Production of metal nanoparticles by agro-industrial wastes. A green opportunity for nanotechnology

The feasibility of producing silver nanoparticles (Ag NPs) using phenolic extracts from agro-industrial wastes as reducing agents was investigated. Phenolic extracts were obtained from bilberry wastes (BW) and spent coffee grounds (SCG) with aqueous ethanol as extraction solvent. Experiments were carried out in batch at 25 °C by adding appropriate amounts of phenolic extracts to a silver nitrate aqueous solution. The formation of Ag NPs was monitored spectrophotometrically by measuring the intensity of the surface plasmon resonance (SPR) band of silver at 415-435 nm. Depending on the process conditions, the synthesis of Ag NPs was completed in 3 to 5 hours. Characterization of the resulting reaction products by XRD, SEM and DLS showed that nanoparticles were formed with a spherical shape and an average size of 10-20 nm. Overall, the results obtained suggest that BW and SCG could be used as a source of reducing agents for the production of metal NPs and that agro-industrial wastes may represent a valid alternative to the use of microorganisms, whole plants or plant parts for the biogenic synthesis of NPs

Description of the biofouling phenomena affecting membranes by the boundary flux concept

Membrane fouling, showing up with a significant reduction of process productivity and membrane lifetime, is one of the main issues in membrane technologies and has been successfully described by the boundary flux concept. Although the concept was applied for both organic and inorganic fouling, biofouling enjoys partial treatises in literature. In this work, a model extending the boundary flux concept to biofouling issues was developed. A population dynamics-based model considering the development of a fouling layer originated by attached growing biomass on the surface of the membrane using nutrients and substrates available in the processed feed has been developed. The manuscript highlights the critical aspects of the developed model and the possible connection points between it and the boundary flux concept

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

Fabrication and characterisation of vegetable chitosan derived microcapsules

Microencapsulation is a highly effective technology to deliver value-added actives at end-use applications, such as in food, personal care, and detergent products. The goal of the present research was to develop a novel microencapsulation system to encapsulate perfume/flavour oils by complex coacervation using plant-based biopolymers. Complex coacervation entails the electrostatic interplay between pairs of polymers carrying opposite charges. Specifically, this research was aimed towards: (i) investigating the feasibility and the experimental conditions required to induce complex coacervation between fungal chitosan (fCh) and gum Arabic (GA); (ii) determining the optimum fabrication conditions of fCh-GA complexes including pH and the weight ratio of GA-to-fCh based on their electrokinetic charge and turbidimetric analysis; (iii) developing methodologies for encapsulating perfumes (i.e. hexylsalicylate) and food flavour (i.e. L-carvone) oils within a safe fCh-GA shell via complex coacervation; (iv) understanding the physico-chemical, structural, surface topographic, mechanical, and barrier properties of the resulting plant-based microcapsules using several analytical techniques, such as scanning (SEM) and transmission electron microscopy (TEM), micromanipulation, UV-Visible spectrometer, and Fourier-transform infrared spectroscopy (FT-IR). The electrokinetic analysis of fCh and GA revealed that complex coacervation was optimised at a GA-to-fCh weight ratio approximately equal to 7:1. The interactions of the biopolymer pair was examined as a function of pH (1.0~8.0), which enabled to identify their complex coacervation comfort zone (CCCZ) as well as critical turbidity zone (CTZ). The optimised pH was 3.4, which triggered the strongest electrostatic attraction between fCh and GA. The stability of oil-in-water emulsions was investigated via interfacial tension analysis, which included the use of sorbitan esters (Spans), polysorbates (Tweens), and their combined adducts as the stabilising agents. Under the above conditions, microcapsules with a plant-based shell and a core of value-added oil were produced. Elongated as well as spherically shaped microcapsules could be fabricated conditionally upon the stirring rate during coacervation. Surface topography by SEM revealed well sealed microcapsules with a core of oil. The mechanical properties of microcapsules were determined via a micromanipulation technique. The rupture force and nominal rupture stress of perfume oil microcapsules were 2.0±0.1 mN and 3.6±0.3 MPa, respectively, which are comparable to those of commercially available melamine formaldehyde (MF) based microcapsules. In-depth shell thickness analysis on the resulting microcapsules was performed by TEM. The results were used to validate the predicted shell thickness of microcapsules using experimental micromanipulation data combined with the simulation results of finite element analysis (FEA), which also enabled to quantify the intrinsic material property parameter (i.e. Young’s modulus of the shell material). The oil leakage tests were carried out to assess the barrier properties of the microcapsules. Furthermore, the oil leakage data were fitted to a solute-diffusion model, which allowed to estimate the shell permeability. As a further step towards developing highly versatile cutting-edge microencapsulation systems with a potential application in food industry as well, several formulation modifications were made to encapsulate L-carvone. The introduction of a two-stage microencapsulation process (i.e. complex coacervation followed by spray drying) allowed to achieve food grade free-flowing powders with a load of L-carvone, which proved stable for over a month. Overall, the results evidenced that perfume/flavour oil microcapsules within a safe plant-based shell could be fabricated via complex coacervation. Moreover, the fCh-GA system has shown to be a promising carrier for the encapsulation of fragrance/flavour ingredients, which presents a new opportunity to globally overcome cultural and religious concerns associated with animal sourced products

Relationship between the Young’s Moduli of Whole Microcapsules and Their Shell Material Established by Micromanipulation Measurements Based on Diametric Compression between Two Parallel Surfaces and Numerical Modelling

Micromanipulation is a powerful technique to measure the mechanical properties of microparticles including microcapsules. For microparticles with a homogenous structure, their apparent Young’s modulus can be determined from the force versus displacement data fitted by the classical Hertz model. Microcapsules can consist of a liquid core surrounded by a solid shell. Two Young’s modulus values can be defined, i.e., the one is that determined using the Hertz model and another is the intrinsic Young’s modulus of the shell material, which can be calculated from finite element analysis (FEA). In this study, the two Young’s modulus values of microplastic-free plant-based microcapsules with a core of perfume oil (hexyl salicylate) were calculated using the aforementioned approaches. The apparent Young’s modulus value of the whole microcapsules determined by the classical Hertz model was found to be EA = 0.095 ± 0.014 GPa by treating each individual microcapsule as a homogeneous solid spherical particle. The previously obtained simulation results from FEA were utilised to fit the micromanipulation data of individual core–shell microcapsules, enabling to determine their unique shell thickness to radius ratio (h/r)FEA = 0.132 ± 0.009 and the intrinsic Young’s modulus of their shell (EFEA = 1.02 ± 0.13 GPa). Moreover, a novel theoretical relationship between the two Young’s modulus values has been derived. It is found that the ratio of the two Young’s module values (EA/EFEA) is only a function on the ratio of the shell thickness to radius (h/r) of the individual microcapsule, which can be fitted by a third-degree polynomial function of h/r. Such relationship has proven applicable to a broad spectrum of microcapsules (i.e., non-synthetic, synthetic, and double coated shells) regardless of their shell chemistry

Artificial Neural Network in Fibres Length Prediction for High Precision Control of Cellulose Refining

Paper, a web of interconnected cellulose fibres, is widely used as a base substrate. It has been applied in several applications since it features interesting properties, such as renewability, biodegradability, recyclability, affordability and mechanical flexibility. Furthermore, it offers a broad possibility to modify its surface properties toward specifics additives. The fillers retention and the fibres bonding ability are heavily affected by the cellulose refining process that influences chemical and morphological features of the fibres. Several refining theories were developed in order to determine the best refining conditions. However, it is not trivial to control the cellulose refining as different phenomena occur simultaneously. Therefore, it is intuitively managed by experienced papermakers to improve paper structures and properties. An approach based on the machine learning aimed at estimating the effects of refining on the fibres morphology is proposed in this study. In particular, an artificial neural network (ANN) was implemented and trained with experimental data to predict the fibres length as a function of refining process variables. The prediction of this parameter is crucial to obtain a high-performance process in terms of effectiveness and the optimisation of the final product performance as a function of the process parameter. To achieve these results, data mining of the experimental patterns collected was exploited. It led to the achievement of excellent performance and high accuracy in fibres length prediction

Ostracismo e orientamento sessuale: una rassegna sulle conseguenze del fenomeno

The present work was elaborated with a twofold aim. On one side we review the most important studies investigating the consequences of ostracism and on the other side we provide a deepening of the negative consequences of ostracism for people belonging to stigmatized groups, specifically towards gay people. Being ostracized represents a negative and painful experience that is moderated by the group membership only when it is an essential part of the self-identity, such as the race. The literature also shows that the sexual orientation plays a moderating role on the negative consequences of ostracism. Gay people resent from a greater reduction in executive functioning when they are ostracized and this influences the way in which they respond to ostracism in terms of cognitive performance and self-regulation

Binge Drinking and Drunkorexia Among Italian Adolescents and Second-Generation Immigrants.

The purpose of this study was to examine the differences on binge drinking and drunkorexia among Italian natives and second-generation immigrants in a sample of 530 adolescents (121 second-generation immigrants and 409 Italian natives). The short form of the Alcohol Use Disorders Identification Test (AUDIT-C) and the Compensatory Eating and Behaviors in Response to Alcohol Consumption Scale (CEBRACS) were used to assess respectively alcohol abuse and drunkorexia. The factorial Anova 2x2 showed two principal effects related to gender and birth status. There was not interaction effect between variables. Italian natives reported more unhealthy drinking behaviors than second-generation immigrants and boys were more likely to engage in binge drinking. For drunkorexia behaviors, 40% of the overall sample reported to limit their caloric intake before or after drinking. The ANOVA did not show gender differences. A statistically significant effect of immigrant status was found among the adolescents who report to engage in drunkorexia behaviors. This research highlighted the importance to realize programs to prevent and decrease the prevalence of this peculiar risky behavior during adolescence