Ex-situ bioremediation of 2,4-D herbicide-contaminated soil was studied using a slurry bioreactor operate at aerobic conditions. The performance of the slurry bioreactor was tested for three types of soil (sand, sandy loam and clay) contaminated with different concentration of 2,4-D, 200,300and500mg/kg soil. Sewage sludge was used as an inexpensive source of microorganisms which is available in large quantities in wastewater treatment plants. The results show that all biodegradation experiments demonstrated a significant decreases in 2,4-D concentration in the tested soils. The degradation efficiency in the slurry bioreactor decreases as the initial concentration of 2,4-D in the soils increases.A 100 % removal was achieved at initial con

New Schiff bases derived from D-galactose were synthesized by condensation of aldehyde (1,2:3,4-Di-O-isopropylidene-6-carboxaldehyde-α-D-galactopyranose) with different aromatic amines such as (4-bromo, 3-hydroxy, 4-iodo, 4-methoxy) aniline in dry benzene using glacial acetic acid as a catalyst. These compounds were converted to oxazepine derivatives by addition reaction with maleic anhydride in dry benzene as a solvent. The structures of the synthesized compounds have been characterized by elemental analysis, FTIR spectra, some of them by using 1HNMR spectra and measurement of its physical properties.

Consider a simple graph   on vertices and edges together with a total  labeling . Then ρ is called total edge irregular labeling if there exists a one-to-one correspondence, say  defined by  for all  where  Also, the value  is said to be the edge weight of . The total edge irregularity strength of the graph G is indicated by  and is the least  for which G admits   edge irregular h-labeling.  In this article,   for some common graph families are examined. In addition, an open problem is solved affirmatively.

 The new schiff bases derived from D-erythroascorbic acid contaning heterocyclic unit were synthesized by condensation of D-erythroascorbic acid with aromatic amine (containing 1,3,4oxadiazole or 1,3,4-thiadiazole unit) in dry benzene using glacial acetic acid as a catalyst.  Derythroascorbic acid [IV] was synthesized by four steps (Scheme 1), while the primary aromatic amine which is containing 1,3,4-oxadiazole [VII] or 1,3,4-thiadiazole [VIII] synthesized by the reaction of 4methoxy benzoyle hydrazine [VI] with 4-amino benzoic acid or by the reaction  tuloic acid with thiosemicarbazide, respectively in the presence of POCl3. The new  1,3-oxazepine derivatives were obtained by addition reaction of Schiff bases with d

The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

Fiber Bragg Grating has many advantages where it can be used as a temperature sensor, pressure sensor or even as a refractive index sensor. Designing each of this fiber Bragg grating sensors should include some requirements. Fiber Bragg grating refractive index sensor is a very important application. In order to increase the sensing ability of fiber Bragg gratings, many methods were followed. In our proposed work, the fiber Bragg grating was written in a D-shaped optical fiber by using a phase mask method with KrFexcimer. The resultant fiber Bragg grating has a high reflectivity 99.99% with a Bragg wavelength of 1551.2 nm as a best result obtained from a phase mask with a grating period of 1057 nm. In this work it was found that the rota