Monitoring Complex Processes to Verify System Conformance: A Declarative Rule-Based Framework

Over the last 60 years, computers and software have favoured incredible advancements in every field. Nowadays, however, these systems are so complicated that it is difficult – if not challenging – to understand whether they meet some requirement or are able to show some desired behaviour or property. This dissertation introduces a Just-In-Time (JIT) a posteriori approach to perform the conformance check to identify any deviation from the desired behaviour as soon as possible, and possibly apply some corrections. The declarative framework that implements our approach – entirely developed on the promising open source forward-chaining Production Rule System (PRS) named Drools – consists of three components: 1. a monitoring module based on a novel, efficient implementation of Event Calculus (EC), 2. a general purpose hybrid reasoning module (the first of its genre) merging temporal, semantic, fuzzy and rule-based reasoning, 3. a logic formalism based on the concept of expectations introducing Event-Condition-Expectation rules (ECE-rules) to assess the global conformance of a system. The framework is also accompanied by an optional module that provides Probabilistic Inductive Logic Programming (PILP). By shifting the conformance check from after execution to just in time, this approach combines the advantages of many a posteriori and a priori methods proposed in literature. Quite remarkably, if the corrective actions are explicitly given, the reactive nature of this methodology allows to reconcile any deviations from the desired behaviour as soon as it is detected. In conclusion, the proposed methodology brings some advancements to solve the problem of the conformance checking, helping to fill the gap between humans and the increasingly complex technology.

Computational methods for the analysis of protein structure and function

The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.

Semantic Service Architectures for Smart Environments

Many industries and academic institutions share the vision that an appropriate use of information originated from the environment may add value to services in multiple domains and may help humans in dealing with the growing information overload which often seems to jeopardize our life. It is also clear that information sharing and mutual understanding between software agents may impact complex processes where many actors (humans and machines) are involved, leading to relevant socioeconomic benefits. Starting from these two input, architectural and technological solutions to enable “environment-related cooperative digital services” are here explored. The proposed analysis starts from the consideration that our environment is physical space and here diversity is a major value. On the other side diversity is detrimental to common technological solutions, and it is an obstacle to mutual understanding. An appropriate environment abstraction and a shared information model are needed to provide the required levels of interoperability in our heterogeneous habitat. This thesis reviews several approaches to support environment related applications and intends to demonstrate that smart-space-based, ontology-driven, information-sharing platforms may become a flexible and powerful solution to support interoperable services in virtually any domain and even in cross-domain scenarios. It also shows that semantic technologies can be fruitfully applied not only to represent application domain knowledge. For example semantic modeling of Human-Computer Interaction may support interaction interoperability and transformation of interaction primitives into actions, and the thesis shows how smart-space-based platforms driven by an interaction ontology may enable natural ad flexible ways of accessing resources and services, e.g, with gestures. An ontology for computational flow execution has also been built to represent abstract computation, with the goal of exploring new ways of scheduling computation flows with smart-space-based semantic platforms.

Non-Markovian stochastic processes and their applications: from anomalous diffusion to time series analysis

This work provides a forward step in the study and comprehension of the relationships between stochastic processes and a certain class of integral-partial differential equation, which can be used in order to model anomalous diffusion and transport in statistical physics. In the first part, we brought the reader through the fundamental notions of probability and stochastic processes, stochastic integration and stochastic differential equations as well. In particular, within the study of H-sssi processes, we focused on fractional Brownian motion (fBm) and its discrete-time increment process, the fractional Gaussian noise (fGn), which provide examples of non-Markovian Gaussian processes. The fGn, together with stationary FARIMA processes, is widely used in the modeling and estimation of long-memory, or long-range dependence (LRD). Time series manifesting long-range dependence, are often observed in nature especially in physics, meteorology, climatology, but also in hydrology, geophysics, economy and many others. We deepely studied LRD, giving many real data examples, providing statistical analysis and introducing parametric methods of estimation. Then, we introduced the theory of fractional integrals and derivatives, which indeed turns out to be very appropriate for studying and modeling systems with long-memory properties. After having introduced the basics concepts, we provided many examples and applications. For instance, we investigated the relaxation equation with distributed order time-fractional derivatives, which describes models characterized by a strong memory component and can be used to model relaxation in complex systems, which deviates from the classical exponential Debye pattern. Then, we focused in the study of generalizations of the standard diffusion equation, by passing through the preliminary study of the fractional forward drift equation. Such generalizations have been obtained by using fractional integrals and derivatives of distributed orders. In order to find a connection between the anomalous diffusion described by these equations and the long-range dependence, we introduced and studied the generalized grey Brownian motion (ggBm), which is actually a parametric class of H-sssi processes, which have indeed marginal probability density function evolving in time according to a partial integro-differential equation of fractional type. The ggBm is of course Non-Markovian. All around the work, we have remarked many times that, starting from a master equation of a probability density function f(x,t), it is always possible to define an equivalence class of stochastic processes with the same marginal density function f(x,t). All these processes provide suitable stochastic models for the starting equation. Studying the ggBm, we just focused on a subclass made up of processes with stationary increments. The ggBm has been defined canonically in the so called grey noise space. However, we have been able to provide a characterization notwithstanding the underline probability space. We also pointed out that that the generalized grey Brownian motion is a direct generalization of a Gaussian process and in particular it generalizes Brownain motion and fractional Brownain motion as well. Finally, we introduced and analyzed a more general class of diffusion type equations related to certain non-Markovian stochastic processes. We started from the forward drift equation, which have been made non-local in time by the introduction of a suitable chosen memory kernel K(t). The resulting non-Markovian equation has been interpreted in a natural way as the evolution equation of the marginal density function of a random time process l(t). We then consider the subordinated process Y(t)=X(l(t)) where X(t) is a Markovian diffusion. The corresponding time-evolution of the marginal density function of Y(t) is governed by a non-Markovian Fokker-Planck equation which involves the same memory kernel K(t). We developed several applications and derived the exact solutions. Moreover, we considered different stochastic models for the given equations, providing path simulations.

Modelling coupled physical-biogeochemical processes in ice-covered oceans

The last decades have seen a large effort of the scientific community to study and understand the physics of sea ice. We currently have a wide - even though still not exhaustive - knowledge of the sea ice dynamics and thermodynamics and of their temporal and spatial variability. Sea ice biogeochemistry is instead largely unknown. Sea ice algae production may account for up to 25% of overall primary production in ice-covered waters of the Southern Ocean. However, the influence of physical factors, such as the location of ice formation, the role of snow cover and light availability on sea ice primary production is poorly understood. There are only sparse localized observations and little knowledge of the functioning of sea ice biogeochemistry at larger scales. Modelling becomes then an auxiliary tool to help qualifying and quantifying the role of sea ice biogeochemistry in the ocean dynamics. In this thesis, a novel approach is used for the modelling and coupling of sea ice biogeochemistry - and in particular its primary production - to sea ice physics. Previous attempts were based on the coupling of rather complex sea ice physical models to empirical or relatively simple biological or biogeochemical models. The focus is moved here to a more biologically-oriented point of view. A simple, however comprehensive, physical model of the sea ice thermodynamics (ESIM) was developed and coupled to a novel sea ice implementation (BFM-SI) of the Biogeochemical Flux Model (BFM). The BFM is a comprehensive model, largely used and validated in the open ocean environment and in regional seas. The physical model has been developed having in mind the biogeochemical properties of sea ice and the physical inputs required to model sea ice biogeochemistry. The central concept of the coupling is the modelling of the Biologically-Active-Layer (BAL), which is the time-varying fraction of sea ice that is continuously connected to the ocean via brines pockets and channels and it acts as rich habitat for many microorganisms. The physical model provides the key physical properties of the BAL (e.g., brines volume, temperature and salinity), and the BFM-SI simulates the physiological and ecological response of the biological community to the physical enviroment. The new biogeochemical model is also coupled to the pelagic BFM through the exchange of organic and inorganic matter at the boundaries between the two systems . This is done by computing the entrapment of matter and gases when sea ice grows and release to the ocean when sea ice melts to ensure mass conservation. The model was tested in different ice-covered regions of the world ocean to test the generality of the parameterizations. The focus was particularly on the regions of landfast ice, where primary production is generally large. The implementation of the BFM in sea ice and the coupling structure in General Circulation Models will add a new component to the latters (and in general to Earth System Models), which will be able to provide adequate estimate of the role and importance of sea ice biogeochemistry in the global carbon cycle.

Study of the circulation processes in the northern Adriatic sea - coastal area and Venice lagoon inlets

This work is a detailed study of hydrodynamic processes in a defined area, the littoral in front of the Venice Lagoon and its inlets, which are complex morphological areas of interconnection. A finite element hydrodynamic model of the Venice Lagoon and the Adriatic Sea has been developed in order to study the coastal current patterns and the exchanges at the inlets of the Venice Lagoon. This is the first work in this area that tries to model the interaction dynamics, running together a model for the lagoon and the Adriatic Sea. First the barotropic processes near the inlets of the Venice Lagoon have been studied. Data from more than ten tide gauges displaced in the Adriatic Sea have been used in the calibration of the simulated water levels. To validate the model results, empirical flux data measured by ADCP probes installed inside the inlets of Lido and Malamocco have been used and the exchanges through the three inlets of the Venice Lagoon have been analyzed. The comparison between modelled and measured fluxes at the inlets outlined the efficiency of the model to reproduce both tide and wind induced water exchanges between the sea and the lagoon. As a second step, also small scale processes around the inlets that connect the Venice lagoon with the Northern Adriatic Sea have been investigated by means of 3D simulations. Maps of vorticity have been produced, considering the influence of tidal flows and wind stress in the area. A sensitivity analysis has been carried out to define the importance of the advection and of the baroclinic pressure gradients in the development of vortical processes seen along the littoral close to the inlets. Finally a comparison with real data measurements, surface velocity data from HF Radar near the Venice inlets, has been performed, which allows for a better understanding of the processes and their seasonal dynamics. The results outline the predominance of wind and tidal forcing in the coastal area. Wind forcing acts mainly on the mean coastal current inducing its detachment offshore during Sirocco events and an increase of littoral currents during Bora events. The Bora action is more homogeneous on the whole coastal area whereas the Sirocco strengthens its impact in the South, near Chioggia inlet. Tidal forcing at the inlets is mainly barotropic. The sensitivity analysis shows how advection is the main physical process responsible for the persistent vortical structures present along the littoral between the Venice Lagoon inlets. The comparison with measurements from HF Radar not only permitted a validation the model results, but also a description of different patterns in specific periods of the year. The success of the 2D and the 3D simulations on the reproduction both of the SSE, inside and outside the Venice Lagoon, of the tidal flow, through the lagoon inlets, and of the small scale phenomena, occurring along the littoral, indicates that the finite element approach is the most suitable tool for the investigation of coastal processes. For the first time, as shown by the flux modeling, the physical processes that drive the interaction between the two basins were reproduced.

Thermochronologic and geodynamic evolution of the Pontides: Sakarya terrane (Karakaya Complex) and Istanbul terrane, Turkey.

An integrated array of analytical methods -including clay mineralogy, vitrinite reflectance, Raman spectroscopy on carbonaceous material, and apatite fission-track analysis- was employed to constrain the thermal and thermochronological evolution of selected portions of the Pontides of northern Turkey. (1) A multimethod investigation was applied for the first time to characterise the thermal history of the Karakaya Complex, a Permo-Triassic subduction-accretion complex cropping out throughout the Sakarya Zone. The results indicate two different thermal regimes: the Lower Karakaya Complex (Nilüfer Unit) -mostly made of metabasite and marble- suffered peak temperatures of 300-500°C (greenschist facies); the Upper Karakaya Complex (Hodul and the Orhanlar Units) –mostly made of greywacke and arkose- yielded heterogeneous peak temperatures (125-376°C), possibly the result of different degree of involvement of the units in the complex dynamic processes of the accretionary wedge. Contrary to common belief, the results of this study indicate that the entire Karakaya Complex suffered metamorphic conditions. Moreover, a good degree of correlation among the results of these methods demonstrate that Raman spectroscopy on carbonaceous material can be applied successfully to temperature ranges of 200-330°C, thus extending the application of this method from higher grade metamorphic contexts to lower grade metamorphic conditions. (2) Apatite fission-track analysis was applied to the Sakarya and the İstanbul Zones in order to constrain the exhumation history and timing of amalgamation of these two exotic terranes. AFT ages from the İstanbul and Sakarya terranes recorded three distinct episodes of exhumation related to the complex tectonic evolution of the Pontides. (i) Paleocene - early Eocene ages (62.3-50.3 Ma) reflect the closure of the İzmir-Ankara ocean and the ensuing collision between the Sakarya terrane and the Anatolide-Tauride Block. (ii) Late Eocene - earliest Oligocene (43.5-32.3 Ma) ages reflect renewed tectonic activity along the İzmir-Ankara. (iii) Late Oligocene- Early Miocene ages reflect the onset and development of the northern Aegean extension. The consistency of AFT ages, both north and south of the tectonic contact between the İstanbul and Sakarya terranes, suggest that such terranes were amalgamated in pre-Cenozoic times. (3) Fission-track analysis was also applied to rock samples from the Marmara region, in an attempt to constrain the inception and development of the North Anatolian Fault system in the region. The results agree with those from the central Pontides. The youngest AFT ages (Late Oligocene - early Miocene) were recorded in the western portion of the Marmara Sea region and reflect the onset and development of northern Aegean extension. Fission-track data from the eastern Marmara Sea region indicate rapid Early Eocene exhumation induced by the development of the İzmir-Ankara orogenic wedge. Thermochronological data along the trace of the Ganos Fault –a segment of the North Anatolian Fault system- indicate the presence of a tectonic discontinuity active by Late Oligocene time, i.e. well before the arrival of the North Anatolian Fault system in the area. The integration of thermochronologic data with preexisting structural data point to the existence of a system of major E-W-trending structural discontinuities active at least from the Late Oligocene. In the Early Pliocene, inception of the present-day North Anatolian Fault system in the Marmara region occurred by reactivation of these older tectonic structures. 


Spatial and temporal variability and ecological processes in the epibenthic assemblages of the northern Adriatic Sea

Several coralligenous reefs occur in the soft bottoms of the northern Adriatic continental shelf. Mediterranean coralligenous habitats are characterised by high species diversity and are intrinsically valuable for their biological diversity and for the ecological processes they support. The conservation and management of these habitats require quantifying spatial and temporal variability of their benthic assemblages. This PhD thesis aims to give a relevant contribution to the knowledge of the structure and dynamics of the epibenthic assemblages on the coralligenous subtidal reefs occurring in the northern Adriatic Sea. The epibenthic assemblages showed a spatial variation larger compared to temporal changes, with a temporal persistence of reef-forming organisms. Assemblages spatial heterogeneity has been related to morphological features and geographical location of the reefs, together with variation in the hydrological conditions. Manipulative experiments help to understand the ecological processes structuring the benthic assemblages and maintaining their diversity. In this regards a short and long term experiment on colonization patterns of artificial substrata over a 3-year period has been performed in three reefs, corresponding to the three main types of assemblages detected in the previous study. The first colonisers, largely depending by the different larval supply, played a key role in determining the heterogeneity of the assemblages in the early stage of colonisation. Lateral invasion, from the surrounding assemblages, was the driver in structuring the mature assemblages. These complex colonisation dynamics explained the high heterogeneity of the assemblages dwelling on the northern Adriatic biogenic reefs. The buildup of these coralligenous reefs mainly depends by the bioconstruction-erosion processes that has been analysed through a field experiment. Bioconstruction, largely due to serpulid polychaetes, prevailed on erosion processes and occurred at similar rates in all sites. Similarly, the total energy contents in the benthic communities do not differ among sites, despite being provided by different species. Therefore, we can hypothesise that both bioconstruction processes and energetic storage may be limited by the availability of resources. Finally the major contribution of the zoobenthos compared to the phytobenthos to the total energetic content of assemblages suggests that the energy flow in these benthic habitats is primarily supported by planktonic food web trough the filter feeding invertebrates.

New catalytic processes for the upgrading of furfural and 5-hydroxymethylfurfural to chemicals and fuels

The demand of energy, fuels and chemicals is increasing due to the strong growth of some countries in the developing world and the development of the world economy. Unfortunately, the general picture derived sparked an exponential increase in crude oil prices with a consequent increase of the chemical, by-products and energy, depleting the global market. Nowadays biomass are the most promising alternative to fossil fuels for the production of chemicals and fuels. In this work, the development of three different catalytic processes for the valorization of biomass-derived has been investigated. 5-hydroxymethylfurfural oxidation was studied under mild reaction condition using gold and gold/copper based catalysts synthetized from pre-formed nanoparticles and supported onto TiO2 and CeO2. The analysis conducted on catalysts showed the formation of alloys gold/copper and a strong synergistic effect between the two metals. For this reason the bimetallic catalysts supported on titania showed a higher catalytic activity respect to the monometallic catalysts. The process for the production of 2,5-bishydroxymethyl furan (BHMF) was also optimized by means the 5-hydroxymethylfurfural hydrogenation using the Shvo complex. Complete conversion of HMF was achieved working at 90 °C and 10 bar of hydrogen. The complex was found to be re-usable for at least three catalytic cycles without suffering any type of deactivation. Finally, the hydrogenation of furfural and HMF was carried out, developing the process of hydrogen transfer by using MgO as a catalyst and methanol as a hydrogen donor. Quantitative yields to alcohols have been achieved in a few hours working in mild condition: 160 °C and at autogenous pressure. The only by-products formed were light products such as CO, CO2 and CH4 (products derived from methanol transformation), easily separable from the reaction solution depressurizing the reactor.

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.

Microbial ecology of biotechnological processes

The investigation of phylogenetic diversity and functionality of complex microbial communities in relation to changes in the environmental conditions represents a major challenge of microbial ecology research. Nowadays, particular attention is paid to microbial communities occurring at environmental sites contaminated by recalcitrant and toxic organic compounds. Extended research has evidenced that such communities evolve some metabolic abilities leading to the partial degradation or complete mineralization of the contaminants. Determination of such biodegradation potential can be the starting point for the development of cost effective biotechnological processes for the bioremediation of contaminated matrices. This work showed how metagenomics-based microbial ecology investigations supported the choice or the development of three different bioremediation strategies. First, PCR-DGGE and PCR-cloning approaches served the molecular characterization of microbial communities enriched through sequential development stages of an aerobic cometabolic process for the treatment of groundwater contaminated by chlorinated aliphatic hydrocarbons inside an immobilized-biomass packed bed bioreactor (PBR). In this case the analyses revealed homogeneous growth and structure of immobilized communities throughout the PBR and the occurrence of dominant microbial phylotypes of the genera Rhodococcus, Comamonas and Acidovorax, which probably drive the biodegradation process. The same molecular approaches were employed to characterize sludge microbial communities selected and enriched during the treatment of municipal wastewater coupled with the production of polyhydroxyalkanoates (PHA). Known PHA-accumulating microorganisms identified were affiliated with the genera Zooglea, Acidovorax and Hydrogenophaga. Finally, the molecular investigation concerned communities of polycyclic aromatic hydrocarbon (PAH) contaminated soil subjected to rhizoremediation with willow roots or fertilization-based treatments. The metabolic ability to biodegrade naphthalene, as a representative model for PAH, was assessed by means of stable isotope probing in combination with high-throughput sequencing analysis. The phylogenetic diversity of microbial populations able to derive carbon from naphthalene was evaluated as a function of the type of treatment.