Cell-protection mechanism through autophagy in HGFs/<Emphasis Type="Italic">S. mitis</Emphasis> co-culture treated with Chitlac-nAg

Silver-based products have been proven to be effective in retarding and preventing bacterial growth since ancient times. In the field of restorative dentistry, the use of silver ions/nanoparticles has been explored to counteract bacterial infections, as silver can destroy bacterial cell walls by reacting with membrane proteins. However, it is also cytotoxic towards eukaryotic cells, which are capable of internalizing nanoparticles. In this work, we investigated the biological effects of Chitlac-nAg, a colloidal system based on a modified chitosan (Chitlac), administered for 24–48?h to a co-culture of primary human gingival fibroblasts and Streptococcus mitis in the presence of saliva, developed to mimic the microenvironment of the oral cavity. We sought to determine its efficiency to combat oral hygiene-related diseases without affecting eukaryotic cells. Cytotoxicity, reactive oxygen species production, apoptosis induction, nanoparticles uptake, and lysosome and autophagosome metabolism were evaluated. In vitro results show that Chitlac-nAg does not exert cytotoxic effects on human gingival fibroblasts, which seem to survive through a homoeostasis mechanism involving autophagy. That suggests that the novel biomaterial Chitlac-nAg could be a promising tool in the field of dentistry.     

Process optimization in the self-reacting friction stir welding of aluminum 6061-T6

Self-reacting friction stir welding (SR-FSW), also called bobbin-tool friction stir welding (BT-FSW), is a solid state welding process similar to friction stir welding (FSW) except that the tool has two opposing shoulders instead of the shoulder and a backing plate found in FSW. The tool configuration results in greater heat input and a symmetrical weld macrostructure. A significant amount of information has been published in the literature concerning traditional FSW while little has been published about SR-FSW. An optimization experiment was performed using a factorial design to evaluate the effect of process parameters on the weld temperature, surface and internal quality, and mechanical properties of self-reacting friction stir welded aluminum alloy 6061-T6 butt joints. The parameters evaluated were tool rotational speed, traverse speed, and tool plunge force. A correlation between weld temperature, defect formation (specifically galling and void formation), and mechanical properties was found. Optimum parameters were determined for the welding of 8-mm-thick 6061-T6 plate.     

Nanocrystalline Nd–Fe–B Anisotropic Magnets by Flash Spark Plasma Sintering

Flash spark plasma sintering (flash SPS) is an attractive method to obtain Nd–Fe–B magnets with anisotropic magnetic properties when starting from melt-spun powders. Compared to the benchmark processing route via hot pressing with subsequent die upsetting, flash SPS promises electroplasticity as an additional deformation mechanism and reduced tool wear, while maximizing magnetic properties by tailoring the microstructure—fully dense and high texture. A detailed parameter study is conducted to understand the influence of Flash SPS parameters on the densification and magnetic properties of commercial MQU-F powder. It is revealed that the presintering conditions and preheating temperature before applying the power pulse play a major role for tailoring grain size and texture in the case of hot deformation via Flash SPS. Detailed microstructure and magnetic domain evaluation disclose the texture enhancement with increasing flash SPS temperature at the expense of coercivity. The best compromise between remanence and coercivity (1.37 T and 1195 kA m⁻¹, respectively) is achieved through a combination of presintering at 500 °C for 120 s and preheating temperature of 600 °C, resulting in a magnet with energy product (BH)_max of 350 kJm⁻³. These findings show the potential of flash SPS to obtain fully dense anisotropic nanocrystalline magnets with high magnetic performance.     

Pseudo Bond Graph modelling and on-line estimation of unknown kinetics for a wastewater biodegradation process

This paper deals with the problem of modelling and on-line estimation of kinetics for a biomethanation process. This bioprocess is in fact a wastewater biodegradation process with production of methane gas, which takes place inside a Continuous Stirred Tank Bioreactor. The reaction scheme and the analysis of biochemical phenomena inside the bioreactor are used in order to obtain a nonlinear dynamic model of the bioprocess, by means of the pseudo Bond Graph method. Two nonlinear estimation strategies are developed for the identification of unknown kinetics of the bioprocess. First, an estimator is developed by using a state observer based technique. Second, an observer based on high-gain approach is designed and implemented. Several numerical simulations are performed in order to analyse and compare the behaviour and the performance of the proposed estimators.     

The labeled maximum matching problem

Given a graph G where a label is associated with each edge, we address the problem of looking for a maximum matching of G using the minimum number of different labels, namely the labeled maximum matching problem. It is a relatively new problem whose application is related to the timetabling problem. We prove it is NP-complete and present four different mathematical formulations. Moreover, we propose an exact algorithm based on a branch-and-bound approach to solve it. We evaluate the performance of our algorithm on a wide set of instances and compare our computational times with the ones required by CPLEX to solve the proposed mathematical formulations. Test results show the effectiveness of our procedure, that hugely outperforms the solver.     

An haptic-based immersive environment for shape analysis and modelling

Currently, the design of aesthetic products is a process that requires a set of activities where digital models and physical mockups play a key role. Typically, these are modified (and built) several times before reaching the desired design, increasing the development time and, consequently, the final product cost. In this paper, we present an innovative design environment for computer-aided design (CAD) surface analysis. Our system relies on a direct visuo-haptic display system, which enables users to visualize models using a stereoscopic view, and allows the evaluation of sectional curves using touch. Profile curves are rendered using an haptic device that deforms a plastic strip, thanks to a set of actuators, to reproduce the curvature of the shape co-located with the virtual model. By touching the strip, users are able to evaluate shape characteristics, such as curvature or discontinuities (rendered using sound), and to assess the surface quality. We believe that future computer-aided systems (CAS)/CAD systems based on our approach will contribute in improving the design process at industrial level. Moreover, these will allow companies to reduce the product development time by reducing the number of physical mockups necessary for the product design evaluation and by increasing the quality of the final product, allowing a wider exploration and comparative evaluation of alternatives in the given time.     

Non-parametric statistical background modeling for efficient foreground region detection

Most methods for foreground region detection in videos are challenged by the presence of quasi-stationary backgrounds—flickering monitors, waving tree branches, moving water surfaces or rain. Additional difficulties are caused by camera shake or by the presence of moving objects in every image. The contribution of this paper is to propose a scene-independent and non-parametric modeling technique which covers most of the above scenarios. First, an adaptive statistical method, called adaptive kernel density estimation (AKDE), is proposed as a base-line system that addresses the scene dependence issue. After investigating its performance we introduce a novel general statistical technique, called recursive modeling (RM). The RM overcomes the weaknesses of the AKDE in modeling slow changes in the background. The performance of the RM is evaluated asymptotically and compared with the base-line system (AKDE). A wide range of quantitative and qualitative experiments is performed to compare the proposed RM with the base-line system and existing algorithms. Finally, a comparison of various background modeling systems is presented as well as a discussion on the suitability of each technique for different scenarios.     

Thermal assisted direct bonding between structured glasses for lab-on-chip technology

A thermal assisted direct bonding (TADB) technique between structured glasses is proposed for micro-fluidic device fabrication. The bonded glass pairs were characterized by optical microscopy, scanning electron microscopy (SEM), apparent shear strength tests and Vickers hardness measurements across the bonded interface. The optimisation of TADB parameters on flat glasses and on structured glasses was analysed. This technique is user-friendly and low cost, and can be considered for mass production of glass-based micro-fluidic devices.