Roughness length is one of the key variables in micrometeorological studies and environmental studies in regards to describing development of cities and urban environments. By utilizing the three dimensions ultrasonic anemometer installed at Mustansiriyah university, we determined the rate of the height of the rough elements (trees, buildings and bridges) to the surrounding area of the university for a radius of 1 km. After this, we calculated the zero-plane displacement length of eight sections and calculated the length of surface roughness. The results proved that the ranges of the variables above are Z_H (9.2-13.8) m, Z_d (4.3-8.1) m and Z_o (0.24-0.48) m.

This study included isolation and characterization of extremely halophilic bacteria from Al-Massab Al-Aam region in South of Iraq Fifty isolates were identified by using numerical taxonomy 40 strains belonged to the genus Halobacterium which inclucted Hb. halobium Hb. cutirubrum Hb. salinarium Hb. saccharovorum Hb. valismortis and Hb. volcanii. Ten strains belonged to the genus Halococcus which included Hc. morrhuae Hc. saccharolyticus. Growth curves were sensitive mutants determined for wild type and salt Generation time in logarthmic phase was measured and found to be (10.37 2hr 7 0.59) for Hb. salinarium / 18 (6.490 hr 0.24) for Hb. cutirubrum / 32, (6.700 hr + 0.488) for Hb. valismortis / 20, (11.243 hr + 0.96) for Hb. volcanii / 7. (7

دُرِست العوامل المؤثرة في عدد ساعات تجهيز الكهرباء في مدينة بغداد، وتكونت عينة الدراسة من (365) مشاهدة يومية لعام 2018، وتمثلت بستة متغيرات استعملت في الدراسة. كان الهدف الرئيس هو دراسة العلاقة بين هذه المتغيرات، وتقدير تأثيرات المتغيرات التنبؤية في المتغير التابع (عدد ساعات تجهيز الكهرباء في مدينة بغداد). ولتحقيق ذلك استعملت نمذجة المعادلات الهيكلية/ تحليل المسار وبرنامج AMOS

Interface bonding between asphalt layers has been a topic of international investigation over the last thirty years. In this condition, a number of researchers have made their own techniques and used them to examine the characteristics of pavement interfaces. It is obvious that test findings won't always be comparable to the lack of a globally standard methodology for interface bonding. Also, several kinds of research have shown that factors like temperature, loading conditions, materials, and others have an impact on surface qualities. This study aims to solve this problem by thoroughly investigating interface bond testing that might serve as a basis for a uniform strategy. First, a general explanation of how

Interface bonding between asphalt layers has been a topic of international investigation over the last thirty years. In this condition, a number of researchers have made their own techniques and used them to examine the characteristics of pavement interfaces. It is obvious that test findings won't always be comparable to the lack of a globally standard methodology for interface bonding. Also, several kinds of research have shown that factors like temperature, loading conditions, materials, and others have an impact on surface qualities. This study aims to solve this problem by thoroughly investigating interface bond testing that might serve as a basis for a uniform strategy. First, a general explanation of how the bonding strength

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

Each Intensity Modulated Radiation Therapy (IMRT) plan needs to be tested and verified before any treatment to check its quality. Octavius 4D-1500 phantom detector is a modern and qualified device for quality assurance procedure. This study aims to compare the common dosimetric criteria 3%/3 mm with 2%/2 mm for H&N plans for the IMRT technique. Twenty-five patients with head and neck (H&N) tumor were with 6MV x-ray photon beam using Monaco 5.1 treatment planning software and exported to Elekta synergy linear accelerator then tested for pretreatment verification study using Octavius 4D-1500 phantom detector. The difference between planned and measured dose were assessed by using local and global gamma index (GI) analysis method at