Lymphoma is a cancer arising from B or T lymphocytes that are central immune system ‎components. It is one of the three most common cancers encountered in the canine; ‎lymphoma affects middle-aged to older dogs and usually stems from lymphatic tissues, ‎such as lymph nodes, lymphoid tissue, or spleen. Despite the advance in the management of ‎canine lymphoma, a better understanding of the subtype and tumor aggressiveness is still ‎crucial for improved clinical diagnosis to differentiate malignancy from hyperplastic ‎conditions and to improve decision-making around treating and what treatment type to use. ‎This study aimed to evaluate a potential novel biomarker related to iron metabolism,

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

Several industrial wastewater streams may contain heavy metal ions, which must be effectively removal
before the discharge or reuse of treated waters could take place. In this paper, the removal of copper( II)
by foam flotation from dilute aqueous solutions was investigated at laboratory scale. The effects of
various parameters such as pH, collector and frother concentrations, initial copper concentration, air flow
rate, hole diameter of the gas distributor, and NaCl addition were tested in a bubble column of 6 cm inside
diameter and 120 cm height. Sodium dodecylsulfate (SDS) and Hexadecyl trimethyl ammonium bromide
(HTAB) were used as anionic and cationic surfactant, respectively. Ethanol was used as frothers and the

Objective: The aim of this study to detect the correlation between trace elements such as zinc, copper and
spermatogenesis, sperm viability and motility.
Methodology: Serum and semen samples were collected from one hundred twenty patients with age ranged (20-
50 years) attending the high institute for Embryo Research and Infertility Treatment/ Baghdad University, in
addition to thirty fertile males their age comparable to that of patients. The period of this study was from June
2004 until the end of October 2004.
Results: The result of routine seminal fluid analysis of all infertile males was divided according to WHO, (1999) limit
into four groups: Asthenospermia(A), Asthenoteratospermia(AT), Oligoasthenoteratospermi

Nanocrystalline copper sulphide (Cu2-xS) powders were synthesized by chemical precipitation from their aqueous solutions composed of different molar ratio of copper sulfate dehydrate (CuSO4.5H2O) and thiorea (NH2)2CS as source of Cu+2, S-2 ions respectively, and sodium ethylene diamine tetra acetic acid dehydrate (EDTA) as a complex agent. The compositions, morphological and structural properties of the nanopowders were characterized by energy dispersive spectroscopy (EDS), scanning electron microscope (SEM), and X-ray diffraction (XRD), respectively. The compositional results showed that the copper content was high and the Sulfur content was low for both CuS and Cu2S nanopowders. SEM images shows that all products consist of aggregate o