Characterization,in vitro bioactivity and biological studies of sol-gel-derived TiO2 substituted 58S bioactive glass

Bioactive glasses (BGs) have been used for bone formation and bone repair processes in recent years. This study investigated the titanium substitution effect on 58S BGs (Ti-BGs) 60SiO₂-(36 − X)CaO-4P₂O₅-XTiO₂ (X = 0, 3, and 5 mol.%) prepared by the sol-gel technique, and the main goal was to find the optimum amount of titanium in Ti-BGs. Synthesized BGs, which were investigated after immersion in simulated body fluid (SBF), were tested by X-ray diffraction (XRD) analysis, Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy. Moreover alkaline phosphate (ALP) activity, 3-(4,5dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, and antibacterial studies were employed to investigate the biological properties of Ti-BGs. According to the FTIR and XRD test results, hydroxyapatite (HA) formation on Ti-BGs surfaces was confirmed. Meanwhile, the presence of 5 mol.% compared to 3 mol.% increased the HA grain distribution and their size on the Ti-BGs surface. Additionally, MTT and ALP results confirmed that the optimal amount of titanium substitution in BG was 5 mol.%. Since 5 mol.% Ti incorporated BG (BG-5) had the highest biocompatibility level, antibacterial properties, maximum cell proliferation, and ALP activity among the synthesized Ti-BGs, it is presented as the best candidate for further in vivo investigations.     

Optimal motion planning for parallel robots via convex optimization and receding horizon

In this paper, the problem of motion planning for parallel robots in the presence of static and dynamic obstacles has been investigated. The proposed algorithm can be regarded as a synergy of convex optimization with discrete optimization and receding horizon. This algorithm has several advantages, including absence of trapping in local optimums and a high computational speed. This problem has been fully analyzed for two three-DOF parallel robots, ie 3s-RPR parallel mechanism and the so-called Tripteron, while the shortest path is selected as the objective function. It should be noted that the first case study is a parallel mechanism with complex singularity loci expression from a convex optimization problem standpoint, while the second case is a parallel manipulator for which each limb has two links, an issue which increases the complexity of the optimization problem. Since some of the constraints are non-convex, two approaches are introduced in order to convexify them: (1) A McCormick-based relaxation merged with a branch-and-prune algorithm to prevent it from becoming too loose and (2) a first-order approximation which linearizes the non-convex quadratic constraints. The computational time for the approaches presented in this paper is considerably low, which will pave the way for online applications.     

BNC-VLA: bayesian network structure learning using a team of variable-action set learning automata

Bayesian Network (BN) is a probabilistic graphical model which describes the joint probability distribution over a set of random variables. One of the most important challenges in the field of BNs is to find an optimal network structure based on an available training dataset. Since the problem of searching the optimal BN structure belongs to the class of NP-hard problems, typically greedy algorithms are used to solve it. In this paper a learning automata-based algorithm has been proposed to solve the BNs structure learning problem. There is a learning automaton corresponding with each random variable and at each stage of the proposed algorithm, named BNC-VLA, a set of learning automata is randomly activated and determined the graph edges that must be appeared in that stage. Finally, the constructed network is evaluated using a scoring function. As BNC-VLA algorithm proceeds, the learning process focuses on the BN structure with higher scores. The convergence of this algorithm is theoretically proved; and also some experiments are designed to evaluate the performance of it. Experimental results show that BNC-VLA is capable of finding the optimal structure of BN in an acceptable execution time; and comparing against other search-based methods, it outperforms them.     

Structure,Microstructure, Magnetic,Electromagnetic, and Dielectric Properties of Nanostructured Mn–Zn Ferrite Synthesized by Microwave-Induced Urea–Nitrate Process

In this work, the effect of urea-to-nitrate molar ratio on the synthesis and properties of Mn_0.5Zn_0.5Fe₂O₄ ferrite prepared by microwave-induced combustion method has been studied. The product powders synthesized at three different molar ratios of urea to nitrate (U/N ratio), varying from 0.58 to 1.08. X-ray diffraction patterns confirm formation of a spinel-type structure of ferrite and also hematite in the as-synthesized powders. The average of particle size is found to be in the range 30–80 nm. The values of saturation magnetization and permeability are increased with the increase in U/N ratio. Dielectric parameters were measured as a function of frequency. The real and imaginary parts of dielectric constant are found to decrease with the increase in frequency, while the ac conductivity is found to increase with increasing frequency. The complex impedance analysis shows only one semicircle indicating the predominant effect of grain boundary property of the material.     

Dependence of Potential Well Depth on the Magnetic Field Intensity in a Polywell Reactor

Using OOPIC-Pro assisted-two dimensional simulation we have considered the dependencies of the electron and ion densities, as well as the central electric potential on the magnetic-field intensity in the Polywell fusion reactor. It is shown that the potential well depth increases with decreasing the magnetic intensity, while much narrower well width (thus more effective deuteron trapping) is achieved with increasing the magnetic field intensity. The results obtained can be employed to adjust the magnetic field intensities at which more effective electron confinement, thus more effective ion-flux convergence, is expected. Furthermore, this study can be used to reach the optimized conditions of the reactor operation as well as to relate to the next generation fusion fuels.     

A Comprehensive Study of Market Prediction from Efficient Market Hypothesis up to Late Intelligent Market Prediction Approaches

Computational Economics - This paper has scrutinized the process of testing market efficiency, data generation process and the feasibility of market prediction with a detailed, coherent and...     

Identifying the time of step change in binary profiles

Control charts are intended to aid quality practitioners in monitoring whether a change has occurred in a process. When a control chart indicates an out-of-control signal, it means that the process has changed. However, control chart signals do not indicate the real time of process changes; so estimators are applied to indicate the time when a change in the process takes place, which is referred to as the change point. This paper provides a maximum likelihood estimator to identify the real time of a step change in phase II monitoring of binary profiles, in which the quality of a process is characterized by a logistic regression between the response and predictor variables. Simulation studies are provided to evaluate the effectiveness of the change point estimator.     

Matrix based method for synthesis of main intensified and integrated distillation sequences

The objective of many studies in this area has involved access to a column-sequencing algorithm enabling designers and researchers alike to generate a wide range of sequences in a broad search space, and be as mathematically and as automated as possible for programing purposes and with good generality. In the present work an algorithm previously developed by the authors, called the matrix method, has been developed much further. The new version of the algorithm includes thermally coupled, thermodynamically equivalent, intensified, simultaneous heat and mass integrated and divided-wall column sequences which are of gross application and provide vast saving potential both on capital investment, operating costs and energy usage in industrial applications. To demonstrate the much wider searchable space now accessible, a three component separation has been thoroughly examined as a case study, always resulting in an integrated sequence being proposed as the optimum.     

A critical review of bioceramics for magnetic hyperthermia

Magnetic hyperthermia (HT) using biocompatible ceramics is a ground-breaking, competent, and safe thermo-therapeutic strategy for cancer treatment. The magnetic properties of bioceramics, along with their structure and synthesis parameters, are responsible for the controlled heating of malignant tumors and are the key to clinical success. After providing a brief overview of magnetism and its significance in biomedicine, this review deals with materials selection and synthesis methods of bioceramics/glasses used for HT. Relevant research carried out on promising bioceramics for magnetic HT, with a focus on their size, shape, surface functionalization, magnetic field parameters, and in vitro/in vivo properties to optimize cancer therapy, is also discussed. Recent progress in magnetic HT combined with chemotherapy and phototherapy is especially highlighted, with the aim to provide interdisciplinary knowledge to advance further the applications of bioceramics in this field.