Electrical Properties of Polyethylene Composites with Low Content of Neodymium

The effects of Neodymium (Nd) on the electrical properties of low density polyethylene in relation with morphological aspects are reported in this article. Scanning electron microscopy and optical microscopy revealed a quasi-uniform dispersion of Nd particles in polyethylene, both individual particles and clusters being observed. Contact angle measurements showed a decrease of contact angle values and, thus, of surface hydrophobicity, with the increase of Nd content. The addition of Nd in polyethylene determined the increase of electric permittivity and conductivity. The variation of permittivity was explained considering the influence of polar species (additives, oxidation products, neodymium oxide), highlighted by Fourier transform infrared analysis.     

Development of a stability intelligent control system for turning

This paper presents a stability control system based on a new strategy, with application in turning. It works by permanent assessment of the system operating point position relative to the stability limit, and process parameter permanent, in-process modification such as this point is always placed in the stable domain zone that gives the highest process performance. In the case of turning, here approached: (1) this zone is the stability limit proximity; (2) the system operating point position is determined by assessing a cutting force monitored signal feature; and (3) this position is changed by modifying the cutting edge setting angle, the feed rate, and the cutting speed, as it follows: when the risk of overpassing the stability limit is imminent, the setting angle is increased, followed by a feed rate diminishing and then by a worked piece rotation speed reduction, while immediately after surpassing the risk, the three variables modification is reversed, this way the chatter onset being permanently avoided and the performance kept in every moment at the highest possible level. The system was experimentally implemented on a transversal lathe. The results of tests on dedicatedly designed specimens are showing a machining productivity significant increase, in conditions of a stable cutting process. The system is simple, and it can be easily added to the existing CNC machine tools, without important modifications.     

Hierarchically structured polymer blends based on silsesquioxane hybrid nanocomposites with quaternary ammonium units for antimicrobial coatings

The paper reports the first study on hierarchical assemblies (nanofibrillar micelles confined within semi-cylindrical shells) with silsesquioxane and quaternary ammonium units obtained through polymer blending intended for antimicrobial/antifungal stone coatings. The formation of hierarchical structures on solid surfaces is due to the multiple intermolecular ionic interactions, intermolecular Van der Waals and hydrophobic interactions acting among the component molecules. Their antimicrobial/antifungal properties toward the Gram-negative bacteria, Escherichia coli, Gram-positive bacteria, Staphylococcus aureus, and Candida albicans fungus were determined in aqueous solution and were found to be strongly dependent of the topographical features of the coating.     

Comparative Antimicrobial Activity of Silver Nanoparticles Obtained by Wet Chemical Reduction and Solvothermal Methods

The synthesis of nanoparticles from noble metals has received high attention from researchers due to their unique properties and their wide range of applications. Silver nanoparticles (AgNPs), in particular, show a remarkable inhibitory effect against microorganisms and viruses. Various methods have been developed to obtain AgNPs, however the stability of such nanostructures over time is still challenging. Researchers attempt to obtain particular shapes and sizes in order to tailor AgNPs properties for specific areas, such as biochemistry, biology, agriculture, electronics, medicine, and industry. The aim of this study was to design AgNPs with improved antimicrobial characteristics and stability. Two different wet chemical routes were considered: synthesis being performed (i) reduction method at room temperatures and (ii) solvothermal method at high temperature. Here, we show that the antimicrobial properties of the obtained AgNPs, are influenced by their synthesis route, which impact on the size and shape of the structures. This work analyses and compares the antimicrobial properties of the obtained AgNPs, based on their structure, sizes and morphologies which are influenced, in turn, not only by the type or quantities of precursors used but also by the temperature of the reaction. Generally, AgNPs obtained by solvothermal, at raised temperature, registered better antimicrobial activity as compared to NPs obtained by reduction method at room temperature.     

Optimising residential electric vehicle charging under renewable energy: Multi‐agent learning in software simulation and hardware‐in‐the‐loop evaluation

The integration of intermittent renewable energy sources coupled with the increasing demand of electric vehicles (EVs) poses new challenges to the electrical grid. To address this, many solutions based on demand response have been presented. These solutions are typically tested only in software‐based simulations. In this paper, we present the application in hardware‐in‐the‐loop (HIL) of a recently proposed algorithm for decentralised EV charging, prediction‐based multi‐agent reinforcement learning (P‐MARL), to the problem of optimal EV residential charging under intermittent wind power and variable household baseload demands. P‐MARL is an approach that can address EV charging objectives in a demand response aware manner, to avoid peak power usage while maximising the exploitation of renewable energy sources. We first train and test our algorithm in a residential neighbourhood scenario using GridLAB‐D, a software power network simulator. Once agents learn optimal behaviour for EV charging while avoiding peak power demand in the software simulator, we port our solution to HIL while emulating the same scenario, in order to decrease the effects of agent learning on power networks. Experimental results carried out in a laboratory microgrid show that our approach makes full use of the available wind power, and smooths grid demand while charging EVs for their next day's trip, achieving a peak‐to‐average ration of 1.67, down from 2.24 in the baseline case. We also provide an analysis of the additional demand response effects observed in HIL, such as voltage drops and transients, which can impact the grid and are not observable in the GridLAB‐D software simulation.     

Inter-process communication in MVS/XA and applications for scientific and engineering information processing

This paper surveys inter-process communication in MVS/XA (multiple virtual system/extended architecture) and explores the use of cross-memory services for this purpose. The lack of high-level interfaces to system services is a major handicap in MVS/XA. Tools to provide high-level services, in particular, tools for inter-process communication, can be implemented in a simple, elegant and efficient way. The implementation and use of a communication subsystem, the extended communication facility (ECF), are also described. The ideas and mechanisms presented are useful for many scientific and engineering applications running under MVS/XA. Examples include distributed systems, applications using concurrent programming, a quasi-batch environment, communication subsystems, and mail subsystems.     

A sufficient condition for instability of buffer priority policies in re-entrant lines

We use a buffer-boundedness approach to study the stability of re-entrant lines with a buffer priority scheduling policy. Using Petri net models we establish a sufficient condition for instability of such systems having a positive feedback loop. An example of unstable systems is also given.     

Weighted heuristic anytime search: new schemes for optimization over graphical models

Weighted heuristic search (best-first or depth-first) refers to search with a heuristic function multiplied by a constant w [31]. The paper shows, for the first time, that for optimization queries in graphical models the weighted heuristic best-first and weighted heuristic depth-first branch and bound search schemes are competitive energy-minimization anytime optimization algorithms. Weighted heuristic best-first schemes were investigated for path-finding tasks. However, their potential for graphical models was ignored, possibly because of their memory costs and because the alternative depth-first branch and bound seemed very appropriate for bounded depth. The weighted heuristic depth-first search has not been studied for graphical models. We report on a significant empirical evaluation, demonstrating the potential of both weighted heuristic best-first search and weighted heuristic depth-first branch and bound algorithms as approximation anytime schemes (that have sub-optimality bounds) and compare against one of the best depth-first branch and bound solvers to date.     

Effects of working parameters on surface finish in ball-burnishing of hardened steels

Burnishing is a chipless finishing method, which employs a rolling tool, pressed against the workpiece, in order to achieve plastic deformation of the surface layer. Recent developments made possible burnishing of heat-treated steel components up to 65 HRC. Features of burnishing include a good roughness (comparable to grinding), as well as improvement of mechanical characteristics of the surface (fatigue strength, corrosion resistance, and bearing ratio), due to implementation of compressive stresses into the surface layer. This paper will present influences of certain burnishing parameters upon roughness, for a hardened steel component (64 HRC).     

The injectivity of the canonical signal module for multidimensional linear systems of difference equations with variable coefficients

We consider discrete behaviors with varying coefficients. Our results are new also for one-dimensional systems over the time-axis of natural numbers and for varying coefficients in a field, we derive the results, however, in much greater generality: Instead of the natural numbers we use an arbitrary submonoid N of an abelian group, for instance the standard multidimensional lattice of r-dimensional vectors of natural numbers or integers. We replace the base field by any commutative self-injective ring F, for instance a direct product of fields or a quasi-Frobenius ring or a finite factor ring of the integers. The F-module W of functions from N to F is the canonical discrete signal module and is a left module over the natural associated noncommutative ring A of difference operators with variable coefficients. Our main result states that this module is injective and therefore satisfies the fundamental principle: An inhomogeneous system of linear difference equations with variable coefficients has a solution if and only if the right side satisfies the canonical compatibility conditions. We also show that for the typical cases of partial difference equations and in contrast to the case of constant coefficients the A-module W is not a cogenerator. We also generalize the standard one-dimensional theory for periodic coefficients to the multidimensional situation by invoking Morita equivalence.