The properties of capturing of peristaltic flow to a chemically reacting couple stress fluid through an inclined asymmetric channel with variable viscosity and various boundaries are investigated. we have addressed the impacts of variable viscosity, different wave forms, porous medium, heat and mass transfer for peristaltic transport of hydro magnetic couple stress liquid in inclined asymmetric channel with different boundaries. Moreover, The Fluid viscosity assumed to vary as an exponential function of temperature. Effects of almost flow parameters are studied analytically and computed. An rising in the temperature and concentration profiles return to heat and mass transfer Biot numbers. Noteworthy, the Soret and Dufour number effect resul

A novel azo dye was prepared by reacting the diazonium salt of 3-aminophenol with 8-hydroxyquinoline and subsequently used to prepare a series of Ni+2, Pd+2, Pt+4, and Cu+2 complexes. The ligand structure was characterized via1H-and 13C-nuclear magnetic resonance spectroscopy. The as-synthesized materials were characterized via Fourier-transform infrared, ultraviolet‒visible, and mass spectroscopy, as well as thermo gravimetry, differential scanning calorimetry, and elemental analysis. Conductivity, magnetic susceptibility, and the metal and chloride contents of the complexes were also determined. The ligand exhibited a trigonal geometry, whereas the Cu+2, Pd+2, Pt+4, and Ni+2 complexesexhibited tetrahedral, square planar, octahedral, and

Background: Rheumatoid arthritis (RA) is a chronic and systemic autoimmune disease that is characterized by severe synovial inflammation, cartilage erosion, bone loss, and generalized vasculopathy. Although the immunologic mechanism of RA is still unclear, it is now thought to be a primarily Th17-driven disease. Along with other factors, IL-23 stimulates the expansion of Th17 cells from naive CD4+ T cells.

Objective: The objective of this study is to assess the circulating levels of interleukin (IL)-23 in rheumatoid arthritis (RA) and determine the correlation between plasma/serum IL-23 levels and disease activity. So, we performed a systematic review with meta-analysis comparing

      In this work, a test room was built in Baghdad city, with (2*1.5*1.5) m³  in dimensions, while the solar chimneys (SC) were designed with aspect ratio (ar) bigger than 12. Test room was supplied by many solar collectors; vertical single side of air pass with ar equals 25, and tilted 45^o double side of air passes with ar equals 50 for each pass, both collectors consist of flat thermal energy storage box collector (TESB) that covered by transparent clear acrylic sheet, third type of collector is array of evacuated tubular collectors with thermosyphon in 45^o instelled  in the bottom of TESB of vertical SC. The TESB was

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

To create a highly efficient photovoltaic-thermal (PV-T) system and maximise the energy and exergy efficiency, this study aims to propose an innovative configuration of a PV-T system comprising wavy tubes with twisted-tape inserts. Following the validation of a numerical model, a parametric study has been conducted to assess the geometrical effects of twisted tape and wavy tubes, as well as the coolant fluid type and velocity, on the overall performance of a PV-T system, located in Shiraz, Iran. It is found that employing twisted tape improves the energy and exergy efficiency by approx. 6.3%. The best configuration yields 12.4% and 16.8% increase in energy and exergy efficiency compared to conventional PV systems. This is achieved at 15% vo

Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia