Compacton formation under Allen--Cahn dynamics

We study the solutions of a generalized Allen-Cahn equation deduced from a Landau energy functional, endowed with a non-constant higher order stiffness. We analytically solve the stationary problem and deduce the existence of so-called compactons, namely, connections on a finite interval between the two phases. The dynamics problem is numerically solved and compacton formation is described

Facing Loss: Reactions of Microeconomic Agents

The first part of the thesis is the paper \u201cA Bank Competition Model with TBTF Subsidy\u201d, develops a theoretical model which could offer some insights on the effects of a systemic subsidy on the competition dynamics among banks. In Chapter 1, there is the introduction to the work, with the research objective. In Chapter 2, there is the literature review on the subject. In Chapter 3, there is the description of the modelled economy and the agents. In Chapter 4, the static symmetric game case is developed. In Chapter 5, the static asymmetric game, with the subsidy, is developed and the Sub-game Perfect Nash Equilibria is found. In Chapter 6, the effects of the too-big-to-fail are analysed. In Chapter 7, conclusions are drawn. The second part of the thesis is the paper \u201cResponse Time under Gains and Losses\u201d, which has investigated cognitive effort exercised by subjects in a variety of games - binary and continuous choices, in both the individual context and in the social one - taking response times as a proxy. Its main focus has been the difference in the level of cognitive effort between the loss and the gain domain. In Chapter 1, there is the introduction to the work and the research objective is stated. In Chapter 2, there is the literature review on the subject. In Chapter 3, there is the description of the experiment held in CESARE lab at LUISS Guido Carli university. In Chapter 4, there is the analysis of response times, with a particular emphasis on the role of the domain. In Chapter 5, conclusions are drawn

An end-to-end KNN-based PTV approach for high-resolution measurements and uncertainty quantification

We introduce a novel end-to-end approach to improving the resolution of PIV measurements. The method blends information from different snapshots without the need for time-resolved measurements on grounds of similarity of flow regions in different snapshots. The main hypothesis is that, with a sufficiently large ensemble of statistically-independent snapshots, the identification of flow structures that are morphologically similar but occurring at different time instants is feasible. Measured individual vectors from different snapshots with similar flow organisation can thus be merged, resulting in an artificially increased particle concentration. This allows to refine the interrogation region and, consequently, increase the spatial resolution. The measurement domain is split in subdomains. The similarity is enforced only on a local scale, i.e. morphologically-similar regions are sought only among subdomains corresponding to the same flow region. The identification of locally-similar snapshots is based on unsupervised K-nearest neighbours search in a space of significant flow features. Such features are defined in terms of a Proper Orthogonal Decomposition, performed in subdomains on the original low-resolution data, obtained either with standard cross-correlation or with binning of Particle Tracking Velocimetry data with a relatively large bin size. A refined bin size is then selected according to the number of sufficiently close snapshots identified. The statistical dispersion of the velocity vectors within the bin is then used to estimate the uncertainty and to select the optimal K which minimises it. The method is tested and validated against datasets with a progressively increasing level of complexity: two virtual experiments based on direct simulations of the wake of a fluidic pinball and a channel flow and the experimental data collected in a turbulent boundary layer.This project has received funding from the European Research Council (ERC) under the European Union Horizon 2020 research and innovation program (grant agreement No 949085). Funding for APC: Universidad Carlos III de Madrid (Read & Publish Agreement CRUE-CSIC 2022)

Genetically-inspired convective heat transfer enhancement in a turbulent boundary layer

The convective heat transfer in a turbulent boundary layer (TBL) on a flat plate is enhanced using an artificial intelligence approach based on linear genetic algorithms control (LGAC). The actuator is a set of six slot jets in crossflow aligned with the freestream. An open-loop optimal periodic forcing is defined by the carrier frequency, the duty cycle and the phase difference between actuators as control parameters. The control laws are optimised with respect to the unperturbed TBL and to the actuation with a steady jet. The cost function includes the wall convective heat transfer rate and the cost of the actuation. The performance of the controller is assessed by infrared thermography and characterised also with particle image velocimetry measurements. The optimal controller yields a slightly asymmetric flow field. The LGAC algorithm converges to the same frequency and duty cycle for all the actuators. It is noted that such frequency is strikingly equal to the inverse of the characteristic travel time of large-scale turbulent structures advected within the near-wall region. The phase difference between multiple jet actuation has shown to be very relevant and the main driver of flow asymmetry. The results pinpoint the potential of machine learning control in unravelling unexplored controllers within the actuation space. Our study furthermore demonstrates the viability of employing sophisticated measurement techniques together with advanced algorithms in an experimental investigation.Comment: 20 pages, 13 figure

A simple trick to improve the accuracy of PIV/PTV data

Particle Image Velocimetry (PIV) estimates velocities through correlations of particle images within interrogation windows, leading to a spatial modulation of the velocity field. Although in principle Particle Tracking Velocimetry (PTV) estimates locally a non-modulated particle displacement, to exploit the scattered data from PTV it is necessary to interpolate these data on a structured grid, which implies a spatial modulation effect that biases the resulting velocity field. This systematic error due to finite spatial resolution inevitably depends on the interrogation window size and on the interparticle spacing. It must be observed that all these operations (cross-correlation, direct interpolation or averaging in windows) induce modulation on both the mean and the fluctuating part. We introduce a simple trick to reduce this systematic error source of PIV/PTV measurements exploiting ensemble statistics. Ensemble Particle Tracking Velocimetry (EPTV) can be leveraged to obtain the high-resolution mean flow by merging the different instantaneous realisations. The mean flow can be estimated with EPTV, and the fluctuating part can be measured from PIV/PTV. The high-resolution mean can then be superposed to the instantaneous fluctuating part to obtain velocity fields with lower systematic error. The methodology is validated against datasets with a progressively increasing level of complexity: two virtual experiments based on direct numerical simulations (DNS) of the wake of a fluidic pinball and a channel flow and the experimental data of a turbulent boundary layer. For all the cases both PTV and PIV are analysed.This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement No 949085, project: NEXTFLOW).Publicad

Design principles for metamorphic block copolymer assemblies

Certain block copolymer assemblies in selective solvents undergo dynamic morphology transitions (metamorphism) on varying the solution temperature. Despite the great application potential, there is a lack of fundamental understanding of the relationship between copolymer composition and the thermally-induced metamorphic behavior. Herein this relationship is studied by applying Scheutjens-Fleer Self-Consistent Field (SF-SCF) theory to develop fundamental design principles for thermoresponsive diblock copolymers exhibiting metamorphic behavior. It is found that metamorphism is caused by variation in the degree of stretching of the lyophobic blocks in response to changes in solvency. An optimal lyophobic/lyophilic block length ratio interval 3.5 ≲ fB ≲ 5.5 is identified. Such a fB window allows switching between spheres, cylinders and vesicles as preferred morphologies, with relatively small changes in the lyophobic block solvency. The transition from spheres to cylinders and from cylinders to bilayers can be controlled by varying fB, the overall degree of polymerization of the diblock copolymer, and by choosing an appropriate lyophilic block. Empirical relationships are provided to establish a connection between the SCF–SCF predictions and experimental observations

Lactoferrin's anti-cancer properties. Safety, selectivity, and wide range of action

Despite recent advances in cancer therapy, current treatments, including radiotherapy, chemotherapy, and immunotherapy, although beneficial, present attendant side effects and long-term sequelae, usually more or less affecting quality of life of the patients. Indeed, except for most of the immunotherapeutic agents, the complete lack of selectivity between normal and cancer cells for radio- and chemotherapy can make them potential antagonists of the host anti-cancer self-defense over time. Recently, the use of nutraceuticals as natural compounds corroborating anti-cancer standard therapy is emerging as a promising tool for their relative abundance, bioavailability, safety, low-cost effectiveness, and immuno-compatibility with the host. In this review, we outlined the anti-cancer properties of Lactoferrin (Lf), an iron-binding glycoprotein of the innate immune defense. Lf shows high bioavailability after oral administration, high selectivity toward cancer cells, and a wide range of molecular targets controlling tumor proliferation, survival, migration, invasion, and metastasization. Of note, Lf is able to promote or inhibit cell proliferation and migration depending on whether it acts upon normal or cancerous cells, respectively. Importantly, Lf administration is highly tolerated and does not present significant adverse effects. Moreover, Lf can prevent development or inhibit cancer growth by boosting adaptive immune response. Finally, Lf was recently found to be an ideal carrier for chemotherapeutics, even for the treatment of brain tumors due to its ability to cross the blood-brain barrier, thus globally appearing as a promising tool for cancer prevention and treatment, especially in combination therapies

Kink Localization under Asymmetric Double-Well Potential

We study diffuse phase interfaces under asymmetric double-well potential energies with degenerate minima and demonstrate that the limiting sharp profile, for small interface energy cost, on a finite space interval is in general not symmetric and its position depends exclusively on the second derivatives of the potential energy at the two minima (phases). We discuss an application of the general result to porous media in the regime of solid-fluid segregation under an applied pressure and describe the interface between a fluid-rich and a fluid-poor phase. Asymmetric double-well potential energies are also relevant in a very different field of physics as that of Brownian motors. An intriguing analogy between our result and the direction of the dc soliton current in asymmetric substrate driven Brownian motors is pointed out