Natural polymers are often non-toxic, biodegradable, biocompatible, and safe. A novel ligand was synthesized as a natural polymer using chitosan and oleander plant extract [(2R,3S,4R,5S)-5-(acetoxyamino)-4-hydroxy-3,6-dimethoxytetrahydro-2H-pyran-2-yl) methyl (16R)-3-(((2S,4S,5R)-4-methoxy-2,5-dimethyltetrahydro-2H-pyran-2-yl)oxy-10,13,16-trimethyl-17-(5-oxo-2,5-dihydrofuran-3-yl) hexadecahydro-14H-cyclopenta [a] phenanthren-14-yl) phthalate] (Chitosan-Ph-Oleander). This ligand and its complexes with several metals (Cr+3, Mn+2, Fe+3, Ni+2, Cu+2, Zn+2) were characterized using FTIR, UV-visible and 1H-NMR spectroscopy, as well as by molar conductivity, magnetic moment, and TGA analysis. The biological activity for the prepared polymer

Groundwater quality deterioration due to anthropogenic natural activities and its immense utilization in various sectors is considered a great concern. The aim of this study is to determine the groundwater quality parameters at various sources in and around Dhaka city and compare them with Bangladesh drinking water standards. In this study, six groundwater quality parameters (pH, DO, COD, TS, TDS, and arsenic) and ten groundwater samples are analyzed to determine the water quality. The collected samples have maximum and minimum pH values of 6.9 and 6.4, respectively. Maximum and minimum DO values are 0.3 and 0.1 mg/L, respectively. The arsenic concentration is 0 mg/L for all collected groundwater samples. The maximum and minimum COD

PMMA (Poly methyl methacrylate) is considered one of the most commonly used materials in denture base fabrication due to its ideal properties. Although, a major problem with this resin is the frequent fractures due to heavy chewing forces which lead to early crack and fracture in clinical use. The addition of nanoparticles as filler performed in this study to enhance its selected mechanical properties. The Nano-additive effect investigated in normal circumstances and under a different temperature during water exposure. First, tests applied on the prepared samples at room temperature and then after exposure to water bath at (20, 40, 60) C^° respectively. SEM, PSD, EDX were utilized for samples evaluation in this study. Flexural

The aim of this paper is to demonstrate the effect of Na2[Fe(CN)5.NO].2H2O impurity (0.1 M) concentration on the dielectrical properties of poly (P-Aminobenzaldehyde) terminated by pheneylenediamine in the frequency and temperature ranges (1-100)KHz and (283-348) K respectively.These properties include dissipation factor, series and parallel resistance, series and parallel capacitance, real and imaginary part of the dielectric constant, a.c conductivity and impedance (real and imaginary) part, that have been deduced from equivalent circuit. The investigation shows that adding Na2[Fe(CN)5.NO].2H2O as additive to the polymer lead to increase of the dielectric constant with increasing temperature and it is decreasing with increasing the freq

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par