial, namely both (i)luminescent and (ii)surface-functionalized SCSSNPs. Focus shifts in chapter 6 to confinement effects in an upper size scale. Moving from nanometers to micrometers, we investigate the interplay between microparticles flowing in microchannels where a constriction affects at very long ranges structure and dynamics of the colloidal paste.

New molecular approaches to control rhabdomyosarcoma onset and metastasis in preclinical systems

Rhabdomyosarcoma is the most common soft tissue sarcoma of childhood. The aim of this study was to identify molecular events involved in rhabdomyosarcoma onset for the development of new therapeutic approaches against specific molecular targets. BALB-p53neu mice develop pelvic rhabdomyosarcoma and combines the activation of HER-2/neu oncogene with the inactivation of an allele of p53 oncosuppressor gene. Gene expression profiling led to the identification of genes potentially involved in rhabdomyosarcoma genesis and therefore of candidate targets. The pattern of expression of p53, HER-2/neu, CDKN2A/p19ARF and IGF-2 suggested that these alterations might be involved in gender-, site- and strain-specific development of rhabdomyosarcoma. Other genes such as CDKN1A/p21 might be involved. The role of IGF-2, CDKN2A/p19ARF and CDKN1A/p21 in tumor growth was investigated with siRNA in murine rhabdomyosarcoma cells. Silencing of p19ARF and p21 induced inhibition of growth and of migration ability, indicating a possible pro-tumor and pro-metastatic role in rhabdomyosarcoma in absence of p53. In addition the autocrine IGF-2/IGF-1R loop found in early phases of cancer progression strengthens its key role in sustaining rhabdomyosarcoma growth. As rhabdomyosarcoma displays defective myogenic differentiation, a therapeutic approach aimed at enhancing myogenic differentiation of rhabdomyosarcoma cells. Forced expression of myogenin was able to restore myogenic differentiation, significantly reduced cell motility and impaired tumor growth and metastatic spread. IL-4 treatment increased rhabdomyosarcoma cell growth, decreased myogenin expression and promoted migration of cells lacking myogenin. Another approach was based on small kinase inhibitors. Agents specifically targeting members of the HER family (Lapatinib), of the IGF system (NVP-AEW541) or downstream signal transducers (NVP-BEZ235) were investigated in vitro in human rhabdomyosarcoma cell lines as therapeutic anti-tumor and anti-metastatic tools. The major effects were obtained with NVP-BEZ235 treatment that was able to strongly inhibit cell growth in vitro and showed anti-metastatic effects in vivo.

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.