Combustion synthesis of NbC/ZrO2 composites: Influence of Cr additives on the microstructure and mechanical properties

Composites of NbC/ZrO₂ reinforced with different weight ratios of Cr metal were prepared by dynamic compaction combustion from a blend of Nb₂O₅–Zr–Cr powders. Factors controlling the synthesis process, the microstructure, and the mechanical properties of the samples, such as Cr wt% and the compression loads were studied. The samples were characterized by XRD, SEM, porosity, and hardness measurements. The porosity value of the sample with no additives was high and reached 31.6 vol%. A sudden decrease in the sample porosity to 2.4 vol % was noticed for the sample containing 3.0 wt% of Cr. A high-density sample with less than 2.0 vol % porosity and maximum hardness of 1038 HV was produced using 5.0 wt% Cr under 300 MPa compression load. Detailed thermodynamic calculations for the effect of Cr additives on the physicochemical properties of the system were introduced.     

Study on pharyngeal and uvular consonants in foreign accented Arabic for ASR

This paper investigates the unique pharyngeal and uvular consonants of Arabic from the point of view of automatic speech recognition (ASR). Comparisons of the recognition error rates for these phonemes are analyzed in five experiments that involve different combinations of native and non-native Arabic speakers. The most three confusing consonants for every investigated consonant are discussed. All experiments use the Hidden Markov Model Toolkit (HTK) and the Language Data Consortium (LDC) WestPoint Modern Standard Arabic (MSA) database. Results confirm that these Arabic distinct consonants are a major source of difficulty for Arabic ASR. While the recognition rate for certain of these unique consonants such as // can drop below 35% when uttered by non-native speakers, there is advantage to include non-native speakers in ASR. Besides, regional differences in pronunciation of MSA by native Arabic speakers require the attention of Arabic ASR research.     

Artificial Neural Networks for Prediction of COVID-19 in Saudi Arabia

In this study, we have proposed an artificial neural network (ANN) model to estimate and forecast the number of confirmed and recovered cases of COVID-19 in the upcoming days until September 17, 2020. The proposed model is based on the existing data (training data) published in the Saudi Arabia Coronavirus disease (COVID-19) situation—Demographics. The Prey-Predator algorithm is employed for the training. Multilayer perceptron neural network (MLPNN) is used in this study. To improve the performance of MLPNN, we determined the parameters of MLPNN using the prey-predator algorithm (PPA). The proposed model is called the MLPNN–PPA. The performance of the proposed model has been analyzed by the root mean squared error (RMSE) function, and correlation coefficient (R). Furthermore, we tested the proposed model using other existing data recorded in Saudi Arabia (testing data). It is demonstrated that the MLPNN-PPA model has the highest performance in predicting the number of infected and recovering in Saudi Arabia. The results reveal that the number of infected persons will increase in the coming days and become a minimum of 9789. The number of recoveries will be 2000 to 4000 per day.     

NUMERICAL SIMULATION OF THE THERMAL CONTROL OF HEAT EXCHANGERS

The temperature control of outlet air by changing the water flow rate in a single-pass waterto-air cross-flow heat exchanger is investigated. The conservation laws are applied to finite control volumes and an implicit formulation is used for transient numerical solutions. Conjugate forced convection heat transfer from the tube is solved to calculate the temperatures of the air and water coming out of the heat exchanger. In the simulations the outlet air temperature is controlled by changing the water flow rate entering the heat exchanger using a proportional-integral (PI) controller. The range of controllability of the heat exchanger was studied first. Then disturbances in the form of step changes in the inlet air temperature, the air flow rate, and the set point temperature were separately introduced. The effects of the limiting-condition constraints and different control parameters on controlling the outlet air temperature are presented. The results show that the control behavior can be simulated numerically and that this control methodology is effective within limits.     

LCZ696 Protects against Diabetic Cardiomyopathy-Induced Myocardial Inflammation,ER Stress,and Apoptosis through Inhibiting AGEs/NF-κB and PERK/CHOP Signaling Pathways

The present study is designed to determine the effect of LCZ696 on DCM in rats and investigate the underlying mechanism involved. Diabetes was induced by feeding rats with a high-fat diet for six weeks following a single injection of STZ (30 mg/kg). Diabetic rats were divided into three groups (n = 10). LCZ696 and valsartan treatment was started two weeks after diabetic induction and continued for eight weeks. At the end of the treatment, serum and cardiac tissues were analyzed by RT-PCR, Western blot, and ELISA kits. LCZ696 and valsartan ameliorated DCM progression by inhibiting AGEs formation at activity levels; pro-apoptotic markers (BAX/Bcl2 ratio and caspase-3) in mRNA and protein expressions, the NF-κB at mRNA; and protein levels associated with the restoration of elevated proinflammatory cytokines such as the TNF-α, IL-6, and IL-1β at the activity level. Furthermore, LCZ696 and valsartan contribute to restoring the induction of ER stress parameters (GRP78, PERK, eIF2a, ATF4, and CHOP) at mRNA and protein levels. LCZ696 and valsartan attenuated DCM by inhibiting the myocardial inflammation, ER stress, and apoptosis through AGEs/NF-κB and PERK/CHOP signaling cascades. Collectively, the present results reveal that LCZ696 had a more protective solid effect against DCM than valsartan.     

Speech recognition

The authors have designed, successfully trained and tested an Arabic speech recognition system. This system was implemented using C++ programming language on Windows 95. It can be partitioned into five main modules. These modules are the front-end, feature extraction, training, pattern recognition and decision making and display. The front-end module functions as signal preparation and calibration. This includes: setting the signal sampling rate, removing the DC component from the signal, setting the scaling factor of the signal and detecting the endpoints of the utterance. The endpoint task removes the non-speech signal portions created by the speaker's pauses. This reduces the system computation time needed and the memory requirements. The feature extraction module is mainly a digital signal processor. The training module is the one that finds the best templates for every word or sound (phonemes) in the system's database. In short, this module needs to be executed only one time before users can utilize the system. The next module is the pattern recognition module. Its function is to compare the given utterance (test utterance) to all the stored templates (the reference module). The decision and display module functions as an interface between the user and the hidden system modules. In other words, after getting the recognition module results, this module displays the best candidate(s) and/or their likelihood percentage. The error rates are computed and displayed in this module     

Multifractal analysis of Mg-doped ZnO thin films deposited by sol–gel spin coating method

A multifractal analysis has been performed on the 3D (three-dimensional) surface microtexture of magnesium-doped zinc oxide (ZnO:Mg) thin films with doping concentration of 0, 2, 4, and 5%. Thin films were deposited onto the glass substrates via the sol–gel spin coating method. The effect of magnesium doping, on the crystal structure, morphology, and band gap for ZnO:Mg thin films has been analyzed by X-ray diffraction (XRD), scanning electron microscopy (SEM), atomic force microscopy (AFM), and UV–Vis spectroscopy. It has been observed that the surface of ZnO thin films is multifractal in nature. However, multifractality and complexity observed to decrease with increasing content of Mg in ZnO thin films due to formation of islands on the surface in accordance with Volmer–Weber growth mechanism. The investigations revealed that crystallinity, microtexture, morphology, and optical properties of the thin films can be tuned by controlling the Mg content within the ZnO lattice. In particular, their optical band gap energies were 3.27, 3.31, 3.34, and 3.33 eV at 0, 2, 4, and 5%, respectively. The prepared thin films of ZnO:Mg with tuned characteristics would have promising applications in optoelectronic devices.     

Impact of bismuth oxide on the structure,optical features and ligand field parameters of borosilicate glasses doped with nickel oxide

Understanding the impact of bismuth cations on the optical properties of borosilicate glass is significant for manipulating borate glass applications. In this paper, the influence of bismuth cations on both structural and optical properties of borosilicate glass doped with NiO was investigated. Different glass samples, containing different amounts of Bi₂O₃ and a constant amount of NiO, were prepared and studied. Infrared (IR) analysis was carried out to study the internal structure within the investigated glass samples. Optical absorption studies were performed to investigate the impact of Bi₂O₃ content on optical properties of the BiBaNiB-glasses. Astonishingly, with Bi₂O₃ addition, an absorption band at 380 nm has appeared. Moreover, this band is overlapped with the Urbach edge; which regularly produced an artificial edge-like feature at ~450 nm. A detailed deconvolution protocol has been implemented for an appropriate understanding of these spectra and unraveling the hidden Urbach edge. Optical band gap energy, linear and nonlinear refractive index for each BiBaNiB sample were calculated. Furthermore, the metallization criterion was calculated to examine the metallic or insulating nature of the BiBaNiB-glasses. The values of the nonlinear third-order susceptibility and nonlinear refractive index were increased with Bi₂O₃ doping. The BiBaNiB-glasses exhibited outstanding stability and optical band gap than the pristine glass sample, which makes it possible for practical applications.