This research discusses the verbal follow phenomenon in Al-Amali Abi Al-Qali’s book (seq.356 Hijri). It aims to limit the examples of this phenomenon in the book, and examine it phonologically. Accordingly, the researcher adopted the analaytical descriptive approach, taking into account Al-Rawi’s letter when ordering the verbal follow-based examples, and the order they took in the book in question. The purposes behind this phonological study of verbal follow in Al-Amali’s book are to: reach the sounds which Arabs prefer in the process of following, confirm different beautiful and desirable senses, have easy and speedy pronunciation, maintain harmony between adjacent sounds, count the sounds that occur at the beginning of the follower- a disputable phonological issue between the follower and following- and spot the phonological change that occurs to the follower. Accordingly, a caution is needed to maintain harmony and homogeneity between two pronunciations to achieve the process of following. Or, the structure of the word follower is changed to match its peer followed word.The study has shown that Al-Qali was the eldest in dealing with the formal aspect of the phenomenon. He pointed to the idea of merging the last letter in the subordinate and the follower, and compared it with a stylistic, artistic, and acoustic characteristic, which is included in the innate rhetoric, i.e., assonance. By that, he has determined the most important formal acoustic features of the rhythmic complex as represented by the endings of the sequences, which have a musical rhythm.
Abstract:
Objective: To self-evaluate the effect of SBAR (Situation, Background, Assessment, and Recommendation) educational program on nurse and midwives practices in maternal health report documentation accuracy.
Methods: A quasi- experimental design was carried with the application of pre- post test for nurses and midwives’ knowledge and practices regarding SBAR communication tool. The study was held in Al-Elwia maternity teaching hospital, Al –Karckh maternity hospital and Al-Yarmouk teaching Hospital. purposive sample as it was convenient with inclusion criteria consisted of (84) nurse and midwives. The questionnaire comprised of demographic data, nurses- midwives practices of SBAR using (5) level Likert scale for assessme
An experiment was conducted in pots under field conditions during fall seasons of 2017 and 2018. This study aimed to improve a weak growth of seedlings under salt stress in sorghum. Three factors were studied. 1st factor was three cultivars (Inqath, Rabeh, and Buhoth70). 2nd factor was seed priming (primed and unprimed seed). Seed were primed by soaking for 12 hours in a solution containing 300 + 70 mg L−1 of gibberellic (GA3) and salicylic (SA) acids, respectively. 3rd factor was irrigation with saline water (6, 9 and 12 dS m−1) resulting from dissolving sodium chloride in distilled water in addition to control treatment (distilled water). Randomized complete block design was used with four replications. In both seasons: the results sh
... Show MoreWe aimed to obtain magnesium/iron (Mg/Fe)-layered double hydroxides (LDHs) nanoparticles-immobilized on waste foundry sand-a byproduct of the metal casting industry. XRD and FT-IR tests were applied to characterize the prepared sorbent. The results revealed that a new peak reflected LDHs nanoparticles. In addition, SEM-EDS mapping confirmed that the coating process was appropriate. Sorption tests for the interaction of this sorbent with an aqueous solution contaminated with Congo red dye revealed the efficacy of this material where the maximum adsorption capacity reached approximately 9127.08 mg/g. The pseudo-first-order and pseudo-second-order kinetic models helped to describe the sorption measure
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
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