Targeted design of polyaniline-graphene oxide,barium-strontium titanate,hard-soft ferrite,and polyester multi-phase nanocomposite for highly efficient microwave absorption

The current paper focuses on synthesizing a high-efficiency microwave absorber via incorporating the nanofillers of graphene oxide-polyaniline (GO-PANI), barium-strontium titanate (BST), and soft-hard ferrite within the polyester matrix. The nanocomposite magnets of (Ba_0.5Sr_0.5Fe₁₂O₁₉)_1-x hard/(CoFe₂O₄)_x soft (x = 0.2, 0.5, and 0.8) were prepared using sol-gel auto-combustion method. The GO-PANI and BST were successfully synthesized by in situ polymerization and improved polymerization, respectively. The phase structure, chemical structure, morphology, and microwave absorption properties of the synthesized nanocomposites were characterized by X-ray diffractometer (XRD), Fourier-transform infrared spectroscopy (FT-IR), and scanning electron microscope (SEM), vector network analyzer (VNA) techniques, respectively. The results showed that the synergistic effects of the combination of dielectric (BST), conductive (GO-PANI), and magnetic materials (hard-soft ferrites) provided the reflection loss values of less than ?20 dB (>99% absorption) in the X-band region. The minimum reflection loss of ?35 dB (>99.99% absorption) was obtained by the optimal formulation including (Ba_0.5Sr_0.5Fe₁₂O₁₉)_0.2 (CoFe₂O₄)_0.8, and the weight ratio of 1: 2 for both BST/soft-hard ferrite and hard-soft ferrite + BST/GO-PANI with the thickness of 1 mm. According to the results, the thickness factor plays a key role in improving the impedance matching. Consequently, the proposed nanocomposite can be employed as a novel kind of microwave absorbers with good impendence matching and high absorption.     

AMBO: All Members-Based Optimizer for Solving Optimization Problems

There are many optimization problems in different branches of science that should be solved using an appropriate methodology. Population-based optimization algorithms are one of the most efficient approaches to solve this type of problems. In this paper, a new optimization algorithm called All Members-Based Optimizer (AMBO) is introduced to solve various optimization problems. The main idea in designing the proposed AMBO algorithm is to use more information from the population members of the algorithm instead of just a few specific members (such as best member and worst member) to update the population matrix. Therefore, in AMBO, any member of the population can play a role in updating the population matrix. The theory of AMBO is described and then mathematically modeled for implementation on optimization problems. The performance of the proposed algorithm is evaluated on a set of twenty-three standard objective functions, which belong to three different categories: unimodal, high-dimensional multimodal, and fixed-dimensional multimodal functions. In order to analyze and compare the optimization results for the mentioned objective functions obtained by AMBO, eight other well-known algorithms have been also implemented. The optimization results demonstrate the ability of AMBO to solve various optimization problems. Also, comparison and analysis of the results show that AMBO is superior and more competitive than the other mentioned algorithms in providing suitable solution.     

Amino Functionalized Nano Fe3O4@SiO2 as a Magnetically Green Catalyst for the One-Pot Synthesis of Spirooxindoles Under Mild Conditions

(3-Aminopropyl)-triethoxysilane attached to Fe₃O₄@SiO₂ nanoparticles has been characterized by powder X-ray diffraction, vibrating sample magnetometer, scanning electronic microscope, transmission electron microscope, energy dispersive X-ray, thermal gravimetric analysis, and Fourier transform infrared spectroscopy. The prepared nanoparticles employed as a heterogeneous catalyst in the synthesis of spirooxindoles derivatives in one-pot four-component reactions of isatin, methyl cyanoacetate or malononitrile, hydrazine hydrate, and ethyl acetoacetate. Amino-functionalized magnetic nanoparticles showed high catalytic activity in mild reaction conditions and excellent yields of products in short reaction times. Also, this nanocatalyst can be easily recovered by a magnet and reused for subsequent reactions for at least 5 times without noticeable loss in catalytic activity.     

CRWSNP: cooperative range-free wireless sensor network positioning algorithm

Sensing events occur in an area without knowing the events locations, is meaningless. Since there is no priorly knowledge about the locations of most of the sensors which scattered randomly in an area, wireless sensor network localization methods try to find out where sensors are located. A new cooperative and distributed range-free localization algorithm, based on only connectivity information is proposed in this paper. The method first uses convex optimization techniques to find primitive target nodes locations estimation, then nodes cooperate with each other in several iterations to improve the whole network location estimation. CRWSNP converges after a finite number of iterations because of applying two novel heuristic location correction techniques. As well as, results of the algorithm have been compared with six range-free based methods like CPE, DV-hop, APIT; and CRWSNP algorithm provides more accurate results over 50 random topologies for the network, in mean error and maximum error metrics.     

Microstructure and Optical Bandgap of Cobalt Selenide Nanofilms

Semiconductors - The purpose of this research is to explore the properties of CoSe nanostructured thin films on glass substrates prepared by a chemical solution deposition method. Special attention...     

An Optically Responsive Soft Etalon Based on Ultrathin Cellulose Hydrogels

Stimuli‐responsive optical etalons are an exciting class of next‐generation sensors because they are scalable, cost‐effective and offer tunability of their optical response across the entire UV–vis–NIR wavelength range. In this study, double‐network cellulose hydrogels are used as a soft, responsive medium and are incorporated into Fabry–Pérot optical etalons. The thin cellulose hydrogel layer can be solution processed. The hygroscopic hydrogel undergoes both refractive index and thickness changes in response to changes in humidity. This leads to strong changes in reflection due to optical interference within the metal–insulator–metal (MIM) cavity. The response can be optimized by adjusting the chemical crosslinker ratio. These flexible MIM structures provide a robust platform for optically based chemical sensors.     

An evolutionary game theory–based security model in vehicular ad hoc networks

The word population is growing on a daily basis; consequently, the growth of commute and transport, developing efficient and intelligent transportation systems (ITS), has become one of the most popular requirements and the most significant attempts in modern urban areas containing large population. A key component of intelligent transportation systems is a vehicular ad hoc network. Devising internet‐based practical programs such as awareness of climatic conditions, geographical location, practical programs like on‐line payment services in the vehicular ad hoc network has led to safer driving, prevention of deadly accidents, transportation improvement, more welfare and convenience for passengers, and even offering more commercial opportunities. The special features of vehicular ad hoc network, such as intense activity, constantly‐changing topology, the vehicles' high speed, etc, will lead to challenges in gaining security. Therefore, providing vehicular ad hoc networks with security is of extreme importance in terms of users' anonymity, identification, and data privacy. In this paper, a security model is presented using a method based on evolutionary games. This method, in every vehicle, is applied as a node in the network while interacting with other vehicles; it aims at distinguishing some common attacks and defending against attackers. In this method, defending (honest) vehicles and attacking vehicles take part in an asymmetrical game; each vehicle aims at gaining the most utility and achieving its goals. The proposed method is simulated using various scenarios. The simulation results reveal that the proposed method is efficient and it reaches equilibrium and convergence at the end of the game in each scenario.     

Real-Time Operation of Pumping Systems for Urban Flood Mitigation: Single-Period vs. Multi-Period Optimization

To reduce flood risk in urban regions, it is important to optimize the performance of operational elements such as gates and pumps. This paper compares the performances of two approaches of multi-period and single-period simulation-optimization that are used to derive real-time control policies for operating urban drainage systems. The EPA storm water management model (SWMM), converting real-time rainfall data to surface runoff at network control points, i.e. pump stations, is linked to the particle swarm optimization (PSO) algorithm, evaluating the system operation performance measure (objective function) for different sets of control policies. A prototype network in a portion of the Seoul urban drainage system is used to investigate the efficiency of the proposed approaches. Results justify the high efficiency of multi-period optimization, leading to 32 and 29% average reductions in peak water level violations from a pre-defined permissible threshold at target points and the number of pump switches, respectively, in comparison with the online single-period optimization. The myopic policies derived by single-period optimization are not reliable, and in some cases, they even perform worse than ad-hoc policies applied by system operators based on their past experiences.