Optimal deflection and stacking sequence prediction of curved composite structure using hybrid (FEM and soft computing) technique

Engineering with Computers - The bending deflections and the corresponding optimal fiber angle sequences of the subsequent layers have been predicted in this article using a hybrid technique. The...     

A detailed comparative study on the main electrical parameters of Au/n-Si and Au/PVA:Zn/n-Si Schottky barrier diodes

We have fabricated Au/n-Si and Au/PVA:Zn/n-Si Schottky barrier diodes (SBDs) to investigate the effect of organic interfacial layer on the main electrical characteristics. Zn doped poly(vinyl alcohol) (PVA:Zn) was successfully deposited on n-Si substrate by using the electrospinning system and surface morphology of PVA:Zn was presented by SEM images. The current–voltage (I–V) characteristics of these SBDs have been investigated at room temperature. The experimental results show that interfacial layer enhances the device performance in terms of ideality factor (n), zero-bias barrier height (Φ_B0), series resistance (R_s), and shunt resistance (R_sh) with values of 1.38, 0.75 eV, 97.64 Ω, and 203 MΩ whereas those of Au/n-Si SBD are found as 1.65, 0.62 eV, 164.15 Ω and 0.597 MΩ, respectively. Also, this interfacial layer at metal/semiconductor (M/S) interface leads to a decrease in the magnitude of leakage current and density of interface states (N_ss). The values of N_ss range from 1.36×10¹² at E_c—0.569 eV to 1.35×10¹³ eV^?1 cm^?2 at E_c—0.387 eV for Au/PVA:Zn/n-Si SBD and 3.34×10¹² at E_c—0.560 eV to 1.35×10¹³ eV^?1 cm^?2 at E_c—0.424 eV for Au/n-Si SBD. The analysis of experimental results reveals that the existence of PVA:Zn interfacial layer improves the performance of such devices.     

Dissolution kinetics of colemanite in potassium dihydrogen phosphate solution (KH2PO4)

Colemanite is rich in boron, and it is a common raw material used to produce boron components. The first step in this process is the dissolution of colemanite using different leaching solutions. The main aim of this study was to investigate the dissolution kinetics of colemanite in potassium dihydrogen phosphate (KH₂PO₄) solution. The reaction temperature?(T), the KH₂PO₄ concentration (C), the stirring speed (W), the solid-to-liquid ratio (S/L) and particle size (D) of the colemanite were selected as parameters affecting the rate of its dissolution. The Statistica software package was used to correlate the experimental results. The findings of the study showed that the dissolution rate of colemanite in KH₂PO₄ solution increased with increasing reaction temperature and KH₂PO₄ concentration, while an increase in particle size and solid-to-liquid ratio caused a decrease. Heterogeneous and homogeneous reaction models were tried in order to derive a proper kinetic model for colemanite dissolution. According to the results, it was determined that the colemanite dissolution process is controlled by a chemical reaction model. The activation energy value (41.88 kJ mol^?1) also verified this conclusion.     

Achieving zT > 1 in Inexpensive Zintl Phase Ca9Zn4+xSb9 by Phase Boundary Mapping

Complex multinary compounds (ternary, quaternary, and higher) offer countless opportunities for discovering new semiconductors for applications such as photovoltaics and thermoelectrics. However, controlling doping has been a major challenge in complex semiconductors as there are many possibilities for charged intrinsic defects (e.g., vacancies, interstitials, antisite defects) whose energy depends on competing impurity phases. Even in compounds with no apparent deviation from a stoichiometric nominal composition, such defects commonly lead to free carrier concentrations in excess of 10²⁰ cm^?3. Nevertheless, by slightly altering the nominal composition, these defect concentrations can be tuned with small variation of the chemical potentials (composition) of each element. While the variation of chemical composition is undetectable, it is shown that the changes can be inferred by mapping (in nominal composition space) the boundaries where different competing impurity phases form. In the inexpensive Zintl compound Ca₉Zn_4+x Sb₉, the carrier concentrations can be finely tuned within three different three‐phase regions by altering the nominal composition (x = 0.2–0.8), enabling the doubling of thermoelectric performance (zT). Because of the low thermal conductivity, the zT can reach as high as 1.1 at 875 K, which is one of the highest among the earth abundant p‐type thermoelectrics with no ion conducting.     

Left ventricular assist device patient maintained on home hemodialysis: A novel class of patients to the home dialysis population

Severe heart failure is increasingly being managed by cardiac transplantation, and in some cases mechanical support devices serve as destination therapies. Left ventricular assist devices (LVADs) were approved for destination therapy for end stage heart failure patients before the more advanced total artificial heart modality became available. One common complication of mechanical assist device placement is acute kidney injury. Historically, patients with mechanical support devices have had to have inpatient hemodialysis until combined heart kidney transplant. Though, some units have started accepting LVAD patients in outpatient dialysis clinics. The cost of in center hemodialysis remains high and home dialysis modalities are becoming increasingly popular. We report the first patient with an LVAD to undergo training and successful home hemodialysis while awaiting combined heart kidney transplantation.     

Classification of Coronavirus (COVID‐19) from X‐ray and CT images using shrunken features

Necessary screenings must be performed to control the spread of the COVID‐19 in daily life and to make a preliminary diagnosis of suspicious cases. The long duration of pathological laboratory tests and the suspicious test results led the researchers to focus on different fields. Fast and accurate diagnoses are essential for effective interventions for COVID‐19. The information obtained by using X‐ray and Computed Tomography (CT) images is vital in making clinical diagnoses. Therefore it is aimed to develop a machine learning method for the detection of viral epidemics by analyzing X‐ray and CT images. In this study, images belonging to six situations, including coronavirus images, are classified using a two‐stage data enhancement approach. Since the number of images in the dataset is deficient and unbalanced, a shallow image augmentation approach was used in the first phase. It is more convenient to analyze these images with hand‐crafted feature extraction methods because the dataset newly created is still insufficient to train a deep architecture. Therefore, the Synthetic minority over‐sampling technique algorithm is the second data enhancement step of this study. Finally, the feature vector is reduced in size by using a stacked auto‐encoder and principal component analysis methods to remove interconnected features in the feature vector. According to the obtained results, it is seen that the proposed method has leveraging performance, especially to make the diagnosis of COVID‐19 in a short time and effectively. Also, it is thought to be a source of inspiration for future studies for deficient and unbalanced datasets.     

A comparative analysis of meta-heuristic approaches for facility layout design problem: a case study for an elevator manufacturer

In this study, a facility layout problem having NP-hard problem characteristic is attempted to be solved by using two different meta-heuristic approaches—Genetic Algorithm (GA) and Simulated Annealing (SA)—and a hybrid approach—Genetic Algorithm/Simulated Annealing (HGASA). The case study is completed for a company which can be seen as a small or a medium size enterprise. First, parameter values of GA and SA are determined by testing for various combinations of them. Then, the algorithms are run for one hundred times. The results of the algorithms are compared based on their fitness values and calculation time requirements using the paired-t test, mean and standard values. The results show that SA performs better than the others in terms of the fitness values and the time requirements. In this study, we also test the performance of our GA, SA and HGASA methodologies using some of the well-known test problems from the literature. We obtain very close results to those in literature.     

Spectral feature projections that maximize Shannon mutual information with class labels

Determining optimal subspace projections that can maintain task-relevant information in the data is an important problem in machine learning and pattern recognition. In this paper, we propose a nonparametric nonlinear subspace projection technique that maintains class separability maximally under the Shannon mutual information (MI) criterion. Employing kernel density estimates for nonparametric estimation of MI makes possible an interesting marriage of kernel density estimation-based information theoretic methods and kernel machines, which have the ability to determine nonparametric nonlinear solutions for difficult problems in machine learning. Significant computational savings are achieved by translating the definition of the desired projection into the kernel-induced feature space, which leads to obtain analytical solution.     

The effect of curing lights and modes on dentin bond strength of bulk-fill composites applied in different thickness

To investigate shear bond strength (SBS) to dentin of a conventional and three bulk-fill composites applied in different increment thickness and cured by mono- and multi-wave LED LCUs. Two hundred and fifty-two extracted sound human molars were prepared for SBS test. The teeth were divided into four groups according to the resin composites used. Conventional composite: Tetric N-Ceram (control); high-viscosity bulk-fills: Tetric N-Ceram Bulk Fill, X-tra Fil, and SonicFill. Each group was subdivided (n?=?7) according to increment thickness (2, 4, and 6?mm) and cured by standard mode of a mono-wave LED or two different modes (standard and xtra power) of a multi-wave LED. The failure mode was stereomicroscopically determined at 40× magnification. Data were analyzed using Three-way ANOVA and further comparisons were assessed by Bonferroni’s multiple comparison test. There were no significant differences within X-tra fil and Tetric N-Ceram Bulk Fill groups for any of the variables (p?>?0.05). A significant decrease in SBS values with increase of layer thickness was observed for SonicFill and control groups. Also, curing mode had a significant effect on both composites at 6?mm thickness and standard mode of multi-wave LED caused the highest SBS value (p???0.05). Adhesive failure was the most common fracture pattern especially at 6?mm thickness applications. Based on the results of this study, the bulk-fill composites can be safely applied in one-step with 4?mm increments, although the examined composites performed better at 2?mm thickness. The performance of the composites at 6?mm increment may show differences related to the curing lights and modes.