Novel Color Image Compression Algorithm Based-On Quadtree

This paper presents a novel algorithm having two image processing systems that have the ability to compress the colour image. The proposed systems divides the colour image into RGB components, each component is selected to be divided. The division processes of the component into blocks are based on quad tree method. For each selection, the other two components are divided using the same blocks coordinates of the selected divided component. In the first system, every block has three minimum values and three difference values. While the other system, every block has three minimum values and one average difference. From experiments, it is found that the division according to the G component is the best giving good visual quality of the compressed images with appropriate compression ratios. It is also noticed, the performance of the second system is better than the first one. The obtained compression ratios ofthe second system are between 1.3379 and 5.0495 at threshold value 0.1, and between 2.3476 and 8.9713 at threshold value 0.2

COVID-19 Detection on Chest x-ray Images by Combining Histogram-oriented Gradient and Convolutional Neural Network Features

The COVID-19 coronavirus epidemic has spread rapidly worldwide after a person became infected with a severe health problem. The World Health Organization has declared the coronavirus a global threat (WHO). Early detection of COVID 19, particularly in cases with no apparent symptoms, may reduce the patients mortality rate. COVID 19 detection using machine learning techniques will aid healthcare systems around the world in recovering patients more rapidly. This disease is diagnosed using x-ray images of the chest; therefore, this study proposed a machine vision method for detecting COVID-19 in x-ray images of the chest. The histogram-oriented gradient (HOG) and convolutional neural network (CNN) features extracted from x-ray images were fused and classified using support vector machine (SVM) and softmax. The proposed feature fusion technique (99.36 percent) outperformed individual feature extraction methods such as HOG (87.34 percent) and CNN (93.64 percent)

Prediction of Pressure Drop in Vertical Pneumatic Conveyors

This paper presents a steady state one-dimensional two-fluid model for gas-solid two-phase flow in a vertical riser. The model is solved using conservative variable approach for the gas phase, and fourth order Runge-Kutta method is used for the solid phase. The model predictions for pressure drop are compared with available experimental data and with Eulerian-Lagrangian predictions, and a good agreement is obtained. The results indicate that the pressure drop increases as the solid mass flow rate, particle size, and particles density increase. In addition, the model predictions for minimum pressure drop velocity are compared with experimental data from literature and the mean percentage error. MPE for minimum pressure drop velocity is -9.89%. It is found that the minimum pressure drop velocity increases as the solid mass flow, particle size and particle density increase, and decreases as the system total pressure increases

NUMERICAL INVESTAGATION OF GAS-SOLID SUSPENSION FLOW IN 180 o CURVED DUCT

ABSTRACT In this paper, a two-way coupling EulerianLagrangian approach is presented for the simulation of gassolid two-phase flow in 180 o curved duct. In the present study, Reynolds averaged Navier-Stokes equations (RANS) and two turbulence models namely; standard k-ε model and RNG (Renormalization Group) based k-ε model are adopted. The effects of particle rotation and lift forces are included in the particle tracking model while the effect of inter-particle collisions is neglected. The present predictions are compared with published experimental data for single-phase flow and published particles trajectories. The comparisons show that the RNG based k-ε model predicts the flow behaviour better than the standard k-ε model. Furthermore, the particles trajectories are compared very well with published data. The effects of inlet gas velocity, bend geometry, loading ratio and solid properties on the flow behaviour are also discussed. The results show that the flow behaviour is greatly affected by the above parameters

Novel 1,3-Thiazole Analogues with Potent Activity against Breast Cancer: A Design, Synthesis, In Vitro, and In Silico Study

Breast cancer is the most common cancer in women, responsible for over half a million deaths in 2020. Almost 75% of FDA-approved drugs are mainly nitrogen- and sulfur-containing heterocyclic compounds, implying the importance of such compounds in drug discovery. Among heterocycles, thiazole-based heterocyclic compounds have demonstrated a broad range of pharmacological activities. In the present study, a novel set of 1,3-thiazole derivatives was designed and synthesized based on the coupling of acetophenone derivatives, and phenacyl bromide was substituted as a key reaction step. The activity of synthesized compounds was screened against the proliferation of two breast cancer cell lines (MCF-7 and MDA-MB-231). Almost all compounds exhibited a considerable antiproliferative activity toward the breast cancer cells as compared to staurosporine, with no significant cytotoxicity toward the epithelial cells. Among the synthesized compounds, compound 4 exhibited the most potent antiproliferative activity, with an IC50 of 5.73 and 12.15 µM toward MCF-7 and MDA-MB-231 cells, respectively, compared to staurosporine (IC50 = 6.77 and 7.03 µM, respectively). Exploring the mechanistic insights responsible for the antiproliferative activity of compound 4 revealed that compound 4 possesses a significant inhibitory activity toward the vascular endothelial growth factor receptor-2 (VEGFR-2) with (IC50 = 0.093 µM) compared to Sorafenib (IC50 = 0.059 µM). Further, compound 4 showed the ability to induce programmed cell death by triggering apoptosis and necrosis in MCF-7 cells and to induce cell cycle arrest on MCF-7 cells at the G1 stage while decreasing the cellular population in the G2/M phase. Finally, detailed in silico molecular docking studies affirmed that this class of compounds possesses a considerable binding affinity toward VEGFR2 proteins. Overall, these results indicate that compound 4 could be a promising lead compound for developing potent anti-breast cancer compounds.Faculty of Pharmacy, Suez Canal University, and Faculty of Science, Port Said University, EgyptPrincess Nourah bint Abdulrahman University Researchers SupportingTaif University Researcher

The ligational behavior of a phenolic quinolyl hydrazone towards copper(II)- ions

<p>Abstract</p> <p>Background</p> <p>The heterocyclic hydrazones constitute an important class of biologically active drug molecules. The hydrazones have also been used as herbicides, insecticides, nematocides, redenticides, and plant growth regulators as well as plasticizers and stabilizers for polymers. The importance of the phenolic quinolyl hydrazones arises from incorporating the quinoline ring with the phenolic compound; 2,4-dihydroxy benzaldehyde. Quinoline ring has therapeutic and biological activities whereas, phenols have antiseptic and disinfectants activities and are used in the preparation of dyes, bakelite and drugs. The present study is planned to check the effect of the counter anions on the type and geometry of the isolated copper(II)- complexes as well as the ligational behavior of the phenolic hydrazone; 4-[(2-(4,8-dimethylquinolin-2-yl)hydrazono)methyl] benzene-1,3-diol; (H₂L).</p> <p>Results</p> <p>A phenolic quinolyl hydrazone (H₂L) was allowed to react with various copper(II)- salts (Cl‾, Br‾, NO₃‾, ClO₄‾, AcO‾, SO₄^2-). The reactions afforded dimeric complexes (ClO₄‾, AcO‾ ), a binuclear complex (NO₃‾ ) and mononuclear complexes (the others; Cl‾, Br‾, SO₄^2-). The isolated copper(II)- complexes have octahedral, square pyramid and square planar geometries. Also, they reflect the strong coordinating ability of NO₃‾, Cl‾, Br‾, AcO‾ and SO₄^2-anions. Depending on the type of the anion, the ligand showed three different modes of bonding <it>viz</it>. (NN)⁰for the mononuclear complexes (<b>3, 4, 6</b>), (NO)^-with O- bridging for the dimeric complexes (<b>1, 5</b>) and a mixed mode [(NN)⁰+ (NO)^-with O- bridging] for the binuclear nitrato- complex (<b>2</b>).</p> <p>Conclusion</p> <p>The ligational behavior of the phenolic hydrazone (H₂L) is highly affected by the type of the anion. The isolated copper(II)- complexes reflect the strong coordinating power of the SO₄^2-, AcO‾, Br‾, Cl‾ and NO₃‾ anions. Also, they reflect the structural diversity (octahedral, square pyramid and square planar) depending on the type of the counter anion.</p

Ligand substitution reactions of a phenolic quinolyl hydrazone; oxidovanadium (IV) complexes

<p>Abstract</p> <p>Background</p> <p>Quinoline ring has therapeutic and biological activities. Quinolyl hydrazones constitute a class of excellent chelating agents. Recently, the physiological and biological activities of quinolyl hydrazones arise from their tendency to form metal chelates with transition metal ions. In this context, we have aimed to study the competency effect of a phenolic quinolyl hydrazone (H₂L; primary ligand) with some auxiliary ligands (Tmen, Phen or Oxine; secondary ligands) towards oxidovanadium (IV) ions.</p> <p>Results</p> <p>Mono- and binuclear oxidovanadium (IV) - complexes were obtained from the reaction of a phenolic quinolyl hydrazone with oxidovanadium (IV)- ion in absence and presence of N,N,N',N'- tetramethylethylenediamine (Tmen), 1,10-phenanthroline (Phen) or 8-hydroxyquinoline (Oxine). The phenolic quinolyl hydrazone ligand behaves as monobasic bidentate (NO- donor with O- bridging). All the obtained complexes have the preferable octahedral geometry except the oxinato complex (<b>2</b>) which has a square pyramid geometry with no axial interaction; the only homoleptic complex in this study.</p> <p>Conclusion</p> <p>The ligand exchange (substitution/replacement) reactions reflect the strong competency power of the auxiliary aromatic ligands (Phen/Oxine) compared to the phenolic quinolyl hydrazone (H₂L) towards oxidovanadium (IV) ion; (complexes <b>2 </b>and <b>3</b>). By contrast, in case of the more flexible aliphatic competitor (Tmen), an adduct was obtained (<b>4</b>). The obtained complexes reflect the strength of the ligand field towards the oxidovanadium (IV)- ion; Oxine or Phen >> phenolic hydrazone (H₂L) > Tmen.</p

Reorganizing Neural Network System for Two Spirals and Linear Low-Density Polyethylene Copolymer Problems

This paper presents an automatic system of neural networks (NNs) that has the ability to simulate and predict many of applied problems. The system architectures are automatically reorganized and the experimental process starts again, if the required performance is not reached. This processing is continued until the performance obtained. This system is first applied and tested on the two spiral problem; it shows that excellent generalization performance obtained by classifying all points of the two-spirals correctly. After that, it is applied and tested on the shear stress and the pressure drop problem across the short orifice die as a function of shear rate at different mean pressures for linear low-density polyethylene copolymer (LLDPE) at 190∘C. The system shows a better agreement with an experimental data of the two cases: shear stress and pressure drop. The proposed system has been also designed to simulate other distributions not presented in the training set (predicted) and matched them effectively