The presence and prevalence of V. cholerae were investigated in forty five water samples collected from different locations of Tiger River/ Baghdad city. Twenty one isolates were isolated by adopting a simple isolation techniques. The final identification revealed that only three isolates were confirmed as V. cholerae. They were named 1J, 1R and Dial 131 which are all serogrouped as non-O1. Toxin Coregulated Pili (TCP) and heat labile enterotoxin (LT) were determined in only the environmental isolate 1J while non of the isolates produced heat stabile toxin (ST). The purification scheme was improved, few steps were adopted to include back extraction of ammonium sulfate, saturation between 80-20%, desalting through Sephadex G25, and gel filt

Opportunistic fungal infections due to the immune- compromised status of renal transplant patients are related to high rates of morbidity and mortality regardless of their minor incidence. Delayed in identification of invasive fungal infections (IFIs), will lead to delayed treatment and results in high mortality in those populations. The study aimed to assess the frequency of invasive fungal infection in kidney transplant recipients by conventional and molecular methods. This study included 100 kidney transplant recipients (KTR) (75 males, and 25 females), collected from the Centre of Kidney Diseases and Transplantation in the Medical City of Baghdad. Blood samples were collected during the period from June 2018 to April 2019. Twent

The Cassia glauca Lam. is the tree that belongs to the Fabaceae family and is native to India has many uses in indigenous systems of medicine, folk medicine, and traditional Brazilian medicine. Has many pharmacological activities such as anti-diabetic, antibacterial, antifungal, antioxidant, anti-hemolytic, anticancer, cardio-protective, and Hepato-protection.  The aim of study is to Isolation, identification, and quantification of some compounds from aerial parts of Cassia glauca since no phytochemical investigation had previously been done in Iraq for this plant. The aerial parts were defatted in n. hexane for 48 hours. The defatted materials were extracted in 85% ethanol using the hot method (soxhlet), then the extract was fra

    The plant Borago officinalis, which belongs to the Boraginaceae family and Celebrated as borage, is one of the useful medicinal plants cultivated in Iraq. It was used in olde medicine in Iraq, Irane, Syria and Europe for management of various diseases. It is commonly used as an atonic, tranquilliser, management of cough, sore throat, pneumonia, swelling, inflammatory diseases, antioxidant, and anticancer. This project provides the first comprehensive research done in Iraq to study the phytochemicals and the methods of extraction and isolation of active constituents from Borago officinalis cultivated in Iraq. The plant was harvested in spring from AL-Rifai, Nassiriyah city, IRAQ in February 2019.were w

Aspergillus fumigatus considered to be the most important species to cause respiratory infection cases in both humans and animals especially in cats in the last decades. In this study, we focused on the isolation and identification of Aspergillus fumigates by collecting 40 samples in deferent veterinary clinics and stray cats in Baghdad city, during the period (October 2021 to January 2022), all samples were cultured on Sabouraud dextrose agar and malt extract agar. The isolates identified by the laboratory methods, it’s depend on macroscopic and microscopic appearance. The results showed that (40) swaps taken from the pharynx of infected cats, included: Aspergillus fumigatus 16 (40%), Aspergillus spp. 7 (17.5%), Aspergillus niger

The plant Dianthus Orientalis that belongs to the Caryphyllaceae family is one of the useful plants in Iraq. Its seeds are commonly used for toothache. This project provides the first comprehensive research done in Iraq and the world to study the phytochemicals and the methods of extraction and isolation of active constituents from Dianthus orientalis wildly grown in Iraq. The plant was harvested from Penjwin in AL-Sulaymaniyah city, Iraq in September 2019.The whole plant were washed carefully, dried in shade area for two weeks, and milled in a mechanical grinder to a coarse powder. The plant was defatted by maceration with hexane for 7days and dried after that extracted by cold extraction methods using

Tomato (Solanum lycopersicum) is acknowledged worldwide as one of the major vegetable crops, as is the case in Iraq. This research in 2024 was designed to recognize the species of Root-Knot Nematode (RKN) in central Iraq, assess its distribution, and study the level of susceptibility of 5 tomato varieties (SPEEDY, GS-12, SUPER LUX, TALA, and JUDIVIS). Since there is a threat of chemical nematicides, a greenhouse study was performed to evaluate other control methods, such as the use of organic fertilizers and the extract of nettles (Urtica dioica). Root-knot nematode (RKN) species consisting of Meloidogyne incognita, M. arenaria, and M. javanica were found in Baghdad, while only M. incognita was found in Babil. Molecular identificati

Deep drawing process to produce square cup is very complex process due to a lot of process parameters which control on this process, therefore associated with it many of defects such as earing, wrinkling and fracture. Study of the effect of some process parameters to determine the values of these parameters which give the best result, the distributions for the thickness and depths of the cup were used to estimate the effect of the parameters on the cup numerically, in addition to experimental verification just to the conditions which give the best numerical predictions in order to reduce the time, efforts and costs for producing square cup with less defects experimentally is the aim of this study. The numerical analysis is used to study

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par