Phenotype and genotype characterization of Monilinia spp. isolates and preformed antifungal compounds in peach peel fruit at different developmental stages

The brown rot fungi belong to a group of fungal pathogens that causes considerable damage to cultivated fruits trees, particularly stone fruits and apples in the temperate regions of the World and during the postharvest with an important economic impact. In particular in Italy, it is important to monitor the Monilinia population to control economic losses associated to the peach and nectarine market. This motivates the research steps presented in this dissertation on Monilinia Italian isolates. The Monilinia species collected from stone fruits have been identified using molecular analysis based on specific primers. The relevant role of M. fructicola was confirmed and, for the first time, it was found also on apple fruits. To avoid the development of resistant strains and implement valid treatment strategies, the understanding of the fruit natural resistance during different developmental stages and the assessment of the Monilinia sensitivity/resistance to fungicides are required. The relationship between the inhibition spots and the phenolic compounds in peach fruit peel was highlighted in this research. Three methods were used to assess isolate resistance/sensitivity, the amended medium, the Spiral Gradient Endpoint Method (SGD) and the Alamar Blue method. The PCR was used to find possible mutation points in the b-tubulin gene that is responsible for fungicide resistance. Interestingly, no mutation points were observed in resistant M. laxa isolates, suggesting that the resistance could be stimulated by environmental factors. This lead to the study of the effect of the temperature on the resistance and the preliminary results of in vitro tests showed that maximum inhibition was observed at 30°C.

Automated Analysis Methods for the Assessment of Bicycle Infrastructure and Demand

A first phase of the research activity has been related to the study of the state of art of the infrastructures for cycling, bicycle use and methods for evaluation. In this part, the candidate has studied the "bicycle system" in countries with high bicycle use and in particular in the Netherlands. Has been carried out an evaluation of the questionnaires of the survey conducted within the European project BICY on mobility in general in 13 cities of the participating countries. The questionnaire was designed, tested and implemented, and was later validated by a test in Bologna. The results were corrected with information on demographic situation and compared with official data. The cycling infrastructure analysis was conducted on the basis of information from the OpenStreetMap database. The activity consisted in programming algorithms in Python that allow to extract data from the database infrastructure for a region, to sort and filter cycling infrastructure calculating some attributes, such as the length of the arcs paths. The results obtained were compared with official data where available. The structure of the thesis is as follows: 1. Introduction: description of the state of cycling in several advanced countries, description of methods of analysis and their importance to implement appropriate policies for cycling. Supply and demand of bicycle infrastructures. 2. Survey on mobility: it gives details of the investigation developed and the method of evaluation. The results obtained are presented and compared with official data. 3. Analysis cycling infrastructure based on information from the database of OpenStreetMap: describes the methods and algorithms developed during the PhD. The results obtained by the algorithms are compared with official data. 4. Discussion: The above results are discussed and compared. In particular the cycle demand is compared with the length of cycle networks within a city. 5. Conclusions

DNA hybrid materials consisting of oligonucleotides and organic molecules: synthesis, characterization and applications

The goal of this thesis was to increase the functionality of pristine DNA scaffolds by functionalizing them with fluorescent dyes and hydrophobic moieties. Two important steps were necessary to realize this aim successfully. First, nucleic acids needed to be synthesized making use of multidisciplinary toolbox for the generation and manipulation of polynucleic acids. The most important techniques were the solid phase synthesis involving the incorporation of standard and modified phosphoramidite building blocks as well as molecular biology procedures like the polymerase chain reaction, the bacterial amplification of plasmids and the enzymatic digestion of circular vectors. Second, and evenly important, was the characterization of the novel bioorganic hybrid structures by a multitude of techniques, especially optical measurements. For studying DNA-dye conjugates methods like UV/Vis and photoluminescence spectroscopy as well as time resolved luminescence spectroscopy were utilized. While these measurements characterized the bulk behavior of an ensemble of DNA-dye hybrids it was necessary for a complete understanding of the systems to look at single structures. This was done by single-molecule fluorescence spectroscopy and fluorescence correlation spectroscopy. For complete analysis the optical experiments were complemented by direct visualization techniques, i.e. high resolution transmission electron microscopy and scanning force microscopy.

A soft-tetramer model for diblock copolymer melts: structure formation and geometric characterization

The ability of block copolymers to spontaneously self-assemble into a variety of ordered nano-structures not only makes them a scientifically interesting system for the investigation of order-disorder phase transitions, but also offers a wide range of nano-technological applications. The architecture of a diblock is the most simple among the block copolymer systems, hence it is often used as a model system in both experiment and theory. We introduce a new soft-tetramer model for efficient computer simulations of diblock copolymer melts. The instantaneous non-spherical shape of polymer chains in molten state is incorporated by modeling each of the two blocks as two soft spheres. The interactions between the spheres are modeled in a way that the diblock melt tends to microphase separate with decreasing temperature. Using Monte Carlo simulations, we determine the equilibrium structures at variable values of the two relevant control parameters, the diblock composition and the incompatibility of unlike components. The simplicity of the model allows us to scan the control parameter space in a completeness that has not been reached in previous molecular simulations.The resulting phase diagram shows clear similarities with the phase diagram found in experiments. Moreover, we show that structural details of block copolymer chains can be reproduced by our simple model.We develop a novel method for the identification of the observed diblock copolymer mesophases that formalizes the usual approach of direct visual observation,using the characteristic geometry of the structures. A cluster analysis algorithm is used to determine clusters of each component of the diblock, and the number and shape of the clusters can be used to determine the mesophase.We also employ methods from integral geometry for the identification of mesophases and compare their usefulness to the cluster analysis approach.To probe the properties of our model in confinement, we perform molecular dynamics simulations of atomistic polyethylene melts confined between graphite surfaces. The results from these simulations are used as an input for an iterative coarse-graining procedure that yields a surface interaction potential for the soft-tetramer model. Using the interaction potential derived in that way, we perform an initial study on the behavior of the soft-tetramer model in confinement. Comparing with experimental studies, we find that our model can reflect basic features of confined diblock copolymer melts.

Complex chemical dynamics through engineering-like methods

Most of the problems in modern structural design can be described with a set of equation; solutions of these mathematical models can lead the engineer and designer to get info during the design stage. The same holds true for physical-chemistry; this branch of chemistry uses mathematics and physics in order to explain real chemical phenomena. In this work two extremely different chemical processes will be studied; the dynamic of an artificial molecular motor and the generation and propagation of the nervous signals between excitable cells and tissues like neurons and axons. These two processes, in spite of their chemical and physical differences, can be both described successfully by partial differential equations, that are, respectively the Fokker-Planck equation and the Hodgkin and Huxley model. With the aid of an advanced engineering software these two processes have been modeled and simulated in order to extract a lot of physical informations about them and to predict a lot of properties that can be, in future, extremely useful during the design stage of both molecular motors and devices which rely their actions on the nervous communications between active fibres.

Advanced lithium battery chemistries for sustainable transportation

The specific energy of lithium-ion batteries (LIBs) is today 200 Wh/kg, a value not sufficient to power fully electric vehicles with a driving range of 400 km which requires a battery pack of 90 kWh. To deliver such energy the battery weight should be higher than 400 kg and the corresponding increase of vehicle mass would narrow the driving range to 280 km. Two main strategies are pursued to improve the energy of the rechargeable lithium batteries up to the transportation targets. The first is the increase of LIBs working voltage by using high-voltage cathode materials. The second is the increase of battery capacity by the development of a cell chemistry where oxygen redox reaction (ORR) occurs at the cathode and metal lithium is the anode (Li/O2 battery). This PhD work is focused on the development of high-voltage safe cathodes for LIBs, and on the investigation of the feasibility of Li/O2 battery operating with ionic liquid(IL)-based electrolytes. The use of LiMn1-xFexPO4 as high-voltage cathode material is discussed. Synthesis and electrochemical tests of three different phosphates, more safe cathode materials than transition metal oxides, are reported. The feasibility of Li/O2 battery operating in IL-based electrolytes is also discussed. Three aspects have been investigated: basic aspects of ORR, synthesis and characterization of porous carbons as positive electrode materials and study of limiting factors to the electrode capacity and cycle-life. Regarding LIBs, the findings on LiMnPO4 prepared by soluble precursors demonstrate that a good performing Mn-based olivine is viable without the coexistence of iron. Regarding Li/O2 battery, the oxygen diffusion coefficient and concentration values in different ILs were obtained. This work highlighted that the O2 mass transport limits the Li/O2 capacity at high currents; it gave indications on how to increase battery capacity by using a flow-cell and a porous carbon as cathode.

Silica-Supported Gold Nanoparticles: Synthesis, Characterization and Reactivity

The main aim of this work was the synthesis and applications of functionalized-silica-supported gold nanoparticles. The silica-anchored functionalities employed, e.g. amine, alkynyl carbamate and sulfide moieties, possess a notable affinity with gold, so that they could be able to capture the gold precursor, to spontaneously reduce it (possibly at room temperature), and to stabilize the resulting gold nanoparticles. These new materials, potentially suitable for heterogeneous catalysis applications, could represent a breakthrough among the “green” synthesis of supported gold nanoparticles, since they would circumvent the addition of extra reducing agent and stabilizers, also allowing concomitant absorption of the active catalyst particles on the support immediately after spontaneous formation of gold nanoparticles. In chapter 4 of this thesis is also presented the work developed during a seven-months Marco Polo fellowship stay at the University of Lille (France), regarding nanoparticles nucleation and growth inside a microfluidic system and the study of the corresponding mechanism by in situ XANES spectroscopy. Finally, studies regarding the reparation and reactivity of gold decorated nanodiamonds are also described. Various methods of characterization have been used, such as ultraviolet-visible spectroscopy (UV-Vis), Transmission Electron Microscopy (TEM), Dynamic Light Scattering (DLS), X-ray Fluorescence (XRF), Field Emission Gun Scanning Electron Microscopy (SEM-FEG), X-ray Photoionization (XPS), X ray Absorption Spectroscopy (XAS).

Rheology of arrested colloids : a parameter study using novel experimental methods

The steadily increasing diversity of colloidal systems demands for new theoretical approaches and a cautious experimental characterization. Here we present a combined rheological and microscopical study of colloids in their arrested state whereas we did not aim for a generalized treatise but rather focused on a few model colloids, liquid crystal based colloidal suspensions and sedimented colloidal films. We laid special emphasis on the understanding of the mutual influence of dominant interaction mechanisms, structural characteristics and the particle properties on the mechanical behavior of the colloid. The application of novel combinations of experimental techniques played an important role in these studies. Beside of piezo-rheometry we employed nanoindentation experiments and associated standardized analysis procedures. These rheometric methods were complemented by real space images using confocal microscopy. The flexibility of the home-made setup allowed for a combination of both techniques and thereby for a simultaneous rheological and three-dimensional structural analysis on a single particle level. Though, the limits of confocal microscopy are not reached by now. We show how hollow and optically anisotropic particles can be utilized to quantify contact forces and rotational motions for individual particles. In future such data can contribute to a better understanding of particle reorganization processes, such as the liquidation of colloidal gels and glasses under shear.

Methods and strategies to identify the mode of action of phytoactive compounds

Small molecules affecting biological processes in plants are widely used in agricultural practice as herbicides or plant growth regulators and in basic plant sciences as probes to study the physiology of plants. Most of the compounds were identified in large screens by the agrochemical industry, as phytoactive natural products and more recently, novel phytoactive compounds originated from academic research by chemical screens performed to induce specific phenotypes of interest. The aim of the present PhD thesis is to evaluate different approaches used for the identification of the primary mode of action (MoA) of a phytoactive compound. Based on the methodologies used for MoA identification, three approaches are discerned: a phenotyping approach, an approach based on a genetic screen and a biochemical screening approach.rnFour scientific publications resulting from my work are presented as examples of how a phenotyping approach can successfully be applied to describe the plant MoA of different compounds in detail.rnI. A subgroup of cyanoacrylates has been discovered as plant growth inhibitors. A set of bioassays indicated a specific effect on cell division. Cytological investigations of the cell division process in plant cell cultures, studies of microtubule assembly with green fluorescent protein marker lines in vivo and cross resistant studies with Eleusine indica plants harbouring a mutation in alpha-tubulin, led to the description of alpha-tubulin as a target site of cyanoacrylates (Tresch et al., 2005).rnII. The MoA of the herbicide flamprop-m-methyl was not known so far. The studies described in Tresch et al. (2008) indicate a primary effect on cell division. Detailed studies unravelled a specific effect on mitotic microtubule figures, causing a block in cell division. In contrast to other inhibitors of microtubule rearrangement such as dinitroanilines, flamprop-m-methyl did not influence microtubule assembly in vitro. An influence of flamprop-m-methyl on a target within the cytoskeleton signalling network could be proposed (Tresch et al., 2008).rnIII. The herbicide endothall is a protein phosphatase inhibitor structurally related to the natural product cantharidin. Bioassay studies indicated a dominant effect on dark-growing cells that was unrelated to effects observed in the light. Cytological characterisation of the microtubule cytoskeleton in corn tissue and heterotrophic tobacco cells showed a specific effect of endothall on mitotic spindle formation and ultrastructure of the nucleus in combination with a decrease of the proliferation index. The observed effects are similar to those of other protein phosphatase inhibitors such as cantharidin and the structurally different okadaic acid. Additionally, the observed effects show similarities to knock-out lines of the TON1 pathway, a protein phosphatase-regulated signalling pathway. The data presented in Tresch et al. (2011) associate endothall’s known in vitro inhibition of protein phosphatases with in vivo-effects and suggest an interaction between endothall and the TON1 pathway.rnIV. Mefluidide as a plant growth regulator induces growth retardation and a specific phenotype indicating an inhibition of fatty acid biosynthesis. A test of the cuticle functionality suggested a defect in the biosynthesis of very-long-chain fatty acids (VLCFA) or waxes. Metabolic profiling studies showed similarities with different groups of VLCFA synthesis inhibitors. Detailed analyses of VLCFA composition in tissues of duckweed (Lemna paucicostata) indicated a specific inhibition of the known herbicide target 3 ketoacyl-CoA synthase (KCS). Inhibitor studies using a yeast expression system established for plant KCS proteins verified the potency of mefluidide as an inhibitor of plant KCS enzymes. It could be shown that the strength of inhibition varied for different KCS homologues. The Arabidopsis Cer6 protein, which induces a plant growth phenotype similar to mefluidide when knocked out, was one of the most sensitive KCS enzymes (Tresch et al., 2012).rnThe findings of my own work were combined with other publications reporting a successful identification of the MoA and primary target proteins of different compounds or compound classes.rnA revised three-tier approach for the MoA identification of phytoactive compounds is proposed. The approach consists of a 1st level aiming to address compound stability, uniformity of effects in different species, general cytotoxicity and the effect on common processes like transcription and translation. Based on these findings advanced studies can be defined to start the 2nd level of MoA characterisation, either with further phenotypic characterisation, starting a genetic screen or establishing a biochemical screen. At the 3rd level, enzyme assays or protein affinity studies should show the activity of the compound on the hypothesized target and should associate the in vitro effects with the in vivo profile of the compound.

Secondary Microseisms Characterization and Green’s Function Extraction at the Larderello-Travale Geothermal Field (Italy)

Over the past ten years, the cross-correlation of long-time series of ambient seismic noise (ASN) has been widely adopted to extract the surface-wave part of the Green’s Functions (GF). This stochastic procedure relies on the assumption that ASN wave-field is diffuse and stationary. At frequencies <1Hz, the ASN is mainly composed by surface-waves, whose origin is attributed to the sea-wave climate. Consequently, marked directional properties may be observed, which call for accurate investigation about location and temporal evolution of the ASN-sources before attempting any GF retrieval. Within this general context, this thesis is aimed at a thorough investigation about feasibility and robustness of the noise-based methods toward the imaging of complex geological structures at the local (∼10-50km) scale. The study focused on the analysis of an extended (11 months) seismological data set collected at the Larderello-Travale geothermal field (Italy), an area for which the underground geological structures are well-constrained thanks to decades of geothermal exploration. Focusing on the secondary microseism band (SM;f>0.1Hz), I first investigate the spectral features and the kinematic properties of the noise wavefield using beamforming analysis, highlighting a marked variability with time and frequency. For the 0.1-0.3Hz frequency band and during Spring- Summer-time, the SMs waves propagate with high apparent velocities and from well-defined directions, likely associated with ocean-storms in the south- ern hemisphere. Conversely, at frequencies >0.3Hz the distribution of back- azimuths is more scattered, thus indicating that this frequency-band is the most appropriate for the application of stochastic techniques. For this latter frequency interval, I tested two correlation-based methods, acting in the time (NCF) and frequency (modified-SPAC) domains, respectively yielding esti- mates of the group- and phase-velocity dispersions. Velocity data provided by the two methods are markedly discordant; comparison with independent geological and geophysical constraints suggests that NCF results are more robust and reliable.

Synthesis and characterization of hydroxyapatite modified with (9r)-9-hydroxystearic acid

(9R)-9-hydroxystearic acid (9R-HSA) has been proven to have antitumoral activity because it is shown to inhibit histone deacetylase 1, an enzyme which activates DNA replication, and the (R)-enantiomer has been shown to be more active than the (S)-enantiomer both in vitro and by molecular docking. Hydroxyapatite is the main mineral component of bone and teeth and has been used for over 20 years in prostheses and their coating because it is biocompatible and bioactive. The goal of incorporating 9R-HSA into hydroxyapatite is to have a material that combines the bioactivity of HA with the antitumoral properties of 9R-HSA. In this work, 9R-HSA and its potassium salt were synthesized and the latter was also incorporated into hydroxyapatite. The content of (R)-9-hydroxystearate ion incorporated into the apatitic structure was shown to be a function of its concentration in solution and can reach values higher than 8.5%. (9R)-9-hydroxystearic acid modified hydroxyapatite was extensively characterized to determine the effect of the incorporation of the organic molecule. This incorporation does not significantly alter the unit cell but reduces the size of both the crystals as well as the coherent domains, mainly along the a-axis of hydroxyapatite. This is believed to be due to the coordination of the negatively charged carboxylate group to the calcium ions which are more exposed on the (100) face of the crystal, therefore limiting the growth mainly in this direction. Further analyses showed that the material becomes hydrophobic and more negatively charged with the addition of 9R-HSA but both of these properties reach a plateau at less than 5% wt of 9R-HSA.

Sustainable improvement of water networks : to achieve best decisions for rehabilitation plans using advanced GIS and statistical techniques

Many of developing countries are facing crisis in water management due to increasing of population, water scarcity, water contaminations and effects of world economic crisis. Water distribution systems in developing countries are facing many challenges of efficient repair and rehabilitation since the information of water network is very limited, which makes the rehabilitation assessment plans very difficult. Sufficient information with high technology in developed countries makes the assessment for rehabilitation easy. Developing countries have many difficulties to assess the water network causing system failure, deterioration of mains and bad water quality in the network due to pipe corrosion and deterioration. The limited information brought into focus the urgent need to develop economical assessment for rehabilitation of water distribution systems adapted to water utilities. Gaza Strip is subject to a first case study, suffering from severe shortage in the water supply and environmental problems and contamination of underground water resources. This research focuses on improvement of water supply network to reduce the water losses in water network based on limited database using techniques of ArcGIS and commercial water network software (WaterCAD). A new approach for rehabilitation water pipes has been presented in Gaza city case study. Integrated rehabilitation assessment model has been developed for rehabilitation water pipes including three components; hydraulic assessment model, Physical assessment model and Structural assessment model. WaterCAD model has been developed with integrated in ArcGIS to produce the hydraulic assessment model for water network. The model have been designed based on pipe condition assessment with 100 score points as a maximum points for pipe condition. As results from this model, we can indicate that 40% of water pipeline have score points less than 50 points and about 10% of total pipes length have less than 30 score points. By using this model, the rehabilitation plans for each region in Gaza city can be achieved based on available budget and condition of pipes. The second case study is Kuala Lumpur Case from semi-developed countries, which has been used to develop an approach to improve the water network under crucial conditions using, advanced statistical and GIS techniques. Kuala Lumpur (KL) has water losses about 40% and high failure rate, which make severe problem. This case can represent cases in South Asia countries. Kuala Lumpur faced big challenges to reduce the water losses in water network during last 5 years. One of these challenges is high deterioration of asbestos cement (AC) pipes. They need to replace more than 6500 km of AC pipes, which need a huge budget to be achieved. Asbestos cement is subject to deterioration due to various chemical processes that either leach out the cement material or penetrate the concrete to form products that weaken the cement matrix. This case presents an approach for geo-statistical model for modelling pipe failures in a water distribution network. Database of Syabas Company (Kuala Lumpur water company) has been used in developing the model. The statistical models have been calibrated, verified and used to predict failures for both networks and individual pipes. The mathematical formulation developed for failure frequency in Kuala Lumpur was based on different pipeline characteristics, reflecting several factors such as pipe diameter, length, pressure and failure history. Generalized linear model have been applied to predict pipe failures based on District Meter Zone (DMZ) and individual pipe levels. Based on Kuala Lumpur case study, several outputs and implications have been achieved. Correlations between spatial and temporal intervals of pipe failures also have been done using ArcGIS software. Water Pipe Assessment Model (WPAM) has been developed using the analysis of historical pipe failure in Kuala Lumpur which prioritizing the pipe rehabilitation candidates based on ranking system. Frankfurt Water Network in Germany is the third main case study. This case makes an overview for Survival analysis and neural network methods used in water network. Rehabilitation strategies of water pipes have been developed for Frankfurt water network in cooperation with Mainova (Frankfurt Water Company). This thesis also presents a methodology of technical condition assessment of plastic pipes based on simple analysis. This thesis aims to make contribution to improve the prediction of pipe failures in water networks using Geographic Information System (GIS) and Decision Support System (DSS). The output from the technical condition assessment model can be used to estimate future budget needs for rehabilitation and to define pipes with high priority for replacement based on poor condition. rn

Biochar characterization for its environmental and agricultural utilization. Occurrence, distribution and fate of labile organic carbon and polycyclic aromatic hydrocarbons

In this thesis the potential risks associated to the application of biochar in soil as well the stability of biochar were investigated. The study was focused on the potential risks arising from the occurrence of polycyclic aromatic hydrocarbons (PAHs) in biochar. An analytical method was developed for the determination of the 16 USEPA-PAHs in the original biochar and soil containing biochar. The method was successfully validated with a certified reference material for the soil matrix and compared with methods in use in other laboratories during a laboratory exercise within the EU-COST TD1107. The concentration of 16 USEPA-PAHs along with the 15 EU-PAHs, priority hazardous substances in food, was determined in a suite of currently available biochars for agricultural field applications derived from a variety of parent materials and pyrolysis conditions. Biochars analyzed contained the USEPA and some of the EU-PAHs at detectable levels ranging from 1.2 to 19 µg g-1. This method allowed investigating changes in PAH content and distribution in a four years study following biochar addition in soils in a vineyard (CNR-IBIMET). The results showed that biochar addition determined an increase of the amount of PAHs. However, the levels of PAHs in the soil remained within the maximum acceptable concentration for European countries. The vineyard soil performed by CNR-IBIMET was exploited to study the environmental stability of biochar and its impact on soil organic carbon. The stability of biochar was investigated by analytical pyrolysis (Py-GC-MS) and pyrolysis in the presence of hydrogen (HyPy). The findings showed that biochar amendment significantly influence soil stable carbon fraction concentration during the incubation period. Moreover, HyPy and Py-GC-MS were applied to biochars deriving from three different feedstock at two different pyrolysis temperatures. The results evidenced the influence of feedstock type and pyrolysis conditions on the degree of carbonisation.

Optimization of molecular and crystalline forms of drugs, agrochemicals, pesticides in relation to activity, bioavailability, patentability and to the fabrication of polymorphs, solvates, co-crystals with green chemistry methods

This doctorate was funded by the Regione Emilia Romagna, within a Spinner PhD project coordinated by the University of Parma, and involving the universities of Bologna, Ferrara and Modena. The aim of the project was: - Production of polymorphs, solvates, hydrates and co-crystals of active pharmaceutical ingredients (APIs) and agrochemicals with green chemistry methods; - Optimization of molecular and crystalline forms of APIs and pesticides in relation to activity, bioavailability and patentability. In the last decades, a growing interest in the solid-state properties of drugs in addition to their solution chemistry has blossomed. The achievement of the desired and/or the more stable polymorph during the production process can be a challenge for the industry. The study of crystalline forms could be a valuable step to produce new polymorphs and/or co-crystals with better physical-chemical properties such as solubility, permeability, thermal stability, habit, bulk density, compressibility, friability, hygroscopicity and dissolution rate in order to have potential industrial applications. Selected APIs (active pharmaceutical ingredients) were studied and their relationship between crystal structure and properties investigated, both in the solid state and in solution. Polymorph screening and synthesis of solvates and molecular/ionic co-crystals were performed according to green chemistry principles. Part of this project was developed in collaboration with chemical/pharmaceutical companies such as BASF (Germany) and UCB (Belgium). We focused on on the optimization of conditions and parameters of crystallization processes (additives, concentration, temperature), and on the synthesis and characterization of ionic co-crystals. Moreover, during a four-months research period in the laboratories of Professor Nair Rodriguez-Hormedo (University of Michigan), the stability in aqueous solution at the equilibrium of ionic co-crystals (ICCs) of the API piracetam was investigated, to understand the relationship between their solid-state and solution properties, in view of future design of new crystalline drugs with predefined solid and solution properties.

Learning Methods and Algorithms for Semantic Text Classification across Multiple Domains

Information is nowadays a key resource: machine learning and data mining techniques have been developed to extract high-level information from great amounts of data. As most data comes in form of unstructured text in natural languages, research on text mining is currently very active and dealing with practical problems. Among these, text categorization deals with the automatic organization of large quantities of documents in priorly defined taxonomies of topic categories, possibly arranged in large hierarchies. In commonly proposed machine learning approaches, classifiers are automatically trained from pre-labeled documents: they can perform very accurate classification, but often require a consistent training set and notable computational effort. Methods for cross-domain text categorization have been proposed, allowing to leverage a set of labeled documents of one domain to classify those of another one. Most methods use advanced statistical techniques, usually involving tuning of parameters. A first contribution presented here is a method based on nearest centroid classification, where profiles of categories are generated from the known domain and then iteratively adapted to the unknown one. Despite being conceptually simple and having easily tuned parameters, this method achieves state-of-the-art accuracy in most benchmark datasets with fast running times. A second, deeper contribution involves the design of a domain-independent model to distinguish the degree and type of relatedness between arbitrary documents and topics, inferred from the different types of semantic relationships between respective representative words, identified by specific search algorithms. The application of this model is tested on both flat and hierarchical text categorization, where it potentially allows the efficient addition of new categories during classification. Results show that classification accuracy still requires improvements, but models generated from one domain are shown to be effectively able to be reused in a different one.