ABSTRACT: BACKGROUND: Breast reduction for mammary hypertrophy is a highly effective procedure with high degree of patient satisfaction. There are many methods of breast reduction which involve removal of excess tissue with reshaping of overlying skin while maintaining a viable nipple areolar complex. OBJECTIVE: The purpose of this study is to evaluate the use of the superomedial technique as an effective method for reduction mammoplasty. PATIENTS AND METHODS: A total of 30 patients underwent reduction mammoplasty by utilizing superomedial pedicle technique between 2010 and 2013. Those patients were evaluated postoperatively in terms of their aesthetic and functional satisfaction, viability of nipple – areolar complex and nipple sensory preservation. RESULTS: The distance from suprasternal notch to nipple ranged 28-32cm on both breasts. The mean breast tissue resection was less than 1000 g on both breasts, the amount of nipple transposition ranged from 8cm – 10cm. All patients were satisfied with postoperative results. All patients had viable nipple, except in one breast who had partial nipple – areolar complex necrosis (1.6%). nipple areolar sensation was preserved in 93.3% in the immediate postoperative period, and after 6 month all patient had preserved nipple areolar sensation. CONCLUSION: The superomedial pedicle technique for reduction mammaplasty is simple and safe procedure with good postoperative aesthetic results. KEY WORDS: reduction mammoplasty, superomedial pedicle, nipple areolar complex.
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Little is known about hesitancy to receive the COVID‐19 vaccines. The objectives of this study were (1) to assess the perceptions of healthcare workers (HCWs) and the general population regarding the COVID‐19 vaccines, (2) to evaluate factors influencing the acceptance of vaccination using the health belief model (HBM), and (3) to qualitatively explore the suggested intervention strategies to promote the vaccination.
This was a cross‐sectional study based on electronic survey data that was collected in Iraq during December first‐19th, 2020. The electronic surve
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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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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
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