This study was carried out to investigate the possibility of chickpea soaked water as a substitute for yeast in dough fermentation and its effects on sensory properties of the laboratory loaf bread. Chickpea was soaked for 24,48 and 72 hours at room temperature and used in proportion with or without yeast in dough fermentation . The results revealed that , as the percentage of soaked chickpea water substitution increased, the volume of the produced loaf bread decreased as compared with the control treatment (only yeast ).Best results were obtained by using soaked chickpea water for 24 hours in proportion of 1:1 soaked chickpea water : yeast regarding the sensory properties ,volume and leavening of the loaf bread.
Keywords: chickpea so

A solid Phase Extraction (SPE) followed by HPLC-UV method is described for the simultaneous quantitative determination of nine priority pollutant phenols : Phenol, 2- and 4-Nitrophenol, 2,4-Dimethylphenol, 2-, 2,4-Di-, 2,4,6-Tri-, and Penta- chlorophenol, 4 Chloro-3-methylphenol. The phenols were separated using a C-18 column with UV detector at wave length of 280nm. The Flow of mobile phase was isocratic consisted of 50:50 Acetonitrile: phosphate buffer pH=7.1, column temperature 45 C°, Flow Rate 0.7 ml/min. Calibration curves were linear (R2 = 0.9961-0.9995). The RSDs (1.301-5.805)%, LOD(39.1- 412.4) µg/L, LOQ(118.5-1250.8) µg/L, the Robustness (1.55-4.89), Ruggedness (2.82-4.00), Repeatability (2.1-4.95), Recoveries%

Glassy carbon electrode (GCE) was modified with carbon nanotubes CNT and C60 by attachment and solution evaporation techniques, respectively. CNT/Li+/GCE and C60/Li+/GCE were prepared by modifying CNT/GCE and C60/GCE in Li+ solution via cyclic voltammetry (CV) potential cycling. The sensing characteristics of the modified film electrodes, demonstrated in this study for interference of Mn2+ in different heavy metals ion esp. Hg2+, Cd2+ and Cu2+. The interfering effect was investigated that exert positive interference on the redox peaks of Mn2+. The modification of GCE with nano materials and Li+ act an enhancement for the redox current peaks to observe the effect of interference for Mn2+ in 1:1 ratio with different heavy metals ion.

Poisoning with toxic substances accidently or deliberately can be life threatening and especially in some countries that lack the essential tests and facilities to identify the types and causes of these toxic substances. In Iraq, as many other countries, poisoning is one of the chronic public health problems. However, very little literature about the pattern of poisoning cases, types and age is available in Duhok Governorate. Therefore, this study was conducted to determine the most common patterns of poisoning and the related age and gender in Duhok Governorate from 2016-2018, which would possibly contribute to the early diagnosis and treatment of poisoning. The present study was conducted for three years, started from 1^st of

A study was carried out to analysis of some heavy metals in nine different types of vinegar, belong to Grape, Apple, Synthetic White, Date, Hawthorn, Garlic, Cactus, Pomegranate and Ginger vinegar, which are locally available in Iraqi folk medicine markets. The concentrations of heavy metals in the studied samples including, Cr, Mg, Mn, Zn, Fe, Cd, Ni, Pb and Ag, were determining by using flame atomic absorption spectrophotometry. All data were subjected to statistical analysis by calculating accuracy, precision and correlation coefficient for each concentrations level. The results indicate that Ni was recorded the highest concentration in all studied samples except, Ginger and cactus vinegar, each one receded the highest concentration valu

Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte