Biodiversity is one of the important biological factors in determining water quality and maintaining the
ecological balance. In this study, there are 223 species of phytoplankton were identified, and they are as
follows: 88 species of Bacillariophyta and were at 44%,70 species of Chlorophyta and they were at 29 %, 39
species of Cyanophyta and they were at 16 %, 12 species of Euglenozoa and they were at 4 %, four species of
Miozoa and they were at 3 %, and, Phylum Charophyta and Ochrophyta were only eight and two species,
respectively and both of them were at 2%. The common phytoplankton recorded in the sites studied
include Nitzschia palea, Scenedesmus quadricauda, Oscillatoria princeps, and Peridinium bipes, These
species recorded a significant positive correlation with Ec, Sio3, and WT. Phytoplankton
including Gomphosphaeria semen-Vitis, Dicloster acuatus, Tetrastrum heteracanthum, and Dictyocha fibula,
recorded a significant positive correlation with NO3, PO4, DO, and PH. Water temperature ranged between
14.200 -33.900 ºc in Al-Mansoury and Al-Sada respectively. Electrical conductivity ranged between 2.790 -
11.900 ms/cm in Al-Sada and Al-Mansoury respectively. PH ranged between7.750-8.600 in Al-Dawody and
Al-Mansoury respectively. Dissolved Oxygen (DO) ranged between 5.950 -13.000 mg/l in Al-Dawody and
Al-Mansoury respectively.WT recorded negative correlation with pH (r= - 0.591), NO3-2
(r= - 0.463) and DO
(r= - 0.603). Nitrate ranged between 0.570-12.200 µg /l in Al- and Al-Sada respectively. Phosphate ranged
between 0.003-0.154 µg/l, in Al-Dawody and Al-Mansoury respectively. Silicate ranged between 51.200-
198.600 µg /l in Al-Baraka and Al-Dawody respectively. Shannon - Weiner index (H`) ranged between 2.275-
3.162 in Al-Dawody and Al-Mansoury respectively. Simpson index ranged between 0.856-0.950 in AlMansoury and Al-Sada respectively, while the Evenness index was 0.514-0.933 in Al-Dawody and Al-Baraka
respectively. Shannon- Weiner index (H`) recorded a significant positive correlation with the Simpson index .
Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
... Show MoreThis experiment presented essential oils by GC/MS, pigment content, and their antioxidant activities as well as sensory evaluation of delight samples. Limonene (66.88%) was the most prevalent yield. The peels of clementine had DPPH and ABT Scavenging activity. All levels of pigment extract had better scores for all sensory values and recorded acceptable scores in terms of appearance, color, aroma, and overall acceptability compared to control delight. Besides, delight samples containing 15 mg astaxanthin pigment extract showed maximum sensory scores compared to other samples and control delight. On the other hand, the product was less acceptable to the panelists compared to control in the case of the addition of 3.75 mg astaxanthin pigme
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