Due to the significance of hospital drinking water, a study was done to assess the water in three hospitals in Baghdad (Al-Yarmouk Teaching Hospital, Ibn Sina Hospital, and Ibn-Al-Nafis Hospital) for its nature and quality, compare it to other hospitals in terms of its physical, chemical, and bacterial specifications, and compare it to international standards. According to Iraqi standards from 2009 and WHO standards from 2011, Chemical factors were measured, which included pH, Total Dissolved Solids (TDS), and Calcium Ion (Ca+2). Reported readings are all within acceptable ranges for drinking water. In contrast, turbidity, total hardness (T.H.), chlorides (Cl-), magnesium (Mg+2), the number of aerobic plates (APC), total coliform (T

Mandali Basin is located between latitudes (33◦ 39' 00" and 33^◦
54' 55") to the north and longitudes (45ο 11' 00" and 45ο 40' 00") to the
east; to the east of Diyala province at the Iraqi-Iranian border; the
basin area is approximately 491 km².
From the study of climate reality of the basin between 1990-
2013and assessment of the basic climate transactions, it was found
that the annual rate of rainfall is 253.02 mm, the relative humidity
(44.4%), the temperature (21.3 ◦C), wind speed (2.08 m /sec.),
sunshine (8.27 h/day) and evaporation of the basin class (a) (271.98
mm) and corrected potential evapotranspiration (80.03 mm). The
results of the data analysis show that, there are

The toxicological risks and lifetime cancer risks associated with exposure to disinfection by-products (DBPs) including Halloacetic acids (HAAs) and trihalomethanes (THMs) compounds by drinking water in several districts in Wassit Province were estimated. The seasonal variation of HAAs and THMs compounds in drinking water have indicated that the mean values for total HAAs (THAAs) and total THMs (TTHMs) ranged from 43.2 to 72.4 mg/l and from 40 to 115.5 mg/l, respectively. The World health organization index for additive toxicity approach was non-compliant with the WHO guideline value in summer and autumn seasons and this means that THMs concentration has adverse toxic health effects. The multi-pathway of lifetime hu

The present study develops the sorption model for simulating the effects of pH and temperature on the uptake of cadmium from contaminated water using waste foundry sand (WFS) by allowing the variation of the maximum adsorption capacity and affinity constant. The presence of two acidic functional groups with the same or different affinity is the basis in the derivation of the two models; Model 1 and Model 2 respectively. The developed Bi-Langmuir model with different affinity (Model 2) has a remarkable ability in the description of process under consideration with coefficient of determination > 0.9838 and sum of squared error < 0.08514. This result is proved by FTIR test where the weak acids responsible of cadmium ions removal

This study was aimed to conduct one of the vertical garden systems , selecting suitable plant species that with stand the climate conditions of Baghdad city in outer space to determine the appropriate growing medium for the (LWS), and to assess the impact of spraying with potassium silicate on the resistance of the cultivated plants to heat stresses . The study carried out at at Al-Batool Park of (Al-Kadhimiya Holy City). Two experiments were carried out, each one with a different plant species, including Wedelia trilobata and Tradescantia pallida, during the winter season of 2021 and summer season of 2022. The experiments were designed using a split block design. The experiments included two factors, the first being the growing med

A field experiment was conducted during winter season of 2021 at a research station of college of agricultural engineering sciences, university of Baghdad to determine the response of active fertility percentage and seed yield and its components of faba bean (Vicia faba L. cv. Aguadulce) to distance between plants and spraying of nano and traditional boron. A Randomized Complete Block Design according to split-plots arrangement was used at three replicates. The main plots were three distances between plants (25, 35 and 45 cm), while the sub plots including spraying of distilled water only (control treatment), spraying of boron at a 100 mg L-1 and spraying of nano boron at two concentrations (10 and 15 mg L-1). The results showed that the 25

Three isolated bacteria were examined to remove heavy metals from the industrial wastewater of the Diala State Company of Electrical Industries, Diyala-Iraq. The isolated bacteria were identified as Pseudomonas aeruginosa, Escherichia coli and Sulfate Reducing Bacteria (SRB). The three isolates were used as an adsorption factor for different concentrations of Lead and Copper (100, 150, and 200 ppm.), in order to examine the adsorption efficiency of these isolates. In addition, the effect of three factors on heavy metals adsorption were examined; temperature (25, 30, and 37 ?C), pH (3 and 4.5) and contact time (2 and 24 hrs). The results showed that the highest level of lead adsorption was obtained at 37 ?C by E. coli, P, aerugenosa and

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de