Assessment of the water content in extra virgin olive oils by Time Domain Reflectometry (TDR) and Partial Least Squares (PLS) regression methods

In the present research we discuss a novel way to set up a predictive method for determining the water content of oil based on the Partial Least Squares (PLS) regression analysis of reflectometric signals. Ten different extra virgin olive oils with a water content ranging from 714 to 2008 mg of water/kg of oil were submitted to reflectometric measurement by means of a hand made probe connected to a digital sample oscilloscope with TDR functions interfaced with a PC. Limits of the classical approach based on the TDR electromagnetic theory in the prediction of these small water content differences were also discussed.     

A dynamic Bayesian network based framework to evaluate cascading effects in a power grid

In recent years, the growing interest toward complex critical infrastructures and their interdependencies have solicited new efforts in the area of modeling and analysis of large interdependent systems. Cascading effects are a typical phenomenon of dependencies of components inside a system or among systems. The present paper deals with the modeling of cascading effects in a power grid. In particular, we propose to model such effects in the form of dynamic Bayesian networks (DBN) which can be derived by means of specific rules, from the power grid structure expressed in terms of series and parallel modules. In contrast with the available techniques, DBN offer a good trade-off between the analytical tractability and the representation of the propagation of the cascading event. A case study taken from the literature, is considered as running example.     

Handy: A real-time three color glove-based gesture recognizer with learning vector quantization

This paper presents Handy, a real-time hand gesture recognizer based on a three color glove. The recognizer is formed by three modules. The first module, fed by the frame acquired by a webcam, identifies the hand image in the scene. The second module, a feature extractor, represents the image by a nine-dimensional feature vector. The third module, the classifier, is performed by means of learning vector quantization. The recognizer, tested on a dataset of 907 hand gestures, has shown very high recognition rate.     

Correlations between microstructural characterization and thermal properties of well defined poly(ε-caprolactone) samples by ring opening polymerization with neutral and cationic bis(2,4,6-triisopropylphenyl)tin(IV) compounds

In this paper a study of correlations between the microstructure of well defined poly(ε-caprolactone) (PCL) samples and their physical properties such as thermal degradation, crystallization kinetics and melting behavior is described. The PCL samples were obtained in the presence of the compound benzyl-methoxy-bis(2,4,6-triisopropylphenyl)tin (1), acting as single-site and living initiator, as well as in the presence of compounds Tip₂SnRR′ [Tip = 2,4,6-triisopropylbenzene; R = R′ = CHCH₂ (2); R = CH₂Ph, R′ = Br (3)] activated by ionizing agents. PCL samples having different end groups, molecular weight and molecular weight distribution were obtained. The samples were fully characterized by GPC and NMR. The thermal degradation of the synthesized samples were studied by thermogravimetric analysis (TGA) in air flow. The experimental results suggested that the presence of ester chain end groups has a beneficial effect on the thermal stability of the PCL samples, independently on the molecular weights and molecular weight distribution. The crystallization behavior was studied in isothermal conditions at 37 °C, 40 °C, and 43 °C through differential scanning calorimetry (DSC). In this case, either the molecular weight (M_w) or the polydispersivity index (PDI) have a significant effect on the kinetics of crystallization of PCLs.     

Endogenous Enzymatic Activity in Dentin Treated with a Chitosan Primer

The aim of this study was to evaluate the effect of different concentrations of chitosan polymer on dentinal enzymatic activity by means of gelatin and in situ zymography. Human dentin was frozen and ground in a miller. Dentin powder aliquots were demineralized with phosphoric acid and treated with three different concentrations of lyophilized chitosan polymer (1, 0.5 and 0.1 wt%) dissolved in distilled water. Dentin proteins were extracted from each experimental group and electrophoresed under non-reducing conditions in 10% SDS-PAGE containing fluorescein-labeled gelatin. After 48 h in the incubation buffer at 37 °C, proteolytic activity was registered under long-wave UV light scanner and quantified by using Image J software. Furthermore, additional teeth (n = 4) were prepared for the in situ zymographic analysis in unrestored as well as restored dentin pretreated with the same chitosan primers. The registered enzymatic activity was directly proportional to the chitosan concentration and higher in the restored dentin groups (p < 0.05), except for the 0.1% chitosan primer. Chitosan 0.1% only showed faint expression of enzymatic activity compared to 1% and 0.5% concentrations. Chitosan 0.1% dissolved in water can produce significant reduction in MMPs activity and could possibly contribute to bond strength preservation over time.     

Confinement effects on optical phonons in polar tetrapod nanocrystals detected by resonant inelastic light scattering

We investigated CdTe nanocrystal tetrapods of different sizes by resonant inelastic light scattering at room temperature and under cryogenic conditions. We observe a strongly resonant behavior of the phonon scattering with the excitonic structure of the tetrapods. Under resonant conditions we detect a set of phonon modes that can be understood as confined longitudinal-optical phonons, surface-optical phonons, and transverse-optical phonons in a nanowire picture.     

Mechanical and barrier properties of epoxy resin filled with multi-walled carbon nanotubes

Different multi-walled carbon nanotube (MWCNT) concentrations were incorporated in an epoxy resin and both the epoxy precursor and the composite were cured at 110 °C with a tertiary amine. Infrared spectroscopy was used to follow the curing progress by determining the decrease of the band due to the epoxy group. It was shown that the presence of MWCNTs accelerates the process, halving the time for the disappearance of the epoxy band. Atomic force microscopy demonstrated that the carbon nanotubes are well embedded in the epoxy matrix and singularly dispersed or in bundles, depending on their concentration. As a consequence of the good dispersion and interpenetration of the carbon nanotubes in the epoxy matrix, the glass transition temperature increased with increasing MWCNT concentration. Dynamic-mechanical analysis indicated a higher elastic modulus, particularly at high temperatures. The study of the transport properties, sorption and diffusion of water vapour at different activities, showed improved barrier properties on increasing the CNT concentration.     

Insights into the Mechanisms of Heat Priming and Thermotolerance in Tobacco Pollen

Global warming leads to a progressive rise in environmental temperature. Plants, as sessile organisms, are threatened by these changes; the male gametophyte is extremely sensitive to high temperature and its ability to preserve its physiological status under heat stress is known as acquired thermotolerance. This latter can be achieved by exposing plant to a sub-lethal temperature (priming) or to a progressive increase in temperature. The present research aims to investigate the effects of heat priming on the functioning of tobacco pollen grains. In addition to evaluating basic physiological parameters (e.g., pollen viability, germination and pollen tube length), several aspects related to a correct pollen functioning were considered. Calcium (Ca²⁺) level, reactive oxygen species (ROS) and related antioxidant systems were investigated, also to the organization of actin filaments and cytoskeletal protein such as tubulin (including tyrosinated and acetylated isoforms) and actin. We also focused on sucrose synthase (Sus), a key metabolic enzyme and on the content of main soluble sugars, including UDP-glucose. Results here obtained showed that a pre-exposure to sub-lethal temperatures can positively enhance pollen performance by altering its metabolism. This can have a considerable impact, especially from the point of view of breeding strategies aimed at improving crop species.     

Silver Nanoparticles Derived by Artemisia arborescens Reveal Anticancer and Apoptosis-Inducing Effects

The fight against cancer is one of the main challenges for medical research. Recently, nanotechnology has made significant progress, providing possibilities for developing innovative nanomaterials to overcome the common limitations of current therapies. In this context, silver nanoparticles (AgNPs) represent a promising nano-tool able to offer interesting applications for cancer research. Following this path, we combined the silver proprieties with Artemisia arborescens characteristics, producing novel nanoparticles called Artemisia–AgNPs. A “green” synthesis method was performed to produce Artemisia–AgNPs, using Artemisia arborescens extracts. This kind of photosynthesis is an eco-friendly, inexpensive, and fast approach. Moreover, the bioorganic molecules of plant extracts improved the biocompatibility and efficacy of Artemisia–AgNPs. The Artemisia–AgNPs were fully characterized and tested to compare their effects on various cancer cell lines, in particular HeLa and MCF-7. Artemisia–AgNPs treatment showed dose-dependent growth inhibition of cancer cells. Moreover, we evaluated their impact on the cell cycle, observing a G1 arrest mediated by Artemisia–AgNPs treatment. Using a clonogenic assay after treatment, we observed a complete lack of cell colonies, which demonstrated cell reproducibility death. To have a broader overview on gene expression impact, we performed RNA-sequencing, which demonstrated the potential of Artemisia–AgNPs as a suitable candidate tool in cancer research.