Degradation is one of the key processes governing the impact of pharmaceuticals in the aquatic environment. Most studies on the degradation of pharmaceuticals have focused on soil and sludge, with fewer exploring persistence in aquatic sediments. We investigated the dissipation of 6 pharmaceuticals from different therapeutic classes in a range of sediment types. Dissipation of each pharmaceutical was found to follow first‐order exponential decay. Half‐lives in the sediments ranged from 9.5 (atenolol) to 78.8 (amitriptyline) d. Under sterile conditions, the persistence of pharmaceuticals was considerably longer. Stepwise multiple linear regression analysis was performed to explore the relationships between half‐lives of the pharmaceuticals, sediment physicochemical properties, and sorption coefficients for the compounds. Sediment clay, silt, and organic carbon content and microbial activity were the predominant factors related to the degradation rates of diltiazem, cimetidine, and ranitidine. Regression analysis failed to highlight a key property which may be responsible for observed differences in the degradation of the other pharmaceuticals. The present results suggest that the degradation rate of pharmaceuticals in sediments is determined by different factors and processes and does not exclusively depend on a single sediment parameter.
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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