Mercantilism and Class Struggle: Italy in the International Economy, 1960-1990

The outbreak of the world-wide economic crisis in 2008 and its later worsening brought the topic of Italy’s ‘economic decline’ to the forefront of public debate The most common explanations of this decline revolve round the inability of Italian society to adapt to the new conditions caused by the advent of the ‘second wave of globalisation’ after the 1970s. Emphasis falls on the burden of public debt, the inadequacy of the reforms of Italy’s economic and social institutions (privatisation, flexibility in the labour market, market liberalisation and deregulation) and on the need for investment in education. Here, we adopt a different outlook, one which hinges on class interests and the conflict between them. The chapter covers the development of the Italian economy from 1945 to the 1990s, focusing in particular on the period starting with the crisis which put an end to the ‘economic miracle’ in 1963 and ends in 1992, when the lira left the European Monetary System. This was a period of sustained, and unprecedented, growth for the Italian economy, during which Italy caught up with other advanced industrial economies. At the same time, those were the years in which we can find the roots of the problems which have afflicted the Italian economy in the last two decades

Piezoelectric vibration energy harvesting from airflow in HVAC (Heating Ventilation and Air Conditioning) systems

This study focuses on the design and wind tunnel testing of a high efficiency Energy Harvesting device, based on piezoelectric materials, with possible applications for the sustainability of smart buildings, structures and infrastructures. The development of the device was supported by ESA (the European Space Agency) under a program for the space technology transfer in the period 2014-2016. The EH device harvests the airflow inside Heating, Ventilation and Air Conditioning (HVAC) systems, using a piezoelectric component and an appropriate customizable aerodynamic appendix or fin that takes advantage of specific airflow phenomena (vortex shedding and galloping), and can be implemented for optimizing the energy consumption inside buildings. Focus is given on several relevant aspects of wind tunnel testing: different configurations for the piezoelectric bender (rectangular, cylindrical and T-shaped) are tested and compared, and the effective energy harvesting potential of a working prototype device is assessed

Stabilization through integration: the European rescue of Italian capitalism

Since its origins European integration has been closely connected to the social tensions that capitalism generates. During the interwar years, one of the main rationales behind the push to deeper European economic integration was the search for increased prosperity as a means to prevent class conflict. After the economic collapse of the 1930s and the Second World War, the European Communities were an essential part of a larger effort towards the restoration of capitalism\u2019s legitimacy and hierarchies. Since the end of the 1970s, following the crisis of the post-Second World War regime, the stabilizing role of European integration assumed new modes. Italy, as a weak link in the chain of capitalist development, showed in advance and with the utmost clarity how this new role worked. In two crucial passages of the post-1945 country\u2019s history, when workers\u2019 unrest strongly challenged the existing capitalist hierarchies, European governance played a crucial role in their restoration. Both in the early 1960s and in the late 1970s the European \u2018vincolo esterno\u2019 (external constraint) decisively helped the affirmation of the domestic deflationary forces

biomedical applications of shape memory alloys

Shape memory alloys, and in particular NiTi alloys, are characterized by two unique behaviors, thermally or mechanically activated: theshape memory effectandpseudo-elastic effect. These behaviors, due to the peculiar crystallographic structure of the alloys, assure the recovery of the original shape even after large deformations and the maintenance of a constant applied force in correspondence of significant displacements. These properties, joined with good corrosion and bending resistance, biological and magnetic resonance compatibility, explain the large diffusion, in the last 20 years, of SMA in the production of biomedical devices, in particular for mini-invasive techniques. In this paper a detailed review of the main applications of NiTi alloys in dental, orthopedics, vascular, neurological, and surgical fields is presented. In particular for each device the main characteristics and the advantages of using SMA are discussed. Moreover, the paper underlines the opportunities and the room for new ideas able to enlarge the range of SMA applications. However, it is fundamental to remember that the complexity of the material and application requires a strict collaboration between clinicians, engineers, physicists and chemists for defining accurately the problem, finding the best solution in terms of device design and accordingly optimizing the NiTi alloy properties

Experimental Study on Steel Slit and Shear Panel for Seismic Resistance

AbstractThis paper summarizes the experimental campaign carried out for the development of new steel energy dissipative devices named Slit Dampers (SDs) designed for earthquake protection of structures. A total of eighty‐two steel shear plates with different openings and thicknesses are tested to investigate their behaviour under cyclic pseudo‐static loading. Eight types of steel shear plates are studied, including the SD with narrow slits that divide the plate into rectangular links, and the butterfly fuse with a diamond‐shaped opening that creates butterfly shape links in the plate. Other varying test parameters are loading rate, material strength, and the number of in‐parallel damper elements. It is expected that the proposed model can be successfully used to predict the behaviour of dampers in real‐world applications

A probabilistic approach to Performance-Based Wind Engineering (PBWE)

Performance-Based Design (PBD) is a modern and efficient framework to conceive and assess complex structural systems, which allow designers to consistently take into account both natural and man-made hazards, both in the design of new facilities and in the rehabilitation or retrofitting of existing ones. The first formal applications of PBD were devoted to seismic engineering and design; later it has been extended to other engineering fields, like Blast Engineering and Fire Engineering. Wind engineering has appeared of great potential interest for further developments of PBD. The expression "Performance-Based Wind Engineering" (PBWE) was introduced for the first time in 2004 by an Italian research project. In this work, the approach proposed by the Pacific Earthquake Engineering Research Center (PEER) for Performance-Based Earth-quake Engineering is extended to the case of PBWE. The general framework of the approach is illustrated and applied to two example cases: a long span suspension bridge and an offshore wind turbine

Optimal design of the ideal grounded tuned mass damper inerter for comfort performances improvement in footbridges with practical implementation considerations

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Artificial Time Histories of Wind ActionsFor Structural Analysis of Wind Turbines

A computational method for generating artificial time histories of wind loads on wind turbine towers is presented, based on wind turbine aerodynamics and a wind field model. First, the forces acting on the blades parallel and perpendicular to the rotor’s plane are calculated according to aerodynamics theory for given mean wind velocity. Due to the blades’ aerodynamic behavior the inflow wind velocity is transformed into the relative wind velocity, depending on the axial and tangential flow induction factors, the blades’ angular velocity and their radius. Then, the forces acting on the blades are calculated combining relative velocity with two-dimensional aerofoil coefficients depending on the blades’ geometry and crosssection. The flow induction factors are estimated by an iterative process taking into account the flow angle between the relative wind velocity and the rotor’s plane and the aerofoil coefficients. Next, the turbulence component of the wind is determined by the stochastic theory, in order to describe the total wind field model and compute more realistic wind induced actions on the blades. Each fluctuating component is modeled as Gaussian, stationary stochastic process with zero-mean value and is completely characterized by the correlation matrix in time domain or the power spectral density matrix in frequency domain. Wind time histories are simulated by the decomposition of the power spectral density matrix. Then, finite element models of the wind turbine tower are subjected to the load time histories derived above and dynamic analyses are performed. Ultimate objective of this research is to study fatigue at bolted and welded connections between adjacent parts of wind turbine towers and to investigate the importance of dynamic effects on local buckling of the tower shell

How deep convolutional neural networks lose spatial information with training

A central question of machine learning is how deep nets manage to learn tasks in high dimensions. An appealing hypothesis is that they achieve this feat by building a representation of the data where information irrelevant to the task is lost. For image datasets, this view is supported by the observation that after (and not before) training, the neural representation becomes less and less sensitive to diffeomorphisms acting on images as the signal propagates through the net. This loss of sensitivity correlates with performance, and surprisingly correlates with a gain of sensitivity to white noise acquired during training. These facts are unexplained, and as we demonstrate still hold when white noise is added to the images of the training set. Here, we (i) show empirically for various architectures that stability to image diffeomorphisms is achieved by spatial pooling in the first half of the net, and by channel pooling in the second half, (ii) introduce a scale-detection task for a simple model of data where pooling is learned during training, which captures all empirical observations above and (iii) compute in this model how stability to diffeomorphisms and noise scale with depth. The scalings are found to depend on the presence of strides in the net architecture. We find that the increased sensitivity to noise is due to the perturbing noise piling up during pooling, after being rectified by ReLU units