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The exploration of efficient and reliable data analysis tools is a constant endurance in statistical community. Stratification bring enhancement in estimates by capturing the heterogeneity in the data. This work introduces a novel data-driven machine learning algorithm aiming stratification problem, formally based on subjective approach. The development of efficient variance estimators of finite population and the exploration of using various transformation to auxiliary variable on precision enhancement of variance estimators is also under consideration in this research. We also examine the improvement in efficiency enhancement using various transformations and build superiority space for each of these transformations. These superiority regions offer significant understandings of the precise and accurate conditions favoring one transformation over another. We carefully investigate the theoretical basis of the proposed estimators, defining the superiority space for each transformation and obtained biases and mean square errors up to the first-order approximation. We conduct simulation studies and empirical analysis using COVID-19 data and artificial data to assess and validate our methods thoroughly. The results clearly show that the proposed variance estimatoElbow-Methodrs perform significantly better than the competing estimators. Further, the proposed estimator can be seamlessly adapted in other sampling designs as well as in efficient parameter estimation.

An updated checklist of Uzbekistan aphids (Hemiptera: Sternorrhyncha: Aphidomorpha) is presented based on literature records with the latest taxonomic and nomenclatural changes. This comprehensive checklist of aphids is the first checklist for Uzbekistan and represents a total of 301 species and 31 subspecies, within 103 genera, 63 subgenuses, belonging to seven subfamilies, of the Aphididae family, recorded from 1910 to 2023 in Uzbekistan. According to the association of the identified aphids with their host plants, it was noted that 301 species of aphids live and feed on plants belonging to 64 families of plants. Of these, the largest number of species was found in plants belonging to the families of Asteraceae (71), Rosaceae (58) and Salicaceae (33).

Abstract Clean water is a necessity for all life to survive and flourish. However, natural waters are being continuously contaminated due to the release of waste streams in water. Hence, it is important to remove pollutants from wastewater to fulfill human needs. Conventional treatment methods are neither efficient nor economical for wastewaters that especially contain refractory toxic pollutants. This requires novel techniques like Advanced oxidation processes (AOPs), that may successfully degrade persistent micropollutants more efficiently. In this study, an azo dye Acid Red 1 was removed by three AOPs, namely Photocatalytic oxidation, Ozonation and Photocatalytic Ozonation, by employing heterogenous catalysts. TiO2 was used as photocatalyst, whereas Fe-Zeolite has been further added as Ozonation catalyst. The study revealed that photocatalysis degraded only 28% Acid red dye after 15 min, whereas for ozonation, the degradation percentage was 95% in same time. In combined photocatalytic ozonation process using TiO2, 95% degradation was achieved in just 9 min and treatment time further reduced to 5 min when Fe-zeolite was added. Optimization studies for initial concentration, UV intensity and catalyst loading were performed. Finally, rate constants and Electrical Energy per Order (EEO) values were determined for all AOPs, and mechanism was proposed.

This article aims to develop two novel mean estimators of finite populations under ranked set sampling. The suggested estimators result in a high-efficiency gain due to their efficient formulation by taking the linear combination of classical estimators using optimization constants. We also discuss the theoretical properties and derive bias and mean squared error up to the first order of approximation. To theoretically validate our proposed estimators, we derive the conditions under which our estimators prevail over the competing estimators. The findings suggest that when ranked set sampling is implemented effectively, it saves cost and improves precision, serving as a potent instrument for improved decision-making, specifically in engineering applications, such as environmental monitoring, resource management, and quality control. An empirical and simulation study has been conducted using real and synthetic data to validate our methodology empirically. The suggested estimators offer a significant contribution to survey sampling in estimating mean under ranked set sampling. Further, the proposed estimator can be seamlessly adapted in other sampling designs such as simple random sampling, stratified random sampling, cluster sampling, etc, as well as in estimating other parameters such as variance, skewness, coefficient of correlation, etc. in various domains.

In this study, the Yamada-Ota model is used to look for an analysis of irreversibility when there is nonsymmetric magnetohydrodynamic flow inside a nanoliquid made of carbon nanotubes (CNTs) across an unsteady three-dimensional stretching surface. In this investigation, both single- and multi-walled carbon nanotubes (SWCNTs and MWCNTs, respectively) are considered, as they are both suspended in a water solution. Anisotropic slip conditions, nonlinear thermal radiation, and an induced magnetic field are all accounted for in the model. The PDEs are changed into a group of nonlinear Equations using the non-similarity transformations and then solved by using the BVP4c program in MATLAB. The effects of important parameters like magnetic field strength, unsteadiness, nanoparticle volume fraction, slip conditions and nonlinear thermal radiation are also looked at. Increasing the nanoparticle volume percentage results in a greater velocity field for SWCNTs than for MWCNTs. The profile of entropy production exhibits an upward trend in relation to the parameters Φ, M , Br, Rd and θw , however, it has a downward trend in relation to the parameter α. The Bejan number profile shows an upward trend in the concentration of α, while showing a decline in the cases of Φ, M , Br, Rd and θw.

Nanofluid flow over a rotating disk has several applications in engineering and industrial sectors, such as in cooling systems, heat exchangers, aerospace systems, and renewable energy systems. In the current analysis, the couple stress nanofluid flow over a rotating disk is reported. The nanofluid consists of ethylene glycol and titanium aluminum vanadium (Ti6Al4V) nanoparticles (NPs). The unique properties of Ti6Al4V-NPs, such as biocompatibility, high strength, high boiling point (1604–1660 °C), and high corrosion resistance, make them more suitable for automobile industries. For the heat and mass transfer, the Cattaneo–Christov concept is introduced. In addition, the fluid flow is subjected to magnetic field, Hall current, thermal radiation, and Joule heating. The modeled equations are restructured into the dimensionless system of ordinary differential equations (ODEs) by using the similarity approach. The system of ODEs is further numerically solved through a MATLAB package based on the finite difference method (BVP4c). The results are presented in figures. It has been observed that the energy and curves of the nanofluid decline with the influence of thermal and solutal time relaxation parameters, respectively.

Thermal analysis in nanolubricants is a topic of interest. The nanolubricants are uniform mixture of nanoparticles and oil. These fluids extensively use for thermal applications and friction reduction. Hence, the key objectives of this work to analyze the dynamics of ZnO-SAE50 through a curved surface. The traditional problem modified using novel effects of non-uniform thermal source, variable thermal conductivity, non-linear thermal radiations and Newtonian heating in the presence of convective condition. Further, enhanced properties of ZnO-SAE50 used to achieve the desired results. The physical results for the problem obtained through numerical approach (RK scheme coupled with shooting method). It is examined that the velocity enhances by increasing the curvature of the surface (K=5.0,10.0,15.0,20.0) while stronger Hartmann effects (M=0.1,0.5,0.9,1.3) and concentration of ZnO reduce the motion over the surface. The momentum boundary layer declines for S>0 as compared to S

Worldwide fragmentation of production stages enable the developed and developing economies' firms to gain from ‘foreign outsourcing collaboration (FOC)’. Literature indicates that the majority of studies on foreign outsourcing are based on the perspective of developed countries. Nevertheless, a meager amount of literature is available from the perspective of developing countries. This study bridges the research gap by employing field survey based data collected from 217 textile and apparel firms located in Faisalabad-Pakistan, for the fiscal year 2022. This study mainly examines the impact of: (i) investment in information technology (IT) on FOC in the production process; (ii) strategic integration of outsourcing policies on FOC in the production process; and (iii) strategic policy firms' adopted on FOC in the production process. SmartPLS 4 has been utilized to estimate the partial least square structural equation model. The results signify that investment and utilization of IT induce a higher level of firm performance by enhancing firms' efficiency and improving product quality. Moreover, FOC in production processes increases product quality whereas investment in IT attracts FOC in production processes. The study concludes by offering specific policy recommendations.

The current study investigates the steady two-dimensional (2D) hybrid nanofluid (Hnf) flow over an inclined permeable plate/cylinder. The Hnf flow has been examined in the context of mixed convection, heterogeneous/homogenous chemical reaction, and permeable medium. The Hnf is prepared by dispersing silver (Ag), and iron ferrite (Fe 3 O 4 ) nanoparticles (NPs) in water. The current research is motivated by the increasing demand for highly efficient cooling devices in a variety of industries and energy-associated operations. The energy transmission and fluid flow are mathematically specified by using a coupled nonlinear system of partial differential equations (PDEs). The system of PDEs is simplified into a dimensionless form of ODEs, which are then further numerically treated with the MATLAB package based on the finite difference method (bvp4c). It has been noticed that the permeability component develops the heat transfer curve while decreasing the flow rate of the fluid. The impact of heat source/sink increases the energy profile. Moreover, the plate surface demonstrates the dominant behavior of energy transportation than a cylinder with the variance of Ag-Fe 3 O 4 -NPs.

Significance of nanofluids cannot be overlooked because of their enhanced characteristics which play vibrant role in their thermal performance. These make them more effective for practical applications. Addition of multiple types of nanoparticles potentially affect the thermal conductivity of base fluid which directly contribute in the heat transfer mechanism. Hence, the current work deals with the study of tetra nanofluid model including the influence of different parameters. The results obtained through numerical approach and examined that the fluid motion enhanced at variable saddle/nodal regions and reverse variations examined for higher λ values. The inclusion of surface convection Bi=0.1,0.2,0.3,0.4 particles concentration from 0.04 to 0.16, heat generation factor (Q1=0.5,1.0,1.5,2.0) and radiation effects (Rd=1.0,2.0,3.0,4.0) are observed reliable physical tools to enhance the heat performance of nanofluids which is advantageous from engineering as well as industrial point of view. Further, thermal boundary layer enlarges for Rd and reduced for Q1 and nanoparticles strength ϕi,i=1,2,3.

Abstract Textile wastewater is among the most polluted types of industrial waste. Wastewater treatment in the textile industry is notoriously difficult because of the use of complex chemicals and dyes in the textile production steps, and conventional methods are not enough to treat these. Textile wastewater, known for its high pollution levels, poses challenges for treatment due to complex chemicals and dyes. A comparative study was conducted on simple ozonation and catalytic ozonation (CO) using alum to degrade methylene blue (MB). The authors analyzed various factors like time, pH, catalyst loading and ozone dosages during the study. Results showed that catalytic activity in ozonation depends on pH and ozone flow. The maximum MB elimination was achieved at pH 6.6 and 200 V ozone flow. Scanning electron microscopy (SEM) was used to characterize the surface morphology of the catalyst, Fourier transform infrared spectroscopy (FTIR) was used to identify the important functional groups, and energy dispersive X-ray spectroscopy (EDS) was used to characterize the catalyst's elemental composition. Compared to simple ozonation, CO showed higher removal in the initial phase. Real textile wastewater analysis confirmed the effectiveness of alum catalysts in achieving significant removal of MB (87%) through this novel cost-efficient process. Graphical Abstract

The study focuses on a vertical Riga surface-induced mixed convective, unsteady stagnation point flow of Casson fluid. This flow exhibits nonlinearity due to thermal radiation, chemical processes, Brownian motion, thermophoresis, Maxwell slip velocity, and Smoluchowski slip temperature conditions. The study’s goal is to improve thermal efficiency. By using suitable similarity variables, the partial differential equations are transformed into ordinary differential equations. Subsequently, these equations are resolved using the bvp4c function in MATLAB. The numerical findings for concentration, shear stress, Nusselt number, Sherwood number, velocity, and temperature distribution are shown graphically. When the values of the Casson parameter increase, the velocity profile was also increased while the concentration and temperature profiles decreased. The unsteadiness parameter increase was followed by a rise in the skin friction and a decrease in the profiles of Nusselt number and Sherwood number. Profiles of skin friction, Nusselt number, and Sherwood number were raised with the increased values of the modified Hartmann number. Increasing parameter values of Brownian motion result in a decrease of the Nusselt number profile, while the Sherwood number profile increases. On the other hand, as the thermophoresis parameter increase, the profiles of the Nusselt number and Sherwood number decrease. This study will aid in the improvement of the understanding of fluid dynamics and nanotechnology and, eventually, the creation of more effective and sustainable engineering-based solutions. When we compared our results to those of other studies in the literature, we discovered that they were quite consistent.

In this study, biocrude was successfully produced by the hydrothermal liquefaction of municipal solid waste collected from the landfill site of Lahore, the capital of Punjab, Pakistan, boasting a population of 12 million and an annual waste collection of 10 million tons. The hydrothermal liquefaction process was performed at reaction parameters of 350 °C and 165 bars with 15 min of residence time. The solid waste was found to have 78 % dry matter, 22 % moisture contents, 22.2 % ash, 22.69 MJ/kg higher heating value, 52.062 % C, 8.007 % H, 0.764 % N, and 39.164 % O. Non-catalytic process only produced 10.57 % oil, however when using the catalytic process, the biocrude yield improved to 17.61 %, with 22.61 % energy recovery for biocrude and 12.14 % for solids, when using 2 g dose of K2CO3. The resultant biocrude has a 28.61 MJ/kg higher heating value, having 60.28 % C and 9.28 % H. In contrast, the aqueous phase generated had 4.43 pH, 71.5 g/L TOC, and 1.35 g/L Total Nitrogen. TGA indicated that biocrude contains approximately 80 % of volatile fractions of different fuels. The organic compounds having the six highest peak areas in GC-MS were Ethyl ether 25.74 %, 2-pentanone, 4-hydroxy-4-methyl 9.08 %, 2-propanone, 1,1-dimethoxy 5.62 %, Silane, dimethyl (docosyloxy) butoxy 5.08 %, 1-Hexanol, 2-ethyl 4.53 %, and. Phenol 4.07 %. This work makes the first-ever successful use of indigenous solid waste from a landfill dumping site in Lahore to successfully produce useful biocrude with aims of waste reduction and management, circular economy, and energy recovery.

This work’s main objective is to investigate the thermal behavior of a tetra-ferrite-based nanofluid model under four physical controls. The tetra-nanofluid contains Fe3O4, CoFe2O4, NiZnFe2O4, and MnZnFe2O4 tetra-nanoparticles over a porous surface using ethylene and water (50%–50%) as the base fluid. The fundamental constitutive models are reduced nonlinear ordinary differential equations using appropriate transformative functions. The resulting set of governing equations are found using the Runge–Kutta algorithm. The impacts of critical quantities on the heat transfer, shear factor, and Nusselt number are illustrated through graphs and numerical data. It is noticed that when the concentration of nanoparticles is from 0.1% to 0.6%, the thermal conductivity varies from 102.661% to 116.706% for nanofluid (NF), 108.893% to 140.384% for hybrid nanofluid, and 117.994% to 195.794% for tetra-nanofluid (Tet.NF), which played a crucial role in the temperature performance of the fluidic system. Furthermore, the velocity depreciated against ϕ1 = 1%, 2%, 3%, 4%, 5%, 6%, and 7%. The Forchheimer effects Fr = 1.0, 2.0, 3.0, 4.0, Q = 0.1, 0.4, 0.7, 1.0, and Rd = 0.1, 0.2, 0.3, 0.4 enhanced the temperature of all types of NFs, while the stretching parameter S = 0.01, 0.08, 0.15, 0.22 reduced it. The results would benefit the researchers about the prediction of the parametric ranges and nanoparticle concentration to acquire the heat transfer results for practical applications, particularly in applied thermal engineering.

The study of melting thermal process in ternary nanofluidic system (MoS2-SiO2-Au)/H2O near the point of separation is a fascinating research area. The potential applications of SPFs frequently occurs in analytical chemistry, life sciences, and in mechanical engineering etc. Therefore, the current attempt is made towards the development of new ternary SPFM by considering the thermal radiations, Joule heating, combined convection and magnetic field that act normally to the working domain. Further, using transformation functions and the ternary nanofluid characteristics, the new third order SPFM is developed and implemented RK as mathematical tool. It is examined that the particles movement enlarges for γ1=0.1,0.3,0.5,0.7 and γ2=0.1,0.2,0.3,0.4. The ternary nanofluids velocity increased slowly due to stronger internal viscous forces. Further, the temperature of ternary fluidic system (TFS) increased rapidly for assisting case and γ3=1.0,2.0,3.0,4.0 keeping the nanoparticles concentration 0.06. Moreover, thermal conductivity of nanofluid enhanced by increasing the amount of nanoparticles (MoS2-SiO2-Au) which directly influenced the model dynamics.

This article proposes and discusses a novel approach for generating trigonometric G-families using hybrid generalizers of distributions. The proposed generalizer is constructed by utilizing the tangent trigonometric function and distribution function of base model G(x). The newly proposed family of uni-variate continuous distributions is named the “Lomax Tangent Generalized Family of Distributions (LT-G)” and structural-mathematical-statistical properties are derived. Some special and sub-models of the proposed family are also presented.A Weibull-based model, ‘The Lomax Tangent Weibull (LT-W) Distribution,” is discussed and the plots of density (pdf) and hazard (hrf) functions are also explained. Model parameter estimates are estimated by employing the maximum likelihood estimation (MLE) procedure. The accuracy of the MLEs is evaluated through Monte Carlo simulation. Last but not least, to demonstrate the flexibility and potential of the proposed distribution, two actual hydrological and strength data sets are analyzed. The obtained results are compared with well-known, competitive, and related existing distributions.

In light of the exciting potential of nanofluids, this work presents a new mathematical model for enhancing heat transfer using tri-hybrid nanofluids. In this study, the influence of heat production/abstraction and mass suction on MHD stagnation point flow in a nonlinearly stretching/shrinking sheet of a tri-hybrid nanofluid based on water is investigated. Boundary conditions based on the Maxwell velocity slip and the Smoluchowski temperature are also considered. We shall model the flow-control equations based on our assumptions. An ordinary differential equation system may be constructed from nonlinear partial differential equations for which a similarity transformation does not provide an exact solution. In MATHEMATICA 10, the shooting with Runge-Kutta (RK-IV) technique will be used to solve the reduced equations analytically. There were charts and figures showing how different variables affected the speeds of motion, temperature, skin friction coefficient, and local heat transmission. The characteristics of volume fraction, mass suction, magnetic field, and stretching all contribute to the acceleration of nanoparticles. When the nanoparticle volume fraction and heat production parameters increase, the temperature profile improves, but the mass suction, magnetic, and stretching parameters decrease. Compared to ordinary fluid, the Nusselt number reveals an improvement of around 9.8% for nanofluid, 19.85% for hybrid nanofluid, and 44.04% for tri-hybrid nanofluid when the strength of S is raised from 2.0 to 2.4. The heat transfer rate of the tri-hybrid nanofluid is also superior to that of the hybrid nanofluid and the traditional nanofluid. Results from this study were compared to those already in the literature, and they were determined to be quite consistent. Many other fields might benefit from this study, including those dealing with extreme heat or cold, aerospace technology, medicine, metal coatings, and biosensors.

Due to advancements in telecommunications, towers need special attention in terms of the analysis and design under wind loads. The Telecommunications Industry Association (TIA) in 2005 released a standard “TIA-222-G” which has gained a widespread reference for the analysis and design of communication towers. In 2018, TIA released the latest standard TIA-222-H. The latest TIA-222-H standard has some additional features, e.g. limit states for analysis of mounting systems, enhanced climber safety requirements, construction-related loading, etc. To date, not many studies are available describing how much change in member axial forces occurs with the tower height while using the latest standard for analysis. This study’s main objective is to provide guidelines for wind load calculation on tower body, appurtenances, and other structures and compare the member axial forces induced by the wind loads on different tower heights (40, 60, and 80 m) as per TIA-222-G and TIA-222-H standards. The procedure presented in the paper about the design calculations of wind load is a useful guide for structural engineers involved in the analysis and design of communication towers. The analysis results showed that the member axial forces increased by 22% to 37%, which can assist the practitioner in more optimized design.

This study seeks to examine the impact of convective heat transfer, buoyancy ratios, hall current effect, nonlinear thermal radiation, Schmidt number, Prandtl number and mass flux condition on the temperature profiles, velocity profiles and concentration profiles. The research explores into mass and heat transfer characteristics of a stagnation point flow of a free convective triple diffusion with considerations for convective boundary constraints and nonlinear thermal radiation over a mobile vertical plate. To elucidate the aims and methodology, the study utilizes similarity transformation to convert the governing partial differential equations into a set of nonlinear ordinary differential equations. Numerical solutions are obtained employing a fourth-order Runge-Kutta shooting strategy. The findings, showcased through graphical representations, unravel the intricate interplay of parameters, shedding light on flow distribution, temperature, and velocity profiles. These quantitative results not only enhance our scientific understanding of fluid dynamics but also hold practical implications across diverse sectors. Notably, the acquired insights are poised to benefit fields such as environmental science and engineering, where optimizing heat and mass transfer processes is paramount. This research thus contributes valuable perspectives to both the theoretical framework of fluid dynamics and its real-world applications.

The significance of advanced hybrid type nanofluids cannot be avoided because of their multiple heat transport applications. These are not only in applied thermal, mechanical, chemical engineering but also use as coolant for nuclear reactors, paint, medical sciences and manufacturing of various home products. The dynamical study of fluid characteristics inside a channel with slowly expanding/contracting walls is a fascinating research topic. Therefore, the key aims of this research are to formulate a hybrid nanoliquid model using graphene and Fe3O4 nanoparticles. Further, physical effects of practical interest like Joule heating, magnetic field are merged in the model. After that, numerical tool used to solve it and then demonstrated the results via graphical aid. The results shown that the when the nanoparticles amount taken from 0.01 % to 0.06 % then the density changes from 1.00042 to 1.00252 (nanofluid), 1.00067 to 1.00277 (hybrid) and 1.00025 to 1.0015 (nano), 1.00125 to 1.0025 (hybrid). In similar way, thermal conductance boosted from 1.00025 to 1.0015 (nano) and 1.00085 to 1.0021 (hybrid). For elongating walls (α=2.0,4.0,6.0,8.0), the velocity increased and examined maximum at the center. The absorber walls (S=0.1,0.2,0.3,0.4) highly controlled the fluid motion and the particles at η=−1.0 and η=1.0 accelerates inconsequentially. The high energy dissipation, thermal radiations (Rd=0.1,0.3,0.5,0.7) and Re1=0.1,0.2,0.3,0.4 augmented the temperature mechanism in nano, hybrid and simple fluids.

In this study, the mixed convective stagnation-point flow of a Al2O3-Cu/H2O hybrid nanofluid towards a stretched disc with a convective boundary and zero mass flux condition is described with mass suction and viscous dissipation effects. The process is accomplished by using thermophoretic and Brownian motion physical phenomena. After performing a similarity transformation on the PDEs in order to convert them into an ODE system, the bvp4c solver is then employed in order to carry out a numerical solution. In the study that was described above, the flow, heat, and mass transfer characteristics were investigated with the assistance of the Buongiorno model and the Devi and Devi model. The following characteristics were brought up as points of contention: ϕ1,ϕ2,λ,S,Nt,Nb,Le,Ec,Bi and B. There is a very good consonance among the existing and antecedent results in undeniable cases, as well as a connection error of approximately 0%. The velocity and temperature profiles upsurge with the increment of the nanoparticle volume fraction and mixed convection parameter, while the velocity increases with the addition of the suction parameters. As a result of this study, we are able to estimate the flow and thermal behavior of Al2O3-Cu/H2O when the physical parameters are embedded.

The purpose of this research was to examine the impact of NP shape on the entropy production of a water-alumina nanofluid over a permeable MHD stretching sheet at quadratic velocities with viscous dissipation and joule heating. The hot fluid is water-alumina nanofluid, which consists of four different NP shapes (brick, platelet, blade, and oblate spheroid), and the cool fluid is water itself. As a result of its exceptional ability to enhance heat transmission, Al2O3-H2O nanofluid is used extensively in industrial production. The governing PDEs are changed into a nonlinear differential system of coupled ODEs by a series of similarity transformations. The code, in MATLAB, is an effective version of the Runge-Kutta technique for obtaining numerical solutions. In the region behind a stretching sheet, the wall shear stress increases by almost 6.3% for increases in the volume fraction of nanoparticles from 0% to 2% and by 12.6% for increases from 0% to 4%. When the magnetic effect accounts for roughly 5 percent of the boundary layer flow, there is an approximately 16.4 percent increase in the rate of convective heat transfer. The frictional force and thermal entropy produced by nanofluids with blade-, brick-, and Os-shaped NPs was lower than that produced by nanofluids with platelet-shaped NPs. On the cold fluid side, the nanofluid with Os-shaped NPs develops thermal entropy at a faster rate than those with brick-, blade-, cylinder-, and platelet-shaped NPs.

Background: According to the WHO, antimicrobial resistance (AMR) occurs when bacteria, viruses, fungi, and parasites change over time and no longer respond to medicines making infections harder to treat and increasing the risk of disease spread, severe illness, and death and is a global issue and measures to halt this is the need of the hour. Aims and Objectives: This study aims at identifying awareness as well as knowledge, attitude, perception, and practice regarding AMR and antibiotic use among medical undergraduate students, so to get insight and take appropriate actions to enhance their knowledge that will help in reducing AMR as they are the future prescribers. Materials and Methods: A descriptive cross-sectional study was conducted among 483 undergraduate medical students enrolled in government medical college, Haldwani. A pretested, semi structured questionnaire was designed to collect data from participants through Google forms regarding sociodemographic profile, and behavior of the participants regarding antibiotic use which comprises: Attitude, perceptions, and practice. Results: Majority of study participants have heard about AMR before (97%) of which most of them got information about antibiotic resistance by web/internet (35%). Majority of study participants were aware (>90%) of phenomenon of antibiotic resistance, 98.9% of them were correctly able to identify Amoxicillin and Penicillin as antibiotics, most of them had correct knowledge about role of antibiotics. Majority (83.6%) of participants take antibiotic only after the prescription of doctor, 78.9% of them reported use of antibiotics in the last year. Conclusion: A fair good amount of awareness, knowledge, attitude, perception, and practice regarding AMR and its use was found among study participants. Still, there is scope of improvement in it that can be addressed through giving more emphasis on this in undergraduate teaching curriculum.

An interesting study is reported on establishing secret mining activity resulting in severe ground subsidence which occurred and was corrected later in a village called Dhery Saydan located near the world famous salt range region of Pakistan and is located on a hill top with about 2000 inhabitants. After reviewing many cases of similar nature and on basis of geophysical techniques like resistivity survey, it was established that secret mining activity had taken place resulting in massive cracking of dwellings coupled with sinking of water table. Thereafter a suitable construction methodology was applied to correct the huge structural defects and make the dwellings functional.

The magnetohydrodynamic (MHD) rotating flow that occurs across a stretching surface has numerous practical applications in a variety of domains. These fields include astronomy, engineering, the material sciences, and space exploration. The combined examination of magnetohydrodynamics rotating flow across a stretching surface, taking into consideration fluctuating viscosity and nanoparticle aggregation, has significant ramifications across several different domains. It is essential for both the growth of technology and the attainment of deeper insights into the complicated fluid dynamics to maintain research in this field. Given the aforementioned motivation, the principal aim of this study is to examine the effects of variable viscosity on the bidirectional rotating magnetohydrodynamic flow over a stretching surface. Aggregation effects on nanoparticles are used in the analysis. Titania (TiO2) is taken nanoparticle and ethylene glycol as base fluid. The nonlinear ordinary differential equations and the boundary conditions that correspond to them can be transformed into a dimensionless form by using a technique called similarity transformation. To get a numerical solution to the transformed equation, the Runge-Kutta 4th order (RK-4) method is utilized, and this is done in conjunction with the shooting method. The impact of various leading variables on dimensionless velocity, the coefficients of temperature, skin friction and local Nusselt number are graphically represented. Velocity profiles in both direction increases with increasing values of φ. The Nusselt number increases with increasing values of the radiation and temperature ratio parameters. When a 1 % volume fraction of nanoparticles is introduced, the Nusselt number exhibits a 0.174 % increase for the aggregation model compared to the regular fluid in the absence of radiation effects. When the aggregation model is used with a 1 % volume fraction of nanoparticles, the skin friction increases by 0.1153 % in the x direction and by 0.1165 % in the y direction compared to the regular fluid. Tables show the variation in Nusselt numbers, as well as a comparison of the effects of nanoparticle's aggregation model without and with radiation. Moreover, the numerical results obtained were compared with previously published data, demonstrating a satisfactory agreement. We firmly believe that this finding will have extensive implications for engineering and various industries.

Periodic changes in the environmental conditions affect significantly on the biosynthesis of bioactive compounds and the therapeutic potential in medicinal plants. Although Berberis lycium is being extensively used against various ailments, specifically infectious diseases, impact of seasonal variations on its polyphenolic contents and antibacterial activities has rarely been explored yet. Consequently, present study was focused on the determination of phenolics and flavonoids content and antibacterial activities in the root and stem bark of B. lycium harvested throughout the year from same location (Abbottabad) using standard analytical approaches. Relatively, stem bark had high concentration of total phenolics than root bark, but in the case of total flavonoids there was no significant difference. In root bark, the highest concentration of TPC was in the month of December (373.5±0.58 mg GAE/100 g DW), while stem bark exhibited highest concentration of TPC (476.1±13.7 mg GAE/100 g DW) in the month of January. In root bark, TFC ranged from 32.00±7.62 to 124.5±5.58 mg QE/100 g DW with highest concentration in April. Whereas, in stem bark, TFC varied from 19.51±4.94 to 135.50±7.11 mg QE/100 g DW, with highest concentration in the month of April. Likewise, in January, November and December inhibition potential was maximum against Escherichia coli and Staphylococcus aureus both in root and stem bark samples. Although, significant associations were observed between total phenolics and antibacterial activities. However total phenolics, total flavonoids, and antibacterial activities depicted negative correlations with growing conditions viz. temperature, rain fall and humidity. Our findings confirm the impact of seasonal variations on the phytochemical composition and bioactive potential in medicinal plants. Specifically, to get maximum health benefits from B. lycium, winter season could be more appropriate in the Himalayan region.

Many stakeholders including students, teachers, and educational institutions, benefit from accurately predicting student performance and facilitating data-driven policies. In this field, providing users with accurate and understandable predictions is challenging, but equally important. The goals of this study are multifaceted: to identify students at-risk; to identify differences in assessment across different environments; methods for assessing students; and to determine the relationship between teacher employment status and student achievement. This study performs an empirical comparison of the performance and efficiency of ensemble classification methods based on bagging, boosting, stacking, and voting for successful predictions. An ensemble model is developed and validated using double, triple, and quadruple combinations of classification algorithms using Naive Bayes, J48 decision trees, Adaboost, logistics, and multilayer perceptron. This study uses primary quantitative data from the learning management system of a university in Pakistan to analyze the performance of these models. The boosted tree detection method outperforms bagged trees when the standard deviation is higher and the data size is large, while stacking is best for smaller datasets. Based on behavioral analysis results of students, academic advice can be given for selected case studies. These will help educational administrators and policymakers working in education to introduce new policies and curricula accordingly.

Recent advances in the digital gaming industry have provided impressive demonstrations of highly skilful artificial intelligence agents capable of performing complex intelligent behaviours. Additionally, there is a significant increase in demand for intelligent agents that can imitate video game characters and human players to increase the perceived value of engagement, entertainment, and satisfaction. The believability of an artificial agent’s behaviour is usually measured only by its ability in a specific task. Recent research has shown that ability alone is not enough to identify human-like behaviour. In this work, we propose a case-based reasoning (CBR) approach to develop human-like agents using human gameplay traces to reduce model-based programming effort. The proposed framework builds on the demonstrated case storage, retrieval and solution methods by emphasizing the impact of seven different similarity measures. The goal of this framework is to allow agents to learn from a small number of demonstrations of a given task and immediately generalize to new scenarios of the same task without task-specific development. The performance of the proposed method is evaluated using instrumental measures of accuracy and similarity with multiple loss functions, e.g. by comparing traces left by agents and players. The study also developed an automated process to generate a corpus for a simulation case study of the Pac-Man game to validate our proposed model. We provide empirical evidence that CBR systems recognize human player behaviour more accurately than trained models, with an average accuracy of 75%, and are easy to deploy. The believability of play styles between human players and AI agents was measured using two automated methods to validate the results. We show that the high p-values produced by these two methods confirm the believability of our trained agents.

Over the last several decades, many algebraic generalized families and classes of statistical distributions have been developed. This research aims to construct a new cotangent exponentiated generalized and generator of distributions with support on the real line. After that, two novel families of distributions incorporating the cotangent function are proposed: one called the cotangent exponentiated generalized (CE-G) family, and the other called the logistic cotangent exponentiated generalized (LCE-G) family. A comprehensive analysis of the mathematical and structural properties of the recently suggested G-family and a Burr-based novel model (LCEB) is presented here. The maximum likelihood method estimates model parameters and evaluates model performance in Monte Carlo simulation studies. These tasks are carried out using the maximum likelihood technique. The statistical analysis on the survival and waiting times data sets are carried out, and the outcomes confirm the competence, superiority, and utility of the suggested generator, G-family, and novel distribution compared to similar and competing Burr-based models already well-known.

Abstract Introduction Ullrich congenital muscular dystrophy (UCMD) is a severe form of inherited muscle weakness at birth. Recent genetic studies discovered that different gene mutations are responsible for UCMD clinical manifestation. Case report In this study, we carried out whole exome sequencing (WES) to recognize probable gene defects in an Iranian boy with UCMD. We found a novel disease-causing COL6α1 gene mutation (c.2551_2562del; p.Phe851_Arg854del), located in exon35 (NM_001848.3), causing a deletion mutation that has eliminated 12 bp. The WES-identified variant that was confirmed by Sanger sequencing for the patient and his consanguineous parents. Here, we report the clinical manifestations of 4-year-old Iranian patient who presented with muscle weakness since birth and proved compound homozygous mutation of the COL6A1 gene. Conclusion Our findings established that this detected COL6α1 mutation is the pathogenic variant for UCMD. This is the first genetic study indicating that c.2551_2562 mutation in homozygous state in COL6α1 gene is responsible for the UCMD phenotype.

Virtual globes render large-scale real-world earth’s surface in real-time for geographic information visualization. Modern GPUs have introduced hardware tessellation features for high-performance rendering. Patch-based terrain rendering using hardware tessellation introduces cracks and swimming artifacts during navigation. Hardware tessellation-based terrain rendering methods limit the tessellation factors to power-of-two and render patches with discrete-level-of-detail (DLOD). We present a novel method for adaptive terrain rendering using tessellation codes. In the proposed method, we present novel memory-efficient bit-field-based tessellation codes to encode patch Level-of-detail (LOD). The encoding scheme enabled patch rendering with Continuous-level-of-detail (CLOD) on tessellation hardware. The view-dependent simplification algorithm simplifies and encodes the patch’s Level-of-detail (LOD) in tessellation codes. The proposed method, based on tessellation codes, tessellates patches as uniformly spaced vertices grid. A novel relocation algorithm, based on tessellation codes, relocates uniformly spaced vertices to construct an encoded simplified vertices grid to avoid boundary cracks and swimming artifacts. The tessellation codes consumed 28 kilobytes of memory for a patch size of 65. The proposed method rendered 2.5 million triangles with a frame rate of 570 frames-per second for an ultra-HD display. The proposed method achieved a high simplification and rendering rate with low computational and memory usage as compared to state-of-the-art methods.

The thermal performance of nanofluids, which include a base fluid and three kinds of suspended nanosized particles, is unparalleled. In this work, we analyzed the impact of many parameters on coolant applications, including MHD stagnation point flow, ternary hybrid nanofluid, viscous dissipation, variable viscosity, thermal stratification, and velocity slip conditions. Researchers synthesized ternary hybrid nanoparticles by combining Al2O3), (Cu), (TiO2) and then investigated their behavior in the presence of a symmetrically stretched disc in H2O. Because of its implications for heat transmission, the study of flow across a stretched disc is crucial to the investigation of momentum and thermal boundary layers. Numerous sectors and areas of technology will greatly benefit from this study. Similarity transformation is used to convert the PDEs into an ODE system, which can then be numerically solved using the shooting technique and the RKF scheme. The acquired results show remarkable consistency with earlier findings in certain circumstances, with an estimated relative error of 0%. The temperature profile drops as the value of the magnetic parameter rises, whereas the velocity rises as a result of the rise in magnetic parameters. Nusselt number improvements of around 8.4% for nanofluids, 16.8% for hybrid nanofluids, and 38.05% for ternary hybrid nanofluids are seen when the strength of the parameter S is raised from 2.0 to 2.4 compared to regular fluids. For an accurate prediction of how Al2O3-Cu-TiO2/ H2O will flow and how it will heat up, physical factors must be included in the analysis.

The transfer of heat is a phenomenon that is significant in a variety of contexts due to the different ways in which it may be utilized in industrial settings. To increase the rate at which heat is transferred, carbon nanotubes (CNTs), which can either be single-wall or multi-walled, are suspended in base fluids, and the resulting mixture is referred to as a “nanofluid. This study looks at how heat transfers through nanofluids that are suspended in carbon nanotubes with different lengths and radii over a stretching surface. It also looks at how changing viscosity and joule heating affect motion. Water is taken as base fluid. This study looks at both carbon nanotubes with one wall and those with more than one. The flow is governed by a series of partial differential equations, which, to control the flow, are transformed into a series of nonlinear ordinary differential equations. Similarity transformation is used to convert the obtained nonlinear ordinary differential equations and accompanying boundary conditions into a form that is dimensionless. To numerically solve the transformed equation, RK-4 with shooting method is used. Graphs and in-depth discussions are used to look at how velocity and temperature profiles are affected by the leading variables. The expression for skin friction and local Nusselt number are written down and graphs show how these two numbers change for different parameter values. The temperature profile goes down when the viscosity parameter goes down, but the velocity profile goes up. When the magnetic parameter goes up, the velocity profile f′(η), goes down, but the velocity profile g(η) and temperature θ(η) both go up at the same time. The rate of heat transfer increases with the addition of φ and S. When the suction parameter (S = 2.1) with 1% of φ is used, it is reported that rate of heat transfer increases by 1.135% for Single walled and 1.275% for Multi Walled carbon nanotubes. To determine whether or not the proposed numerical model is legitimate, a comparison is made between the current results and those that have previously been published.

Abstract Using a thermally stratified water-based nanofluid and a permeable stretching sheet as a simulation environment, this research examines the impact of nanoparticle aggregation on MHD mixed convective stagnation point flow. Nanoparticle aggregation is studied using two modified models: the Krieger–Dougherty and the Maxwell–Bruggeman. The present problem's governing equations were transformed into a solvable mathematical model utilizing legitimate similarity transformations, and numerical solutions were then achieved using shooting with Runge–Kutta Fehlberg (RKF) technique in Mathematica. Equilibrium point flow toward permeable stretching surface is important for the extrusion process because it produces required heat and mass transfer patterns and identifies and clarifies fragmented flow phenomena using diagrams. Nanoparticle volume fraction was shown to have an impact on the solutions' existence range, as well. Alumina and copper nanofluids have better heat transfer properties than regular fluids. The skin friction coefficients and Nusselt number, velocity, temperature profiles for many values of the different parameters were obtained. In addition, the solutions were shown in graphs and tables, and they were explained in detail. A comparison of the current study's results with previous results for a specific instance is undertaken to verify the findings, and excellent agreement between them is observed.

The assessment of in situ permeability of rock mass is challenging for large-scale projects such as reservoirs created by dams, where water tightness issues are of prime importance. The in situ permeability is strongly related to the frequency and distribution of discontinuities in the rock mass and quantified by rock quality designation (RQD). This paper analyzes the data of hydraulic conductivity and discontinuities sampled at different depths during the borehole investigations in the limestone and sandstone formations for the construction of hydraulic structures in Oman. Cores recovered from boreholes provide RQD data, and in situ Lugeon tests elucidate the permeability. A modern technique of multivariate adaptive regression splines (MARS) assisted in correlating permeability and RQD along with the depth. In situ permeability shows a declining trend with increasing RQD, and the depth of investigation is within 50 m. This type of relationship can be developed based on detailed initial investigations at the site where the hydraulic conductivity of discontinuous rocks is required to be delineated. The relationship can approximate the permeability by only measuring the RQD in later investigations on the same site, thus saving the time and cost of the site investigations. The applicability of the relationship developed in this study to another location requires a lithological similarity of the rock mass that can be verified through preliminary investigation at the site.

It is still not quite apparent how suspended nanoparticles improve heat transmission. Multiple investigations have demonstrated that the aggregation of nanoparticles is a critical step in improving the thermal conductivity of nanofluids. However, the thermal conductivity of the nanofluid would be greatly affected by the fractal dimension of the nanoparticle aggregation. The purpose of this research is to learn how nanoparticle aggregation, joule heating, and a heat source affect the behavior of an ethylene glycol-based nanofluid as it flows over a permeable, heated, stretched vertical Riga plate and through a porous medium. Numerical solutions to the present mathematical model were obtained using Mathematica's Runge-Kutta (RK-IV) with shooting technique. In the stagnation point flow next to a permeable, heated, extending Riga plate, heat transfer processes and interrupted flow phenomena are defined and illustrated by diagrams in the proposed mixed convection, joule heating, and suction variables along a boundary surface. Data visualizations showed how different variables affected temperature and velocity distributions, skin friction coefficient, and the local Nusselt number. The rates of heat transmission and skin friction increased when the values of the suction parameters were raised. The temperature profile and the Nusselt number both rose because of the heat source setting. The increase in skin friction caused by changing the nanoparticle volume fraction from φ=0.0 to φ=0.01 for the without aggregation model was about 7.2% for the case of opposing flow area (λ=−1.0) and 7.5% for the case of aiding flow region (λ=1.0). With the aggregation model, the heat transfer rate decreases by approximately 3.6% for cases with opposing flow regions (λ=−1.0) and 3.7% for cases with assisting flow regions (λ=1.0), depending on the nanoparticle volume fraction and ranging from φ=0.0 to φ=0.01, respectively. Recent findings were validated by comparing them to previously published findings for the same setting. There was substantial agreement between the two sets finding.

It is well established that adding a certain number of nanoparticles to a nanofluid improves its thermal conductivity. The cause of this remarkable development is as of yet unidentified. Therefore, knowing the kinematics of nanoparticle aggregation is essential for determining the correct thermal impact of nanoscale particles. There are several potential technical and industrial uses for nanomaterials. From the perspective of these many application aspects, this paper examines the Al2O3-H2O nanofluid flow caused by a permeable stretching surface with the influence of an inclined Lorentz force and viscous dissipation. Entropy generation on nanofluid stagnation point flow with the influences of heat generation/absorption, nanoparticles aggregation with suction are also discussed in the current context. With and without nanoparticle aggregation, measurements of velocity, temperature, and entropy production are made. By applying the necessary transformations for heat and motion, ordinary differential equations may be derived from partial differential equations in certain circumstances. For the solution of ordinary differential equations, the Bvp4c technique is used. The effects of several dimensionless limitations on velocity, temperature, and entropy production, skin friction, and Nusselt number profiles are investigated, both when nanoparticle aggregation is present and when it is not. It is concluded that the velocity field is boosted for the velocity ratio and inclined Lorentz force parameters, while the temperature and entropy generation rise for the nanoparticle volume fraction, angle of inclination and Eckert number parameters. The rate of heat transmission improves as a result of the addition of ϕ and ε respectively. When the suction parameter of ε=0.5 is used for the aggregation model, it is claimed that there is an increase of roughly 13.2478% in the heat transfer rate. Temperature and entropy generation profiles for all pertinent parameters is higher for nanoparticles that have aggregated together as opposed to nanoparticles that have not aggregated together. This research was compared with previously published results to validate the findings, and great agreement was found.

The goal of this study was to determine the effect that NP shape has on the entropy produced by Al2O3−H2O nanofluid across a permeable MHD stretching sheet under the conditions of quadratic velocity, thermal radiation, and viscous dissipation. H2O is the cold fluid, while Al2O3−H2O nanofluid, which includes five various NP forms (oblate spheroid, platelet, blade, brick, and cylinder), is the hot fluid. Nanofluid containing Al2O3−H2O sees widespread use in industrial production because of its remarkable capacity to boost heat transfer. Via a sequence of similarity transformations, the controlling PDEs are converted into a nonlinear differential system of linked ODEs. An efficient implementation of the Runge-Kutta method for getting numerical solutions may be found in the code, which is written in MATLAB. As the φ grows from 0% to 2% or from 0% to 4%, the wall shear stress rises by roughly 6.3% and 12.6%, respectively, in the area that is behind the stretched sheet. Including the magnetic effect in the boundary layer flow at a rate of around 5%, the rate of convective heat transfer increases by about 16.4%. In comparison to nanofluids containing brick-, blade-, cylinder-, and platelet-shaped NPs, the Os-shaped NP nanofluid experiences a greater increase in thermal entropy on the cold fluid side.

Significance of study: Nanofluids with aggregation effects mediated by nanoparticles, like geothermal panels and crossflow heat exchangers, ignite new industrial interests. Polymer and conversion processes have transport phenomena in the stagnation zone that must be continuously improved to raise the process quality standard. Aim of study: Hence, the current computational study examines a TiO2−C2H6O2 nanofluid's unsteady stagnation-point flow performance via a shrinking horizontal cylinder. In addition, the effects of a magnetic field, joule-heating viscous dissipation, nanoparticles aggregation and mass suction on the boundary layer flow are reflected. Method: ology: The RK-IV with shooting method is applied to resolve the simplified mathematical model numerically in computing software MATHEMATICA. In certain circumstances, comparing the current and prior findings indicates good agreement with a relative error of around 0%. Findings: The implementation of a heat transfer operation may be improved by increasing suction settings. Unsteadiness, nanoparticle volume fraction, magnetic, curvature, and Eckert number (implies the operating Joule heating and viscous dissipation) all influence heat transfer rate. The velocity and temperature profiles both increase as the unsteadiness, magnetic field, and nanoparticle volume fraction parameters increase, whereas the curvature and suction parameters show the opposite behavior. When the values of the suction parameters were changed from 2.0 to 2.5 with φ = 0.01, the heat transfer rates rose by 4.751%. A comparison shows that the model with aggregation has a better velocity profile, while the model without aggregation has a better temperature profile.

The modern trend in distribution theory is to propose hybrid generators and generalized families using existing algebraic generators along with some trigonometric functions to offer unique, more flexible, more efficient, and highly productive G-distributions to deal with new data sets emerging in different fields of applied research. This article aims to originate an odd sine generator of distributions and construct a new G-family called "The Odd Lomax Trigonometric Generalized Family of Distributions". The new densities, useful functions, and significant characteristics are thoroughly determined. Several specific models are also presented, along with graphical analysis and detailed description. A new distribution, "The Lomax cosecant Weibull" (LocscW), is studied in detail. The versatility, robustness, and competency of the LocscW model are confirmed by applications on hydrological and survival data sets. The skewness and kurtosis present in this model are explained using modern graphical methods, while the estimation and statistical inference are explored using many estimation approaches.

To aid in the prevention of reaction explosions, chemical engineers and scientists must analyze the Arrhenius kinetics and activation energies of chemical reactions involving binary chemical mixtures. Nanofluids with an Arrhenius kinetic are crucial for a broad variety of uses in the industrial sector, involving the manufacture of chemicals, thermoelectric sciences, biomedical devices, polymer extrusion, and the enhancement of thermal systems via technology. The goal of this study is to determine how the presence of thermal radiation influences heat and mass transfer during free convective unsteady stagnation point flow across extending/shrinking vertical Riga plate in the presence of a binary chemical reaction where the activation energy of the reaction is known in advance. For the purpose of obtaining numerical solutions to the mathematical model of the present issue the Runge-Kutta (RK-IV) with shooting technique in Mathematica was used. Heat and mass transfer processes, as well as interrupted flow phenomena, are characterized and explained by diagrams in the suggested suction variables along boundary surface in the stagnation point flow approaching a permeable stretching/shrinking Riga Plate. Graphs illustrated the effects of many other factors on temperature, velocity, concentration, Sherwood and Nusselt number as well as skin friction in detail. Velocity profile increased with Z,λ and S and decreased with ε. Increasing values of ε,λ and S decline the temperature profile. The concentration profile boosts up with Z,α and slow down with ε,Sc,β,δ and n1 parameters. Skin friction profile increased with Z and S and decreased with ε. Nusselt number profile increased with S,Z, ε and radiation. Sherwood number profile shows upsurges with ε,Z,α,Sc,β,S and n1 whereas slow down with δ. So that the verdicts could be confirmed, a study was done to compare the most recent research with the results that had already been published for a certain case. The outcomes demonstrated strong concordance between the two sets of results.

Significance of study: Typical liquids aren't great for engineering because of their low heat conductivity. To enhance heat transfer capabilities in industries as diverse as computers, pharmaceuticals, and molten metals, researchers and scientists have developed nanofluids, which are composed of nanoparticles distributed in a base fluid. Aim of study: Mathematical modeling of micropolar Cu−H2O nanofluid driven by a deformable sheet in the stagnation area with nanoparticle aggregation, thermal radiation, and the mass suction action has been investigated in this paper. In this case, copper (Cu) nanoparticles make up the nanofluid. Method: ology: We have used suitable transformations to arrive at a system of nonlinear ODEs, which we then solve numerically in MATHEMATICA using Runge-Kutta methods of the fourth order coupled with shooting approaches. Findings: Tables and graphs are used to examine the effects of immersed flow and display profiles of physical parameters of interest. This includes velocities, temperatures, skin friction, and Nusselt numbers. The average heat transfer rate increased to 17.725% as the volume percentage of copper nanoparticles in micropolar nanofluid increased from 0.0 to 0.01. Additionally, the results showed that the local Nusselt number of the micropolar nanofluid increased along with an increase in the unsteady and radiation parameters. However, its value is reduced in an undeniable fashion if a material parameter is present. The impact of radiation on the aggregation of nanoparticles is compared and contrasted with the effects of a non-radiative scenario, and the resulting fluctuations in Nusselt numbers are provided in tables. When the results of this study were compared to data that had already been published about some cases, a lot of agreement was found.

The stretched surface's convective heat transfer capability can be improved by using nanoparticles. There is a significant role of the Prandtl number in determining the thermal and momentum stretching layer surfaces. It is proposed in this study that an effective Prandtl number model be used to explore the two-dimensional oblique stagnation point flow of γAl2O3−H2O and γAl2O3−C2H6O2 nanofluids moving over a convective stretching surface. The fluid in question is subjected to a thorough investigation. It is necessary to apply non-linear ordinary differential equations in order to connect the controlling partial differential equations with the boundary conditions. To solve these equations, an efficient and reliable numerical technique is used. Shooting Method with Runge Kutta-IV in Mathematica software. Visual representations of normal and tangential velocity and temperature as well as streamlines as a function of many physical parameters are shown. The results show that as the volume fraction of nanoparticles increases, the fluid flow f(y), h(y) and velocity f′(y), h′(y) all increase, whereas the flow f(y) and velocity f′(y) both increase against the stretching ratio parameter, while the flow h(y) and velocity h′(y) both decrease. When the volume percentage of nanoparticles and the Biot number are both increased, the temperature rises. However, when the stretching ratio parameter is increased, the temperature falls. Physical attributes like the local skin friction coefficient and the heat flow may be characterized in many ways. A nanofluid comprised of γAl2O3−C2H6O2 outperformed a γAl2O3−H2O nanofluid in terms of heat transfer rate. The source of zero skin friction may be observed to move to the left or right depending on the balance of obliqueness and straining motion at point xs. The computed numerical results of the current research correspond well with those accessible in the literature for the limiting scenario.

The research of single and multi-wall carbon nanotubes (SWCNTs/MWCNTs) mixed in sodium alginate-based nanofluid with MHD stagnation-point flow on a convective heated stretching disk with viscous dissipation and suction effects is being done with the intention of decoding the heat and mass transmission mechanism. It is possible to transform PDEs that govern the boundary layer into ODEs. MATLAB’s Bvp5c is used to numerically solve the revised equations. The Yamada-Ota model and the Buongiorno model are used in this work to scrutinize the flow, heat, and mass transfer parameters. The following parameters were brought up for discussion: volume fraction nanoparticle, magnetic parameter, suction, Brownian motion, thermophoresis, Lewis number, Eckert number, Biot number, stretching, and thermophoresis. This study found that nanofluid (SWCNT/sodium alginate) has a superior flow, heat, and mass transfer rate than nanofluid (MWCNT/sodium alginate). Graphical representations of the effects of various factors are shown, and a comparison of current and prior findings is given in a table. A comparison of current and previous findings reveals a 0% relative inaccuracy. The velocity ratio parameter has solutions that look close to the separation value. The performance of heat and mass transfer operations may be improved by increasing suction parameters. Increases in Brownian motion Nb and suction decrease the temperature profile, whereas increases in velocity ratio and magnetic parameters increase velocity. This research is critical for estimating flow, temperature, and concentration behavior for CNTs with incorporated physical properties.

Heat flow may be improved using a new form of nanofluid known as ternary hybrid nanofluid. Magnetic field, mass suction, and heat source effects on the stagnation area of ( Cu − F e 3 O 4 − Si O 2 / polymer ) ternary hybrid nanofluid toward convectively heated stretching/shrinking cylinder with cylindrical shape nanoparticles are studied in this work. There will be an equation modeled under the given assumptions. It is feasible, with the help of similarity transformation, to convert nonlinear partial differential equations that are not quite solvable into ordinary differential equations that can be resolved numerically. The prevailing role of heat transfer and the features of movement of ternary hybrid nanofluids have been found to be significantly affected by the combination of Runge–Kutta-IV and the shotting technique in Mathematica. Many variables, including suction, Reynold number, nanoparticle volume fraction, magnetic field, Biot number, heat source, and stretching/shrinking influenced temperature, velocity, skin friction, and the local heat transfer rate, as shown in the graphs in the study. When magnetic field, suction, and Reynold number are present velocity increases, but inverse is true for nanoparticle volume fraction and stretching/shrinking parameter. The greatest influence on the surface is shown by the ternary hybrid nanofluid. Additionally, the heat transfer rate of the ternary hybrid nanofluid is faster than that of the hybrid and regular nanofluids.