Genetic Algorithm for the Multiple-Query Optimization Problem

Producing answers to a set of queries with common tasks efficiently is known as the multiple-query optimization (MQO) problem. Each query can have several alternative evaluation plans, each with a different set of tasks. Therefore, the goal of MQO is to choose the right set of plans for queries which minimizes the total execution time by performing common tasks only once. Since MQO is an NP-hard problem, several, mostly heuristics based, solutions have been proposed for solving it. To the best of our knowledge, this correspondence is the first attempt to solve MQO using an evolutionary technique, genetic algorithms     

Solver and Shell Element Performances for Curved Bridge Analysis

A study has been undertaken to investigate different solver and shell element performances for curved bridge finite-element analysis. Three sparse solvers were implemented into a bridge finite-element analysis code, and the solution times and memory requirements for typical bridges were compared. In addition, the use of four-node and nine-node shell elements in modeling was investigated for different mesh densities. Based on the comparative studies performed, modeling guidelines for practicing engineers have been developed and are presented herein.     

Solubility Enhancement of Fe in ZnO Nanoparticles Prepared by Co-Precipitation Method

Journal of Superconductivity and Novel Magnetism - Crystalline ZnO offers an excellent host matrix to create a dilute magnetic semiconductor (DMS) owing to its facile Zn-atom substitution with the...     

Synthesis and thermal properties of poly(styrene-co-ally alcohol)-graft-stearic acid copolymers as novel solid–solid PCMs for thermal energy storage

A series of poly(styrene-co-allyalcohol)-graft-stearic acid copolymers were synthesized as novel polymeric solid–solid phase change materials (SSPCMs). The graft copolymerization reactions between poly(styrene-co-allyalcohol) and stearoyl chloride were verified by Fourier transform infrared (FT-IR) and Proton Nuclear Magnetic Resonance (¹H NMR) spectroscopy techniques. The crystal morphology of the SSPCMs was investigated using polarized optical microscopy (POM) technique. Thermal energy storage properties of the synthesized SSPCMs were measured using differential scanning calorimetry (DSC) analysis. The POM results showed that the crystalline phase of the copolymers transformed to amorphous phase above their phase transition temperatures. Thermal energy storage properties of the synthesized SSPCMs were investigated by differential scanning calorimetry (DSC) and found that they had typical solid–solid phase transition temperatures in the range of 27–30 °C and high latent heat enthalpy between 34 and 74 J/g. Especially, the copolymer with the mole ratio of 1/1 (poly(styrene-co-allyalcohol)/stearoyl chloride) is the most attractive one due to the highest latent heat storage capacity among them. The results of DSC and FT-IR analysis indicated that the synthesized SSPCMs had good thermal reliability and chemical stability after 5000 thermal cycles. Thermogravimetric (TG) analysis results suggested that the synthesized SSPCMs had high thermal resistance. In addition, thermal conductivity measurements signified that the synthesized PCMs had higher thermal conductivity compared to that of poly(styrene-co-allyalcohol). The synthesized copolymers as novel SSPCMs have considerable potential for thermal energy storage applications such as solar space heating and cooling in buildings and greenhouses.     

Experimental study for high effective mobility with directly deposited HfO2/La2O3 MOSFET

We experimentally examine the effective mobility in nMOSFETs with La₂O₃ gate dielectrics without SiO_x-based interfacial layer. The reduced mobility is mainly caused by fixed charges in High-k gate dielectrics and the contribution of the interface state density is approximately 30% at N_s = 5 × 10¹¹ cm^?2 in the low 10¹¹ cm^?2 eV^?1 order. It is considered that one of the effective methods for improving mobility is to utilize La-silicate layer formed by high temperature annealing. However, there essentially exists trade-off relationship between high temperature annealing and small EOT.     

The accumulation of La,Ce and Y by Lemna minor and Lemna gibba in the Keban gallery water,Elazig Turkey

This study investigated the phytoremediation ability of Lemna minor and Lemna gibba to accumulate lanthanum, cerium and yttrium from gallery water polluted by metals. L. minor and L. gibba were settled in the mining water and adapted to separate reactors. During the experiment, the water and plant samples were daily taken and the temperature, electric conductivity and pH of the water were daily measured in situ. These plants were firstly washed, dried in and then ashed at 300°C for 24 h in an oven. Both water and ashed plant samples were measured by ICP‐MS to detect the concentrations of lanthanum (La), cerium (Ce) and yttrium (Y). Although these elements are at low concentrations in gallery water, they were accumulated at the highest levels in L. gibba and in L. minor. This study showed that both plants have high ability to remove lanthanum, cerium and yttrium in gallery water polluted by different elements.     

Detection of COVID-19 and its pulmonary stage using Bayesian hyperparameter optimization and deep feature selection methods

Since the first case of COVID-19 was reported in December 2019, many studies have been carried out on artificial intelligence for the rapid diagnosis of the disease to support health services. Therefore, in this study, we present a powerful approach to detect COVID-19 and COVID-19 findings from computed tomography images using pre-trained models using two different datasets. COVID-19, influenza A (H1N1) pneumonia, bacterial pneumonia and healthy lung image classes were used in the first dataset. Consolidation, crazy-paving pattern, ground-glass opacity, ground-glass opacity and consolidation, ground-glass opacity and nodule classes were used in the second dataset. The study consists of four steps. In the first two steps, distinctive features were extracted from the final layers of the pre-trained ShuffleNet, GoogLeNet and MobileNetV2 models trained with the datasets. In the next steps, the most relevant features were selected from the models using the Sine–Cosine optimization algorithm. Then, the hyperparameters of the Support Vector Machines were optimized with the Bayesian optimization algorithm and used to reclassify the feature subset that achieved the highest accuracy in the third step. The overall accuracy obtained for the first and second datasets is 99.46% and 99.82%, respectively. Finally, the performance of the results visualized with Occlusion Sensitivity Maps was compared with Gradient-weighted class activation mapping. The approach proposed in this paper outperformed other methods in detecting COVID-19 from multiclass viral pneumonia. Moreover, detecting the stages of COVID-19 in the lungs was an innovative and successful approach.     

Investigation of the Microstructural,Mechanical and Corrosion Properties of Grade A Ship Steel-Duplex Stainless Steel Composites Produced <Emphasis Type="Italic">via</Emphasis> Explosive Welding

Grade A ship-building steel-AISI 2304 duplex stainless steel composite plates were manufactured via explosive welding. The AISI 2304 plates were used to clad the Grade A plates. Optical microscopy studies were conducted on the joining interface for characterization of the manufactured composite plates. Notch impact, tensile-shear, microhardness, bending and twisting tests were carried out to determine the mechanical properties of the composites. In addition, the surfaces of fractured samples were examined by scanning electron microscopy (SEM), and neutral salt spray (NSS) and potentiodynamic polarization tests were performed to examine corrosion behavior. Near the explosion zone, the interface was completely flat, but became wavy as the distance from the explosion zone increased. The notch impact tests indicated that the impact strength of the composites decreased with increasing distance from the explosion zone. The SEM studies detected brittle behavior below the impact transition temperature and ductile behavior above this temperature. Microhardness tests revealed that the hardness values increased with increasing distance from the explosion zone and mechanical tests showed that no visible cracking or separation had occurred on the joining interface. The NSS and potentiodynamic polarization tests determined that the AISI 2304 exhibited higher corrosion resistance than the Grade A steel.     

Thermal inactivation kinetics of peroxidase and lipoxygenase from fresh pinto beans (Phaseolus vulgaris)

 Thermal inactivation kinetics of crude peroxidase (POX) and lipoxygenase (LOX) in fresh pinto beans were studied over the temperature range of 55–90°C. The inactivation of both enzymes followed first-order kinetics. The biphasic inactivation curves for POX indicate the existence of several isoenzymes of varying heat stability. In the temperature range of 55–70°C, the activation energies (E _a) of POX were 46.5 kcal·mol^–1 for the heat-labile portion and 37.6 kcal·mol^–1 for the heat-stable portion. On the other hand, the LOX enzyme had an E _a value of 42.26 kcal·mol^–1 at 55–75°C and 49.1 kcal·mol^–1 at 55–90°C. Received: 28 July 1997 / Revised version: 16 October 1997