Which way out of poverty? the human capital versus human capabilities approaches

La pobreza es un problema mundial que afecta a personas de diferentes maneras. El propósito de este artículo es explorar dos teorías principales que abordan la pobreza y la posibilidad de su superación, que son los enfoques de capital humano y de capacidades humanas. El enfoque del capital humano se centra exclusivamente en la faceta económica de la pobreza; en esta perspectiva, la pobreza se define como la falta de dinero y puede abordarse mediante el aumento de los ingresos financieros de las personas que viven en la pobreza. El enfoque de las capacidades humanas ve la pobreza como un problema multidimensional que va más allá de la economía para áreas como la salud, la educación y la libertad. Este enfoque se orienta hacia el cambio social y ayudar a las personas en situación de pobreza para descubrir y desarrollar su potencial. El autor considera que las capacidades humanas abarcan con mayor precisión el alcance de la pobreza y las personas afectadas por el mismo, aunque debido a su amplia gama ha sido difícil diseñar e implementar políticas eficaces que aborden todas las facetas de la pobreza.

Innovative approaches of regional policy of rural tourism development

The present work intends to study Rural Tourism. More specifically: regional policy of Rural Tourism development. Purpose of this research is creation of innovative qualitative model of regional policy of Rural Tourism development for Ukraine. With this aim literature review was made, developed a research methodology and analysis made. It was established a way of creation of qualitative model, based on studied information and scientific papers. Research methodology was described in next part. Decided to do it in three stages: (1) justification of analytical research; (2) data sample collection and analysis; (3) creating of innovative model of regional policy of Rural Tourism development. Each of these stages have sub stages supported by results of previous. In accordance to methodology, analytical part was made in two steps: (1) analysis of statistical information about rural houses availability; (2) analysis of resources needed for successfully Rural Tourism activity. This part gave information about placement of rural houses by geographical regions and defined most attractive geographical regions for Rural Tourism development. The results showed that the highest rural houses availability is in Western geographical region. Other regions have low level of rural houses availability. However, analysis of resources needed for successful Rural Tourism development showed, that all geographical regions are attractive for organizing Rural Tourism activity. Based on this information an innovative qualitative model of Rural Tourism development was created.

Shaping the Dicot Fruit: Molecular and Genomic Approaches to Fruit Development

The fruit is one of the most complex and important structures produced by flowering plants, and understanding the development and maturation process of fruits in different angiosperm species with diverse fruit structures is of immense interest. In the work presented here, molecular genetics and genomic analysis are used to explore the processes that form the fruit in two species: The model organism Arabidopsis and the diploid strawberry Fragaria vesca. One important basic question concerns the molecular genetic basis of fruit patterning. A long-standing model of Arabidopsis fruit (the gynoecium) patterning holds that auxin produced at the apex diffuses downward, forming a gradient that provides apical-basal positional information to specify different tissue types along the gynoecium’s length. The proposed gradient, however, has never been observed and the model appears inconsistent with a number of observations. I present a new, alternative model, wherein auxin acts to establish the adaxial-abaxial domains of the carpel primordia, which then ensures proper development of the final gynoecium. A second project utilizes genomics to identify genes that regulate fruit color by analyzing the genome sequences of Fragaria vesca, a species of wild strawberry. Shared and distinct SNPs among three F. vesca accessions were identified, providing a foundation for locating candidate mutations underlying phenotypic variations among different F. vesca accessions. Through systematic analysis of relevant SNP variants, a candidate SNP in FveMYB10 was identified that may underlie the fruit color in the yellow-fruited accessions, which was subsequently confirmed by functional assays. Our lab has previously generated extensive RNA-sequencing data that depict genome-scale gene expression profiles in F. vesca fruit and flower tissues at different developmental stages. To enhance the accessibility of this dataset, the web-based eFP software was adapted for this dataset, allowing visualization of gene expression in any tissues by user-initiated queries. Together, this thesis work proposes a well-supported new model of fruit patterning in Arabidopsis and provides further resources for F. vesca, including genome-wide variant lists and the ability to visualize gene expression. This work will facilitate future work linking traits of economic importance to specific genes and gaining novel insights into fruit patterning and development.

Exact solutions for the agricultural and the two-dimensional packing problems

Objectives and study method: The objective of this study is to develop exact algorithms that can be used as management tools for the agricultural production planning and to obtain exact solutions for two of the most well known twodimensional packing problems: the strip packing problem and the bin packing problem. For the agricultural production planning problem we propose a new hierarchical scheme of three stages to improve the current agricultural practices. The objective of the first stage is to delineate rectangular and homogeneous management zones into the farmer’s plots considering the physical and chemical soil properties. This is an important task because the soil properties directly affect the agricultural production planning. The methodology for this stage is based on a new method called “Positions and Covering” that first generates all the possible positions in which the plot can be delineated. Then, we use a mathematical model of linear programming to obtain the optimal physical and chemical management zone delineation of the plot. In the second stage the objective is to determine the optimal crop pattern that maximizes the farmer’s profit taken into account the previous management zones delineation. In this case, the crop pattern is affected by both management zones delineation, physical and chemical. A mixed integer linear programming is used to solve this stage. The objective of the last stage is to determine in real-time the amount of water to irrigate in each crop. This stage takes as input the solution of the crop planning stage, the atmospheric conditions (temperature, radiation, etc.), the humidity level in plots, and the physical management zones of plots, just to name a few. This procedure is made in real-time during each irrigation period. A linear programming is used to solve this problem. A breakthrough happen when we realize that we could propose some adaptations of the P&C methodology to obtain optimal solutions for the two-dimensional packing problem and the strip packing. We empirically show that our methodologies are efficient on instances based on real data for both problems: agricultural and two-dimensional packing problems. Contributions and conclusions: The exact algorithms showed in this study can be used in the making-decision support for agricultural planning and twodimensional packing problems. For the agricultural planning problem, we show that the implementation of the new hierarchical approach can improve the farmer profit between 5.27% until 8.21% through the optimization of the natural resources. An important characteristic of this problem is that the soil properties (physical and chemical) and the real-time factors (climate, humidity level, evapotranspiration, etc.) are incorporated. With respect to the two-dimensional packing problems, one of the main contributions of this study is the fact that we have demonstrate that many of the best solutions founded in literature by others approaches (heuristics approaches) are the optimal solutions. This is very important because some of these solutions were up to now not guarantee to be the optimal solutions.

Characterization and age determination of Quaternary volcanism in the southern Ankaratra region (central Madagascar) through novel approaches in luminescence dating

This work introduces two novel approaches for the application of luminescence dating techniques to Quaternary volcanic eruptions: crystalline xenoliths from lava flows are demonstrated to be basically suitable for luminescence dating, and a set of phreatic explosion deposits from the Late Quaternary Vakinankaratra volcanic field in central Madagascar is successfully dated with infrared stimulated luminescence (IRSL). Using a numerical model approach and experimental verification, the potential for thermal resetting of luminescence signals of xenoliths in lava flows is demonstrated. As microdosimetry is an important aspect when using sample material extracted from crystalline whole rocks, autoradiography using image plates is introduced to the field of luminescence dating as a method for detection and assessment of spatially resolved radiation inhomogeneities. Determinations of fading rates of feldspar samples have been observed to result in aberrant g-values if the pause between preheat and measurement in the delayed measurements was kept short. A systematic investigation reveals that the phenomenon is caused by the presence of three signal components with differing individual fading behaviour. As this is restricted to short pauses, it is possible to determine a minimal required delay between preheating and measurement after which the aberrant behaviour disappears. This is applied in the measuring of 12 samples from phreatic explosion deposits from the Antsirabe – Betafo region in the Late Quaternary Vakinankaratra volcanic field. The samples were taken from stratigraphically correlatable sections and appear to represent at least three phreatic events, one of which created the Lac Andraikiba maar near Antsirabe. The obtained ages indicate that the eruptive activity in the region started in the Late Pleistocene between 113.9 and 99.6 ka. A second layer in the Betafo area is dated at approximately 73 ka and the Lac Andraikiba deposits give an age between 63.9 and 50.7 ka. The youngest phreatic layer is dated between 33.7 and 20.7 ka. These ages are the first recorded direct ages of such volcanic deposits, as well as the first and only direct ages for the Late Quaternary volcanism in the Vakinankaratra volcanic field. This illustrates the huge potential of this new method for volcanology and geochronology, as it enables direct numerical dating of a type of volcanic deposit which has not been successfully directly dated by any other method so far.

Synthetic approaches to flexible fluorescent conjugated polymers

Conjugated polymers (CPs) are intrinsically fluorescent materials that have been used for various biological applications including imaging, sensing, and delivery of biologically active substances. The synthetic control over flexibility and biodegradability of these materials aids the understanding of the structure-function relationships among the photophysical properties, the self-assembly behaviors of the corresponding conjugated polymer nanoparticles (CPNs), and the cellular behaviors of CPNs, such as toxicity, cellular uptake mechanisms, and sub-cellular localization patterns. ^ Synthetic approaches towards two classes of flexible CPs with well-preserved fluorescent properties are described. The synthesis of flexible poly( p-phenylenebutadiynylene)s (PPBs) uses competing Sonogashira and Glaser coupling reactions and the differences in monomer reactivity to incorporate a small amount (∼10%) of flexible, non-conjugated linkers into the backbone. The reaction conditions provide limited control over the proportion of flexible monomer incorporation. Improved synthetic control was achieved in a series of flexible poly(p-phenyleneethynylene)s (PPEs) using modified Sonogashira conditions. In addition to controlling the degree of flexibility, the linker provides disruption of backbone conjugation that offers control of the length of conjugated segments within the polymer chain. Therefore, such control also results in the modulation of the photophysical properties of the materials. ^ CPNs fabricated from flexible PPBs are non-toxic to cells, and exhibit subcellular localization patterns clearly different from those observed with non-flexible PPE CPNs. The subcellular localization patterns of the flexible PPEs have not yet been determined, due to the toxicity of the materials, most likely related to the side-chain structure used in this series. ^ The study of the effect of CP flexibility on self-assembly reorganization upon polyanion complexation is presented. Owing to its high rigidity and hydrophobicity, the PPB backbone undergoes reorganization more readily than PPE. The effects are enhanced in the presence of the flexible linker, which enables more efficient π-π stacking of the aromatic backbone segments. Flexibility has minimal effects on the self-assembly of PPEs. Understanding the role of flexibility on the biophysical behaviors of CPNs is key to the successful development of novel efficient fluorescent therapeutic delivery vehicles.^

A cautionary tale of two ‘tigers’: Industrial policy ‘lessons’ from Ireland and Hungary?

This paper draws industrial policy lessons for small Central and Eastern European states through a critical evaluation of recent Irish and Hungarian experiences. The paper outlines a ‘holistic view’ of industrial policy before exploring the experiences of the two economies. Whilst both have managed to ‘do’ policy well in some regards, substantial challenges remain in making FDI attraction the centrepiece of industrial policy, as has been highlighted recently. Overall, the paper suggests that wholesale emulation of the Irish and Hungarian approach is problematic for small open CEE states, and that more balanced approaches to development - and hence industrial policy – are warranted.

Development of molecular approaches to assess the diversity and abundance of marine nematodes assemblages for assessment of Good Environmental Status of the estuarine and marine ecosystems

In Europe, the concerns with the status of marine ecosystems have increased, and the Marine Directive has as main goal the achievement of Good Environmental Status (GES) of EU marine waters by 2020. Molecular tools are seen as promising and emerging approaches to improve ecosystem monitoring, and have led ecology into a new era, representing perhaps the most source of innovation in marine monitoring techniques. Benthic nematodes are considered ideal organisms to be used as biological indicator of natural and anthropogenic disturbances in aquatic ecosystems underpinning monitoring programmes on the ecological quality of marine ecosystems, very useful to assess the GES of the marine environment. dT-RFLP (directed Terminal-Restriction Fragment Length Polymorphism) allows to assess the diversity of nematode communities, but also allows studying the functioning of the ecosystem, and combined with relative real-time PCR (qPCR), provides a high-throughput semi-quantitative characterization of nematode communities. These characteristics make the two molecular tools good descriptors for the good environmental status assessment. The main aim of this study is to develop and optimize the dT-RFLP and qPCR in Mira estuary (SW coast, Portugal). A molecular phylogenetic analysis of marine and estuarine nematodes is being performed combining morphological and molecular analysis to evaluate the diversity of free-living marine nematodes in Mira estuary. After morphological identification, barcoding of 18S rDNA and COI genes are being determined for each nematode species morphologically identified. So far we generated 40 new sequences belonging to 32 different genus and 17 families, and the study has shown a good degree of concordance between traditional morphology-based identification and DNA sequences. These results will improve the assessment of marine nematode diversity and contribute to a more robust nematode taxonomy. The DNA sequences are being used to develop the dT-RFLP with the ability to easily process large sample numbers (hundreds and thousands), rather than typical of classical taxonomic or low throughput molecular analyses. A preliminary study showed that the digest enzymes used in dT-RFLP for terrestrial assemblages separated poorly the marine nematodes at taxonomic level for functional group analysis. A new digest combination was designed using the software tool DRAT (Directed Terminal Restriction Analysis Tool) to distinguished marine nematode taxa. Several solutions were provided by DRAT and tested empirically to select the solution that cuts most efficiently. A combination of three enzymes and a single digest showed to be the best solution to separate the different clusters. Parallel to this, another tool is being developed to estimate the population size (qPCR). An improvement in qPCR estimation of gene copy number using an artificial reference is being performed for marine nematodes communities to quantify the abundance. Once developed, it is proposed to validate both methodologies by determining the spatial and temporal variability of benthic nematodes assemblages across different environments. The application of these high-throughput molecular approaches for benthic nematodes will improve sample throughput and their implementation more efficient and faster as indicator of ecological status of marine ecosystems.

Innovative therapeutic approaches for the atrophic Age-related Macular Degeneration (“dry” AMD)

Age related macular degeneration (AMD) is a major concern regarding blindness in the world. In western countries, where visual alterations due to minor pathologies as cataract and uncorrected refractive errors are easily resolved, AMD represent the main cause of blindness. Of the two existing forms of the disease, while the neovascular is more aggressive and progress quickly, geographic atrophy is the one still lacking an appropriate therapy. My PhD program was focused on investigating AMD features, trying to understand if some approaches I tested could be able to provide some suggestion about potential future therapies on “dry” AMD. In my research I developed three main projects. The most important part of the work regards the study of integrins and their fundamental role in cell adhesion in a context of interaction between retinal pigmented epithelium (RPE) and immune cells. I investigated how co-culture of these different cell lines can lead to simulate an inflammatory state inducing cell signaling, cytokine production and cell death. The use of integrin antagonists developed in our laboratory, showed how these effects can be reverted. A secondary approach regards the use of antioxidants and their role in epigenetic modifications in ARPE-19 cells to investigate how these compounds might exert their well-known protective role on AMD. Commonly used antioxidants as Lutein and Quercetin do not induce clear epigenetic modifications through histone H3 acetylation indicating only a limited involvement.

Analytical instrumental approaches and strategies to support the sensory assessment of virgin olive oils

At the beginning, this Ph.D. project led to an overview of the most common and emerging types of fraud and possible countermeasures in the olive oil sector. Furthermore, possible weaknesses in the current conformity check system for olive oil were highlighted. Among those, despite the organoleptic assessment is a fundamental tool for establishing the virgin olive oils (VOOs) quality grade, the scientific community has evidenced some drawbacks in it. In particular, the application of instrumental screening methods to support the panel test could reduce the work of sensory panels and the cost of this analysis (e.g. for industries, distributors, public and private control laboratories), permitting the increase in the number and the efficiency of the controls. On this basis, a research line called “Quantitative Panel Test” is one of the main expected outcomes of the OLEUM project that is also partially discussed in this doctoral dissertation. In this framework, analytical activities were carried out, within this PhD project, aimed to develop and validate analytical protocols for the study of the profiles in volatile compounds (VOCs) of the VOOs headspace. Specifically, two chromatographic approaches, one targeted and one semi-targeted, to determine VOCs were investigated in this doctoral thesis. The obtained results, will allow the possible establishment of concentration limits and ranges of selected volatile markers, as related to fruitiness and defects, with the aim to support the panel test in the commercial categorization of VOOs. In parallel, a rapid instrumental screening method based on the analysis of VOCs has been investigated to assist the panel test through a fast pre-classification of VOOs samples based on a known level of probability, thus increasing the efficiency of quality control.

Characterization of DNA sequence properties through network and statistical approaches

In this thesis we will see that the DNA sequence is constantly shaped by the interactions with its environment at multiple levels, showing footprints of DNA methylation, of its 3D organization and, in the case of bacteria, of the interaction with the host organisms. In the first chapter, we will see that analyzing the distribution of distances between consecutive dinucleotides of the same type along the sequence, we can detect epigenetic and structural footprints. In particular, we will see that CG distance distribution allows to distinguish among organisms of different biological complexity, depending on how much CG sites are involved in DNA methylation. Moreover, we will see that CG and TA can be described by the same fitting function, suggesting a relationship between the two. We will also provide an interpretation of the observed trend, simulating a positioning process guided by the presence and absence of memory. In the end, we will focus on TA distance distribution, characterizing deviations from the trend predicted by the best fitting function, and identifying specific patterns that might be related to peculiar mechanical properties of the DNA and also to epigenetic and structural processes. In the second chapter, we will see how we can map the 3D structure of the DNA onto its sequence. In particular, we devised a network-based algorithm that produces a genome assembly starting from its 3D configuration, using as inputs Hi-C contact maps. Specifically, we will see how we can identify the different chromosomes and reconstruct their sequences by exploiting the spectral properties of the Laplacian operator of a network. In the third chapter, we will see a novel method for source clustering and source attribution, based on a network approach, that allows to identify host-bacteria interaction starting from the detection of Single-Nucleotide Polymorphisms along the sequence of bacterial genomes.

Urban air quality: new high-resolution modeling approaches and forecasting tools for citizens

Air pollution is one of the greatest health risks in the world. At the same time, the strong correlation with climate change, as well as with Urban Heat Island and Heat Waves, make more intense the effects of all these phenomena. A good air quality and high levels of thermal comfort are the big goals to be reached in urban areas in coming years. Air quality forecast help decision makers to improve air quality and public health strategies, mitigating the occurrence of acute air pollution episodes. Air quality forecasting approaches combine an ensemble of models to provide forecasts from global to regional air pollution and downscaling for selected countries and regions. The development of models dedicated to urban air quality issues requires a good set of data regarding the urban morphology and building material characteristics. Only few examples of air quality forecast system at urban scale exist in the literature and often they are limited to selected cities. This thesis develops by setting up a methodology for the development of a forecasting tool. The forecasting tool can be adapted to all cities and uses a new parametrization for vegetated areas. The parametrization method, based on aerodynamic parameters, produce the urban spatially varying roughness. At the core of the forecasting tool there is a dispersion model (urban scale) used in forecasting mode, and the meteorological and background concentration forecasts provided by two regional numerical weather forecasting models. The tool produces the 1-day spatial forecast of NO2, PM10, O3 concentration, the air temperature, the air humidity and BLQ-Air index values. The tool is automatized to run every day, the maps produced are displayed on the e-Globus platform, updated every day. The results obtained indicate that the forecasting output were in good agreement with the observed measurements.

Big Code Applications and Approaches

The availability of a huge amount of source code from code archives and open-source projects opens up the possibility to merge machine learning, programming languages, and software engineering research fields. This area is often referred to as Big Code where programming languages are treated instead of natural languages while different features and patterns of code can be exploited to perform many useful tasks and build supportive tools. Among all the possible applications which can be developed within the area of Big Code, the work presented in this research thesis mainly focuses on two particular tasks: the Programming Language Identification (PLI) and the Software Defect Prediction (SDP) for source codes. Programming language identification is commonly needed in program comprehension and it is usually performed directly by developers. However, when it comes at big scales, such as in widely used archives (GitHub, Software Heritage), automation of this task is desirable. To accomplish this aim, the problem is analyzed from different points of view (text and image-based learning approaches) and different models are created paying particular attention to their scalability. Software defect prediction is a fundamental step in software development for improving quality and assuring the reliability of software products. In the past, defects were searched by manual inspection or using automatic static and dynamic analyzers. Now, the automation of this task can be tackled using learning approaches that can speed up and improve related procedures. Here, two models have been built and analyzed to detect some of the commonest bugs and errors at different code granularity levels (file and method levels). Exploited data and models’ architectures are analyzed and described in detail. Quantitative and qualitative results are reported for both PLI and SDP tasks while differences and similarities concerning other related works are discussed.