Indagini in Deep Inference

La tesi è uno studio di alcuni aspetti della nuova metodologia “deep inference”, abbinato ad una rivisitazione dei concetti classici di proof theory, con l'aggiunta di alcuni risultati originali orientati ad una maggior comprensione dell'argomento, nonché alle applicazioni pratiche. Nel primo capitolo vengono introdotti, seguendo un approccio di stampo formalista (con alcuni spunti personali), i concetti base della teoria della dimostrazione strutturale – cioè quella che usa strumenti combinatoriali (o “finitistici”) per studiare le proprietà delle dimostrazioni. Il secondo capitolo focalizza l'attenzione sulla logica classica proposizionale, prima introducendo il calcolo dei sequenti e dimostrando il Gentzen Hauptsatz, per passare poi al calcolo delle strutture (sistema SKS), dimostrando anche per esso un teorema di eliminazione del taglio, appositamente adattato dall'autore. Infine si discute e dimostra la proprietà di località per il sistema SKS. Un percorso analogo viene tracciato dal terzo ed ultimo capitolo, per quanto riguarda la logica lineare. Viene definito e motivato il calcolo dei sequenti lineari, e si discute del suo corrispettivo nel calcolo delle strutture. L'attenzione qui è rivolta maggiormente al problema di definire operatori non-commutativi, che mettono i sistemi in forte relazione con le algebre di processo.

Genetic variability and structuring of deep Corallium rubrum (Linnaeus, 1758) populations

ABSTRACT Given the decline of shallow-water red coral populations resulting from over-exploitation and mass mortality events, deeper populations below 50 metres depth (mesophotic populations) are currently the most harvested; unfortunately, very little is known about their biology and ecology. The persistence of these populations is tightly linked to their adult density, reproductive success, larval dispersal and recruitment. Moreover, for their conservation, it is paramount understand processes such as connectivity within and among populations. Here, for the first time, genetic variability and structuring of Corallium rubrum populations collected in the Tyrrhenian Sea ranging from 58 to 118 metres were analyzed using ten microsatellite loci and two mitochondrial markers (mtMSH and MtC). The aims of the work were 1) to examine patterns of genetic diversity within each geographic area (Elba, Ischia and Praiano) and 2) to define population structuring at different spatial scales (from tens of metres to hundreds of kilometres). Based on microsatellite data set, significant deviations from Hardy-Weinberg equilibrium due to elevated heterozygote deficiencies were detected in all samples, probably related to the presence of null alleles and/or inbreeding, as was previously observed in shallow-water populations. Moreover, significant levels of genetic differentiation were observed at all spatial scale, suggesting a recent isolation of populations. Biological factors which act at small spatial scale and/or abiotic factors at larger scale (e.g. summer gyres or absence of suitable substrata for settlement) could determine this genetic isolation. Using mitochondrial markers, significant differences were found only at wider scale (between Tuscany and Campania regions). These results could be related to the different mutation rate of the molecular makers or to the occurrence of some historical links within regions. A significant isolation by distance pattern was then observed using both data sets, confirming the restricted larval dispersal capability of the species. Therefore, the hypothesis that deeper populations may act as a source of larvae helping recovery of threatened shallow-water populations is not proved. Conservation strategies have to take into account these results, and management plans of deep and currently harvested populations have to be defined at a regional or sub regional level, similarly to shallow-water populations. Nevertheless, further investigations should be needed to understand better the genetic structuring of this species in the mesophotic zone, e.g. extending studies to other Mediterranean deep-water populations.

Spatio-temporal variation of macrofaunal assemblages in the deep Blanes submarine canyon

The spatio-temporal variations in diversity and abundance of deep-sea macrofaunal assemblages (excluding meiofaunal taxa, as Nematoda, Copepoda and Ostracoda) from the Blanes Canyon (BC) and adjacent open slope are described. The Catalan Sea basin is characterized by the presence of numerous submarine canyons, which are globally acknowledged as biodiversity hot-spots, due to their disturbance regime and incremented conveying of organic matter. This area is subjected to local deep-sea fisheries activities, and to recurrent cold water cascading events from the shelf. The upper canyon (~900 m), middle slope (~1200 m) and lower slope (~1500 m) habitats were investigated during three different months (October 2008, May 2009 and September 2009). A total of 624 specimens belonging to 16 different taxa were found into 67 analyzed samples, which had been collected from the two study areas. Of these, Polychaeta, Mollusca and Crustacea were always the most abundant groups. As expected, the patterns of species diversity and evenness were different in time and space. Both in BC and open slope, taxa diversity and abundance are higher in the shallowest depth and lowest at -1500 m depth. This is probably due to different trophic regimes at these depths. The abundance of filter-feeders is higher inside BC than in the adjacent open slope, which is also related with an increment of predator polychaetes. Surface deposit-feeders are more abundant in the open slope than in BC, along with a decrement of filter-feeders and their predators. Probably these differences are due to higher quantities of suspended organic matter reaching the canyon. The multivariate analyses conducted on major taxa point out major differences effective taxa richness between depths and stations. In September 2009 the analyzed communities double their abundances, with a corresponding increase in richness of taxa. This could be related to a mobilizing event, like the release of accumulated food-supply in a nepheloid layer associated to the arrival of autumn. The highest abundance in BC is detected in the shallowest depth and in late summer (September), probably due to higher food availability caused by stronger flood events coming from Tordera River. The effects of such events seemed to involve adjacent open slope too. The nMDS conducted on major taxa abundance shows a slight temporal difference between the three campaigns samples, with a clear clustering between samples of Sept 09. All depth and all months were dominated by Polychaeta, which have been identified to family level and submitted to further analysis. Family richness have clearly minimum at the -1200 m depth of BC, highlighting the presence of a general impact affecting the populations in the middle slope. Three different matrices have been created, each with a different taxonomic level (All Taxa “AT”, Phylum Level “PL” and Polychaeta Families “PF”). Multivariate analysis (MDS, SIMPER) conducted on PL matrix showed a clear spatial differences between stations (BC and open slope) and depths. MDSs conducted on other two matrices (AT and PF) showed similar patterns, but different from PL analysis. A 2 nd stage analysis have been conducted to understand differences between different taxonomic levels, and PL level has been chosen as the most representative of variation. The faunal differences observed were explained by depth, station and season. All work has been accomplished in the Centre d’estudis avançats de Blanes (CEAB-CSIC), within the framework of Spanish PROMETEO project "Estudio Integrado de Cañones y Taludes PROfundos del MEdiTErráneo Occidental: un hábitat esencial", Ref. CTM2007-66316-C02- 01/MAR.

Mitigazione sequestro e stoccaggio di diossido di carbonio

The main objective of my thesis was the technical-economic feasibility of a system of electricity generation integrated with CCS. The policy framework for development processing is part of the recent attention that at the political level has been directed towards the use of CCS technologies with the aim of addressing the problems of actual climate change. Several technological options have been proposed to stabilize and reduce the atmospheric concentrations of carbon dioxide (CO2) among which, the most promising for IPPC (Intergovernmental Panel on Climate Change)are the CCS technologies (Carbon Capture and Storage & Carbon Capture and Sequestration). The remedy proposed for large stationary CO2 sources as thermoelectric power plants is to separate the flue gas capturing CO2 and to store it into deep subsurface geological formations (more than 800 meters of depth). In order to support the identification of potential CO2 storage reservoirs in Italy and in Europe by Geo Capacity(an European database) new studies are developing. From the various literature data analyzed shows that most of the CO2 emitted from large stationary sources comes from the processes of electricity generation (78% of total emissions) and from (about 60%) those using coal especially. The CCS have the objective of return "to the sender" , the ground, the carbon in oxidized form (CO2) after it has been burned by man starting from its reduced form (CH4, oil and coal), then the carbon dioxide is not a "pollutant" if injected into the subsurface, CO2 is an acid reagent that interacts with the rock, with underground fluid and the characteristics of the host rock. The results showed that the CCS technology are very urgent, because unfortunately there are too many industrial sources of CO2 in assets (power plants, refineries, cement plants, steel mills) in the world who are carrying too quickly the CO2 atmospheric concentration levels to values that aren't acceptable for our dear planet.

Hydrogeochemical characterization of Seehausen territory - Bremen

The aim of this thesis is to provide a geochemical characterization of the Seehausen territory (a neighborhood) of Bremen, Germany. In this territory it is hosted a landfill of dredged sediments coming both from Bremerhaven (North See) and Bremen harbor (directly on the river Weser). For this reason this work has been focused also on possible impacts of the landfill on the groundwaters (shallow and deep aquifer). The Seehausen landfill uses the dewatering technique to manage the dredged sediments: incoming sediments are put into dewatering fields until they are completely dried (it takes almost a year). Then they are randomly sampled and analyzed: if the pollutants content is acceptable, sediments are treated with other materials and used instead of raw material for embankment, bricks, etc., otherwise they are disposed in the landfill. During this work it has been made a study of the natural geology and hydrogeology of the whole area of interest, especially because it is characterized by ancient natural salt deposits. Then, together with the Geological Survey of Bremen and the Harbor Authority of Bremen there have been identified all useful piezometers for a monitoring net around the landfill. During the sampling campaign there have been collected data of the principal anions and cations, physical parameters and stable water isotopes. Data analysis has been focused particularly on Cl, Na, SO4 and EC because these parameters might be helpful to attribute geochemical trends to the landfill or to a natural background. Furthermore dataloggers have been installed for a month in some piezometers and EC, pressure, dissolved oxygen and temperature data have been collected. Finally there has been made a deep comparison between current and historical data (1996 – 2011) and between old interpolation maps and current ones in order to see time trends of the aquifer geochemistry.

Diversity of microbial communities at shallow-hydrothermal vents off Dominica, Lesser Antilles

Hydrothermal vents are often compared to desert oases, because of the presence of highly diverse and abundant biotic communities inhabiting these extreme environments. Nevertheless, the microbial communities associated with shallow-hydrothermal systems have been poorly studied. Hydrothermal activity at Dominica Island is quite well known under the geological and geochemical aspects, but no previous information existed about the microbial communities associated to this area. This thesis is therefore targeting the microbiology of hydrothermal sediments combining geochemical and molecular biological investigations, focusing on differences between hydrothermal vents and background (i.e. control) areas, and between hydrothermal sites. It was also intended to assess relationship between geochemical parameters and microbial diversity at the two hydrothermally impacted sites. Two shallow-sea hydrothermal vents located south-west off Dominica Island (Lesser Antilles) have been investigated in this study: Champagne Hot Springs and Soufriere Bay offshore vent. During this study, sediments for geochemical and molecular analyses were collected every 2 cm from the two impacted areas and from two control sites not associated with hydrothermal activity; in situ temperatures measurements were also taken every 5 cm deep in the sediment for all the sites. A geochemical characterization of the sediment porewater was performed through the analysis of several elements’ concentrations (i.e. H2S, Cl-, Br-, SO42-, Fe2+, Na+, K+, B+, Si+). Microbial communities at the different sites were studied by Automated Intergenic Spacer Analysis (ARISA). Inspection of the operational taxonomic units (OTUs) distribution was performed, as well as statistical analyses for communities’ structure and composition differences, and for changes of β-diversity along with sediment geochemistry. Data suggested that mixing between hydrothermal fluids and seawater results in distinct different environmental gradients and potential ecological niches between the two investigated hydrothermal vents, reflecting a difference in microbial community structures between them.

Darknet e deep web: Il lato oscuro del web per la privacy e la protezione dei dati

Un argomento di attualità è la privacy e la sicurezza in rete. La tesi, attraverso lo studio di diversi documenti e la sperimentazione di applicazioni per garantire l'anonimato, analizza la situazione attuale. La nostra privacy è compromessa e risulta importante una sensibilizzazione globale.

Segmentazione e categorizzazione di oggetti mediante immagini depth e deep learning

Questo lavoro è iniziato con uno studio teorico delle principali tecniche di classificazione di immagini note in letteratura, con particolare attenzione ai più diffusi modelli di rappresentazione dell’immagine, quali il modello Bag of Visual Words, e ai principali strumenti di Apprendimento Automatico (Machine Learning). In seguito si è focalizzata l’attenzione sulla analisi di ciò che costituisce lo stato dell’arte per la classificazione delle immagini, ovvero il Deep Learning. Per sperimentare i vantaggi dell’insieme di metodologie di Image Classification, si è fatto uso di Torch7, un framework di calcolo numerico, utilizzabile mediante il linguaggio di scripting Lua, open source, con ampio supporto alle metodologie allo stato dell’arte di Deep Learning. Tramite Torch7 è stata implementata la vera e propria classificazione di immagini poiché questo framework, grazie anche al lavoro di analisi portato avanti da alcuni miei colleghi in precedenza, è risultato essere molto efficace nel categorizzare oggetti in immagini. Le immagini su cui si sono basati i test sperimentali, appartengono a un dataset creato ad hoc per il sistema di visione 3D con la finalità di sperimentare il sistema per individui ipovedenti e non vedenti; in esso sono presenti alcuni tra i principali ostacoli che un ipovedente può incontrare nella propria quotidianità. In particolare il dataset si compone di potenziali ostacoli relativi a una ipotetica situazione di utilizzo all’aperto. Dopo avere stabilito dunque che Torch7 fosse il supporto da usare per la classificazione, l’attenzione si è concentrata sulla possibilità di sfruttare la Visione Stereo per aumentare l’accuratezza della classificazione stessa. Infatti, le immagini appartenenti al dataset sopra citato sono state acquisite mediante una Stereo Camera con elaborazione su FPGA sviluppata dal gruppo di ricerca presso il quale è stato svolto questo lavoro. Ciò ha permesso di utilizzare informazioni di tipo 3D, quali il livello di depth (profondità) di ogni oggetto appartenente all’immagine, per segmentare, attraverso un algoritmo realizzato in C++, gli oggetti di interesse, escludendo il resto della scena. L’ultima fase del lavoro è stata quella di testare Torch7 sul dataset di immagini, preventivamente segmentate attraverso l’algoritmo di segmentazione appena delineato, al fine di eseguire il riconoscimento della tipologia di ostacolo individuato dal sistema.

Deep learning for computer vision: a comparison between convolutional neural networks and hierarchical temporal memories on object recognition tasks

In recent years, Deep Learning techniques have shown to perform well on a large variety of problems both in Computer Vision and Natural Language Processing, reaching and often surpassing the state of the art on many tasks. The rise of deep learning is also revolutionizing the entire field of Machine Learning and Pattern Recognition pushing forward the concepts of automatic feature extraction and unsupervised learning in general. However, despite the strong success both in science and business, deep learning has its own limitations. It is often questioned if such techniques are only some kind of brute-force statistical approaches and if they can only work in the context of High Performance Computing with tons of data. Another important question is whether they are really biologically inspired, as claimed in certain cases, and if they can scale well in terms of "intelligence". The dissertation is focused on trying to answer these key questions in the context of Computer Vision and, in particular, Object Recognition, a task that has been heavily revolutionized by recent advances in the field. Practically speaking, these answers are based on an exhaustive comparison between two, very different, deep learning techniques on the aforementioned task: Convolutional Neural Network (CNN) and Hierarchical Temporal memory (HTM). They stand for two different approaches and points of view within the big hat of deep learning and are the best choices to understand and point out strengths and weaknesses of each of them. CNN is considered one of the most classic and powerful supervised methods used today in machine learning and pattern recognition, especially in object recognition. CNNs are well received and accepted by the scientific community and are already deployed in large corporation like Google and Facebook for solving face recognition and image auto-tagging problems. HTM, on the other hand, is known as a new emerging paradigm and a new meanly-unsupervised method, that is more biologically inspired. It tries to gain more insights from the computational neuroscience community in order to incorporate concepts like time, context and attention during the learning process which are typical of the human brain. In the end, the thesis is supposed to prove that in certain cases, with a lower quantity of data, HTM can outperform CNN.

Simulation of bistatic radar experiments with deep space missions

L’obiettivo del lavoro esposto nella seguente relazione di tesi ha riguardato lo studio e la simulazione di esperimenti di radar bistatico per missioni di esplorazione planeteria. In particolare, il lavoro si è concentrato sull’uso ed il miglioramento di un simulatore software già realizzato da un consorzio di aziende ed enti di ricerca nell’ambito di uno studio dell’Agenzia Spaziale Europea (European Space Agency – ESA) finanziato nel 2008, e svolto fra il 2009 e 2010. L’azienda spagnola GMV ha coordinato lo studio, al quale presero parte anche gruppi di ricerca dell’Università di Roma “Sapienza” e dell’Università di Bologna. Il lavoro svolto si è incentrato sulla determinazione della causa di alcune inconsistenze negli output relativi alla parte del simulatore, progettato in ambiente MATLAB, finalizzato alla stima delle caratteristiche della superficie di Titano, in particolare la costante dielettrica e la rugosità media della superficie, mediante un esperimento con radar bistatico in modalità downlink eseguito dalla sonda Cassini-Huygens in orbita intorno al Titano stesso. Esperimenti con radar bistatico per lo studio di corpi celesti sono presenti nella storia dell’esplorazione spaziale fin dagli anni ’60, anche se ogni volta le apparecchiature utilizzate e le fasi di missione, durante le quali questi esperimenti erano effettuati, non sono state mai appositamente progettate per lo scopo. Da qui la necessità di progettare un simulatore per studiare varie possibili modalità di esperimenti con radar bistatico in diversi tipi di missione. In una prima fase di approccio al simulatore, il lavoro si è incentrato sullo studio della documentazione in allegato al codice così da avere un’idea generale della sua struttura e funzionamento. È seguita poi una fase di studio dettagliato, determinando lo scopo di ogni linea di codice utilizzata, nonché la verifica in letteratura delle formule e dei modelli utilizzati per la determinazione di diversi parametri. In una seconda fase il lavoro ha previsto l’intervento diretto sul codice con una serie di indagini volte a determinarne la coerenza e l’attendibilità dei risultati. Ogni indagine ha previsto una diminuzione delle ipotesi semplificative imposte al modello utilizzato in modo tale da identificare con maggiore sicurezza la parte del codice responsabile dell’inesattezza degli output del simulatore. I risultati ottenuti hanno permesso la correzione di alcune parti del codice e la determinazione della principale fonte di errore sugli output, circoscrivendo l’oggetto di studio per future indagini mirate.

Ricerca di AGN oscurati nei Chandra Deep Fields

La forma spettrale dell’X-ray background richiede l’esistenza di un grande numero di AGN mediamente oscurati, oltre alla presenza di AGN fortemente oscurati, la cui densità di colonna supera il limite Compton (Nh>10^24 cm^(-2)). A causa della loro natura, questi oggetti risultano di difficile osservazione, per cui è necessario adottare un approccio multi-banda per riuscire a rivelarli. In questo lavoro di tesi abbiamo studiato 29 sorgenti osservate nel CDF-S e 10 nel CDF-N a 0.0710^23, spettro piatto, riga del ferro): a seguito di questa analisi sono state individuate 9 sorgenti che presentano indicazioni di forte oscuramento. Dallo studio del rapporto tra la luminosità X (2-10 keV) e quella MIR (12.3um) dedotta dal SED-fitting, si è ottenuta una conferma della possibile presenza di forte oscuramento nelle 9 sorgenti selezionate a seguito dell’analisi spettrale. Abbiamo inoltre confrontato il tasso di formazione stellare dedotto dalla banda X (0.5-8 keV) e da quella IR (8-1000um) per identificare le sorgenti nelle quali l’emissione da AGN risulta essere dominante. A seguito di questa analisi abbiamo identificato 9 sorgenti (le stesse di cui sopra) con indicazione di forte oscuramento; di queste, 3 mostrano chiare indicazioni della presenza di un AGN Compton Thick (Nh>10^24 cm^(-2), riga del ferro intensa, basso rapporto LX/MIR).

Processes influencing the nitrate concentration in an aquifer for drinking water production in Bremen-Nord - Northern Germany

Groundwater represents the most important raw material. Germany struggles to maintain the best water quality possible by providing advanced monitoring systems and legal measures to prevent further pollution. In areas involved in the intensive growing of plantations, one of the major contamination factors derives from nitrate. The aim of this master thesis is the characterisation of the Water Protection Area of Bremen (Germany). Denitrification is a natural process, representing the best means of natural reduction of the hazardous nitrate ion, which is dangerous both for human health and for the development of eutrophication. The study has been possible thanks to the collaboration with the University of Bremen, the Geological Service of Bremen (GDfB) and Peter Spiedt (Water Supply Company of Bremen). It will be defined whether nitrate amounts in the groundwater still overcome the threshold legally imposed, and state if the denitrification process takes place, thanks to new samples collected in 2015 and their integration with historical data. Gas samples have been gathered to test them with the “N2/Ar method”, which is able to estimate the denitrification rate quantitatively. Analyses stated the effective occurrence of the reaction, nevertheless showing that it only affects the chemical of the deep aquifers and not shallow ones. Temporal trends concentrations of nitrate have shown that no real improvement took place in the past years. It will be commented that despite the denitrification being responsible for an efficacious lowering in the nitrate ion, it needs reactive materials to take place. Since the latter are finite elements, it is not an endless process. It is thus believed that is clearly necessary to adopt a better attitude in order to maintain the best chemical qualities possible in such an important area, providing drinking water.