This study delves into the realm of advanced cooling techniques by examining the performance of a two-stage parallel flow indirect evaporative cooling system enhanced with aspen pads in the challenging climate of Baghdad. The objective was to achieve average air dry bulb temperatures (43 ^oC) below the ambient wet bulb temperatures (24.95 ^oC) with an average relative humidity of 23%, aiming for unparalleled cooling efficiency. The research experiment was carried out in the urban environment of Baghdad, characterized by high temperature conditions. The investigation focused on the potential of the two-stage parallel flow setup, combined with the cooling capability of aspen pads, to surpass the limitat

Designing high-performance solid polymer electrolytes (SPEs) remains a key challenge, primarily due to their inherently low ionic conductivity, which hampers the advancement of all-solid-state lithium-ion batteries (ASSLiBs). In this work, we address this limitation by developing a green, crosslinked polymer blend comprising carboxymethyl cellulose (CMC) - extracted and functionalized from palm frond fibers - and poly (vinyl alcohol) (PVA). Citric acid (CA) was utilized as a crosslinking agent, while lithium perchlorate (LiClO4) was incorporated as a dopant to enhance ionic conductivity. The SPE membranes were fabricated via solution casting, with the optimized formulation - designated CP-15X-Li25 - containing 15 wt.-% CA and 25 wt.-% LiClO

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

Silybum marianum, from which silymarin (SM) is extracted, is a medicinal herb. In the Biopharmaceutics Classification System, it is of the class II type, meaning it is almost completely insoluble in water. It has a number of therapeutic properties, including anti-inflammatory as well as properties that promote wound healing.

This research target is to promote the dissolution and solubility of SM by employing a technique called solid dispersion and then incorporating the formula of solid dispersion into a topical gel that can be used for wound healing.

Solid dispersion is a technique used to enhance solubility and dissolve pharmaceuticals that are not water-soluble. This method is widely used because of its low cos

Signature verification involves vague situations in which a signature could resemble many reference samples or might differ because of handwriting variances. By presenting the features and similarity score of signatures from the matching algorithm as fuzzy sets and capturing the degrees of membership, non-membership, and indeterminacy, a neutrosophic engine can significantly contribute to signature verification by addressing the inherent uncertainties and ambiguities present in signatures. But type-1 neutrosophic logic gives these membership functions fixed values, which could not adequately capture the various degrees of uncertainty in the characteristics of signatures. Type-1 neutrosophic representation is also unable to adjust to various

This study computationally investigates to examine the impacts of repeated loading on L-shaped spandrel beams made of reinforced concrete, which were strengthened by externally bonded carbon fiber reinforced plastic sheets. The object of the research is to evaluate the following three aspects of structural behavior: degradation of reaction forces, evolution of inertia forces, and residual performance. Ayad and Oukaili's experimental impact-loading program, which featured midspan drop-weight loading on RC spandrel beams before and after strengthening, was used to validate a comprehensive three-dimensional finite element model created in ABAQUS. A sequence of 25 impacts before and 25 impacts after CFRP application was simulated to tra

Glass fiber–reinforced polymer (GFRP) reinforcement provides an effective alternative to conventional steel in concrete structures due to its corrosion resistance. Nevertheless, the lower elastic modulus of GFRP necessitates careful consideration of serviceability behavior in GFRP-reinforced concrete members. This study presents a numerical sectional analysis model for predicting the flexural response and ultimate capacity of hybrid reinforced concrete beams incorporating embedded GFRP profiles in combination with either mild steel or GFRP reinforcement bars under monotonic static loading. The proposed model employs realistic nonlinear stress–strain relationships for concrete and steel, together with secant moduli of elasticity