Studio Sperimentale e Modellazione della Separazione di Proteine con Membrane di Affinità

Chromatography represents one of the most important and widely used unit operation in the biotechnology industry. However this technique suffers from several limitations such as high pressure drop, slow mass transfer through the diffusive pores and strong dependence of the binding capacity on flow rate. In this work, affinity membranes with improved capacity have been considered as an alternative technology for the capturing step in antibody manufacturing. Several affinity membranes have been prepared starting from various membrane supports. Different affinity ligands have been utilized like Protein A, the natural ligand of choice for antibodies, as well as synthetic ligands that exhibit affinity for the Fc portion of antibodies. The membranes have been characterized in detail: binding and elution performance was evaluated in adsorption experiments using pure IgG solutions, while membrane selectivity was evaluated using complex solutions like a cell culture supernatant. The most promising affinity membranes were extensively tested in dynamic experiments. The effects of operating parameters like feed concentration and flow rate on separation performances like binding capacity, selectivity and process yield have been studied in detail in order to find the optimal conditions for binding and elution steps. The membranes have been used over several complete chromatographic cycles to evaluate the effects of ageing and of membrane regeneration on dynamic binding capacity. A novel mathematical model is proposed that can describe all the chromatographic steps involved in the membrane affinity chromatography process for protein purification. The mathematical description is based on the species continuity equation coupled with a proper binding kinetic equation, and suitable to describe adequately the dispersion phenomena occurring both in the micro-porous membranes as well as in the extra-column devices used in the system. The model considers specifically all the different chromatographic steps, namely adsorption, washing and elution. The few relevant fitting parameters of the model were derived from a calibration with the experimental affinity cycles performed with pure IgG solutions, then the model is used to describe experimental data obtained in chromatographic cycles carried out with complex feeds as the cell culture supernatant. Simulations reveal a good agreement with experimental data in all the chromatography steps, both in the case of pure IgG solutions and for the cell culture supernatant considered.

Support infrastructures for multimedia services with guaranteed continuity and QoS

Advances in wireless networking and content delivery systems are enabling new challenging provisioning scenarios where a growing number of users access multimedia services, e.g., audio/video streaming, while moving among different points of attachment to the Internet, possibly with different connectivity technologies, e.g., Wi-Fi, Bluetooth, and cellular 3G. That calls for novel middlewares capable of dynamically personalizing service provisioning to the characteristics of client environments, in particular to discontinuities in wireless resource availability due to handoffs. This dissertation proposes a novel middleware solution, called MUM, that performs effective and context-aware handoff management to transparently avoid service interruptions during both horizontal and vertical handoffs. To achieve the goal, MUM exploits the full visibility of wireless connections available in client localities and their handoff implementations (handoff awareness), of service quality requirements and handoff-related quality degradations (QoS awareness), and of network topology and resources available in current/future localities (location awareness). The design and implementation of the all main MUM components along with extensive on the field trials of the realized middleware architecture confirmed the validity of the proposed full context-aware handoff management approach. In particular, the reported experimental results demonstrate that MUM can effectively maintain service continuity for a wide range of different multimedia services by exploiting handoff prediction mechanisms, adaptive buffering and pre-fetching techniques, and proactive re-addressing/re-binding.

Bayesian Analysis of Linear Inverse Problems with Applications in Economics and Finance

In my PhD thesis I propose a Bayesian nonparametric estimation method for structural econometric models where the functional parameter of interest describes the economic agent's behavior. The structural parameter is characterized as the solution of a functional equation, or by using more technical words, as the solution of an inverse problem that can be either ill-posed or well-posed. From a Bayesian point of view, the parameter of interest is a random function and the solution to the inference problem is the posterior distribution of this parameter. A regular version of the posterior distribution in functional spaces is characterized. However, the infinite dimension of the considered spaces causes a problem of non continuity of the solution and then a problem of inconsistency, from a frequentist point of view, of the posterior distribution (i.e. problem of ill-posedness). The contribution of this essay is to propose new methods to deal with this problem of ill-posedness. The first one consists in adopting a Tikhonov regularization scheme in the construction of the posterior distribution so that I end up with a new object that I call regularized posterior distribution and that I guess it is solution of the inverse problem. The second approach consists in specifying a prior distribution on the parameter of interest of the g-prior type. Then, I detect a class of models for which the prior distribution is able to correct for the ill-posedness also in infinite dimensional problems. I study asymptotic properties of these proposed solutions and I prove that, under some regularity condition satisfied by the true value of the parameter of interest, they are consistent in a "frequentist" sense. Once I have set the general theory, I apply my bayesian nonparametric methodology to different estimation problems. First, I apply this estimator to deconvolution and to hazard rate, density and regression estimation. Then, I consider the estimation of an Instrumental Regression that is useful in micro-econometrics when we have to deal with problems of endogeneity. Finally, I develop an application in finance: I get the bayesian estimator for the equilibrium asset pricing functional by using the Euler equation defined in the Lucas'(1978) tree-type models.

Continuity and Change in New Products

This doctoral dissertation is triggered by an emergent problem: how can firms reinvent themselves? Continuity- and change-oriented decisions fundamentally shape overtime the activities and potential revenues of organizations and other adaptive systems, but both types of actions draw upon limited resources and rely on different organizational routines and capabilities. Most organizations appear to have difficulties in making tradeoffs, so that it is easier to overinvest in one of them than to successfully achieve a mixture of both. Nevertheless, theory and empirical evidence suggest that too little of either may reduce performance, indicating a need to learn more about how organizations reconcile these tensions. In the first paper, I moved from the consideration that rapid changes in competitive environments increasingly require firms to be “ambidextrous” implementing organizational mechanisms and structures that allow continuity- and change-oriented activities to be engaged at the same time. More specifically, I show that continuity- and change-related decisions can’t be confined either inside or outside the firm, but span overtime across distinct decision domains located within and beyond the organizational boundaries. Reconciling static and dynamic perspectives of ambidexterity, I conceptualize a firm’s strategy as a bundle of decisions about product attributes and components of the production team, proposing a multidimensional and dynamic model of structural ambidexterity that explains why and how firms could manage conflicting pressures for continuity and change in the context of new products. In the second study I note how rigorous systematic evidence documenting the success of ambidextrous organizations is lacking, and there has been very little investigation of how firms deal with continuity and change in new products. How to manage the transition form a successful product to another? What to change and what to keep? Incumbents that deal with series of products over time need to update their offerings in order to have the most relevant attributes to prospect clients without disappoint the current customer base. They need to both match and anticipate consumers’ preferences, blending something old with something new to satisfy the current demand and enlarge the herd by appealing to newer audiences. This paper contributes to strategic renewal and ambidexterity-related research with the first empirically assessment of a positive consumer response to ambidexterity in new products. Also, this study provides a practical method to monitor overtime the degree to which a brand or a firm is continuity- or change- oriented and evaluate different strategy profiles across two decision domains that play a pivotal role in new products: product attributes and components of the production team.

Spectrum reconstruction from a scattering measurement using the adjoint Boltzmann transport equation for photons

Quality control of medical radiological systems is of fundamental importance, and requires efficient methods for accurately determine the X-ray source spectrum. Straightforward measurements of X-ray spectra in standard operating require the limitation of the high photon flux, and therefore the measure has to be performed in a laboratory. However, the optimal quality control requires frequent in situ measurements which can be only performed using a portable system. To reduce the photon flux by 3 magnitude orders an indirect technique based on the scattering of the X-ray source beam by a solid target is used. The measured spectrum presents a lack of information because of transport and detection effects. The solution is then unfolded by solving the matrix equation that represents formally the scattering problem. However, the algebraic system is ill-conditioned and, therefore, it is not possible to obtain a satisfactory solution. Special strategies are necessary to circumvent the ill-conditioning. Numerous attempts have been done to solve this problem by using purely mathematical methods. In this thesis, a more physical point of view is adopted. The proposed method uses both the forward and the adjoint solutions of the Boltzmann transport equation to generate a better conditioned linear algebraic system. The procedure has been tested first on numerical experiments, giving excellent results. Then, the method has been verified with experimental measurements performed at the Operational Unit of Health Physics of the University of Bologna. The reconstructed spectra have been compared with the ones obtained with straightforward measurements, showing very good agreement.

Master Equation: Biological Applications and Thermodynamic Description

It is well known that many realistic mathematical models of biological systems, such as cell growth, cellular development and differentiation, gene expression, gene regulatory networks, enzyme cascades, synaptic plasticity, aging and population growth need to include stochasticity. These systems are not isolated, but rather subject to intrinsic and extrinsic fluctuations, which leads to a quasi equilibrium state (homeostasis). The natural framework is provided by Markov processes and the Master equation (ME) describes the temporal evolution of the probability of each state, specified by the number of units of each species. The ME is a relevant tool for modeling realistic biological systems and allow also to explore the behavior of open systems. These systems may exhibit not only the classical thermodynamic equilibrium states but also the nonequilibrium steady states (NESS). This thesis deals with biological problems that can be treat with the Master equation and also with its thermodynamic consequences. It is organized into six chapters with four new scientific works, which are grouped in two parts: (1) Biological applications of the Master equation: deals with the stochastic properties of a toggle switch, involving a protein compound and a miRNA cluster, known to control the eukaryotic cell cycle and possibly involved in oncogenesis and with the propose of a one parameter family of master equations for the evolution of a population having the logistic equation as mean field limit. (2) Nonequilibrium thermodynamics in terms of the Master equation: where we study the dynamical role of chemical fluxes that characterize the NESS of a chemical network and we propose a one parameter parametrization of BCM learning, that was originally proposed to describe plasticity processes, to study the differences between systems in DB and NESS.