Minimum energy paths for conformational changes of viral capsids

In this work we study how a viral capsid can change conformation using techniques of Large Deviations Theory for stochastic differential equations. The viral capsid is a model of a complex system in which many units - the proteins forming the capsomers - interact by weak forces to form a structure with exceptional mechanical resistance. The destabilization of such a structure is interesting both per se, since it is related either to infection or maturation processes, and because it yields insights into the stability of complex structures in which the constitutive elements interact by weak attractive forces. We focus here on a simplified model of a dodecahederal viral capsid, and assume that the capsomers are rigid plaquettes with one degree of freedom each. We compute the most probable transition path from the closed capsid to the final configuration using minimum energy paths, and discuss the stability of intermediate states.Comment: 27 pages, 4 figures. New version, to appear in Physical Review

Γ\Gamma-limit of the cut functional on dense graph sequences

A sequence of graphs with diverging number of nodes is a dense graph sequence if the number of edges grows approximately as for complete graphs. To each such sequence a function, called graphon, can be associated, which contains information about the asymptotic behavior of the sequence. Here we show that the problem of subdividing a large graph in communities with a minimal amount of cuts can be approached in terms of graphons and the $\Gamma$-limit of the cut functional, and discuss the resulting variational principles on some examples. Since the limit cut functional is naturally defined on Young measures, in many instances the partition problem can be expressed in terms of the probability that a node belongs to one of the communities. Our approach can be used to obtain insights into the bisection problem for large graphs, which is known to be NP-complete.Comment: 25 pages, 5 figure

The RGB-D Triathlon: Towards Agile Visual Toolboxes for Robots

Deep networks have brought significant advances in robot perception, enabling to improve the capabilities of robots in several visual tasks, ranging from object detection and recognition to pose estimation, semantic scene segmentation and many others. Still, most approaches typically address visual tasks in isolation, resulting in overspecialized models which achieve strong performances in specific applications but work poorly in other (often related) tasks. This is clearly sub-optimal for a robot which is often required to perform simultaneously multiple visual recognition tasks in order to properly act and interact with the environment. This problem is exacerbated by the limited computational and memory resources typically available onboard to a robotic platform. The problem of learning flexible models which can handle multiple tasks in a lightweight manner has recently gained attention in the computer vision community and benchmarks supporting this research have been proposed. In this work we study this problem in the robot vision context, proposing a new benchmark, the RGB-D Triathlon, and evaluating state of the art algorithms in this novel challenging scenario. We also define a new evaluation protocol, better suited to the robot vision setting. Results shed light on the strengths and weaknesses of existing approaches and on open issues, suggesting directions for future research.Comment: This work has been submitted to IROS/RAL 201

Boosting Deep Open World Recognition by Clustering

While convolutional neural networks have brought significant advances in robot vision, their ability is often limited to closed world scenarios, where the number of semantic concepts to be recognized is determined by the available training set. Since it is practically impossible to capture all possible semantic concepts present in the real world in a single training set, we need to break the closed world assumption, equipping our robot with the capability to act in an open world. To provide such ability, a robot vision system should be able to (i) identify whether an instance does not belong to the set of known categories (i.e. open set recognition), and (ii) extend its knowledge to learn new classes over time (i.e. incremental learning). In this work, we show how we can boost the performance of deep open world recognition algorithms by means of a new loss formulation enforcing a global to local clustering of class-specific features. In particular, a first loss term, i.e. global clustering, forces the network to map samples closer to the class centroid they belong to while the second one, local clustering, shapes the representation space in such a way that samples of the same class get closer in the representation space while pushing away neighbours belonging to other classes. Moreover, we propose a strategy to learn class-specific rejection thresholds, instead of heuristically estimating a single global threshold, as in previous works. Experiments on RGB-D Object and Core50 datasets show the effectiveness of our approach.Comment: IROS/RAL 202

Effect of strain-induced electronic topological transitions on the superconducting properties of LaSrCuO thin films

We propose a Ginzburg-Landau phenomenological model for the dependence of the critical temperature on microscopic strain in tetragonal high-Tc cuprates. Such a model is in agreement with the experimental results for LSCO under epitaxial strain, as well as with the hydrostatic pressure dependence of Tc in most cuprates. In particular, a nonmonotonic dependence of Tc on hydrostatic pressure, as well as on in-plane or apical microstrain, is derived. From a microscopic point of view, such results can be understood as due to the proximity to an electronic topological transition (ETT). In the case of LSCO, we argue that such an ETT can be driven by a strain-induced modification of the band structure, at constant hole content, at variance with a doping-induced ETT, as is usually assumed.Comment: EPJB, to be publishe

A dynamic analysis of regional R&D efficiency. The case of Italian and Spanish regions

Research and Development activities are key elements in the search of more productive economic outcomes, the generation of new economic sectors and, in general, of a better economic performance at the micro and macro levels. In many European countries, the responsibility of the design and implementation of R&D policies is shifting from the national level to the regional level, making the regional level a relevant field of analysis. Spain and Italy are examples of this progressive change. At the same time, the financial, economic and social crisis that is affecting the countries situated in the periphery of the eurozone is reducing the budget for R&D activities that firms, universities, public administrations and other institutions can devote to this issue. Again, Spain and Italy are clear examples of economic difficulties and diminishing public and private budgets. In this context, it is crucial to assess and measure the efficiency of all kind of expenditures, especially the ones that are directly linked with the achievement of a more competitive economy. In this way, regions achieving more efficiency should be granted with more funding or, alternatively, not efficient regions should adapt efficient R&D policies to their own institutional and social backgrounds. In this paper we will use the DEA (Data Envelopment Analysis) methodology in order to measure at the regional level the efficiency ratio between R&D inputs and the outcomes achieved. DEA methodology compares the amount of inputs used with the outcomes achieved, ordering regions in terms of productivity, not in terms of absolute values. Following this path, the best ranked region will be the one that minimizes the use of inputs maximizing the amount of outputs. Results over time will be discussed and regions will be grouped according to their efficiency level and their evolution in this field over time. Comparisons between regions will be made at the national level (Italian regions on one side and Spanish regions on the other) and also adding all regions from the two countries. Typologies of regions according to their efficiency levels will be outlined and justified. The paper will conclude with some policy recommendations for each group of regions, so that regions can design policies and adopt measures in order to improve their efficiency and their overall results regarding R&D

Strategies to innovate in SMEs: analyzing the key factors of internationalization and interaction in Basque and Sicilian firms

The increasing openness of economies and the phenomenon of globalization has led to know-how and innovation becoming the key factors for business in terms of competitiveness. Thus, the fact that the activities and services are increasingly innovative means that the construction of innovation is channeled through the social sphere, attributing an increasingly important and critical role to the field of local development. For this motive, in recent years, economic literature has focused its attention at the regional and local level. The liberalization of transport and the development of the information technologies have enabled traditional production factors, such as the availability of natural resources, low labor and capital costs, ceasing to be a real competitive advantage for territories. The economy begins to distance from market factors such as contractual relations becoming more relational and especially focusing attention on geographical context conditions capable of promoting interaction between individual and collective subjects. The knowledge of workers becomes, within firms, the raw material from which the company can get innovative products and services. The exchange of knowledge and experiences between firms and within firms together with a high level of interaction among the agents, that constitute the social and economic environment of a region, becomes a source of competitive advantage and represent a key strategy for the generation of innovation at the firm levels. Internationalization and interaction for SMEs represent action strategies in an increasingly complex environment where territory plays a key role. The geographical areas with all their knowledge and experiences present in their context are the source of tacit knowledge that determines the competitive advantage of the new millennium. In this paper we analyze the predictors of innovation generation in SMEs, demonstrating the relevance of internationalization and cooperation strategies in Basque and Sicilian firms comparing the two experiences. SMEs constitute the majority productive Basque and Sicilian territorial reality and their impact on the local economy is crucial for the development of the two regions

Weak helix submanifolds of euclidean spaces

It is shown that there exist nonstrong weak 2-helix surfaces of R

On certain surfaces in the Euclidean space E3{\mathbb{E}}^3

In the present paper we classify all surfaces in \E^3 with a canonical principal direction. Examples of these type of surfaces are constructed. We prove that the only minimal surface with a canonical principal direction in the Euclidean space ${\mathbb{E}}^3$ is the catenoid.Comment: 13 Latex page