Measurement constrained emission estimates of alkylated polycyclic aromatic hydrocarbons in the Canadian Athabasca oil sands region.

Alkylated polycyclic aromatic hydrocarbons (APAH) are important contaminants of crude oil production and exhibit similar toxicity to their parent compounds. This study developed an emission inventory of APAH in a major oil sands development region of Alberta, Canada, and validated the inventory with ambient concentration measurements through dispersion modeling. The initial estimate of regional total annual emissions of 21 APAH species was 362 tonnes/year in the last decade, of which 309 and 53 tonnes/year were in particle-bound and gas-phase APAH, respectively. Fugitive dust from oil sands mining activities is the primary source of particle-bound APAH, emitting 274 tonnes/year. Other major sources of APAH include point sources (31), tailings ponds (21), anthropogenic fuel consumption from mine fleet (17), and local transportation (13). The group of species with highest emissions was C1-C4 alkylnaphthalenes (53%), followed by C1-C4 alkylphenanthrenes/anthracenes (19%), C1-C4 fluorenes (13%), and C1-C4 fluoranthenes/pyrenes and C1-C4 benz[a]anthracenes/chrysene/triphenylenes (7% each). CALPUFF dispersion modeling was performed using the APAH emissions as model input. The model-predicted annual average ambient APAH concentrations at 17 monitoring sites were 1%-52% (19% on average) lower than the measurements. Inverse dispersion modeling was then applied to adjust APAH emissions higher by 19% for each of the 21 APAH species, which resulted in a revised estimate of APAH emissions to 431 tonnes/year. With the revised emissions as model input, model bias in the predicted ambient concentration was reduced from -19% to -8%. The model results showed the highest concentrations of APAH were near tailings ponds and open mining faces and downwind areas, with total APAH concentrations being higher than 50 ng/m3.

Dynamical behavior of water wave phenomena for the 3D fractional WBBM equations using rational sine-Gordon expansion method.

To examine the dynamical behavior of travelling wave solutions of the water wave phenomenon for the family of 3D fractional Wazwaz-Benjamin-Bona-Mahony (WBBM) equations, this work employs the rational Sine-Gordon expansion (RSGE) approach based on the conformable fractional derivative. The method generalizes the well-known sine-Gordon expansion using the sine-Gordon equation as an auxiliary equation. In contrast to the conventional sine-Gordon expansion method, it takes a more general approach, a rational function rather than a polynomial one of the solutions of the auxiliary equation. The method described above is used to generate various solutions of the WBBM equations for hyperbolic functions, including soliton, singular soliton, multiple-soliton, kink, cusp, lump-kink, kink double-soliton, etc. The RSGE method contributes to our understanding of nonlinear phenomena, provides exact solutions to nonlinear equations, aids in studying solitons, advances mathematical techniques, and finds applications in various scientific and engineering disciplines. The answers are graphically shown in three-dimensional (3D) surface plots and contour plots using the MATLAB program. The resolutions of the equation, which have appropriate parameters, exhibit the absolute wave configurations in all screens. Furthermore, it can be inferred that the physical characteristics of the discovered solutions and their features may aid in our understanding of the propagation of shallow water waves in nonlinear dynamics.

Rational Sine-Gordon expansion method to analyze the dynamical behavior of the time-fractional phi-four and (2 + 1) dimensional CBS equations.

This study uses the rational Sine-Gordon expansion (RSGE) method to investigate the dynamical behavior of traveling wave solutions of the water wave phenomena for the time-fractional phi-four equation and the (2 + 1) dimensional Calogero-Bogoyavlanskil schilf (CBS) equation based on the conformable derivative. The technique uses the sine-Gordon equation as an auxiliary equation to generalize the well-known sine-Gordon expansion. It adopts a more broad strategy, a rational function rather than a polynomial one, of the solutions of the auxiliary equation, in contrast to the traditional sine-Gordon expansion technique. Several explanations for hyperbolic functions may be produced using the previously stated approach. The approach mentioned above is employed to provide diverse solutions of the time-fractional phi-four equation and the (2 + 1) dimensional CBS equations involving hyperbolic functions, such as soliton, single soliton, multiple-soliton, kink, cusp, lump-kink, kink double-soliton, and others. The RSGE approach enhances our comprehension of nonlinear processes, offers precise solutions to nonlinear equations, facilitates the investigation of solitons, propels the development of mathematical tools, and is applicable in many scientific and technical fields. The solutions are graphically shown in three-dimensional (3D) surface and contour plots using MATLAB software. All screens display the absolute wave configurations in the resolutions of the equation with the proper parameters. Furthermore, it can be deduced that the physical properties of the found solutions and their characteristics may help us comprehend how shallow water waves move in nonlinear dynamics.

Silicon Carbide-Based DNA Sensing Technologies.

DNA sensing is critical in various applications such as the early diagnosis of diseases and the investigation of forensic evidence, food processing, agriculture, environmental protection, etc. As a wide-bandgap semiconductor with excellent chemical, physical, electrical, and biocompatible properties, silicon carbide (SiC) is a promising material for DNA sensors. In recent years, a variety of SiC-based DNA-sensing technologies have been reported, such as nanoparticles and quantum dots, nanowires, nanopillars, and nanowire-based field-effect-transistors, etc. This article aims to provide a review of SiC-based DNA sensing technologies, their functions, and testing results.

Contributions of the oil sands sources to the ambient concentrations and deposition of particulate elements in the Canadian Athabasca oil sands region.

In this study, model sensitivity tests were conducted to investigate the relative contributions between emission sources of oil sands (OS) activities and other sources to the ambient concentrations and deposition of 29 particulate elements in the Athabasca oil sands region (AOSR) of Canada. Element emission sources from a recently developed emission database were grouped into three source sectors for elements in PM2.5 (OS-Industrial, OS-Dust, and Non-OS) and two source sectors for elements in PM2.5-10 (OS-All and Non-OS). The OS-Dust and OS-Industrial sectors (combined as one sector for PM2.5-10; OS-All) included element sources linked to dust and other industrial activities from the OS activities, respectively, whereas the Non-OS sector included remaining sources in the region, unrelated to the OS activities. The OS-Industrial, OS-Dust, and Non-OS emissions (tonnes/year) of all elements in PM2.5 were 326, 1430, and 562, respectively. The OS-All and Non-OS emissions (tonnes/year) of all elements in PM2.5-10 were 5890 and 2900, respectively. The element concentrations were simulated by the CALPUFF dispersion model. The sum of the domain averaged annual mean concentrations of all elements in PM2.5 and PM2.5-10 from all sources were 57.3 ng/m3 and 30.4 ng/m3, respectively. Except for Co (PM2.5 and PM2.5-10), Sb (PM2.5-10), and Sn (PM2.5-10), major proportions (≥ 59 %) of the ambient concentrations of the individual elements were linked to the OS source sector. Overall, the OS sector was responsible for 78 % and 68 % of the sum of the mean ambient concentrations of all elements in PM2.5 and PM2.5-10, respectively, which are close to the corresponding emission contributions (76 % and 67 %, respectively). Likewise, the bulk proportion (∼74 %) of the sum of the total atmospheric deposition of all elements was also associated with the OS sources. Carcinogenic and non-carcinogenic risks associated with inhalation exposure to airborne elements were below the recommended threshold risk levels.

A calcium peroxide incorporated oxygen releasing chitosan-PVA patch for Diabetic wound healing.

Impaired wound healing is a major healthcare problem in patients with diabetes often resulting in gangrene, microbial infection and amputation of affected limb. The delay or absence in healing process arises from several abnormalities, among them chronic hypoxia is a major concern due to its associated issues such as lack of collagen deposition, epithelization, fibroplasia, angiogenesis, and resistance to infections at the wound site. To address hypoxia, delivery of oxygen at the wound site through oxygen releasing agents have been proven to be effective therapeutics. Several oxygen releasing nanoparticles such as Sodium Percarbonate (SPC), Calcium Peroxide (CPO), Hydrogen Peroxide, Magnesium Peroxide (MPO) have been investigated in wound healing application. However, the uncontrolled/burst release of these nanotherapeutic agents and its accompanied cytotoxicity pose a barrier in expediting the healing process. In this study, a Chitosan-Polyvinyl alcohol (CS-PVA) based hydrogel containing oxygen releasing nanoparticle, calcium peroxide (CPO) was constructed to provide a slow and sustained delivery of oxygen for at least 5 days. In-vitro cell culture studies with this material using fibroblast and endothelial cell line exhibited improved biocompatibility, cell viability and enhanced proliferation in comparison with the control group. Additionally, cell migration study using scratch assay method showed superior cell migration ability of our proposed materials. Furthermore, In vivo study using diabetic rat model showed accelerated wound closure rate compared to untreated control wounds.

Atmospheric deposition mapping of particulate elements in the Canadian Athabasca oil sands region.

This study used a deposition modeling framework to generate gridded dry, wet, and total (dry + wet) deposition fluxes of 27 particulate elements over the Canadian Athabasca oil sands region and its surrounding areas for the years 2016-2017. The framework employed the element concentrations from the CALPUFF dispersion model outputs that were bias-corrected against measured concentrations, modeled dry deposition velocities, precipitation analysis data, and literature values of element-specific fine mode fractions and scavenging ratios by rain and snow. The annual total deposition (mg/m2/year) of all elements (EM) across the domain ranged from 4.49 to 5450 and the mean and median deposition were 60.9 and 31.0, respectively. Total EM deposition decreased rapidly within a short distance from the oil sands mining area. Annual mean total deposition (mg/m2/year) of EM was 717 in Zone 1 (within 30 km from a reference point, representing the center of the oil sands mining area), 115 in Zone 2 (30-100 km from the reference point), and 35.4 in Zone 3 (beyond 100 km from the reference point). The deposition of individual elements was primarily governed by their respective concentrations and among all elements the annual mean total deposition (µg/m2/year) over the domain varied five orders of magnitude ranging from 0.758 (Ag) to 20,000 (Si). Annual mean dry and wet deposition (mg/m2/year) of EM over the domain were 15.7 and 45.2, respectively. Aside from S, which has relatively lower precipitation scavenging efficiencies, wet deposition was the dominant deposition type in the region contributing from 51% (Pb) to 86% (Ca) of the respective total deposition. Total EM deposition over the domain in the warm season (66.2 mg/m2/year) was slightly higher than that in the cold season (55.6 mg/m2/year). Deposition of individual elements in Zone 1 were generally lower than their deposition at other sites across North America.

In-Plane Si Microneedles: Fabrication, Characterization, Modeling and Applications.

Microneedles are getting more and more attention in research and commercialization since their advancement in the 1990s due to the advantages over traditional hypodermic needles such as minimum invasiveness, low material and fabrication cost, and precise needle geometry control, etc. The design and fabrication of microneedles depend on various factors such as the type of materials used, fabrication planes and techniques, needle structures, etc. In the past years, in-plane and out-of-plane microneedle technologies made by silicon (Si), polymer, metal, and other materials have been developed for numerous biomedical applications including drug delivery, sample collections, medical diagnostics, and bio-sensing. Among these microneedle technologies, in-plane Si microneedles excel by the inherent properties of Si such as mechanical strength, wear resistance, biocompatibility, and structural advantages of in-plane configuration such as a wide range of length, readiness of integration with other supporting components, and complementary metal-oxide-semiconductor (CMOS) compatible fabrication. This article aims to provide a review of in-plane Si microneedles with a focus on fabrication techniques, theoretical and numerical analysis, experimental characterization of structural and fluidic behaviors, major applications, potential challenges, and future prospects.

Cysteine focused covalent inhibitors against the main protease of SARS-CoV-2.

In viral replication and transcription, the main protease (Mpro) of SARS-CoV-2 plays an important role and appears to be a vital target for drug design. In Mpro, there is a Cys-His catalytic dyad, and ligands that interact with the Cys145 assumed to be an effective approach to inhibit the Mpro. In this study, approximately 1400 cysteine-focused ligands were screened to identify the best candidates that can act as potent inhibitors against Mpro. Our results show that the selected ligands strongly interact with the key Cys145 and His41 residues. Covalent docking was performed for the selected candidates containing the acrylonitrile group, which can form a covalent bond with Cys145. All atoms molecular dynamics (MD) simulation was performed on the selected four inhibitors including L1, L2, L3 and L4 to validate the docking interactions. Our results were also compared with a control ligand, α-ketoamide (11r). Principal component analysis on structural and energy data obtained from the MD trajectories shows that L1, L3, L4 and α-ketoamide (11r) have structural similarity with the apo-form of the Mpro. Quantitative structure-activity relationship method was employed for pattern recognition of the best ligands, which discloses that ligands containing acrylonitrile and amide warheads can show better performance. ADMET analysis displays that our selected candidates appear to be safer inhibitors. Our combined studies suggest that the best cysteine focused ligands can help to design an effective lead drug for COVID-19 treatment. Communicated by Ramaswamy H. Sarma.

Identification of potent inhibitors against transmembrane serine protease 2 for developing therapeutics against SARS-CoV-2.

In viral binding and entry, the Spike(S) protein of SARS-CoV-2 uses transmembrane serine protease 2 (TMPRSS2) for priming to cleavage themselves. In this study, we have screened 'drug-like' 7476 ligands and found that over thirty ligands can effectively inhibit the TMPRSS-2 better than the control ligand. Finally, the three best drug agents L1, L2, and L6 were selected according to their average binding affinities and fitting score. These ligands interact with Asp435, Cys437, Ser436, Trp461, and Cys465 amino acid residues. The three best candidates and a reported drug Nafamostat mesylate (NAM) were selected to run 250 ns molecular dynamics (MD) simulations. Various properties of ligand-protein interactions obtained from MD simulation such as bonds, angle, dihedral, planarity, coulomb, and van der Waals (VdW) were used for principal component analysis (PCA) calculation. PCA discloses the evidence of the structural similarities to the corresponding complexes of L1, L2, and L6 with the complex of TMPRSS2(TM) and Nafamostat mesylate (TM-NAM). Moreover, Quantitative structure-activity relationship (QSAR) pattern recognition was generated using PCA for the investigation of structural similarities among the selected ligands. Multiple Linear Regression (MLR) model was built to predict the binding energy compared to the binding energy obtained from molecular docking. The MLR regression model reveals an accuracy of 80% for the prediction of the binding energy of ligands. ADMET analysis demonstrates that these drug agents are appeared to be safer inhibitors. These three ligands can be used as potential inhibitors against the TMPRSS2.Communicated by Ramaswamy H. Sarma.

Characterization and source apportionment of airborne particulate elements in the Athabasca oil sands region.

The oil sands industries in Alberta, Canada are potential sources of particulate-bound elements in the region. This study explored the ambient concentrations and size distributions, and conducted source apportionment of 48 particulate elements, based on samples collected in 2016-2017 at four air monitoring sites in the Athabasca oil sands region: Fort McKay (AMS1), Buffalo Viewpoint (AMS4), Wapasu Creek (AMS17), and Stoney Mountain (AMS18). Element concentrations in fine and coarse particulate matter (PM2.5 and PM2.5-10 respectively) at the four sites were generally lower than their typical concentrations at other urban and industrial sites in North America. Among all elements, S was the most abundant in PM2.5 with mean concentrations ranging from 189 ng/m3 (AMS18) to 284 ng/m3 (AMS1). Of the trace, toxic elements in PM2.5, Zn was the most abundant with mean concentrations ranging from 3.43 ng/m3 (AMS18) to 5.37 ng/m3 (AMS4). Positive Matrix Factorization (PMF) modeling of the element concentrations in PM2.5 was used for source apportionment for Zone1 (including AMS 1, 4, and 17, situated closer to industrial activities) and for Zone2 (including AMS18, a background site). The sources of elements for Zone1, included crustal dust, bitumen processing, haul road dust, and biomass burning that explained ~33%, ~43%, ~15%, and ~9% of the total resolved elemental mass, respectively. The sources of elements for Zone2, included Pb-rich source, biomass burning, fugitive oil sands, crustal dust, and bitumen processing explaining ~8%, ~7%, ~3%, ~22%, and ~60% of the total resolved elemental mass, respectively. Elemental mass concentrations of the bitumen processing source factor at Zone2 was two-thirds of that in Zone1. Overall, mass proportions of the bitumen processing source factor at all four sites were significant, suggesting that the oil sands industries played a key role in ambient element concentration levels in the region.

Solitary and periodic wave solutions to the family of new 3D fractional WBBM equations in mathematical physics.

For the newly implemented 3D fractional Wazwaz-Benjamin-Bona-Mahony (WBBM) equation family, the present study explores the exact singular, solitary, and periodic singular wave solutions via the ( G ' / G 2 )-expansion process. In the sense of conformable derivatives, the equations considered are translated into ordinary differential equations. In spite with many trigonometric, complex hyperbolic, and rational functions, some fresh exact singular, solitary, and periodic wave solutions to the deliberated equations in fractional systems are attained by the implementation of the ( G ' / G 2 )-expansion technique through the computational software Mathematica. The unique solutions derived by the process defined are articulated with the arrangement of the functions tanh, sech; tan, sec; coth, cosech, and cot, cosec. With three-dimensional (3D), two dimensional (2D) and contour graphics, some of the latest solutions created have been envisaged, selecting appropriate arbitrary constraints to illustrate their physical representation. The outcomes were obtained to determine the power of the completed technique to calculate the exact solutions of the equations of the WBBM that can be used to apply the nonlinear water model in the ocean and coastal engineering. All the solutions given have been certified by replacing their corresponding equations with the computational software Mathematica.

Dynamical behaviour of travelling wave solutions to the conformable time-fractional modified Liouville and mRLW equations in water wave mechanics.

In this current study, we described a modified extended tanh-function (mETF) method to find the new and efficient exact travelling and solitary wave solutions to the modified Liouville equation and modified regularized long wave (mRLW) equation in water wave mechanics. Travelling wave transformation decreases the leading equation to traditional ordinary differential equations (ODEs). The standardized balance technique provides the instruction of the portended polynomial related result stimulated from the mETF method. The substitution of this result follows the preceding step. Balancing the coefficients of the like powers of the portended solution leads to a system of algebraic equations (SAE). The solution of that SAE for coefficients provides the essential connection between the coefficients and the parameters to build the exact solution. Here the acquired solutions are hyperbolic, rational, and trigonometric function solutions. Our mentioned method is straightforward, succinct, efficient, and powerful and can be emphasized to establish the new exact solutions of different types of nonlinear conformable fractional equations in engineering and further nonlinear treatments.

Imaging cancer cells with nanostructures: Prospects of nanotechnology driven non-invasive cancer diagnosis.

The application of nanostructured materials in medicine is a rapidly evolving area of research that includes both the diagnosis and treatment of various diseases. Metals, metal oxides and carbon-based nanomaterials have shown much promise in medical technological advancements due to their tunable physical, chemical and biological properties. The nanoscale properties, especially the size, shape, surface chemistry and stability makes them highly desirable for diagnosing and treating various diseases, including cancers. Major applications of nanomaterials in cancer diagnosis include in vivo bioimaging and molecular marker detection, mainly as image contrast agents using modalities such as radio, magnetic resonance, and ultrasound imaging. When a suitable targeting ligand is attached on the nanomaterial surface, it can help pinpoint the disease site during imaging. The application of nanostructured materials in cancer diagnosis can help in the early detection, treatment and patient follow-up . This review aims to gather and present the information regarding the application of nanotechnology in cancer diagnosis. We also discuss the challenges and prospects regarding the application of nanomaterials as cancer diagnostic tools.

A molecular modeling approach to identify effective antiviral phytochemicals against the main protease of SARS-CoV-2.

The main protease of SARS-CoV-2 is one of the important targets to design and develop antiviral drugs. In this study, we have selected 40 antiviral phytochemicals to find out the best candidates which can act as potent inhibitors against the main protease. Molecular docking is performed using AutoDock Vina and GOLD suite to determine the binding affinities and interactions between the phytochemicals and the main protease. The selected candidates strongly interact with the key Cys145 and His41 residues. To validate the docking interactions, 100 ns molecular dynamics (MD) simulations on the five top-ranked inhibitors including hypericin, cyanidin 3-glucoside, baicalin, glabridin, and α-ketoamide-11r are performed. Principal component analysis (PCA) on the MD simulation discloses that baicalin, cyanidin 3-glucoside, and α-ketoamide-11r have structural similarity with the apo-form of the main protease. These findings are also strongly supported by root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), and solvent accessible surface area (SASA) investigations. PCA is also used to find out the quantitative structure-activity relationship (QSAR) for pattern recognition of the best ligands. Multiple linear regression (MLR) of QSAR reveals the R2 value of 0.842 for the training set and 0.753 for the test set. Our proposed MLR model can predict the favorable binding energy compared with the binding energy detected from molecular docking. ADMET analysis demonstrates that these candidates appear to be safer inhibitors. Our comprehensive computational and statistical analysis show that these selected phytochemicals can be used as potential inhibitors against the SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Investigating the binding affinity, interaction, and structure-activity-relationship of 76 prescription antiviral drugs targeting RdRp and Mpro of SARS-CoV-2.

SARS-CoV-2 virus outbreak poses a major threat to humans worldwide due to its highly contagious nature. In this study, molecular docking, molecular dynamics, and structure-activity relationship are employed to assess the binding affinity and interaction of 76 prescription drugs against RNA dependent RNA polymerase (RdRp) and Main Protease (Mpro) of SARS-CoV-2. The RNA-dependent RNA polymerase is a vital enzyme of coronavirus replication/transcription complex whereas the main protease acts on the proteolysis of replicase polyproteins. Among 76 prescription antiviral drugs, four drugs (Raltegravir, Simeprevir, Cobicistat, and Daclatasvir) that are previously used for human immunodeficiency virus (HIV), hepatitis C virus (HCV), Ebola, and Marburg virus show higher binding energy and strong interaction with active sites of the receptor proteins. To explore the dynamic nature of the interaction, 100 ns molecular dynamics (MD) simulation is performed on the selected protein-drug complexes and apo-protein. Binding free energy of the selected drugs is performed by MM/PBSA. Besides docking and dynamics, partial least square (PLS) regression method is applied for the quantitative structure activity relationship to generate and predict the binding energy for drugs. PLS regression satisfactorily predicts the binding energy of the effective antiviral drugs compared to binding energy achieved from molecular docking with a precision of 85%. This study highly recommends researchers to screen these potential drugs in vitro and in vivo against SARS-CoV-2 for further validation of utility.

Virtual screening, molecular dynamics and structure-activity relationship studies to identify potent approved drugs for Covid-19 treatment.

Computer-aided drug screening by molecular docking, molecular dynamics (MD) and structural-activity relationship (SAR) can offer an efficient approach to identify promising drug repurposing candidates for COVID-19 treatment. In this study, computational screening is performed by molecular docking of 1615 Food and Drug Administration (FDA) approved drugs against the main protease (Mpro) of SARS-CoV-2. Several promising approved drugs, including Simeprevir, Ergotamine, Bromocriptine and Tadalafil, stand out as the best candidates based on their binding energy, fitting score and noncovalent interactions at the binding sites of the receptor. All selected drugs interact with the key active site residues, including His41 and Cys145. Various noncovalent interactions including hydrogen bonding, hydrophobic interactions, pi-sulfur and pi-pi interactions appear to be dominant in drug-Mpro complexes. MD simulations are applied for the most promising drugs. Structural stability and compactness are observed for the drug-Mpro complexes. The protein shows low flexibility in both apo and holo form during MD simulations. The MM/PBSA binding free energies are also measured for the selected drugs. For pattern recognition, structural similarity and binding energy prediction, multiple linear regression (MLR) models are used for the quantitative structural-activity relationship. The binding energy predicted by MLR model shows an 82% accuracy with the binding energy determined by molecular docking. Our details results can facilitate rational drug design targeting the SARS-CoV-2 main protease.Communicated by Ramaswamy H. Sarma.

Dynamical analysis of long-wave phenomena for the nonlinear conformable space-time fractional (2+1)-dimensional AKNS equation in water wave mechanics.

The main intension of this paper is to extract new and further general analytical wave solutions to the (2 + 1)-dimensional fractional Ablowitz-Kaup-Newell-Segur (AKNS) equation in the sense of conformable derivative by implementing the advanced exp ( - ϕ ( ξ ) ) -expansion method. This method is a particular invention of the generalized exp ( - ϕ ( ξ ) ) -expansion method. By the virtue of the advanced exp ( - ϕ ( ξ ) ) -expansion method, a series of kink, singular kink, soliton, combined soliton, and periodic wave solutions are constructed to our preferred space time-fractional (2 + 1)- dimensional AKNS equation. An extensive class of new exact traveling wave solutions are transpired in terms of, hyperbolic, trigonometric, and rational functions. To express the underlying propagated features, some attained solutions are exhibited by making their three-dimensional (3D), two-dimensional (2D) combined, and 2D line plot with the help of computational packages MATLAB. All plots are given to show the proper wave features through the founded solutions to the studied equation with particular preferring of the selected parameters. Moreover, it may conclude that the attained solutions and their physical features might be helpful to comprehend the water wave propagation in water wave mechanics.