This study was carried out in the bee laboratory in the Faculty of Agriculture –University of Kufa in September 2021 to evaluate some protein sources and hive products against the oriental hornet Vespa orientalis Linnaeus 1771 (Hymenoptera: Vespidae). The food sources included: beef meat, gut fish, beef lung, honeybee, wax, propolis, pollen, bee worker, and water, in addition to control which was an empty petri dish. The number of visits and their duration were calculated. The results showed that the wasps preferred bee honey and wax significantly higher than the rest of the stimuli.

This work is concerned with designing two types of controllers, a PID and a Fuzzy PID, to be used
for flying and stabilizing a quadcopter. The designed controllers have been tuned, tested, and
compared using two performance indices which are the Integral Square Error (ISE) and the Integral
Absolute Error (IAE), and also some response characteristics like the rise time, overshoot, settling
time, and the steady state error. To try and test the controllers, a quadcopter mathematical model has
been developed. The model concentrated on the rotational dynamics of the quadcopter, i.e. the roll,
pitch, and yaw variables. The work has been simulated with “MATLAB”. To make testing the
simulated model and the controllers m

Objective: To identify the effectiveness of instruction oriented intervention for primipara women upon episiotomy and self
perineal care.
Methodology: A quasi-experimental study was carried out to determine the effectiveness of instruction-oriented
intervention for primipara women upon episiotomy and self-perineal care. A purposive "non-probability" sample of (60)
primipara mothers was selected from Ibn AL-Balady Pediatric and Maternity Hospital, Al-russafa, Baghdad. The sample
has been divided into two groups; (30) primipara women who were considered as a study group, and another (30) primipara
women who were considered as a control one. The study group was exposed to an instruction-oriented intervention. While,
the

The rise of antibiotic-resistant bacteria necessitates the exploration of novel antimicrobial agents. Yttrium oxide nanoparticles (Y₂O₃) have shown potential due to their unique physicochemical properties and antibacterial activities against various pathogens. This study investigates the cytotoxic and antibacterial effects of Y₂O₃ nanoparticles against Serratia fonticuli and Citrobacter koseri, bacteria isolated from cholangitis patients. Bacterial strains were isolated from bile specimens and confirmed using standard microbiological techniques. The methods of X-ray diffraction (XRD), (SEM), and Frequency transform-infrared spectroscopic (FT-IR) were used to characterize YO₃ particles. Using a microdilution technique, the minimum

Quorum sensing (QS) is a perfectly orchestrated molecular communication system. It is a boon for Klebsiella pneumoniae, and bane for the host. This system is believed to make K. pneumoniae a leading cause of multidrug-resistant (MDR) nosocomial infections. This study aimed to investigate the antibacterial and anti-biofilm potential of medicinal plant extracts through interfering with QS of K. pneumoniae. The effect of different concentrations of ethanolic extracts of cinnamon and clove on K. pneumoniae was determined by analyzing the growth curve, survival assay (MTT), Qualitative and quantitative biofilm formation, antibiotic resistance, along with studying gene expression of the genes encoding the above traits, using quantitative real tim

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

This 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

The research included preparation of new Schiff base (L) by two steps: preparation of precursor [bis(2-formyl-6-methoxyphenyl) succinate] (P) by reacting (3-methoxy salicyl aldehyde) with (succinoyl dichloride) as first step then react the prepared precursor (P) with (ethanethioamide) to have the new Schiff base [bis(2-((ethane thioyl imino) methyl)-6-methoxy phenyl) succinate] (L) as second step. Characterized compounds based on Mass spectra, 1 H, 13CNMR (for ligand (L)), FT-IR and UV spectrum, melting point, molar conduct, %C, %H, and %N, the percentage of the metal in complexes %M, magnetic susceptibility, while study corrosion inhibition (mild steel) in acid solution by weight loss. These measurements proved that by (Oxygen, Nitrogen, a

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