In this article, an EOQ inventory model of ameliorating items is considered, and the system total cost is optimised in a supply chain framework. The system facilitates growing the live purchased young items up to the targeted maturity stage for customers' consumption. This study is suitable for poultry and fisheries management and marketing, with a focus on revenue generation. We assume that the items are newborn poultry or fish that can grow rapidly after intensive feeding. An inventory cycle is as follows: Purchase of new-born items, screening to sort out weaker items (defective items), feeding period in which it is implemented intensive technological growth process with proper medication and observation, sorting out unsuitable items that do not reach the desired weight, serving the customers until the items are empty, and allowing the shortages that are completely backlogged which are satisfied in next cycle. The novelty of the model is ensured by incorporating screening before amelioration, eliminating deadly stocks after amelioration, and satisfying backlogs immediately after amelioration altogether. Essential cost functions are derived to minimise system cost by an analytical approach. It is recommended by numerical illustration, which gives more light to the investors who are involved in the sale of poultry and fisheries items in optimising total cost.
This study investigates the dispersion of a solute in Casson fluid, representing blood flow, under the influence of an external transverse magnetic field1. The Casson model is utilized to capture the nonNewtonian yield stress and shear-thinning behavior characteristic of blood in micro circulation. By extending the classical theory of Gill and Sankarasubramanian, the mathematical framework accounts for magnetohydro dynamic (MHD) effects, porous boundaries, and chemical reactions. Analytical and numerical results show that increasing the Hartmann number and the Casson parameter significantly reduces the effective dispersion coefficient while increasing mean solute concentration. Furthermore, wall slip is shown to enhance solute transport, providing an additional mechanism for flow control. These findings provide theoretical insights for optimizing targeted drug delivery, contrast agent transport, and tracer movement in cardiovascular systems.
The power graph of a finite group G is a special type of undirected simple graph whose vertex set is a set of elements of G, in which two distinct vertices x and y are adjacent if either x is an element of (y) or y is an element of (x). In this article, we establish a new class of vertex odd as well as even mean graphs through the power graphs of 2-abelian groups Z(2)(k - 1), Z(2)(k - 1) x Z(4) and Z(2)(k - 1) x Z(4) x Z(4).
This article discusses the problem of practical h-stability for certain classes of dynamic equations in Banach spaces. The main objective is to give sufficient conditions on the linear and perturbed term for practical h-stability based on certain nonlinear Gronwall-type integral inequalities over time. ladder. Two examples are given to illustrate the effectiveness and advantages of the results obtained.
. India is the world's third-largest electricity producer. There were 1,378 TWh produced by utilities in the nation in the 2018-19 fiscal year (FY). Globally, there is an increasing need for electrical power because of the growth of industrial activities and the size of the population. A reliable projection of future output is vital for the effective planning and development of policies pertaining to electrical power. In the present study, ARIMA, Support Vector Regression optimized by LSTM, and Modulated Support Vector Regression using python were employed to analyse the electricity generation from coal, gas, hydro, solar, oil, wind, and renewable energy sources in India. The MSE, MAPE, R-2, and RMSE criteria were used to evaluate the models created using those techniques. Among these three models, by the least error metrics of MSVR, RMSE is 0.00726227, R2 is 0.989280593, MSE is 5.27E-05 and MAPE is 1.24E-03%, by DM statistical test and by the graphical representation, MSVR is the best model to fit the electrical generation of India. So the future generations will benefit from early forecasts of India's electricity production by MSVR.
