Attaccamento a Dio, attaccamento ai genitori e ai pari e atteggiamento religioso in un gruppo di adolescenti italiani

Numerosi contributi in letteratura descrivono il rapporto che un credente cattolico ha con Dio facendo riferimento ai concetti della teoria dell’attaccamento di Bowlby. In questa prospettiva le principali caratteristiche degli stili di attaccamento ai genitori e ai pari possono riproporsi nella relazione con Dio. Nel presente lavoro è stata indagata in un gruppo di 992 adolescenti cattolici la relazione tra gli stili di attaccamento ai genitori, ai pari e a Dio e il grado di influenza di questi stili sull’atteggiamento religioso. Dai risultati emerge che le dimensioni insicure dell’attaccamento con i genitori e con i pari sono predittive di un attaccamento altrettanto insicuro e ansioso con Dio. Bassi livelli di attaccamento evitante o ansioso con Dio si riflettono in atteggiamenti positivi verso la religione e una maggiore partecipazione ai riti religiosi. I dati tendono a confermare l’ipotesi che il legame con Dio è influenzato dallo stile di attaccamento che il credente ha instaurato con i genitori e i pari. Tuttavia, dai risultati emerge che bassi livelli in alcune dimensioni dell’attaccamento (Comunicazione e Fiducia) tendono ad essere compensate nella relazione con Dio

Laser Texturing to Increase the Wear Resistance of an Electrophoretic Graphene Coating on Copper Substrates

In the present paper, different surface preparations are investigated with the aim of increasing the wear behaviour of an electrophoretic graphene coating on a copper plate. The study was divided into two steps: In the first step (pre-tests), to detect the most promising pretreatment technology, five different surface preparations were investigated (electropolishing, sandblasting, degreasing and pickling, laser cleaning and laser dots).In the second step, on the basis of the results of the first step, a 3(2) full factorial plan was developed and tested; three treatment types (pickled and degreased, laser-cleaned, and laser dots) and three different voltages (30, 45 and 60 V) were adopted. Analysis of variance (ANOVA) was used to evaluate their influence on wear resistance; in particular, the maximum depth and width of the wear tracks and the coating break distance were investigated. The results of this study show that, in optimal conditions, laser treatment (particularly laser dots) canlead to as high as a four-fold increase in wear resistance

Prediction of laser drilled hole geometries from linear cutting operation by way of artificial neural networks

AbstractThis paper deals on artificial intelligence (AI) application for the estimation of kerf geometry and hole diameters for laser micro-cutting and laser micro-drilling operations. To this aim laser cutting and laser drilling operation were performed on NIMONIC 263 superalloy sheet, 0.38 mm in nominal thickness, by way of a 100 W fibre laser in modulated wave regime. Linear cuts and holes (by trepanning) were performed fixing the average power at 80 W and changing the pulse duration, the cutting speed, the focus depth and the laser path (the latter only for the drilling operations). Kerf width and the holed diameter, at the upper and downsides, were measured by digital microscopy. Different artificial neural networks (ANNs) were developed and tested to predict the kerf widths and the diameters (at the upper and downside). Two ANNs were addressed to the linear cutting process modelling; also, two further ANNs were developed for micro-drilling on the base of the linear cutting process features. The networks were trained with a subset of data containing the process conditions and the kerf/hole geometry. The ANN test was performed with the remaining data. The results show that ANNs can model the cut and hole geometry as a function of the process parameters. Moreover, the ANN trained with kerf geometry is more efficient. Therefore, a functional correlation between the kerf geometries achievable in the linear cutting process and micro-drilling was assessed

Image-based system and artificial neural network to automate a quality control system for cherries pitting process

Abstract This work proposes a non-destructive quality control for a pitting process of cherries. A system composed of a video camera and a light source records pictures of backlit cherries. The images processing in MATLAB environment provides the dynamic histograms of the pictures, which are analysed to state the presence of the pit. A feedforward artificial neural network was implemented and trained with the histograms obtained. The network developed allows a fast detection of stone fractions not visible by human inspection and the reduction of the accidental reject of properly manufactured products

Al2O3 Coatings on Magnesium Alloy Deposited by the Fluidized Bed (FB) Technique

Magnesium alloys are widely employed in several industrial domains for their outstanding properties. They have a high strength-weight ratio, with a density that is lower than aluminum (33% less), and feature good thermal properties, dimensional stability, and damping characteristics. However, they are vulnerable to oxidation and erosion-corrosion phenomena when applied in harsh service conditions. To avoid the degradation of magnesium, several coating methods have been presented in the literature; however, all of them deal with drawbacks that limit their application in an industrial environment, such as environmental pollution, toxicity of the coating materials, and high cost of the necessary machinery. In this work, a plating of Al2O3 film on a magnesium alloy realized by the fluidized bed (FB) technique and using alumina powder is proposed. The film growth obtained through this cold deposition process is analyzed, investigating the morphology as well as tribological and mechanical features and corrosion behavior of the plated samples. The resulting Al2O3 coatings show consistent improvement of the tribological and anti-corrosive performance of the magnesium alloy

The psychometric properties of the Italian translation of the Francis Scale of Attitude toward Christianity : a study among Catholic adolescents

The Italian translation of the Francis Scale of Attitude toward Christianity was developed and tested among a sample of 575 young people between 16 and 17 years of age attending secular secondary schools in Rome, Italy. The data supported the unidimensionality, internal consistency reliability and construct validity of this instrument and commend it for further use in contributing to comparative empirical research within the psychology of religion

Heat Treatment of AZ91 Magnesium Alloy Coated with an Al2O3 Thin Film with Fluidized Bed Technology

Fluidized bed technology is a methodology widely known in the manufacturing environment for surface treatment of metals. Within the field of surface coating, it has already been exploited for the coating of a magnesium alloy creating a compact layer of Al2O3. The result was an improvement in mechanical and tribological properties, along with improved corrosion resistance. In this context, the work proposed is addressed towards the evaluation of the effects of thermal post-treatment on the alumina coating produced by means of the fluidized-bed technology. To analyse the effects of heat treatments the morphology, composition and hardness of the samples were investigated along with adhesion and wear resistance of the alumina film. The results obtained show how the temperature affects the surface morphology and promotes the diffusion of magnesium towards the alumina superficial layer. The mechanisms triggered by heat treatments increase the adhesion of the surface film obtained in the deposition process, improving its mechanical and tribological properties

Prediction of laser drilled hole geometries from linear cutting operation by way of artificial neural networks

This paper deals on artificial intelligence (AI) application for the estimation of kerf geometry and hole diameters for laser micro-cutting and laser micro-drilling operations. To this aim laser cutting and laser drilling operation were performed on NIMONIC 263 superalloy sheet, 0.38 mm in nominal thickness, by way of a 100 W fibre laser in modulated wave regime. Linear cuts and holes (by trepanning) were performed fixing the average power at 80 W and changing the pulse duration, the cutting speed, the focus depth and the laser path (the latter only for the drilling operations). Kerf width and the holed diameter, at the upper and downsides, were measured by digital microscopy. Different artificial neural networks (ANNs) were developed and tested to predict the kerf widths and the diameters (at the upper and downside). Two ANNs were addressed to the linear cutting process modelling; also, two further ANNs were developed for micro-drilling on the base of the linear cutting process features. The networks were trained with a subset of data containing the process conditions and the kerf/hole geometry. The ANN test was performed with the remaining data. The results show that ANNs can model the cut and hole geometry as a function of the process parameters. Moreover, the ANN trained with kerf geometry is more efficient. Therefore, a functional correlation between the kerf geometries achievable in the linear cutting process and micro-drilling was assessed