A novel iron (III)-PVC membrane potentiomeric sensor based on N-(2-hydroxyethyl)ethylenediamine-N,N',N"-triacetic acid

This work introduces a unique ionophore for the selective determination of Fe(III) ions. This ionophore was N-(2-hydroxyethyl)ethylenediamine-N,N′,N″-triacetic acid (NTA), presenting a high affinity towards the trivalent iron cations. The designed sensor exhibited a wide linear response with a slope of 19.5 ± 0.4 mV per decade over the concentration range of 1.0 × 10^− 9–1.0 × 10^− 2 mol L^− 1, while the illustrated detection limit was 3.0 × 10^− 10 mol L^− 1 of the Fe(III) ions concentration. It was concluded that the sensor response was pH independent in the range of 1.8–4.5. The sensor possessed the advantages of short conditioning time, fast response time (10 s) and, especially, good selectivity towards the transition and heavy metal ions as well as some mono, di and trivalent cations. Concerning the electrode lifetime, no considerable potential divergence was noticed for at least 10 weeks. The sensor accuracy was investigated in the potentiometric titration of a Fe(III) solution with EDTA.     

Chitosan reinforced with modified CaCO<Subscript>3</Subscript> nanoparticles to enhance thermal,hydrophobicity properties and removal of cu(II) and cd(II) ions

The role of nanoparticles (NPs) in the enhancement of thermal, wettability and adsorption properties of chitosan (CS) was inspired by loading of CaCO₃ modified with diacid (DA) based on L- phenyl aniline (2–8 wt%) within the CS by ultrasound agitation. The diameter of CaCO₃-DA into the CS extended from 40 to 70 nm. A thermal test on the CS/CaCO₃-DA nanocomposite (NC) 2 wt% revealed that T ₅ (temperature with 5% weight loss) was increased up to 312 °C, which is twice the value of the pure polymer. The wettability property of the CS/CaCO₃-DA NCs was transformed from hydrophilicity to hydrophobicity as the CaCO₃-DA NPs concentration was increased. It is due to decrease of the accessibility of the CS polar groups to water. The CS/CaCO₃-DA NC 5 wt% was selected as the adsorbent for uptake of metal ions from the wastewater. It showed maximum adsorption capacity of 21.74 and 29.41 mg.g^?1 for Cu(II) and Cd(II), respectively. These are attributed to strong complexation reaction between the metal ions and functional groups in the obtained NC.     

RMRPTS: a reliable multi-level routing protocol with tabu search in VANET

Vehicular ad hoc network (VANET), a subclass of mobile ad hoc networks (MANETs), is a promising approach for the intelligent transportation system (ITS). One of the main challenges in VANETs is establishment of vehicular communication and stable routing. Another problem of VANETs is their tendency of being trapped in a local optimum. In this paper, a reliable multi-level routing protocol based on clustering, RMRPTS has been introduced in VANETs. Even if this topology constantly changes, clustering based multi-level routing will create the possibility of self-organization and route maintaining; moreover, it will solve the problem of developing a trap in the local optimum using tabu search. At the first level, the proposed protocol is an extension of AODV routing protocol that has been improved using fuzzy logic in order to create reliable routing between cluster members. Tabu search has been used at a higher level for routing between cluster heads and destination. Tabu search is a meta-heuristic improved learning method used for solving hybrid optimization problems, and it uses cost function to select a solution among a set of possible solutions. The effective parameters used in the proposed method to select the best path include nodes distance, the velocity of nodes, node’s angle, link stability, and link reliability. The proposed protocol was simulated using an NS-2 simulator, and the results of its performance showed increased average packet delivery rate and decreased average end to end delays, number of packet losses compared with earlier protocols.     

Advanced Hydrogels as Exosome Delivery Systems for Osteogenic Differentiation of MSCs: Application in Bone Regeneration

Hydrogels are known as water-swollen networks formed from naturally derived or synthetic polymers. They have a high potential for medical applications and play a crucial role in tissue repair and remodeling. MSC-derived exosomes are considered to be new entities for cell-free treatment in different human diseases. Recent progress in cell-free bone tissue engineering via combining exosomes obtained from human mesenchymal stem cells (MSCs) with hydrogel scaffolds has resulted in improvement of the methodologies in bone tissue engineering. Our research has been actively focused on application of biotechnological methods for improving osteogenesis and bone healing. The following text presents a concise review of the methodologies of fabrication and preparation of hydrogels that includes the exosome loading properties of hydrogels for bone regenerative applications.     

Preparation of Ag-Al₂O₃ nano structures by combustion method and investigation of photocatalytic activity

In this research, Ag-Al₂O₃ nanostructures have been prepared via combustion synthesis and ammonium acetate and urea have been applied as fuels. The prepared Ag-Al₂O₃ nanostructures were characterized by DTA, XRD, SEM, TEM, and BET spectroscopy. The effect of different ratios of silver to alumina and fuel percentage on morphology and particle size of prepared products were investigated. The results showed that using ammonium acetate fuel led to the production of Ag-γ-Al₂O₃ nanocompounds, while using urea produced Ag-α-Al₂O₃. Also, the photocatalytic activity of Ag-Al₂O₃ nanostructures for Congo red degradation was evaluated by UV-Vis diffuse reflectance spectroscopy. The photocatalytic activity of Ag-Al₂O₃ was examined under UV-Vis irradiation and showed significant photocatalytic efficiency.     

A template-free method to synthesize porous G-C3N4 with efficient visible light photodegradation of organic pollutants in water

Porous graphitic carbon nitride with a high surface area was successfully synthesized without using any template or other substances like metals, just by placing melamine powder into a muffle furnace which was heated to 550?°C in advance. To evaluate the structure, morphology, and optical properties, the high performance g-C₃N₄ (HPCN) was analyzed by XRD, SEM-EDX, TEM, N₂ physisorption, FT-IR analysis, UV–Vis DRS, PL, and Zeta potential. HPCN was able to completely degrade rhodamine B under visible light with the rate constant of 0.086?min^?1, which is 3.5 times higher than the traditional g-C₃N₄. The possible mechanism of RhB photodegradation was discussed in detail, which illustrated the reaction is performed in acidic media much better than neutral and basic solutions, and O₂^? and h⁺ are the key reactive species during the reaction. Moreover, the stability of the photocatalyst was investigated and turned out its photocatalytic activity has not considerably changed after 6 cycles, so it was a highly stable photocatalyst.     

Optimization of Model Reference Adaptive Controller for the Inverted Pendulum System Using CCPSO and DE Algorithms

The main aim of this paper is to propose two variants of bio-inspired algorithm, Constriction Coefficient Particle Swarm Optimization (CCPSO) and Differential Evolution (DE), which determine optimal parameters of Proportional-Integral-Derivative (PID) controller. To achieve this purpose, the PID controller has been plugged to the Model Reference Adaptive Controller (MRAC) that balances Inverted Pendulum (IP) with nonlinear characteristic in vertical-upright position. For comparison purpose, efficiency of these intelligent approaches to adjust MRAC parameters has been evaluated in terms of time response performance. Finally, the overall simulation results demonstrate that both the algorithms yield acceptable response in controlling the nonlinear model of IP system. However, the performance of DE algorithm is better than CCPSO in terms of transient response characteristics.     

Multi-fidelity wing aerostructural optimization using a trust region filter-SQP algorithm

A trust region filter-SQP method is used for wing multi-fidelity aerostructural optimization. Filter method eliminates the need for a penalty function, and subsequently a penalty parameter. Besides, it can easily be modified to be used for multi-fidelity optimization. A low fidelity aerostructural analysis tool is presented, that computes the drag, weight and structural deformation of lifting surfaces as well as their sensitivities with respect to the design variables using analytical methods. That tool is used for a mono-fidelity wing aerostructral optimization using a trust region filter-SQP method. In addition to that, a multi-fidelity aerostructural optimization has been performed, using a higher fidelity CFD code to calibrate the results of the lower fidelity model. In that case, the lower fidelity tool is used to compute the objective function, constraints and their derivatives to construct the quadratic programming subproblem. The high fidelity model is used to compute the objective function and the constraints used to generate the filter. The results of the high fidelity analysis are also used to calibrate the results of the lower fidelity tool during the optimization. This method is applied to optimize the wing of an A320 like aircraft for minimum fuel burn. The results showed about 9 % reduction in the aircraft mission fuel burn.     

Unsupervised feature selection in linked biological data

Pattern Analysis and Applications - Feature selection techniques have become an apparent need in many bioinformatics applications, especially when there exist a huge number of features. For...     

Hyperspectral image classification using a spectral–spatial random walker method

This article proposes a spectral–spatial method for classification of hyperspectral images (HSIs) by modifying traditional random walker (RW). The proposed method consists of suggesting two main modifications. First, to construct a spatial edge weighting function, low-frequency edge weighting function is proposed. In this function, the detail weights are removed. Second, to enhance the classification accuracy, a fusion of spectral and spatial Laplacian matrix in RW is suggested. This fusion can improve the classification performances compared to traditional RW using only spatial Laplacian matrix. In comparison with some of the state-of-the-art RW and spectral–spatial classifier methods, the experimental results of the proposed method (spectral–spatial RW) show that the proposed method significantly increases the classification accuracy of HSI.