An investigation was conducted for the study of extraction of metal ions using aqueous biphasic systems. The extraction of iron, zinc and copper from aqueous sulphate media at different kinds of extractants SCN− , Cl- and I- , different values of pH of the feed solution, phase ratio, concentration of metals, concentration of extractant, concentration of polymer, and concentration of salt was investigated. Atomic absorption spectrophotometer was used to measure the concentration of iron, zinc and copper in the aqueous phase throughout the experiments. The results of the extraction experiments showed the use of SCN− as extractant, pH=2.5, phase ratio=1.5, concentration of metals 1g/l, concentration of extractant 0.06 %, concentration o

In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden

 Prepared zeolite type A was used for theremoval of cesium ions from aqueous solution. The experimental data were analyzed by Langmuir, Freundlich isotherms. Various parameters, such as contact time, zeolite weight, pH, and initial concentration, were studied. The results indicated that the highest removal efficiency was95.53% at (2h time, 0.04 g weight, and pH=6.8). The results also showed that the Freundlic model fits well with the experimental results and is better than the Langmuir model.

Purpose: To explore whether baseline matrix metalloproteinase (MMP)-8 level in gingival crevicular fluid (GCF) (exposure) can predict the outcome (reduction in probing pocket depth (PPD) (outcome)) of nonsurgical periodontal therapy (NSPT) (manual or ultrasonic or both) in patients with periodontitis (population/problem) after 3 months. Methods: Six databases (PubMed, Cochrane library, ProQuest, Ovid, Scopus, EBSCO) were searched for relevant articles published until 30 July 2021. Retrieved articles were passed through a three-phase filtration process on the basis of the eligibility criteria. The primary outcome was the change in PPD after 3 months. Quality of the selected articles was assessed using Cochrane Risk of Bias tool (RoB2

Five levels of Zn-EDTA fertilizer and foliar application of boron were used to study the local rice response through studying of some vegetative and reproductive growth characters, by conducting two field experiments at Kanipanka Agricultural Research Station during the summer season of 2004 by using RCBD with three replications. Significant differences were found in studied characters, there were increase in the number of days from seeding to 50% flowering (94.330-96.233) days, from 50% flowering to physiological maturity (37.50-38.28) days, plant height (82.50-91.423) cm and LAI (5.441-7.525). Reproductive characters such as number of grains panicle-1 (74.11-85.88), number of panicles m-2 (321.00-426.083), biological yield (8166.166-11082

Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

The current work is characterized by simplicity, accuracy and high sensitivity Dispersive liquid - Liquid Micro Extraction (DLLME). The method was developed to determine Telmesartan (TEL) and Irbesartan (IRB) in the standard and pharmaceutical composition. Telmesartan and Irbesartan are separated prior to treatment with Eriochrom black T as a reagent and formation ion pair reaction dye. The analytical results of DLLME method for linearity range (0.2- 6.0) mg /L for both drugs, molar absorptivity were (1.67 × 105-    5.6 × 105) L/ mole. cm, limit of detection were (0.0242and0.0238), Limit of quantification were (0.0821and0.0711), the Distribution coefficient were