Bank business model migrations in Europe: determinants and effects

In response to post-crisis regulatory reforms, the European banking sector has undergone significant changes that have led banks to reconsider their strategies, structures and operations. Based on a sample of over 3,000 banks from 32 European countries during the period 2010–2017, we identify banks’ business models based on cluster analysis and track their evolution.We then apply a logistic regression and find that banks with higher risk and lower profitability are more likely to change their business model. Employing a propensity score matching approach, we investigate the effect of migration on bank performance and find that changing the business model affects banks positively (i.e. migrating banks increase their profitability, stability and cost efficiency). The effect of migration differs depending on the target business model. When switches are a consequence of being acquired or motivated by regulatory compliance, the positive impact remains

A graph theoretical analysis of the energy landscape of model polymers

In systems characterized by a rough potential energy landscape, local energetic minima and saddles define a network of metastable states whose topology strongly influences the dynamics. Changes in temperature, causing the merging and splitting of metastable states, have non trivial effects on such networks and must be taken into account. We do this by means of a recently proposed renormalization procedure. This method is applied to analyze the topology of the network of metastable states for different polypeptidic sequences in a minimalistic polymer model. A smaller spectral dimension emerges as a hallmark of stability of the global energy minimum and highlights a non-obvious link between dynamic and thermodynamic properties.Comment: 15 pages, 15 figure

Anticooperativity in diffusion-controlled reactions with pairs of anisotropic domains: a model for the antigen-antibody encounter

The encounter between anisotropic agents in diffusion-controlled reactions is a topic of very general relevance in chemistry and biology. Here we introduce a simplified model of encounter of an isotropic molecule with a pair of partially reacting agents and apply it to the encounter reaction between an antibody and its antigen. We reduce the problem to the solution of dual series relations, which can be solved iteratively, yielding the exact solution for the encounter rate constant at any desired order of accuracy. We quantify the encounter effectiveness by means of a simple indicator and show that the two binding centers systematically behave in an anticooperative fashion. However, we demonstrate that a reduction of the binding active sites allows the composite molecule to recover binding effectiveness, in spite of the overall reduction of the rate constant. In addition, we provide a simple formula that enables one to calculate the anticooperativity as a function of the size of the binding site for any values of the separation between the two active lobes and of the antigen size. Finally, some biological implications of our results are discusse

A Bioinformatics Approach to Investigate Structural and Non-Structural Proteins in Human Coronaviruses

Recent studies confirmed that people unexposed to SARS-CoV-2 have preexisting reactivity, probably due to previous exposure to widely circulating common cold coronaviruses. Such preexistent reactivity against SARS-CoV-2 comes from memory T cells that can specifically recognize a SARS-CoV-2 epitope of structural and non-structural proteins and the homologous epitopes from common cold coronaviruses. Therefore, it is important to understand the SARS-CoV-2 cross-reactivity by investigating these protein sequence similarities with those of different circulating coronaviruses. In addition, the emerging SARS-CoV-2 variants lead to an intense interest in whether mutations in proteins (especially in the spike) could potentially compromise vaccine effectiveness. Since it is not clear that the differences in clinical outcomes are caused by common cold coronaviruses, a deeper investigation on cross-reactive T-cell immunity to SARS-CoV-2 is crucial to examine the differential COVID-19 symptoms and vaccine performance. Therefore, the present study can be a starting point for further research on cross-reactive T cell recognition between circulating common cold coronaviruses and SARS-CoV-2, including the most recent variants Delta and Omicron. In the end, a deep learning approach, based on Siamese networks, is proposed to accurately and efficiently calculate a BLAST-like similarity score between protein sequences

An AT-barrier mechanically controls DNA reannealing under tension

Regulation of genomic activity occurs through the manipulation of DNA by competent mechanoenzymes. Force-clamp optical tweezers that allow the structural dynamics of the DNA molecule to be measured were used here to investigate the kinetics of mechanically-driven strand reannealing. When the force on the torsionally unconstrained lambda-phage DNA is decreased stepwise from above to below the overstretching transition, reannealing occurs via discrete shortening steps separated by exponentially distributed time intervals. Kinetic analysis reveals a transition barrier 0.58 nm along the reaction coordinate and an average reannealing-step size of approximately 750 bp, consistent with the average bp interval separating segments of more than 10 consecutive AT bases. In an AT-rich DNA construct, in which the distance between segments of more than 10 consecutive AT is reduced to approximately 210 bps, the reannealing step reduces accordingly without changes in the position of the transition barrier. Thus, the transition barrier for reannealing is determined by the presence of segments of more than 10 consecutive AT bps independent of changes in sequence composition, while the length of the reannealing strand changes according to the distance between poly-AT segments at least 10 bps long

Stochastic dynamics of model proteins on a directed graph

A method for reconstructing the energy landscape of simple polypeptidic chains is described. We show that we can construct an equivalent representation of the energy landscape by a suitable directed graph. Its topological and dynamical features are shown to yield an effective estimate of the time scales associated with the folding and with the equilibration processes. This conclusion is drawn by comparing molecular dynamics simulations at constant temperature with the dynamics on the graph, defined by a temperature dependent Markov process. The main advantage of the graph representation is that its dynamics can be naturally renormalized by collecting nodes into "hubs", while redefining their connectivity. We show that both topological and dynamical properties are preserved by the renormalization procedure. Moreover, we obtain clear indications that the heteropolymers exhibit common topological properties, at variance with the homopolymer, whose peculiar graph structure stems from its spatial homogeneity. In order to obtain a clear distinction between a "fast folder" and a "slow folder" in the heteropolymers one has to look at kinetic features of the directed graph. We find that the average time needed to the fast folder for reaching its native configuration is two orders of magnitude smaller than its equilibration time, while for the bad folder these time scales are comparable. Accordingly, we can conclude that the strategy described in this paper can be successfully applied also to more realistic models, by studying their renormalized dynamics on the directed graph, rather than performing lengthy molecular dynamics simulations.Comment: 15 pages, 12 figure

Geometry of the energy landscape of the self-gravitating ring

We study the global geometry of the energy landscape of a simple model of a self-gravitating system, the self-gravitating ring (SGR). This is done by endowing the configuration space with a metric such that the dynamical trajectories are identified with geodesics. The average curvature and curvature fluctuations of the energy landscape are computed by means of Monte Carlo simulations and, when possible, of a mean-field method, showing that these global geometric quantities provide a clear geometric characterization of the collapse phase transition occurring in the SGR as the transition from a flat landscape at high energies to a landscape with mainly positive but fluctuating curvature in the collapsed phase. Moreover, curvature fluctuations show a maximum in correspondence with the energy of a possible further transition, occurring at lower energies than the collapse one, whose existence had been previously conjectured on the basis of a local analysis of the energy landscape and whose effect on the usual thermodynamic quantities, if any, is extremely weak. We also estimate the largest Lyapunov exponent $\lambda$ of the SGR using the geometric observables. The geometric estimate always gives the correct order of magnitude of $\lambda$ and is also quantitatively correct at small energy densities and, in the limit $N\to\infty$, in the whole homogeneous phase.Comment: 20 pages, 12 figure

Bank Business Model Migrations in Europe: Determinants and Effects

In response to the post-crisis regulatory reforms, the European banking sector has undergone significant changes that have led banks to reconsider their strategies, structures, and operations. Based on a sample of over 3,000 banks from 32 European countries during the period 2010-2017, we identify banks' business models based on cluster analysis and track their evolution. We then apply a logistic regression and find that banks with higher risk and lower profitability are more likely to change their business model. Employing a propensity score matching approach, we investigate the effect of migration on bank performance and find that changing the business model affects banks positively, i.e., migrating banks increase their profitability, stability, and cost-efficiency. The effect of migration differs depending on the target business model. When switches are a consequence of being acquired or motivated by regulatory compliance, the positive impact remains

Dynamic & Cyclic behaviour of ballast in the long term as determined in Cedex's track box

The 6 cylinder servo-hydraulic loading system of CEDEX's track box (250 kN, 50 Hz) has been recently implemented with a new piezoelectric loading system (±20 kN, 300 Hz) allowing the incorporation of low amplitude high frequency dynamic load time histories to the high amplitude low frequency quasi-static load time histories used so far in the CEDEX's track box to assess the inelastic long term behavior of ballast under mixed traffic in conventional and high- speed lines. This presentation will discuss the results obtained in the first long-duration test performed at CEDEX's track box using simultaneously both loading systems, to simulate the pass-by of 6000 freight vehicles (1M of 225 kN axle loads) travelling at a speed of 120 km/h over a line with vertical irregularities corresponding to a medium quality lin3e level. The superstructure of the track tested at full scale consisted of E 60 rails, stiff rail pads (mayor que 450 kN/mm), B90.2 sleepers with USP 0.10 N/mm and a 0.35 m thick ballast layer of ADIF first class. A shear wave velocity of 250 m/s can be assumed for the different layers of the track sub-base. The ballast long-term settlements will be compared with those obtained in a previous long-duration quasi- static test performed in the same track, for the RIVAS [EU co-funded] project, in which no dynamic loads where considered. Also, the results provided by a high diameter cyclic triaxial cell with ballast tested in full size will be commented. Finally, the progress made at CEDEX's Geotechnical Laboratory to reproduce numerically the long term behavior of ballast will be discussed