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This study aims to examine the cilia-driven flow of magnetohydrodynamics (MHD) non-Newtonian fluid through a porous medium. The Jeffrey fluid model is taken into account. The fluid motion in a two-dimensional symmetric channel emphasizes the dominance of viscous properties over inertial properties in the context of long wavelength and low Reynolds number approximations.

An integrated numerical and analytic results are obtained by hybrid approach. A statistical method analysis of variance along with response surface methodology is used. Sensitivity analysis is used to validate the accuracy of nondimensional numbers.

The impact of various flow parameters is presented graphically and in numerical tables. It is noted that the velocity slip parameter is the most sensitive flow parameter in velocity and relaxation to retardation time ratio in temperature.

A model on cilia-generated flow of MHD non-Newtonian Jeffrey fluid is proposed.

This paper aims to optimize bioconvective heat transfer for magnetohydrodynamics Eyring–Powell nanofluids containing motile microorganisms with variable viscosity and porous media in ciliated microchannels.

The flow problem is first modeled in the two-dimensional frame and then simplified under low Reynolds number and long wavelength approximations. The numerical method is used to examine the impact of thermal radiation, temperature-dependent viscosity, mixed convection, magnetic fields, Ohmic heating and porous media for velocity, temperature, concentration and motile microorganisms. Graphical results are presented to observe the impact of physical parameters on pressure rise, pressure gradient and streamlines.

It is observed that the temperature of nanofluid decreases with higher values of the viscosity parameter. It is absolutely in accordance with the physical expectation as the radiation parameter increases, the heat transfer rate at the boundary decreases. Nanoparticle concentration increases by increasing the values of bioconvection Rayleigh number. The density of motile microorganisms decreases when bioconvection Peclet number is increased. The velocity of the nanofluid decreases with higher value of Darcy number. With increase in the value of bioconvection parameter, the flow of nanofluid is increased.

The bioconvective peristaltic movement of magnetohydrodynamic nanofluid in ciliated media is proposed. The non-Newtonian behavior of the fluid is described by using an Eyring–Powell fluid model.

Due to the abundant use of granular materials in chemical industries, it is inevitable to store raw materials and products in bulk in silos. For this reason, much research has been carried out in the field of construction, operation and maintenance of silos. One of the important issues that must be investigated in silos is the behavior of their structure when the materials inside them are unloaded. Structural vibrations and the creation of normal noise usually discharge the granular of material from the silo. Both of phenomena are undesirable due to the problems they can cause to the structure and its surroundings. According to the said issues, this paper aims to investigate the vibration problem of the sulfur storage silo of the first refinery during discharge with the help of measuring experimental vibration data and simulating the silo model.

In the experimental investigation, the main cause of the vibration of the 400-ton silo in the refinery is used. The mass asymmetry phenomenon when the silo is filled is also considered. The experimental results are authenticated by software analysis too.

The results showed that the natural frequency of the ninth mode is almost equal to the natural frequency of sulfur discharge from the silos and has the largest shape change in the structure and vibration range. It is also concluded that the larger sulfur silo (400 tons) should be prioritized over the smaller sulfur silo (200 tons) in the emptying program, and the 400 tons silo should never be emptied even through the 200 tons silo is empty.

An attempt is made to investigate the issue of vibration in sulfur storage silos in the first refinery of South Pars in the form of experimental investigation and modal analysis.

Lacking lecturers in higher education is an international issue where society faces insufficient educational services to enlighten one’s future, and lecturer work satisfaction also merits higher attention. Work satisfaction is closely associated with turnover rates, lecturer retention, overall university cohesion, lecturers’ well-being, professional teaching improvement and research and publication performances. This study aims to explore how causes of actions (work–family conflict [WFC] and workload) influence consequences (stress and burnout) which affect the overall attitude (lecturer work satisfaction).

Researchers collected data from 450 Thai lecturers from different universities via survey questionnaires. Furthermore, a structural equation model method was used to analyze the data.

Results showed that lecturer stress was significantly influenced by WFC and workload. Next, stress, workload and WFC were the main predictors of lecturer burnout. Then, lecturer work satisfaction was significantly influenced by burnout, except stress. Finally, a relationship between lecturer stress and work satisfaction was mediated by burnout.

This research proposes a theoretical mechanism to analyze how causes of actions (WFC and workload) influence consequences (stress and burnout) which lead to a development of lecturer attitude (work satisfaction) in higher education.

This paper focuses on the commitment of a leading Middle Eastern country – Saudi Arabia – to the United Nations (UN) Sustainable Development Goals (SDGs), particularly SDG13, climate preservation. This paper aims to investigate the determinants of greenhouse gas emissions by examining their correlation with economic growth, population growth, renewable energies, forest area, digitalization and monetary policy.

This research observes greenhouse gas (GHG) emissions and the potential influencing factors during 1990–2023. It employs the autoregressive distributed lag model (ARDL) after testing the stationarity of the variables.

The findings show that population growth, gross domestic product (GDP) growth, percentage of individuals using the internet and forest rents are significant determinants of carbon oxide (CO₂) emissions. Further, methane (CH₄) emissions are significantly associated with population growth, GDP growth, percentage of individuals using the internet and renewable internal freshwater resources. Nitrous oxide (N₂O) emissions depend significantly on the percentage of individuals using the internet and renewable internal freshwater resources.

This research helps policymakers in Saudi Arabia and worldwide identify the factors moderating GHG emissions, and accordingly design targeted interventions. These initiatives would substantially reduce GHG and further global climate goals. Additionally, focusing on Saudi Arabia, a significant emerging country in the Middle East, has broader implications. The findings offer insights that extend beyond its borders, providing valuable lessons for governments in the Middle East and worldwide to assess and improve their initiatives toward SDG13. Therefore, monitoring greenhouse gas emissions in this key country boosts global progress toward the UN’s 2030 Agenda for Sustainable Development. Furthermore, this paper aligns with the Principles for Responsible Management Education (PRME) by leveraging academic and managerial strategies toward sustainability and climate action initiatives.

This study adds to the limited literature on the determinants of GHG emissions in the Middle Eastern region, particularly in Saudi Arabia. In addition to CO₂, it also focuses on CH₄ and N₂O emissions. It shows the beneficial effect of renewable internal freshwater resources. It uses the ARDL model to distinguish between the short- and long-run associations.