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Recently a considerable amount of attention has been directed towards the technological advancements in the study of arterial stenosis. The deposition of adipose tissues and saturated fatty acids and the abnormal growth of flesh, narrows the arteries, leading to restricted blood flow. This causes cardiovascular diseases like atherosclerosis, atherogenesis, atheroma, etc. Considering this the present research paper develops a Casson fluid model to investigate magnetohydrodynamic peristaltic transport of the passage of blood through slightly stenosed arteries due to the influence of copper (Cu) and alumina (Al2O3) nanoparticles. The problem is formulated using appropriate mathematical models employing non-dimensional parameters and stenosis approximations. The study has its applications in the field of medicine. The outcome of this work is that it helps to handle many heart conditions. The findings of this investigation may have benefits in various academic fields, including pharmaceuticals and other industries. In addition, they are remarkably beneficial in the treatment of numerous cardiovascular diseases.

Universities and colleges play a pivotal role in the pursuit of a future that is sustainable through their pedagogical efforts and the execution of state-of-the-art research endeavors aimed at mitigating the effects of climate change. Higher Education Institutions (HEIs) serve as crucial catalysts in advancing sustainable development. HEIs are increasingly embracing precise measures to reduce their carbon footprint (CF) while also educating students on global sustainability. These nano-methods provide a quantitative framework for assessing a campus's sustainability efforts in line with Green Campus (GC) initiatives to lower carbon emissions align with GC goals. This study employs K-means clustering to analyze the integration of green and low-carbon principles in higher education political and ideological studies. Its goal is to identify patterns, assess teaching effectiveness, and improve sustainability education, aligning with Green Campus initiatives to enhance institutional contributions to sustainable growth through informed pedagogical strategies. Input data includes curriculum content, teaching methods, student engagement, and institutional goals related to sustainability. Seeking to improve sustainability education align with Green Campus initiatives, higher education can strategically enhance their contributions to long-term sustainability and growth through effective pedagogical approaches. Cluster 3 has the lowest WCSS value of 1200, indicating tighter cohesion and less variability within this cluster compared to Cluster 1 (1500) and Cluster 2 (1800). Cluster 3 stands out with the highest silhouette score of 0.7, suggesting well-defined and distinct clusters, while Cluster 2 has the lowest score of 0.4, indicating some overlap or ambiguity in data points. Cluster 1 has the lowest Davies-Bouldin Index of 0.4, implying better separation between clusters compared to Cluster 2 (0.6) and Cluster 3 (0.5). Cluster 3 is well-defined and cohesive, showing strong integration of green practices. Cluster 1 displays good separation and cohesion, while Cluster 2 requires refinement due to potential overlap in sustainability integration.

Online supply chain management (OSCM) is the smart way to deal with the vast amounts of data that come in from customers in a disorganized system to meet the quantities, volumes, and types of customer packages during both delivery and pick-up phases using a new design of vehicle boxes managed by IoT and to track their requests based on scheduling requests and sorting them to make a Hamiltonian route that guarantees the shortest travel distance. The OSCM framework consists of two sequential phases. 1st phase has four recruitment stages. The 1st stage discusses exploration resources (the relationship between the client and the vehicle) using IoT to receive customers' requests (Heijunka growth radius), then moves to exploration maturity to build a one-way Hamiltonian growth route direction. The 1st stage is based on tackling a Heijunka matrix fed through deep learning to classify the matrix into many conditional clusters according to customers' request forecasting and make the prediction value, which is the stop condition of cluster radius through next three stages. This study finds that XGboost outperforms Ada-boost by 14.352 % in the prediction stage. A heuristic rule based on NWBS enhances the FP-Growth algorithm over ECLAT by 7.648 % in the classification stage. Phase II is interested in reducing load and unloading activity time. This problem describes needing more than a different service at the same point (i.e., chaotic and unstable interaction leads to unstable delivery). Therefore, the online scheduling and tracking of the logistic routing using the IoT that Smart Lean Heijunka supports will enhance the SCM, increasing the visited points by 31.2 % and improving the profit by 41 %.

The current study addresses the flow of steady electrically conducting hybrid nanofluid (HNF) across an impermeable slender stretchable sheet. The flow distribution takes into consideration the effects of variable magnetic fields, heat production, Hall current and chemical reactions. A computational model is established for the purpose to amplify the energy communication rate and enhance the productivity and performance of thermal energy propagation for several industrial and biological purposes. The hybrid nanofluid is comprised of silver and magnesium oxide nanomaterials in the working fluid water. Among transition metals and alloys, magnesium oxide and silver nanoparticles (NPs) have been extensively documented to have broad-spectrum antibacterial properties. Silver NPs are the most extensively employed inorganic NP, having several applications in biomaterial detection and antibacterial actions. The scenario has been expressed as a system of PDEs. Which are simplified to the system of ODEs through similarity replacements. The computing approach PCM is used to subsequently evaluate the acquired 1st order differential equations. The outcomes are checked with the bvp4c package and existing literature for consistency and validity. It has been noticed that the axial velocity profile enhances with the effect of Hall current m and velocity power index constraint n, while reducing with the variation of nanoparticles volume friction ϕ1,ϕ2 and slender sheet wall thickness parameter δ.

The properties of nanoparticles in the working fluid are affected by many external factors and it further influences the effective properties of the resulting nanofluid. To study the heat transference mechanism in nanofluids, the inclusion of such factors is quite important as it provides the exact illustration of the mechanism. One such factor is the nanoparticle aggregation effect. Authors have studied the titania–ethylene glycol nanofluid (TiO2/EG NF) flow over a wedge with nanoparticle aggregation effect. Through this communication, authors have attempted to make a development on the Falkner-Skan problem. The flow is developed in the presence of the suction/injection effects, mixed convection, thermal radiation, porous medium, and non-uniform heat source/sink. To account for the influence of nanoparticle aggregation, revised forms of the Maxwell and Bruggeman models and the Krieger-Dougherty model are employed to estimate the effective thermal conductivity and viscosity of TiO2/EG NF, respectively. The aforementioned modified models developed for TiO2/EG NF gave a soundly close agreement with the experimental data. The governing equations are numerically solved employing the “bvp4c function in MATLAB”. The effect of the primary relevant parameters on the velocity, temperature, and heat transmission rate is depicted graphically. The heat transmission rate at the surface is higher with aggregated nanoparticles in comparison to its absence. The higher NPs volume fraction and the aggregation effect enhance the effective viscosity, the fluid becomes denser, and as a result, the velocity decreases. The outcomes of this study will be useful in many fields that utilize applications of flow over wedge such as in raw oil extraction, storage of nuclear waste, insulating heat exchangers, etc.

The effect of heat and mass transfer on mixed convection flow field with porous matrix in a vertical channel has investigated analytically. The analytical solutions of the coupled nonlinear differential equations are obtained for velocity, temperatures and concentrations are showed graphically. The results obtained analytically by using regular perturbation method are considered to be favorable as no such investigations are performed previously. The governing equations have been made smaller than Non-linear ordinary differential equations by means of flow parameters. Investigations are carried out on the flow characteristics for different values of Grashof number, Reynolds number, Brinkman number, heat generation/absorption parameter and porous parameter. It is found that an increases in the Grashof number cause the buoyancy to increase, which in turn causes the fluid flow for heat generation and absorption to increase.

Energy is essential for a nation's economic growth. Energy is recognized in contemporary society as being crucial to the development of quality of life and sustainability. The environment transforms/absorbs heat and sunlight in a variety of ways. Some of these transitions lead to the flow of renewable energy sources like wind and biomass. Solar energy has become one of the promising alternative energy sources in the future because to the improvements made to enhance its performance. In this context, the impact of solar radiation on modified nanofluid flow over an exponential stretching sheet is examined. Using the proper similarity transformations, the governing equations for the flow assumptions are reduced to ordinary differential equations. The numerical simulation of these simplified equations is then performed using the Runge-Kutta Fehlberg method and the shooting methodology. With the aid of graphs and tables, the effects of numerous parameters on the involved fields are described. Results reveal that the modified nano liquid shows increased heat transport for opposing flow situation than the assisting flow situation for incremented values of porosity parameter and volume fraction. The modified nanoliquid shows increased heat transport for opposing flow situation with respect to augmented values of radiation parameter.

In this study, the triple diffusive Marangoni convection (TDMC) problem when a steady heat source is present in both layers and a vertical uniform magnetic field in a fluid-porous structure is investigated in closed form. The horizontally infinite fluid-porous structure, which is horizontally surrounded by adiabatic boundaries and subjected to basic uniform and non-uniform temperature profiles. For all three temperature profiles (TP), linear, parabolic and inverted parabolic, the eigenvalues, the thermal Marangoni numbers (TMNs) are determined in closed form for lower rigid and upper free boundaries with surface tension, depending on both temperature and concentrations. The effects of relevant parameters on the eigenvalues, hence on TDMC, against depth ratio are attempted for all TPs. It is noticed that, the inverted parabolic TP on TDMC in a composite layer is the most stable of all the three TPs, the linear TP is the most unstable one and the parabolic TP is the moderate one. The relevant physical parameters considered in the study are effective for porous layer dominant fluid-porous structures.

A number of scientists have indicated interest in the promising area of research that involves improving heat transmission by utilizing nanoparticles. The dynamic properties of nanofluids reflect several applications in the cooling process, thermal engineering, heat exchangers, magnetic cell separation, energy production, hyperthermia, etc. In light of the appealing implications of nanofluids, the current research aims to explore the melting process of MHD hybrid AA7072 and AA7075 alloy nanoparticles from a movable cylinder. It also incorporates the irregular Thompson and Troian slip effect to simulate the intricate features of the nanofluid flow. The primary nonlinear partial differential equations (NPDEs) are converted into nonlinear ordinary differential equations (NODEs) with the use of the similarity technique. These converted equations are unraveled numerically via applying the built-in program bvp4c in MATLAB. It is visually examined that physical parameters affect the temperature and skin friction. The outcomes suggest that double solutions are found in a certain range of movable cylinder parameter. In addition, the skin friction is decelerated due to the critical shear rate and velocity slip factors while it is enhanced with the influence of suction and nanoparticles volume fraction. Moreover, the temperature is uplifted due to nanoparticles volume fraction and is declined due to Stefan number. In case of quanitative descriptions, the skin friction boosted up by almost 3.64% and 1.18% for the particular upper and lower branch outcomes due to the superior influences of nanoparticle volume fraction. Also, the skin friction decelerated for the branch of upper and lower solutions at about 5.26% and 22.55%, respectively, due to the larger velocity slip parameter.

The paper investigates the blood flow analysis through a non-uniform inclined channel by treating blood as a non-Newtonian Phan-Thien-Tanner (PTT) liquid. The impact of the chemical reaction and convective boundary conditions are studied in the current formulation. The interaction referring to such constraints report supporting behavior to simulates the particles motion in surgical systems. The fluid movement is regulated through complictatd systems for which solution is enables via perturbation procedure. The influences of diverse emerging parameters over several physiological quantities are scrutinized explicitly. It is also detected that geometric parameters like amplitudes, non-uniform parameters, and inclination angles play a vital role in operating liquid transport phenomena. The obtained results reveal that controlling of velocity due to magnetic constants is observed while thermal determination of particles showing an enhancing trend. Hence magnetic field is used in blood flow analysis such as a catheter, drug delivery, etc. The objective of applicable pertialtic model provdes assistant in hemodialysis.