Lower bounds for the first eigenvalue of the magnetic Laplacian

We consider a Riemannian cylinder endowed with a closed potential 1-form A and study the magnetic Laplacian with magnetic Neumann boundary conditions associated with those data. We establish a sharp lower bound for the first eigenvalue and show that the equality characterizes the situation where the metric is a product. We then look at the case of a planar domain bounded by two closed curves and obtain an explicit lower bound in terms of the geometry of the domain. We finally discuss sharpness of this last estimate.Comment: Replaces in part arXiv:1611.0193

Impatti dell'automazione sul mercato del lavoro. Prime stime per il caso italiano.

The causes of the present decline of demand in labor markets in developed countries are subject to considerable theoretical debate. More specifically, according to some authors, globalization and offshoring together with technological innovation, could lead to further negative impacts on real employment. Some studies estimate that the contribution of automation is the actual cause of job loss: in the US the introduction of robots by 2021 could lead to a cut of more than 6% of the workforce (FORRESTER 2016), and as much as 54% in Europe in the coming decades (Bowles 2014), although the greatest impact would occur in developing countries, where automation could weaken the traditional comparative advantages in terms of labor costs (UN 2016). The Italian case is particularly interesting, as the automation was introduced in large enterprises over three decades ago, determining a deep impact in terms of loss for low skilled jobs. This paper aims to provide a first quantification of the impacts on Italian labor market determined by the spread of latest technological innovations, both in terms of employment levels and social/territorial mobility, by differentiating its effects per macro-geographical breakdown of the country

From individual behaviour to an evaluation of the collective evolution of crowds along footbridges

This paper proposes a crowd dynamic macroscopic model grounded on microscopic phenomenological observations which are upscaled by means of a formal mathematical procedure. The actual applicability of the model to real world problems is tested by considering the pedestrian traffic along footbridges, of interest for Structural and Transportation Engineering. The genuinely macroscopic quantitative description of the crowd flow directly matches the engineering need of bulk results. However, three issues beyond the sole modelling are of primary importance: the pedestrian inflow conditions, the numerical approximation of the equations for non trivial footbridge geometries, and the calibration of the free parameters of the model on the basis of in situ measurements currently available. These issues are discussed and a solution strategy is proposed.Comment: 23 pages, 10 figures in J. Engrg. Math., 201

Finite population properties of predictors based on spatial patterns

When statistical inference is used for spatial prediction, the model-based framework known as kriging is commonly used. The predictor for an unsampled element of a population is a weighted combination of sampled values, in which weights are obtained by estimating the spatial covariance function. This solution can be affected by model misspecification and can be influenced by sampling design properties. In classical design-based finite population inference, these problems can be overcome; nevertheless, spatial solutions are still seldom used for this purpose. Through the efficient use of spatial information, a conceptual framework for design-based estimation has been developed in this study. We propose a standardized weighted predictor for unsampled spatial data, using the population information regarding spatial locations directly in the weighting system. Our procedure does not require model estimation of the spatial pattern because the spatial relationship is captured exclusively based on the Euclidean distances between locations (which are fixed and do not require assessment after sample selection). The individual predictor is a design-based ratio estimator, and we illustrate its properties for simple random sampling.spatial sampling; ratio estimator; design-based inference; model-based inference; spatial information in finite population inference campionamento spaziale, stimatore del rapporto, inferenza da disegno, inferenza da modello; informazione spaziale nell’inferenza da popolazioni finite

Modeling an offshore container terminal: the Venice case study

In order to reduce marine transportation times and related costs, as well as the environmental impacts, an alternative multimodal route to the current Suez-Gibraltar-North Sea corridor for the containers shipped from Far and Middle East was identified as potentially very effective. A key operational problem to achieve this result is the capacity and the effectiveness of the terminals within the concerned new logistic chain. In this framework, the Venice Port Authority is developing a project aimed to improve relevantly the potential of its container terminals to al-low loading/unloading of containers to and from the Central Europe. The project includes a new offshore terminal for mooring huge ships (up to 18.000 TEU) in the Adriatic Sea and a link operated by barges with an onshore terminal in Venice to overcome the constraints for the navigation of the containers ships in the Venetian lagoon. This innovative operational scheme requires a deep functional analysis to ensure the full capacity operation, assess the reachable performances and correspondingly dimensioning the required equipment (cranes, barges, quays, etc.). For this purpose, the authors developed a specific discrete-events simulation model. The paper includes the presentation of the model and the results of its application to Venice case study, by identifying the benefits achievable with this approach and the potential wider application fields

Nonparaxial dark solitons in optical Kerr media

We show that the nonlinear equation that describes nonparaxial Kerr propagation, together with the already reported bright-soliton solutions, admits of (1 + 1)D dark-soliton solutions. Unlike their paraxial counterparts, dark solitons can be excited only if their asymptotic normalized intensity u²_infinity is below 3/7; their width becomes constant when u²_infinity approaches this value