Trip generation is the first phase in the travel forecasting process. It involves the estimation of the
total number of trips entering or leaving a parcel of land per time period (usually on a daily basis);
as a function of the socioeconomic, locational, and land-use characteristics of the parcel.
The objective of this study is to develop statistical models to predict trips production volumes for a
proper target year. Non-motorized trips are considered in the modeling process. Traditional method
to forecast the trip generation volume according to trip rate, based on family type is proposed in
this study. Families are classified by three characteristics of population social class, income, and
number of vehicle ownersh

The research aims to apply the novel forward osmosis (FO) process to recover pure water
from contaminated water. Phenol was used as organic substance in the feed solution, while sodium
chloride salt was used as draw solution. Membranes used in the FO process is the cellulose
triacetate (CTA) and polyamide (thin film composite (TFC)) membrane. Reverse osmosis process
was used to treatment the draw solution, the exterior from the forward osmosis process. In the FO
process the active layer of the membrane faces the feed solution and the porous support layer faces
the draw solution and this will show the effect of dilutive internal concentration polarization and
concentrative external concentration polarization.
In th

Background: In the present study used device jet plasma needle with atmospheric pressure which  generates non thermal plasma jet to measure treatment potent with plasma against pathogenic bacteria  founded  in UTI  was inactivated with plasma at 10 sec,

Objective:. This work included the application of the plasma produced from the system in the field of bacterial sterilization , where sample of Gram- negative bacteria (Escherichia coli) were exposed to intervals (1-10)second . Midstream Urine samples swabs were obtained from patients with urinary tract infections.

Type of the study: Cross -sectional study.

Methods: The work were used i

The current study aims to assess zooplankton diversity in Bahr Al-Najaf depression using diversity index, specimens were collected from five sites at Bahr Al-Najaf depression, Iraq during April 2017 to March 2018.

Forty-eight taxa of zooplankton were identified including 26 taxa to Copepoda, 17 taxa belonged to Rotifers and 5 taxa to Cladocera: Copepoda was the most dominant group (54.2%); Rotifera comprised (35.4%); Cladocera comprised (10.4%).

Relative abundance index of zooplankton showed Copepodite and nauplii of Harpacticoid, Hexarthra mira, Daphnia sp., Harpacticoid sp., and Copepodite and nauplii of Cyclops were more abundant. According to the constancy index

For two years, from January 1995 till December 1996, a survey on helminth parasites of aquatic birds of Bahr Al-Najaf depression, mid Iraq, was achieved. A total of 663 birds, belonging to 11 species, were captured and examined for helminth parasites. These birds were infected with seven trematodes (Notocotylus gibbus, Cyclocoelum mutabile, Echinostoma chloropodis, Patagifer parvispinosus, Psilochasmus oxyurus, Diplostomum spathaceum and Apharyngostrigea cornu), seven cestodes (Paricterotaenia porosa, Dicranotaenia tsengi, Diorchis brevis, D. inflatus, Tatria acanthorhyncha, T. decacantha and Diplophallus polymorphus) and four nematodes (Capillaria sp., Eustrongylides tubifex, Con

A Genetic Algorithm optimization model is used in this study to find the optimum flow values of the Tigris river branches near Ammara city, which their water is to be used for central marshes restoration after mixing in Maissan River. These tributaries are Al-Areed, AlBittera and Al-Majar Al-Kabeer Rivers. The aim of this model is to enhance the water quality in Maissan River, hence provide acceptable water quality for marsh restoration. The model is applied for different water quality change scenarios ,i.e. , 10%,20% increase in EC,TDS and BOD. The model output are the optimum flow values for the three rivers while, the input data are monthly flows(1994-2011),monthly water requirements and water quality parameters (EC, TDS, BOD, DO and