According to the European Union Water Framework Directive requirements, diatom metrics were used to assess the ecological status of surface waters in the Gaziantep central catchment (Turkey). A total of 42 diatom taxa were identified. A few environmental factors (especially lead, copper, orthophosphate, and chromium) played significant roles on the distribution of diatom assemblages among the sampling stations. The first two axes of the canonical correspondence analysis elucidated 91.6 % of the species–environment correlations with 13.9 % of the cumulative variance of species. The applied diatom indices (TIT – Trophic Index Turkey, TI – Trophic Index, and EPI-D – Eutrophication and/or Pollution Index-Diatom) showed different results in the evaluation of the ecological status of sampling stations. The results of TIT and TI indicate that Kıratlı creek has a poor ecological condition, while a good ecological condition was reported by the EPI-D index. This creek is associated with relatively high nutrient values (e.g., 91.1 µg L–1 P-PO4, 8.6 mg L–1 N-NO3, 0.59 mg L–1 N-NO2, and 97.5 mg L–1 SO4) and characterized by pollution-tolerant taxa (e.g., Amphora ovalis Cocconeis placentula Cyclotella meneghiniana Gomphonema parvulum Fragilaria biceps, and Navicula trivialis). The results of the Spearman correlation analysis reveal that TIT has a significant positive correlation with P-PO4 (p < 0.01, r = 0.780), conductivity (p < 0.01, r = 0.769), N-NO3 (p < 0.01, r = 0.714), and N-NO2 (p < 0.01, r = 0.778). Our results show that TIT is a suitable diatom metric to assess the ecological status of surface waters in the Gaziantep central catchment and for the Mediterranean region in general.
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 MoreBipedal robotic mechanisms are unstable due to the unilateral contact passive joint between the sole and the ground. Hierarchical control layers are crucial for creating walking patterns, stabilizing locomotion, and ensuring correct angular trajectories for bipedal joints due to the system’s various degrees of freedom. This work provides a hierarchical control scheme for a bipedal robot that focuses on balance (stabilization) and low-level tracking control while considering flexible joints. The stabilization control method uses the Newton–Euler formulation to establish a mathematical relationship between the zero-moment point (ZMP) and the center of mass (COM), resulting in highly nonlinear and coupled dynamic equations. Adaptiv
... 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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