Sawdust has the ability to adsorb the dyestuff from aqueous solution. It may be useful low cost adsorbent for the treatment of effluents, discharged from textile industries. The effectiveness of sawdust has been tested for the removal of color from the wastewater samples containing two dyes namely Direct Blue (DB) and Vat Yellow (VY). Effect of various parameters such as agitation time, adsorbent dose and initial concentration of each dye has been investigated in the present study. The adsorption of dyes has been tested with various adsorption isotherm models. The Langmuir isotherms model is found to be the most suitable one for the dye adsorption using sawdust and the maximum adsorption capacity is 8.706 mg/g and 6.975 mg/g for DB and V

In search of novel antibacterial agent, a series of new isatin derivatives (3a-d) have been synthesized by condensation isatin (2,3-indolinendione) with piperidine (hexahydropyridine), hydrazine hydrate and Boc-amino acids respectively. Compounds synthesized have been characterized by IR spectroscopy and elemental analysis. In addition, the in vitro antibacterial properties have been tested against E. coli, P. aeruginosa, and Bacillus cereus, S. aureus by employing the well diffusion technique. A majority of the synthesized compounds were showing good antibacterial activity and from comparisons of the compounds, compound 3d has been determined to be the most active compound.

The present investigation developed the ester prodrugs of Non-steroidal anti inflammatory drugs (NSAIDs), Mefenamic acid and Flurbiprofen by conjugating with the natural antioxidant, 4-methyl umbelliferone that resulted the formation of Mefenamic acid-umbelliferone ester prodrug and Flurbiprofen-umbelliferone ester prodrug .The principal objective this study is the synthesis of the ester prodrugs of NSAIDs with the enhanced therapeutic activity and minimized side effects. Prodrugs were synthesized by coupling method using N,N^’- dicyclohexylcarbodiimide/4-dimethylaminopyrimidine, subjected to  physical, chemical characterization, spectral characterization (IR, ¹H NMR, ¹³C NMR and Mass spectra),hydro

The physical, mechanical, electrical and thermal properties containing (Viscosity, curing, adhesion force, Tensile strength, Lap shear strength, Resistively, Electrical conductivity and flammability) of adhesive material that prepared from Nitrocellulose reinforced with graphite particles and aluminum streat. A comparison is made between the properties of adhesive material with varying percentage of graphite powder (0%, 25%, 30%, 35%, 40%) to find out the effect of reinforcement on the adhesive material. The ability of property an electrical was studied through the measurement of conductivity a function of temperature varying. The results of comparison have clearly shown that the increasing of conten

Thermomechanical analysis (TMA) and differential scanning calorimetry (DSC) are used to investigate the effect of molding and annealing of polyester on the behavior of thermal expansion and crystallization since these factors play role in the reprocessing or recycling of the polymer. The dynamic mode of the TMA provides enhanced characterization information about the polyester since it separates the transitions into reversible and irreversible signals, and also reveals the progress of the amorphous regions as the polyester loses strength with the increasing temperature approaching melting. Slow cooling after annealing brings crystallization that may be attributed to molecular chain straightening due to orientation.

Global concerns are rising due to complications associated with the use of chemical agents and antibiotic resistance. Consequently, research focus has shifted towards the quest for effective agents of biological origin. The aim of the present study was to assess the antioxidant and antimicrobial potentials of aqueous and organic extracts derived from various parts of Alcea kurdica. Different parts of A. kurdica were obtained and prepared into leaf, flower and root powders. The powders were extracted with aqueous and organic solvents. The antimicrobial activity of these extracts was assessed against bacterial pathogens using the agar well-diffusion assay. Additionally, the antioxidant effects of the extracts were evaluated using the

Heterocyclic systems, which are essential in medicinal chemistry due to their promising cytotoxic activity, are one of the most important families of organic molecules found in nature or produced in the laboratory. As a result of coupling N-(4-nitrophenyl)-3-oxo-butanamide (3) using thiourea, indole-3-carboxaldehyde, or piperonal, the pyrimidine derivatives (5a and 5b) were produced. Furthermore, pyrimidine 9 was synthesized by reacting thiophene-2-carboxaldehyde with ethyl cyanoacetate and urea with potassium carbonate as a catalyst. The chalcones 11a and 11b were synthesized by reacting equal molar quantities of 1-naphthaldehy

     This paper develops the work of Mary Florence et.al. on centralizer of semiprime semirings and presents reverse centralizer of semirings with several propositions and lemmas. Also introduces the notion of dependent element and free actions on semirings with some results of free action of centralizer and reverse centralizer on semiprime semirings and some another mappings.

        Peroxidase is a class of oxidation-reduction reaction enzyme that is useful for accelerating many oxidative reactions that protect cells from the harmful effects of free radicals. Peroxidase is found in many common sources like plants, animals and microbes and have extensive uses in numerous industries such as industrial, medical and food processing. In this study, P. aeruginosa was harvested to utilize and study its peroxidases. P. aeruginosa was isolated from a burn patient, and the isolate was verified as P. aeruginosa using staining techniques, biochemical assay, morphological, and a sensitivity test. The gram stain and biochemical test result show rod pink gram-ne

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod