Biosynthesis of silver nanoparticles in collagen gel improves their medical use in periodontitis treatment

Silver nanoparticles (AgNP) suspensions were biosynthesized by silver ions reduction in the presence of collagen, a nontoxic, organic polymer, intending to improve their medical use in periodontitis treatment. Spectrophotometric measurements showed a time- and concentration-dependent increase of AgNP formation in each suspension variant. Transmission electron microscopy revealed spherical morphology of AgNP in collagen and their mean diameter size was around 30?nm. The particle size distribution and zeta potential values of AgNP in collagen were determined by dynamic light scattering measurements. The surface charge of AgNP in collagen was positive, while commercial AgNP stabilized in citrate had negative surface charge. In vitro cytotoxicity testing of AgNP in collagen showed that they were biocompatible with human gingival fibroblasts in a wider range of concentrations than commercial nanoparticles. The antibacterial activity of AgNP in collagen against two pathogenic strains present in the periodontal pocket was dose-dependent and higher than that of AgNP in citrate. All these results demonstrated that AgNP prepared in collagen gel had improved properties, like small diameter, positive surface charge, high biocompatibility in human gingival fibroblasts, efficiency against bacterial growth and, thus, better therapeutic potential in periodontal disease treatment.     

A new approach for solution of vehicle routing problem with hard time window: an application in a supermarket chain

In this study, a vehicle routing problem with hard time windows (VRPHTW) that appears to meet demands of customers’ service within time intervals in a supermarket chain is solved. In VRPHTW, to reach a solution by an exact method is quite difficult and sometimes impossible if number of constraints is large enough (i.e., NP-hard), and solution time of a VRPHTW grows exponentially. As the size of the problem grows, a near optimal solution can be found using a heuristic method. A hierarchical approach consisting of two stages as “cluster-first route-second” is proposed. In the first stage, customers are assigned to vehicles using three different clustering algorithms (i.e., K-means, K-medoids and DBSCAN). In the second stage, a VRPHTW is solved using a MILP. The main contribution of the article is that the proposed hierarchical approach enables us to deal with a large size real problem and to solve it in a short time using the exact method. Finally, the proposed approach is employed on a supermarket chain. An instance of the algorithm is demonstrated to illustrate the applicability of the proposed approach and the results obtained are highly favourable.     

Effect of XRD relative intensities of the Li (002) on surface,optical and electrochemical impedance spectroscopy analyses of the deposited LiCoO<Subscript>2</Subscript> thin film

In this paper, the effect of RF power on LiCoO₂ thin films was investigated using X-ray diffractometer (XRD), atomic force microscopy, UV–Vis spectrophotometer, and potentiostat. The microstructural, surface, optical and electrochemical impedance measurements were performed to LiCoO₂ thin films, are used to for the fully solid-state battery cathode material. According to obtained results, the relative intensities of the Li (002) crystal phase in XRD patterns of deposited LiCoO₂ thin films were increased by increasing applied RF power, for the first time. The intensity of the LiCoO₂ (104) plane is nearly invariant. The relative intensities of the LiCoO₂ (113) plane were decreased by increasing RF power. The peak locations of the Li (002) and LiCoO₂ (104) were not changed. It was found that Li (002) relative intensities affect the all investigated parameters for the LiCoO₂ thin films. Especially, transmittance value increased about 20%. The band gap of the deposited film was changed 100–300 meV drastically. Deposited samples are shown high transparency in the visible region. Randles circuit was used for the equivalent circuit model. Nyquist plots, fitting parameters values and value of the circuit elements were estimated by ZSim software.     

PointProNets: Consolidation of Point Clouds with Convolutional Neural Networks

With the widespread use of 3D acquisition devices, there is an increasing need of consolidating captured noisy and sparse point cloud data for accurate representation of the underlying structures. There are numerous algorithms that rely on a variety of assumptions such as local smoothness to tackle this ill‐posed problem. However, such priors lead to loss of important features and geometric detail. Instead, we propose a novel data‐driven approach for point cloud consolidation via a convolutional neural network based technique. Our method takes a sparse and noisy point cloud as input, and produces a dense point cloud accurately representing the underlying surface by resolving ambiguities in geometry. The resulting point set can then be used to reconstruct accurate manifold surfaces and estimate surface properties. To achieve this, we propose a generative neural network architecture that can input and output point clouds, unlocking a powerful set of tools from the deep learning literature. We use this architecture to apply convolutional neural networks to local patches of geometry for high quality and efficient point cloud consolidation. This results in significantly more accurate surfaces, as we illustrate with a diversity of examples and comparisons to the state‐of‐the‐art.     

Test and Reliability in Approximate Computing

This paper presents an overview of test and reliability approaches for approximate computing architectures. We focus on how specific methods for test and reliability can be used to improve the characteristics of approximate computing in terms of power consumption, area, life expectancy and precision. This paper does not address specification and design of approximate hardware/software/algorithms, but provides an in-depth knowledge on how the reliability and test related techniques can be efficiently used to maximize the benefits of approximate computing.     

Determination of R‐Deprenyl using a Maltodextrin‐Based Enantioselective,Potentiometric Membrane Electrode

Abstract

The enantioselective, potentiometric membrane electrode (EPME) based on maltodextrin with dextrose equivalence (DE) 16.5–19.5 is proposed for the assay of R‐deprenyl. The linear concentration range for the proposed electrode is 10^?10?10^?3 mol L^?1. The slope of the electrode is 53.1 mV per decade of concentration. The detection limit is 3.6×10^?11 mol L^?1. The proposed electrode could be reliably employed for the assay of R‐deprenyl raw material and its pharmaceutical formulation, Lentogesic tablets.     

Multilayer biopolymer/poly(ε-caprolactone)/polycation nanoparticles

Combining two or more materials for carrier construction is one of the topical approaches to avoid/diminish deficiencies and to increase functionality in delivery systems for bioactive compounds. In this context, here, multilayered nanoparticles comprising both natural (atelocollagen—AteCol; hyaluronic acid derivative—HA) and synthetic [poly(ε-caprolactone)—PCL; polyethylenimine—PEI; poly(l-lysine)—PLL] polymers were prepared and characterized. The combination of a modified double-emulsion method with polymer modification reactions allowed improvement of the polymer particle’s functionality. Fourier transform infrared spectroscopy (FTIR), UV–Vis spectroscopy, fluorescence spectroscopy, dynamic light scattering, transmission/scanning electron microscopy and fluorescence microscopy investigations confirmed the obtention of the envisaged nanomaterials with the expected composition and structure. The double-layered biopolymer/PCL-based nanoparticles formed in a first synthesis step could be successfully coated with PEI and PLL. The gel electrophoresis assay attested the DNA packing ability of the formed nano-vehicles involving surface grafting of the former biopolymer/PCL-based nanoparticles in the case of both cationic polymers, for N/P ratios of 10 (PEI coating) and 3.5 (PLL coating), respectively. According to the FTIR registration, the protein’s native form was preserved. Considering the advantage of biocompatibility and high versatility (controlled size, tuned chemistry and biodegradation rate) some of the resulted nanomaterials may appear as potential candidates for biomedical uses (i.e., drug/gene delivery and tissue engineering).     

Phase formation and microstructure of Nd<Superscript>+3</Superscript> doped Pb(Mg<Subscript>1/3</Subscript>Nb<Subscript>2/3</Subscript>)O<Subscript>3</Subscript> prepared by sol–gel method

The aim of this study was to investigate the effects of the rare earth element neodymium on the phase formation and microstructural development of relaxor ferroelectric lead magnesium niobate, Pb(Mg_1/3Nb_2/3)O₃ (PMN) system. Perovskite phase PMN powders were prepared using the sol–gel method and the effect of neodymium doping was investigated at different doping levels ranging from 0.1 mol% to 30 mol%. The precursors employed in the sol–gel process were lead (II) acetate, magnesium ethoxide, and niobium (V) ethoxide. All the experiments were performed at room temperature while the calcination temperatures ranged between 800 °C and 1,100 °C. Results showed that it was possible to obtain the pure perovskite phase at 950 °C using the sol–gel method. Nd⁺³ addition influenced the phase formation and microstructure of the multicomponent system. Pyrochlore was detected along with the perovskite phase above 10 mol% Nd. Results also demonstrated that grain size of the synthesized powders depended on the Nd⁺³ concentration.     

Statistical Evaluation of Factors Affecting the Leaching Process of Waste Electrical and Electronic Equipment using Sodium Persulfate

Recycling of waste electrical and electronic equipment (WEEE) is important not only to reduce the amount of waste requiring treatment, but also to promote the recovery of valuable materials. Implementation of the European Directive on WEEE and recycling targets imposed in the European Union will require new processes to be developed and applied to recover metals from WEEE. This study aims to provide an alternative process for the dissolution of metals from WEEE which contains Cu and Zn based on our previous research. The effects of leaching parameters, such as temperature, Na₂S₂O₈ concentration, and leaching time, were separately investigated on leaching of copper, zinc, and brass (alloy composition ?35% zinc and 65% copper) in Na₂S₂O₈ solution (0.1, 0.2 and 0.3 M). Box–Behnken experimental design (BBD) method was used to determine the number and the condition of necessary leaching experiments. Statistical analysis of variance (ANOVA) was performed to see whether process parameters such as leaching time, temperature, and oxidant concentration are statistically significant or not on the leaching performance. Results show leaching time as the most influential factor in the dissolution process, for the first six models. Two extended models have been developed to optimize the parameters of the investigated process. In these models, we consider the metal composition as a model input next to the earlier investigated parameters. Optimal condition for maximum copper and zinc dissolution in Na₂S₂O₈ environment can be found for parameter values: temperature 45°C, oxidant concentration 0.1 M and leaching time 35 min.