The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

This research proposes the application of the dragonfly and fruit fly algorithms to enhance estimates generated by the Fama-MacBeth model and compares their performance in this context for the first time. To specifically improve the dragonfly algorithm's effectiveness, three parameter tuning approaches are investigated: manual parameter tuning (MPT), adaptive tuning by methodology (ATY), and a novel technique called adaptive tuning by performance (APT). Additionally, the study evaluates the estimation performance using kernel weighted regression (KWR) and explores how the dragonfly and fruit fly algorithms can be employed to enhance KWR. All methods are tested using data from the Iraq Stock Exchange, based on the Fama-French three-f

In this study, the thermal buckling behavior of composite laminate plates cross-ply and angle-ply all edged simply supported subjected to a uniform temperature field is investigated, using a simple trigonometric shear deformation theory. Four unknown variables are involved in the theory, and satisfied the zero traction boundary condition on the surface without using shear correction factors, Hamilton's principle is used to derive equations of  motion depending on a Simple Four Variable Plate Theory for cross-ply and angle-ply, and then solved through Navier's double trigonometric sequence, to obtain critical buckling temperature for laminated composite plates. Effect of changing some design parameters such as, ortho

The present work utilizes polyacrylic acid beads (PAA) to remove Alizarin yellow R (AYR)] and Alizarin Red S (ARS) from its solution. The isotherms of adsorption were investigated and the factors that impact them, such as temperature, ionic strength effect, shaking effect, and wet PAA. The isotherms of adsorption of (ARS) were found obeys the Freundlich equation. The isotherms of adsorption of (AYR) were found obeys the Langmuir equation. At various temperatures, the adsorption process on (PAA) was investigated. According to our data, there is a positive correlation between the (ARS and AYR) adsorption on the PAA and temperature (Endothermic process). The computation of the thermodynamic functions (ΔH, ΔG, and ΔS) is based on the foregoi

The wastewater arising from pulp and paper mills is highly polluted and has to be treated before discharged into rivers. Coagulation-flocculation process using natural polymers has grown rapidly in wastewater treatment. In this work, the performance of alum and Polyaluminum Chloride (PACl) when used alone and when coupled with Fenugreek mucilage on the treatment of pulp and paper mill wastewater were studied. The experiments were carried out in jar tests with alum, PACl and Fenugreek mucilage dosages range of 50-2000 mg/L, rapid mixing at 200 rpm for 2 min, followed by slow mixing at 40 rpm for 15 min and settling time of 30 min. The effectiveness of Fenugreek mucilage was measured by the reduction of turbidity and Chemical Oxygen Demand