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In this paper, an analytical and numerical technique are examined in order to analyse the Stokes flow determination problem due to a viscous sphere droplet moving at a concentric instantaneous position inside a spherical interface separating finite and semi-infinite immiscible fluid phases. Here, when only one of the three phases of the fluid (micropolar fluid) has a microstructure, attention is focused on this case. The motion is considered when Reynolds- and capillary-numbers are low, and the droplet surface and the fluid-fluid interface have insignificant deformation. A general solution is obtained in a spherical coordinate system based on a concentric position to analyse the slow axisymmetric movement of the micropolar fluid, considering microrotation and velocity components. Boundary conditions are initially fulfilled at the fluid-fluid interface and subsequently at the droplet surface. The normalised hydrodynamic drag force applying to a moving viscous droplet appears to be a function of the droplet-to-interface radius ratio, which increases monotonically and becomes unbounded when the droplet surface touches the fluid-fluid interface. The numerical outcomes of the normalised drag force acting on the viscous droplet are derived for different values of the parameters, and are presented in a tabular and graphical framework. A comparison was made between our numerical outcomes for the drag force and the pertinent data for the special cases found in the literature.

Abstract New Series of N-Manniche bases 3,4 (a-c) and 5,6 (a-b) were synthesized through the reaction of benzaldehyde and amine with 3-methyl-4-(aryldiazenyl)-1H-pyrazol-5-ol derivatives 2(a-c), they were fully characterized by FT-IR, (1H, 13C) NMR data in addition to their mass spectra. The Structural Activity Relationship of the target compounds were examined for their cytotoxicity. Some newly synthesized compounds showed promising antiproliferation properties when tested against HepG2 cancer cells. Compounds 4a, 5a, and 6b showed potent cytotoxicity against HepG2 with IC50 values of 4.4, 3.46 and 2.52 µM compared to Sorafenib (IC50 = 2.051 µM) and Roscovitine (IC50 = 4.18 µM). Furthermore, they were safe against the THLE2 cells with higher IC50 values. Compound 6b exhibited promising dual VEGFR2/CDK-2 inhibition activities; it had an IC50 value of 0.2 μM with VEGFR2 inhibition of 93.2%, and it had an IC50 value of 0.458 μM with CDK-2 inhibition of 88.7%. In comparison to the untreated control group (0.95%), compounds 5a (38.32%) and 6b (42.9%) considerably increased the cell population in total apoptosis. In addition, compounds 5a and 6b arrested the cell population at G0-G1 and S phases, respectively. Molecular docking experiments confirmed the virtual binding mechanism of the most active drugs, which were found to have good binding affinities with both receptor active sites.

Due to the increased demand for energy resources these days, especially due to the Russian-Ukrainian war, the focus of the major countries is turning strongly towards improving oil production, especially heavy and extra heavy oil, which represents 40% of the world oil reserve. Steam-based and thermal (EOR) procedures are promising techniques for recovering heavy oil reservoirs, but they suffer from a sequence of problems and complications that arise after long-term application. These complications comprise steam breakthrough, steam overlap, and steam/rock interactions. This research presents the currently applied techniques to maximize the productivity of heavy oil, such as steam injection, cyclic steam stimulation, in-situ combustion, and steam-assisted gravity drainage. Thermal technologies face numerous obstacles, as they are energy and water-intensive processes that are not environmentally friendly. The research also presents future trends in energy-saving and environmentally friendly techniques that enhance heavy oil recovery through vapor extraction (VAPEX) steam-solvent hybrid techniques, electromagnetic energy, sonication, and nanotechnology. The findings of this review reported that all the presented techniques focus on how to reduce the oil viscosity and in-situ upgrade the crude oil properties. In turn, these enhance both the productivity rate and oil recovery and minimize the production cost. This article can be considered a comprehensive review of thermal recovery methods in heavy and extra-heavy oil, in addition to screening criteria used for each method.

Abstract The accurate estimation of gas viscosity remains a pivotal concern for petroleum engineers, exerting substantial influence on the modeling efficacy of natural gas operations. Due to their time-consuming and costly nature, experimental measurements of gas viscosity are challenging. Data-based machine learning (ML) techniques afford a resourceful and less exhausting substitution, aiding research and industry at gas modeling that is incredible to reach in the laboratory. Statistical approaches were used to analyze the experimental data before applying machine learning. Seven machine learning techniques specifically Linear Regression, random forest (RF), decision trees, gradient boosting, K-nearest neighbors, Nu support vector regression (NuSVR), and artificial neural network (ANN) were applied for the prediction of methane (CH4), nitrogen (N2), and natural gas mixture viscosities. More than 4304 datasets from real experimental data utilizing pressure, temperature, and gas density were employed for developing ML models. Furthermore, three novel correlations have developed for the viscosity of CH4, N2, and composite gas using ANN. Results revealed that models and anticipated correlations predicted methane, nitrogen, and natural gas mixture viscosities with high precision. Results designated that the ANN, RF, and gradient Boosting models have performed better with a coefficient of determination (R2) of 0.99 for testing data sets of methane, nitrogen, and natural gas mixture viscosities. However, linear regression and NuSVR have performed poorly with a coefficient of determination (R2) of 0.07 and − 0.01 respectively for testing data sets of nitrogen viscosity. Such machine learning models offer the industry and research a cost-effective and fast tool for accurately approximating the viscosities of methane, nitrogen, and gas mixture under normal and harsh conditions.

This article presents an analytical and numerical investigation on the quasi-steady, slow flow generated by the movement of a micropolar fluid drop sphere of at a concentrical position within another immiscible viscous fluid inside a spherical slip cavity. Additionally, the effect of a cavity with slip friction along with the change in the micropolarity parameter on the movement of the fluid sphere is introduced. When Reynolds numbers are low, the droplet moves along a diameter that connects their centres. The governing and constitutive differential equations are reduced to a computationally convenient form using appropriate transformations. By using the resulting linear partial differential equations for the stream functions and using the method of separation variables, we can obtain their solutions. General solutions for velocity fields are found using spherical coordinate systems, which are based on the concentric point of the cavity; this allows to obtain solutions to the Navier-Stokes equations internal and external to the spherical droplet. The vorticity-microrotation boundary condition is used in regard to the micropolar droplet case in a viscous fluid. The normalised drag forces acted upon the micropolar drop are illustrated via graphs and tables for diverse values of the viscosity ratio and drop-to-wall radius ratio, with the change of the spin parameter that attaches the microrotation to vorticity. The correction wall factor is shown to increase with an increase in the drop-to-wall radius ratio, when moving from the gas bubble case to the solid sphere case, with an increase in the micropolarity parameter, and with an increase in the slip frictional resistance. This study is relevant due to its potential uses in a variety of biological, natural, and industrial processes, including the creation of raindrops, the investigation of blood flow, fluid-fluid extraction, the forecasting of weather conditions, the rheology of emulsions, and sedimentation phenomena.

Background: Aquaporins (AQPs) are transmembrane channel proteins. Aquaporin 1 (AQP1), Aquaporin 3 (AQP3), and Aquaporin 7 (AQP7) are expressed in the jejunum. The purpose of this study was to ascertain how a high-fat high-fructose diet (HFFD) and intermittent fasting (IF) affect AQP1, AQP3, and AQP7 expression in the rat jejunum. Methods: Sixteen adult male rats were divided into control rats (n = 4) fed on a basal diet and water ad libitum for 12 weeks; IF control rats (n = 4) followed the IF protocol, HFFD-fed rats (n = 8) fed HFFD for eight weeks, and rats were randomized into two groups: HFFD only or HFFD and IF protocol from the beginning of the 9th week until the end of the experiment. The lipid profile values were assessed after 12 weeks. Jejunal oxidative markers (malondialdehyde and reduced glutathione) and AQP1, AQP3, and AQP7 mRNA expression were measured. Jejunal sections were used for morphometric analysis of villus length and crypt depth. Immunohistochemical evaluation of AQP1, AQP3, and AQP7 expression was also performed. Results: IF ameliorates HFFD-induced lipid profile, oxidative stress, and jejunal morphometric changes. The results of both mRNA expression using PCR and immunohistochemistry showed a significant increase in AQP1, AQP3, and AQP7 expression in HFFD, whereas IF caused a decline in this expression. Conclusion: These findings suggest that IF can reduce inflammation, and oxidative stress and restore jejunal morphology caused by HFFD.

Plants are often exposed to non-ideal conditions during their growth. The toxicity of heavy metals as abiotic stressors is a significant concern due to their harmful effects on plants. Glycine betaine (GB) is a potent compatible solute that helps plants resist abiotic stresses and plays a crucial role in alleviating them. This study aimed to determine the effective role of glycine betaine (0.5 and 1 mM) as a foliar treatment in sugar beet plants to cope with the toxicity of cadmium (50 mg/kg soil) and lead (100 mg/kg soil). The application of lead (Pb) and cadmium (Cd) in cultivation soil noticeably suppressed morphological growth attributes, such as chlorophylls, carotenoids, sugars, and proteins. At the same time, the aforementioned levels of heavy metals significantly increased the levels of non-enzymatic antioxidants (phenolics and proline) and enzymatic antioxidants (peroxidase, superoxide dismutase, polyphenol oxidase, and catalase) in the root and shoot tissues of sugar beet plants. In contrast, the use of glycine betaine as foliar treatment at 0.5 and 1 mM alleviated the adverse impacts of cadmium and lead by promoting the aforementioned attributes. Furthermore, the application of 1 mM GB was more effective in increasing the contents of phenolics in root by approximately 16% and 29%, phenolics in shoot by about 25% and 10%, peroxidase activity by about 82% and 116%, superoxide dismutase activity by about 56% and 47%, polyphenol oxidase activity by about 9% and 36%, catalase activity by about 19% and 25%, in cadmium- and lead-stressed plants, respectively. Additionally, it reduced the levels of proline in sugar beet tissues. Overall, the application of glycine betaine has the efficacy to counteract the adverse impacts of cadmium and lead toxicity on sugar beet plants by enhancing the metabolic indices as well as the non-enzymatic and enzymatic antioxidant activities.

COVID-19 pandemic has negatively affected all areas of lifestyle, especially the education sector, from both the students' and teachers' points of view. As we are all concerned with students' difficulties, this study focuses on teachers' lived experiences and challenges and their adaptive strategies in class operations, especially in teaching Science Education. This study is interview-based data instrumentation as it is a phenomenological type of research exploring the lived experiences of Science teachers. Lived experiences, challenges, and adaptive strategies are the thematic base of the data. Findings revealed that (1) there are three core themes under the lived experiences of Science teachers, including building relations, call of duty, and instruction reconstruction. (2) Science teachers were also mostly challenged during distance learning during the COVID-19 pandemic, including the authenticity of students' outputs, instruction delivery, internet connectivity, lack of resources, safety, and topography, which resulted in the difficulty of Science class operation. Despite the lived experiences and challenges brought by distance learning, (3) they learned to possess adaptability, accept assistance, be flexible and innovative, manage time, and use a specialized strategy or radio-based instructions. The study recommends that Science teachers exert extra effort, be resourceful, and cope with digital divides such as attending seminars and workshops to better utilize opportunities in distance learning. They must possess a positive outlook in every way possible. The higher office of the education sector initiates adaptive strategies for teachers.

Abstract Egypt observes one of the highest water budget deficits in Africa that is mainly compensated by intensive reuse of untreated agricultural drainage water in the Nile Delta. The implications of untreated water reuse on increasing soil pollution levels remain poorly characterized; however, a large‐scale pollution can compromise crop production and water quality. To address this deficiency, we evaluate the level of heavy metal pollution in the Nile Delta, identify its sources and explore the implications of damming on heavy metal concentration using integrated pollution indicators and statistical modeling. Pollution indicators show moderate to very high contamination by Pb, Ni, Cr, Cd, Cu, and Zn, with unprecedented Cd levels in the sediments (up to 72.0 ppm) and a northward increase in pollution levels. Statistical modeling and historical datasets reveal the association of Cd and Fe on both Nile branches and the clustering of Pb, Ni, Cu, Zn and Cr, which attribute the heavy metal concentrations to the cumulative addition of untreated agricultural drainage water (9.5 BCM/yr) and wastewater. These processes introduced an accelerated pollution in the Nile Delta system. Though, conservation measures are crucial to reverse this degradation, yet the increasingly engineered Nile flow, the low gradient of the delta and the active silting impede heavy metal flushing causing irreversible pollution. Our findings alarm future increase in heavy metal pollution in response to increased untreated drainage water reuse to mitigate the impacts of ongoing upstream damming and call for implementing international cooperative agreements for integrated water management along the Nile River.

This work investigates the efficacy of high-pressure torsion (HPT), as a severe plastic deformation mechanism for processing plain and silicon-carbide-reinforced AA6061, with the broader objective of using the technique for improving the properties of lightweight materials for a range of objectives. The interactions between input variables, such as the pressure and equivalent strain (εeq) applied during HPT processing, and the presence of SiCp and response variables, like the relative density, grain refinement, homogeneity of the structure, and the mechanical properties of the AA6061 aluminum matrix, were investigated. Hot compaction (HC) of the mixed powders followed by HPT were employed to produce AA6061 discs with and without 15% SiCp. The experimental findings were then analyzed statistically using the response surface methodology (RSM) and a machine learning (ML) approach to predict the output variables and to optimize the input parameters. The optimum combination of HPT process parameters was confirmed by the genetic algorithm (GA) and ML approaches. Furthermore, the constructed ML and RSM models were validated experimentally by HPT processing the same material under new conditions not fed into the models and comparing the experimental results to those predicted by the model. From the ML and RSM models, it was found that processing the AA6061/SiCp composite HPT via four revolutions at 3 GPa produced the highest mechanical properties coupled with significant grain refinement compared to the HC condition. ML analysis revealed that the equivalent strain induced by the number of revolutions was the most effective parameter for grain refinement, whereas the presence of SiCp played the highest role in improving both the hardness values and the compressive strength of the AA6061 matrices.

In this paper, bimetallic functionally graded structures were fabricated using wire and arc additive manufacturing (WAAM). The bimetallic walls were built by depositing Si-Bronze and high-strength low-alloy (HSLA) steel, successively. The microstructural evolution of the built structures, especially within the fusion zone between the dissimilar alloys, was investigated in relation to their mechanical properties. The built bimetallic walls showed a high level of integrity. An overall interface length of 9 mm was investigated for microstructural evolution, elemental mapping and microhardness measurements along the building direction. Microhardness profiles showed a gradual transition in hardness passing through the diffusion zone with no evidence for intermetallic compounds. Failure of the tensile specimens occurred at the Si-Bronze region, as expected. Bending tests confirmed good ductility of the joint between the dissimilar alloys. Direct shear test results proved a shear strength comparable to that of HSLA steel. The obtained results confirm that it is appropriate to fabricate HSLA steel/Si-Bronze FGMs using WAAM technology.

Several physics-based models have been utilized in material design for the simulation and prediction of material properties. In this study, several machine-learning (ML) approaches were used to construct a prediction model to analyze the influence of equal-channel angular pressing (ECAP) parameters on the microstructural, corrosion and mechanical behavior of the biodegradable magnesium alloy ZK30. The ML approaches employed were linear regression, the Gaussian process, and support vector regression. For the optimization of the alloy’s performance, experiments were conducted on ZK30 billets using different ECAP routes, channel angles, and number of passes. The adopted ML model is an adequate predictive model which agreed with the experimental results. ECAP die angles had an insignificant effect on grain refinement, compared to the route type. ECAP via four passes of route Bc (rotating the sample 90° on its longitudinal axis after each pass in the same direction) was the most effective condition producing homogenous ultrafine grain distribution of 1.92 µm. Processing via 4-Bc and 90° die angle produced the highest hardness (97-HV) coupled with the highest tensile strength (344 MPa). The optimum corrosion rate of 0.140 mils penetration per year (mpy) and the optimum corrosion resistance of 1101 Ω·cm2 resulted from processing through 1-pass using the 120°-die. Grain refinement resulted in reducing the corrosion rates and increased corrosion resistance, which agreed with the ML findings.

Wire arc additive manufacturing (WAAM) with high deposition rates has attracted industry interest for the demonstrated economic production of medium-to-large-scale metallic components. The structural integrity and mechanical properties of the built parts depend on the selection of the optimum deposition parameters and the tool path strategy. In this study, an alternate orthogonal deposition strategy was employed. The influence of the beads’ geometry and the associated heat input on the mechanical and structural behavior of mild steel (ER70S-6) were investigated. The influence of the bead width (BW) and the overlapping percentage (OP) between the adjacent beads on the average and layer-by-layer hardness of the blocks along the building direction were evaluated. Tensile strength was also characterized. The alternate orthogonal building strategy enhanced the geometrical uniformity of the built blocks and the microstructural isotropy along the building direction. Increasing the BW increased the total heat input per bead per layer, which significantly reduced the hardness and tensile strength of the built blocks by 19% and 17% compared to 8% and 7% when increasing the OP, respectively. Total heat input, number of heating cycles, and cooling rates triggered the phases formed, and their morphologies along the building direction were also characterized.

Viruses pose a serious threat to the sustainable production of economically important crops around the world. In the past 20 years, potato virus Y (PVY) emerged as a relatively new and very serious problem in potatoes, even though it is the oldest known plant virus. Multiple strains of the virus cause various symptoms on the leaves and tubers of potatoes, resulting in yield reduction and poor-quality tubers. Consequently, it would be very interesting to learn what causes systemic PVY resistance in plants. Natural compounds such as chitosan (CHT) and phosphorus have been developed as alternatives to chemical pesticides to manage crop diseases in recent years. In the current study, potato leaves were foliar-sprayed with chitosan and phosphorus to assess their ability to induce PVY resistance. Compared to untreated plants, the findings demonstrated a significant decrease in disease severity and PVY accumulation in plants for which CHT and P were applied. Every treatment includes significantly increased growth parameters, chlorophyll content, photosynthetic characteristics, osmoprotectants (glycine betaine, proline, and soluble sugar), non-enzymatic antioxidants (glutathione, phenols, and ascorbic acid), enzymatic antioxidants (peroxidase, superoxide dismutase, lipoxygenase, glutathione reductase, catalase, β-1,3 glucanase, and ascorbate peroxidase), phytohormones (gibberellic acid, indole acetic acid, jasmonic acid, and salicylic acid), and mineral content (phosphorus, nitrogen, and potassium), compared to infected plants. However, compared to PVY infection values, CHT and P treatments showed a significant decrease in malondialdehyde, DPPH, H2O2, O2, OH, and abscisic acid levels. In addition, increased expression levels of some regulatory defense genes, including superoxide dismutase (SOD), ascorbic acid peroxidase (APX), relative pathogenesis-related 1 basic (PR-1b), and relative phenylalanine ammonia-lyase (PAL), were found in all treated plants, compared to PVY-infected plants. Conclusion: Phosphorus is the most effective treatment for alleviating virus infections.

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.

This study presents a comprehensive evaluation of the effects of multi-channel spiral twist extrusion (MCSTE) processing on the mechanical properties and structural evolution of AA5083. The structural evolution and texture developed were mapped by electron backscatter diffraction (EBSD) for three successive passes and compared with an as-annealed plate. An evaluation of the hardness and tensile properties was presented and correlated with the EBSD findings. The displayed EBSD results revealed that grain refinement was strongly associated with the presence of a high density of low-angle grain boundaries (LAGBs) after one pass, which developed into fine grains of less than 20 μm and high-angle grain boundaries (HAGBs) after three MCSTE passes. The three pass processing led to a 65% reduction in grain size. This reduction in grain size was coupled with an enhancement in the hardness and tensile properties. Additionally, the crystallographic texture study represented a slightly random texture due to the presence of intermetallic particles in AA5083. This study demonstrates the efficacy of MCSTE as a grain refinement tool.