Background The appropriate disposal of medication is a well-recognized issue that has convened growing recognition in several contexts. Insufficient awareness relating to appropriate methods for the disposal of unneeded medicine may result in notable consequences. The current research was conducted among the public in Iraq with the aim of examining their knowledge, attitude, and practices regarding the proper disposal of unused and expired medicines. Methods The present study used an observational cross-sectional design that was community-based. The data were obtained from using an online questionnaire. The study sample included people of diverse genders, regardless of their race or occupational status. The study mandated that all pa

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

Al-Naymi, N.A.Sh., H.A.S. AL-Nuaimi and M.R. Nashaat. 2022. Toxicity Stress of the Durah Power Plant Ash and its Effect on the Alga Chlorococcum humicola (Naeg) Rabenhorst 1868. Arab Journal of Plant Protection, 40(2): 188-192. https://doi.org/10.22268/AJPP-040.2.188192 This study illustrates the acute toxic effect of ash released from Durah power plant (DPP) on the biology of the phytoplankton species Chlorococcum humicola in Iraq. The results showed that the median lethal concentration for killing 50% of the Alga population (LC50) was 0.15 and 0.13 ppt (parts per thousand) for 24 and 48 hours exposure to crude ash concentrations, respectively. In contrast, no LC50 value was recorded for 72 and 96 hrs after exposure. The reduction

Background: One of the most common problem associated with the used of soft denture lining material is microorganisms and fungal growth especially Candida albicans, which can result in chronic mucosal inflammation. The aim of this study was to evaluate the influence of chlorhexidine diacetate (CDA) salt Incorporation into soft denture lining material on antifungal activity; against Candida albicans, and the amount of chlorhexidine di-acetate salt leached out of soft liner/CDA composite. Furthermore, evaluate shear bond strength and hardness after CDA addition to soft liner Materials and methods: chlorhexidine diacetate salt was added to soft denture lining material at four different concentrations (0.05%, 0.1% and 0.2% by weight). Four hund

Wheat straw was modified with malonic acid in order to get low cost adsorbent have a good ability to remove copper and ferric ions from aqueous solutions, chemical modification temperature was 120°C and the time was 12 h. Parameters that affect the adsorption experiments were studied and found the optimum pH were 6 and 5 for copper and iron respectively and the time interval was 120 min and the adsorbent mass was 0.1 g. The values for adsorption isotherms parameters were determined according to Langmuir [qmax were 54.64 and 61.7 mg/g while b values were 0.234 and 0.22 mg/l] , Freundlich [Kf were 16.07 and 18.89 mg/g and n were 2.77 and 3.16], Temkin [B were 0.063 and 0.074 j/mol and At were 0.143 and 1.658 l/g] and for Dubinin-Radushkev