Stochastic models and dynamic measures for the characterization of bistable circuits

During the last few years, a great deal of interest has risen concerning the applications of stochastic methods to several biochemical and biological phenomena. Phenomena like gene expression, cellular memory, bet-hedging strategy in bacterial growth and many others, cannot be described by continuous stochastic models due to their intrinsic discreteness and randomness. In this thesis I have used the Chemical Master Equation (CME) technique to modelize some feedback cycles and analyzing their properties, including experimental data. In the first part of this work, the effect of stochastic stability is discussed on a toy model of the genetic switch that triggers the cellular division, which malfunctioning is known to be one of the hallmarks of cancer. The second system I have worked on is the so-called futile cycle, a closed cycle of two enzymatic reactions that adds and removes a chemical compound, called phosphate group, to a specific substrate. I have thus investigated how adding noise to the enzyme (that is usually in the order of few hundred molecules) modifies the probability of observing a specific number of phosphorylated substrate molecules, and confirmed theoretical predictions with numerical simulations. In the third part the results of the study of a chain of multiple phosphorylation-dephosphorylation cycles will be presented. We will discuss an approximation method for the exact solution in the bidimensional case and the relationship that this method has with the thermodynamic properties of the system, which is an open system far from equilibrium.In the last section the agreement between the theoretical prediction of the total protein quantity in a mouse cells population and the observed quantity will be shown, measured via fluorescence microscopy.

Multilevel Domain Decomposition Algorithms for Monolithic Fluid-Structure Interaction Problems with Application to Haemodynamics

Finite element techniques for solving the problem of fluid-structure interaction of an elastic solid material in a laminar incompressible viscous flow are described. The mathematical problem consists of the Navier-Stokes equations in the Arbitrary Lagrangian-Eulerian formulation coupled with a non-linear structure model, considering the problem as one continuum. The coupling between the structure and the fluid is enforced inside a monolithic framework which computes simultaneously for the fluid and the structure unknowns within a unique solver. We used the well-known Crouzeix-Raviart finite element pair for discretization in space and the method of lines for discretization in time. A stability result using the Backward-Euler time-stepping scheme for both fluid and solid part and the finite element method for the space discretization has been proved. The resulting linear system has been solved by multilevel domain decomposition techniques. Our strategy is to solve several local subproblems over subdomain patches using the Schur-complement or GMRES smoother within a multigrid iterative solver. For validation and evaluation of the accuracy of the proposed methodology, we present corresponding results for a set of two FSI benchmark configurations which describe the self-induced elastic deformation of a beam attached to a cylinder in a laminar channel flow, allowing stationary as well as periodically oscillating deformations, and for a benchmark proposed by COMSOL multiphysics where a narrow vertical structure attached to the bottom wall of a channel bends under the force due to both viscous drag and pressure. Then, as an example of fluid-structure interaction in biomedical problems, we considered the academic numerical test which consists in simulating the pressure wave propagation through a straight compliant vessel. All the tests show the applicability and the numerical efficiency of our approach to both two-dimensional and three-dimensional problems.

Sviluppo di metodi innovativi per la sintesi di nanoparticelle di interesse industriale

Among various nanoparticles, noble metal nanoparticles have attracted considerable attention due to their optical, catalytic and conducting properties. This work has been focused on the development of an innovative method of synthesis for the preparation of metal nanosuspensions of Au, Ag, Cu, in order to achieve stable sols, showing suitable features to allow an industrial scale up of the processes. The research was developed in collaboration with a company interested in the large scale production of the studied nanosuspensions. In order to develop a commercial process, high solid concentration, long time colloidal stability and particle size control, are required. Two synthesis routes, differing by the used solvents, have been implemented: polyol based and water based synthesis. In order to achieve a process intensification the microwave heating has been applied. As a result, colloidal nanosuspensions with suitable dimensions, good optical properties, very high solid content and good stability, have been synthesized by simple and environmental friendly methods. Particularly, due to some interesting results an optimized synthesis process has been patented. Both water and polyol based synthesis, developed in the presence of a reducing agent and of a chelating polymer, allowed to obtain particle size-control and colloidal stability by tuning the different parameters. Furthermore, it has been verified that microwave device, due to its rapid and homogeneous heating, provides some advantages over conventional method. In order to optimize the final suspensions properties, for each synthesis it has been studied the effect of different parameters (temperature, time, precursors concentrations, etc) and throughout a specific optimization action a right control on nucleation and growth processes has been achieved. The achieved nanoparticles were confirmed by XRD analysis to be the desired metal phases, even at the lowest synthesis temperatures. The particles showed a diameter, measured by STEM and dynamic light scattering technique (DLS), ranging from 10 to 60 nm. Surface plasmon resonance (SPR) was monitored by UV-VIS spectroscopy confirming its dependence by nanoparticles size and shape. Moreover the reaction yield has been assessed by ICP analysis performed on the unreacted metal cations. Finally, thermal conductivity and antibacterial activity characterizations of copper and silver sols respectively are now ongoing in order to check their application as nanofluid in heat transfer processes and as antibacterial agent.

Imaging of crustal scatterers using multiple seismic arrays

Array seismology is an useful tool to perform a detailed investigation of the Earth’s interior. Seismic arrays by using the coherence properties of the wavefield are able to extract directivity information and to increase the ratio of the coherent signal amplitude relative to the amplitude of incoherent noise. The Double Beam Method (DBM), developed by Krüger et al. (1993, 1996), is one of the possible applications to perform a refined seismic investigation of the crust and mantle by using seismic arrays. The DBM is based on a combination of source and receiver arrays leading to a further improvement of the signal-to-noise ratio by reducing the error in the location of coherent phases. Previous DBM works have been performed for mantle and core/mantle resolution (Krüger et al., 1993; Scherbaum et al., 1997; Krüger et al., 2001). An implementation of the DBM has been presented at 2D large-scale (Italian data-set for Mw=9.3, Sumatra earthquake) and at 3D crustal-scale as proposed by Rietbrock & Scherbaum (1999), by applying the revised version of Source Scanning Algorithm (SSA; Kao & Shan, 2004). In the 2D application, the rupture front propagation in time has been computed. In 3D application, the study area (20x20x33 km3), the data-set and the source-receiver configurations are related to the KTB-1994 seismic experiment (Jost et al., 1998). We used 60 short-period seismic stations (200-Hz sampling rate, 1-Hz sensors) arranged in 9 small arrays deployed in 2 concentric rings about 1 km (A-arrays) and 5 km (B-array) radius. The coherence values of the scattering points have been computed in the crustal volume, for a finite time-window along all array stations given the hypothesized origin time and source location. The resulting images can be seen as a (relative) joint log-likelihood of any point in the subsurface that have contributed to the full set of observed seismograms.

Portfolio optimization in the energy market

Let’s put ourselves in the shoes of an energy company. Our fleet of electricity production plants mainly includes gas, hydroelectric and waste-to-energy plants. We also sold contracts for the supply of gas and electricity. For each year we have to plan the trading of the volumes needed by the plants and customers: better to fix the price of these volumes in advance with the so-called forward contracts, instead of waiting for the delivery months, exposing ourselves to price uncertainty. Here’s the thing: trying to keep uncertainty under control in a market that has never shown such extreme scenarios as in recent years: a pandemic, a worsening climate crisis and a war that is affecting economies around the world have made the energy market more volatile than ever. How to make decisions in such uncertain contexts? There is an optimization problem: given a year, we need to choose the optimal planning of volume trading times, to meet the needs of our portfolio at the best prices, taking into account the liquidity constraints given by the market and the risk constraints imposed by the company. Algorithms are needed for the generation of market scenarios over a finite time horizon, that is, a probabilistic distribution that allows a view of all the dates between now and the end of the year of interest. Algorithms are needed to solve the optimization problem: we have proposed more than one and compared them; a very simple one, which avoids considering part of the complexity, moving on to a scenario approach and finally a reinforcement learning approach.

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.

Hybrid Methods for Resource Allocation and Scheduling Problems in Deterministic and Stochastic Environments

This work presents exact, hybrid algorithms for mixed resource Allocation and Scheduling problems; in general terms, those consist into assigning over time finite capacity resources to a set of precedence connected activities. The proposed methods have broad applicability, but are mainly motivated by applications in the field of Embedded System Design. In particular, high-performance embedded computing recently witnessed the shift from single CPU platforms with application-specific accelerators to programmable Multi Processor Systems-on-Chip (MPSoCs). Those allow higher flexibility, real time performance and low energy consumption, but the programmer must be able to effectively exploit the platform parallelism. This raises interest in the development of algorithmic techniques to be embedded in CAD tools; in particular, given a specific application and platform, the objective if to perform optimal allocation of hardware resources and to compute an execution schedule. On this regard, since embedded systems tend to run the same set of applications for their entire lifetime, off-line, exact optimization approaches are particularly appealing. Quite surprisingly, the use of exact algorithms has not been well investigated so far; this is in part motivated by the complexity of integrated allocation and scheduling, setting tough challenges for ``pure'' combinatorial methods. The use of hybrid CP/OR approaches presents the opportunity to exploit mutual advantages of different methods, while compensating for their weaknesses. In this work, we consider in first instance an Allocation and Scheduling problem over the Cell BE processor by Sony, IBM and Toshiba; we propose three different solution methods, leveraging decomposition, cut generation and heuristic guided search. Next, we face Allocation and Scheduling of so-called Conditional Task Graphs, explicitly accounting for branches with outcome not known at design time; we extend the CP scheduling framework to effectively deal with the introduced stochastic elements. Finally, we address Allocation and Scheduling with uncertain, bounded execution times, via conflict based tree search; we introduce a simple and flexible time model to take into account duration variability and provide an efficient conflict detection method. The proposed approaches achieve good results on practical size problem, thus demonstrating the use of exact approaches for system design is feasible. Furthermore, the developed techniques bring significant contributions to combinatorial optimization methods.

Primary stability in cementless total hip replacement: measurement techniques and aided-surgery

Primary stability of stems in cementless total hip replacements is recognized to play a critical role for long-term survival and thus for the success of the overall surgical procedure. In Literature, several studies addressed this important issue. Different approaches have been explored aiming to evaluate the extent of stability achieved during surgery. Some of these are in-vitro protocols while other tools are coinceived for the post-operative assessment of prosthesis migration relative to the host bone. In vitro protocols reported in the literature are not exportable to the operating room. Anyway most of them show a good overall accuracy. The RSA, EBRA and the radiographic analysis are currently used to check the healing process of the implanted femur at different follow-ups, evaluating implant migration, occurance of bone resorption or osteolysis at the interface. These methods are important for follow up and clinical study but do not assist the surgeon during implantation. At the time I started my Ph.D Study in Bioengineering, only one study had been undertaken to measure stability intra-operatively. No follow-up was presented to describe further results obtained with that device. In this scenario, it was believed that an instrument that could measure intra-operatively the stability achieved by an implanted stem would consistently improve the rate of success. This instrument should be accurate and should give to the surgeon during implantation a quick answer concerning the stability of the implanted stem. With this aim, an intra-operative device was designed, developed and validated. The device is meant to help the surgeon to decide how much to press-fit the implant. It is essentially made of a torsional load cell, able to measure the extent of torque applied by the surgeon to test primary stability, an angular sensor that measure the relative angular displacement between stem and femur, a rigid connector that enable connecting the device to the stem, and all the electronics for signals conditioning. The device was successfully validated in-vitro, showing a good overall accuracy in discriminating stable from unstable implants. Repeatability tests showed that the device was reliable. A calibration procedure was then performed in order to convert the angular readout into a linear displacement measurement, which is an information clinically relevant and simple to read in real-time by the surgeon. The second study reported in my thesis, concerns the evaluation of the possibility to have predictive information regarding the primary stability of a cementless stem, by measuring the micromotion of the last rasp used by the surgeon to prepare the femoral canal. This information would be really useful to the surgeon, who could check prior to the implantation process if the planned stem size can achieve a sufficient degree of primary stability, under optimal press fitting conditions. An intra-operative tool was developed to this aim. It was derived from a previously validated device, which was adapted for the specific purpose. The device is able to measure the relative micromotion between the femur and the rasp, when a torsional load is applied. An in-vitro protocol was developed and validated on both composite and cadaveric specimens. High correlation was observed between one of the parameters extracted form the acquisitions made on the rasp and the stability of the corresponding stem, when optimally press-fitted by the surgeon. After tuning in-vitro the protocol as in a closed loop, verification was made on two hip patients, confirming the results obtained in-vitro and highlighting the independence of the rasp indicator from the bone quality, anatomy and preserving conditions of the tested specimens, and from the sharpening of the rasp blades. The third study is related to an approach that have been recently explored in the orthopaedic community, but that was already in use in other scientific fields. It is based on the vibration analysis technique. This method has been successfully used to investigate the mechanical properties of the bone and its application to evaluate the extent of fixation of dental implants has been explored, even if its validity in this field is still under discussion. Several studies have been published recently on the stability assessment of hip implants by vibration analysis. The aim of the reported study was to develop and validate a prototype device based on the vibration analysis technique to measure intra-operatively the extent of implant stability. The expected advantages of a vibration-based device are easier clinical use, smaller dimensions and minor overall cost with respect to other devices based on direct micromotion measurement. The prototype developed consists of a piezoelectric exciter connected to the stem and an accelerometer attached to the femur. Preliminary tests were performed on four composite femurs implanted with a conventional stem. The results showed that the input signal was repeatable and the output could be recorded accurately. The fourth study concerns the application of the device based on the vibration analysis technique to several cases, considering both composite and cadaveric specimens. Different degrees of bone quality were tested, as well as different femur anatomies and several levels of press-fitting were considered. The aim of the study was to verify if it is possible to discriminate between stable and quasi-stable implants, because this is the most challenging detection for the surgeon in the operation room. Moreover, it was possible to validate the measurement protocol by comparing the results of the acquisitions made with the vibration-based tool to two reference measurements made by means of a validated technique, and a validated device. The results highlighted that the most sensitive parameter to stability is the shift in resonance frequency of the stem-bone system, showing high correlation with residual micromotion on all the tested specimens. Thus, it seems possible to discriminate between many levels of stability, from the grossly loosened implant, through the quasi-stable implants, to the definitely stable one. Finally, an additional study was performed on a different type of hip prosthesis, which has recently gained great interest thus becoming fairly popular in some countries in the last few years: the hip resurfacing prosthesis. The study was motivated by the following rationale: although bone-prosthesis micromotion is known to influence the stability of total hip replacement, its effect on the outcome of resurfacing implants has not been investigated in-vitro yet, but only clinically. Thus the work was aimed at verifying if it was possible to apply to the resurfacing prosthesis one of the intraoperative devices just validated for the measurement of the micromotion in the resurfacing implants. To do that, a preliminary study was performed in order to evaluate the extent of migration and the typical elastic movement for an epiphyseal prosthesis. An in-vitro procedure was developed to measure micromotions of resurfacing implants. This included a set of in-vitro loading scenarios that covers the range of directions covered by hip resultant forces in the most typical motor-tasks. The applicability of the protocol was assessed on two different commercial designs and on different head sizes. The repeatability and reproducibility were excellent (comparable to the best previously published protocols for standard cemented hip stems). Results showed that the procedure is accurate enough to detect micromotions of the order of few microns. The protocol proposed was thus completely validated. The results of the study demonstrated that the application of an intra-operative device to the resurfacing implants is not necessary, as the typical micromovement associated to this type of prosthesis could be considered negligible and thus not critical for the stabilization process. Concluding, four intra-operative tools have been developed and fully validated during these three years of research activity. The use in the clinical setting was tested for one of the devices, which could be used right now by the surgeon to evaluate the degree of stability achieved through the press-fitting procedure. The tool adapted to be used on the rasp was a good predictor of the stability of the stem. Thus it could be useful for the surgeon while checking if the pre-operative planning was correct. The device based on the vibration technique showed great accuracy, small dimensions, and thus has a great potential to become an instrument appreciated by the surgeon. It still need a clinical evaluation, and must be industrialized as well. The in-vitro tool worked very well, and can be applied for assessing resurfacing implants pre-clinically.

Studies of OPA1 pathogenic mechanisms in Dominant Optic Atrophy and novel protein function in mitochondrial DNA stability

The mitochondrion is an essential cytoplasmic organelle that provides most of the energy necessary for eukaryotic cell physiology. Mitochondrial structure and functions are maintained by proteins of both mitochondrial and nuclear origin. These organelles are organized in an extended network that dynamically fuses and divides. Mitochondrial morphology results from the equilibrium between fusion and fission processes, controlled by a family of “mitochondria-shaping” proteins. It is becoming clear that defects in mitochondrial dynamics can impair mitochondrial respiration, morphology and motility, leading to apoptotic cell death in vitro and more or less severe neurodegenerative disorders in vivo in humans. Mutations in OPA1, a nuclear encoded mitochondrial protein, cause autosomal Dominant Optic Atrophy (DOA), a heterogeneous blinding disease characterized by retinal ganglion cell degeneration leading to optic neuropathy (Delettre et al., 2000; Alexander et al., 2000). OPA1 is a mitochondrial dynamin-related guanosine triphosphatase (GTPase) protein involved in mitochondrial network dynamics, cytochrome c storage and apoptosis. This protein is anchored or associated on the inner mitochondrial membrane facing the intermembrane space. Eight OPA1 isoforms resulting from alternative splicing combinations of exon 4, 4b and 5b have been described (Delettre et al., 2001). These variants greatly vary among diverse organs and the presence of specific isoforms has been associated with various mitochondrial functions. The different spliced exons encode domains included in the amino-terminal region and contribute to determine OPA1 functions (Olichon et al., 2006). It has been shown that exon 4, that is conserved throughout evolution, confers functions to OPA1 involved in maintenance of the mitochondrial membrane potential and in the fusion of the network. Conversely, exon 4b and exon 5b, which are vertebrate specific, are involved in regulation of cytochrome c release from mitochondria, and activation of apoptosis, a process restricted to vertebrates (Olichon et al., 2007). While Mgm1p has been identified thanks to its role in mtDNA maintenance, it is only recently that OPA1 has been linked to mtDNA stability. Missense mutations in OPA1 cause accumulation of multiple deletions in skeletal muscle. The syndrome associated to these mutations (DOA-1 plus) is complex, consisting of a combination of dominant optic atrophy, progressive external ophtalmoplegia, peripheral neuropathy, ataxia and deafness (Amati- Bonneau et al., 2008; Hudson et al., 2008). OPA1 is the fifth gene associated with mtDNA “breakage syndrome” together with ANT1, PolG1-2 and TYMP (Spinazzola et al., 2009). In this thesis we show for the first time that specific OPA1 isoforms associated to exon 4b are important for mtDNA stability, by anchoring the nucleoids to the inner mitochondrial membrane. Our results clearly demonstrate that OPA1 isoforms including exon 4b are intimately associated to the maintenance of the mitochondrial genome, as their silencing leads to mtDNA depletion. The mechanism leading to mtDNA loss is associated with replication inhibition in cells where exon 4b containing isoforms were down-regulated. Furthermore silencing of exon 4b associated isoforms is responsible for alteration in mtDNA-nucleoids distribution in the mitochondrial network. In this study it was evidenced that OPA1 exon 4b isoform is cleaved to provide a 10kd peptide embedded in the inner membrane by a second transmembrane domain, that seems to be crucial for mitochondrial genome maintenance and does correspond to the second transmembrane domain of the yeasts orthologue encoded by MGM1 or Msp1, which is also mandatory for this process (Diot et al., 2009; Herlan et al., 2003). Furthermore in this thesis we show that the NT-OPA1-exon 4b peptide co-immuno-precipitates with mtDNA and specifically interacts with two major components of the mitochondrial nucleoids: the polymerase gamma and Tfam. Thus, from these experiments the conclusion is that NT-OPA1- exon 4b peptide contributes to the nucleoid anchoring in the inner mitochondrial membrane, a process that is required for the initiation of mtDNA replication and for the distribution of nucleoids along the network. These data provide new crucial insights in understanding the mechanism involved in maintenance of mtDNA integrity, because they clearly demonstrate that, besides genes implicated in mtDNA replications (i.e. polymerase gamma, Tfam, twinkle and genes involved in the nucleotide pool metabolism), OPA1 and mitochondrial membrane dynamics play also an important role. Noticeably, the effect on mtDNA is different depending on the specific OPA1 isoforms down-regulated, suggesting the involvement of two different combined mechanisms. Over two hundred OPA1 mutations, spread throughout the coding region of the gene, have been described to date, including substitutions, deletions or insertions. Some mutations are predicted to generate a truncated protein inducing haploinsufficiency, whereas the missense nucleotide substitutions result in aminoacidic changes which affect conserved positions of the OPA1 protein. So far, the functional consequences of OPA1 mutations in cells from DOA patients are poorly understood. Phosphorus MR spectroscopy in patients with the c.2708delTTAG deletion revealed a defect in oxidative phosphorylation in muscles (Lodi et al., 2004). An energetic impairment has been also show in fibroblasts with the severe OPA1 R445H mutation (Amati-Bonneau et al., 2005). It has been previously reported by our group that OPA1 mutations leading to haploinsufficiency are associated in fibroblasts to an oxidative phosphorylation dysfunction, mainly involving the respiratory complex I (Zanna et al., 2008). In this study we have evaluated the energetic efficiency of a panel of skin fibroblasts derived from DOA patients, five fibroblast cell lines with OPA1 mutations causing haploinsufficiency (DOA-H) and two cell lines bearing mis-sense aminoacidic substitutions (DOA-AA), and compared with control fibroblasts. Although both types of DOA fibroblasts maintained a similar ATP content when incubated in a glucose-free medium, i.e. when forced to utilize the oxidative phosphorylation only to produce ATP, the mitochondrial ATP synthesis through complex I, measured in digitonin-permeabilized cells, was significantly reduced in cells with OPA1 haploinsufficiency only, whereas it was similar to controls in cells with the missense substitutions. Furthermore, evaluation of the mitochondrial membrane potential (DYm) in the two fibroblast lines DOA-AA and in two DOA-H fibroblasts, namely those bearing the c.2819-2A>C mutation and the c.2708delTTAG microdeletion, revealed an anomalous depolarizing response to oligomycin in DOA-H cell lines only. This finding clearly supports the hypothesis that these mutations cause a significant alteration in the respiratory chain function, which can be unmasked only when the operation of the ATP synthase is prevented. Noticeably, oligomycin-induced depolarization in these cells was almost completely prevented by preincubation with cyclosporin A, a well known inhibitor of the permeability transition pore (PTP). This results is very important because it suggests for the first time that the voltage threshold for PTP opening is altered in DOA-H fibroblasts. Although this issue has not yet been addressed in the present study, several are the mechanisms that have been proposed to lead to PTP deregulation, including in particular increased reactive oxygen species production and alteration of Ca2+ homeostasis, whose role in DOA fibroblasts PTP opening is currently under investigation. Identification of the mechanisms leading to altered threshold for PTP regulation will help our understanding of the pathophysiology of DOA, but also provide a strategy for therapeutic intervention.

A Multilevel Model with Time Series Components for the Analysis of Tribal Art Prices

In the present work we perform an econometric analysis of the Tribal art market. To this aim, we use a unique and original database that includes information on Tribal art market auctions worldwide from 1998 to 2011. In Literature, art prices are modelled through the hedonic regression model, a classic fixed-effect model. The main drawback of the hedonic approach is the large number of parameters, since, in general, art data include many categorical variables. In this work, we propose a multilevel model for the analysis of Tribal art prices that takes into account the influence of time on artwork prices. In fact, it is natural to assume that time exerts an influence over the price dynamics in various ways. Nevertheless, since the set of objects change at every auction date, we do not have repeated measurements of the same items over time. Hence, the dataset does not constitute a proper panel; rather, it has a two-level structure in that items, level-1 units, are grouped in time points, level-2 units. The main theoretical contribution is the extension of classical multilevel models to cope with the case described above. In particular, we introduce a model with time dependent random effects at the second level. We propose a novel specification of the model, derive the maximum likelihood estimators and implement them through the E-M algorithm. We test the finite sample properties of the estimators and the validity of the own-written R-code by means of a simulation study. Finally, we show that the new model improves considerably the fit of the Tribal art data with respect to both the hedonic regression model and the classic multilevel model.

Fluid-structure interaction by a coupled lattice Boltzmann-finite element approach

In this thesis, a strategy to model the behavior of fluids and their interaction with deformable bodies is proposed. The fluid domain is modeled by using the lattice Boltzmann method, thus analyzing the fluid dynamics by a mesoscopic point of view. It has been proved that the solution provided by this method is equivalent to solve the Navier-Stokes equations for an incompressible flow with a second-order accuracy. Slender elastic structures idealized through beam finite elements are used. Large displacements are accounted for by using the corotational formulation. Structural dynamics is computed by using the Time Discontinuous Galerkin method. Therefore, two different solution procedures are used, one for the fluid domain and the other for the structural part, respectively. These two solvers need to communicate and to transfer each other several information, i.e. stresses, velocities, displacements. In order to guarantee a continuous, effective, and mutual exchange of information, a coupling strategy, consisting of three different algorithms, has been developed and numerically tested. In particular, the effectiveness of the three algorithms is shown in terms of interface energy artificially produced by the approximate fulfilling of compatibility and equilibrium conditions at the fluid-structure interface. The proposed coupled approach is used in order to solve different fluid-structure interaction problems, i.e. cantilever beams immersed in a viscous fluid, the impact of the hull of the ship on the marine free-surface, blood flow in a deformable vessels, and even flapping wings simulating the take-off of a butterfly. The good results achieved in each application highlight the effectiveness of the proposed methodology and of the C++ developed software to successfully approach several two-dimensional fluid-structure interaction problems.

Bayesian space-time data fusion for real-time forecasting and map uncertainty

Environmental computer models are deterministic models devoted to predict several environmental phenomena such as air pollution or meteorological events. Numerical model output is given in terms of averages over grid cells, usually at high spatial and temporal resolution. However, these outputs are often biased with unknown calibration and not equipped with any information about the associated uncertainty. Conversely, data collected at monitoring stations is more accurate since they essentially provide the true levels. Due the leading role played by numerical models, it now important to compare model output with observations. Statistical methods developed to combine numerical model output and station data are usually referred to as data fusion. In this work, we first combine ozone monitoring data with ozone predictions from the Eta-CMAQ air quality model in order to forecast real-time current 8-hour average ozone level defined as the average of the previous four hours, current hour, and predictions for the next three hours. We propose a Bayesian downscaler model based on first differences with a flexible coefficient structure and an efficient computational strategy to fit model parameters. Model validation for the eastern United States shows consequential improvement of our fully inferential approach compared with the current real-time forecasting system. Furthermore, we consider the introduction of temperature data from a weather forecast model into the downscaler, showing improved real-time ozone predictions. Finally, we introduce a hierarchical model to obtain spatially varying uncertainty associated with numerical model output. We show how we can learn about such uncertainty through suitable stochastic data fusion modeling using some external validation data. We illustrate our Bayesian model by providing the uncertainty map associated with a temperature output over the northeastern United States.

A New Prediction Model for Slope Stability Analysis

The instability of river bank can result in considerable human and land losses. The Po river is the most important in Italy, characterized by main banks of significant and constantly increasing height. This study presents multilayer perceptron of artificial neural network (ANN) to construct prediction models for the stability analysis of river banks along the Po River, under various river and groundwater boundary conditions. For this aim, a number of networks of threshold logic unit are tested using different combinations of the input parameters. Factor of safety (FS), as an index of slope stability, is formulated in terms of several influencing geometrical and geotechnical parameters. In order to obtain a comprehensive geotechnical database, several cone penetration tests from the study site have been interpreted. The proposed models are developed upon stability analyses using finite element code over different representative sections of river embankments. For the validity verification, the ANN models are employed to predict the FS values of a part of the database beyond the calibration data domain. The results indicate that the proposed ANN models are effective tools for evaluating the slope stability. The ANN models notably outperform the derived multiple linear regression models.

Simulation of Smart Materials

The aim of this thesis is the elucidation of structure-properties relationship of molecular semiconductors for electronic devices. This involves the use of a comprehensive set of simulation techniques, ranging from quantum-mechanical to numerical stochastic methods, and also the development of ad-hoc computational tools. In more detail, the research activity regarded two main topics: the study of electronic properties and structural behaviour of liquid crystalline (LC) materials based on functionalised oligo(p-phenyleneethynylene) (OPE), and the investigation on the electric field effect associated to OFET operation on pentacene thin film stability. In this dissertation, a novel family of substituted OPE liquid crystals with applications in stimuli-responsive materials is presented. In more detail, simulations can not only provide evidence for the characterization of the liquid crystalline phases of different OPEs, but elucidate the role of charge transfer states in donor-acceptor LCs containing an endohedral metallofullerene moiety. Such systems can be regarded as promising candidates for organic photovoltaics. Furthermore, exciton dynamics simulations are performed as a way to obtain additional information about the degree of order in OPE columnar phases. Finally, ab initio and molecular mechanics simulations are used to investigate the influence of an applied electric field on pentacene reactivity and stability. The reaction path of pentacene thermal dimerization in the presence of an external electric field is investigated; the results can be related to the fatigue effect observed in OFETs, that show significant performance degradation even in the absence of external agents. In addition to this, the effect of the gate voltage on a pentacene monolayer are simulated, and the results are then compared to X-ray diffraction measurements performed for the first time on operating OFETs.

Statistical analysis of the error associated with the simplification of the stratigraphy in geotechnical models

The uncertainties in the determination of the stratigraphic profile of natural soils is one of the main problems in geotechnics, in particular for landslide characterization and modeling. The study deals with a new approach in geotechnical modeling which relays on a stochastic generation of different soil layers distributions, following a boolean logic – the method has been thus called BoSG (Boolean Stochastic Generation). In this way, it is possible to randomize the presence of a specific material interdigitated in a uniform matrix. In the building of a geotechnical model it is generally common to discard some stratigraphic data in order to simplify the model itself, assuming that the significance of the results of the modeling procedure would not be affected. With the proposed technique it is possible to quantify the error associated with this simplification. Moreover, it could be used to determine the most significant zones where eventual further investigations and surveys would be more effective to build the geotechnical model of the slope. The commercial software FLAC was used for the 2D and 3D geotechnical model. The distribution of the materials was randomized through a specifically coded MatLab program that automatically generates text files, each of them representing a specific soil configuration. Besides, a routine was designed to automate the computation of FLAC with the different data files in order to maximize the sample number. The methodology is applied with reference to a simplified slope in 2D, a simplified slope in 3D and an actual landslide, namely the Mortisa mudslide (Cortina d’Ampezzo, BL, Italy). However, it could be extended to numerous different cases, especially for hydrogeological analysis and landslide stability assessment, in different geological and geomorphological contexts.