<p>In combinatorial testing development, the fabrication of covering arrays is the key challenge by the multiple aspects that influence it. A wide range of combinatorial problems can be solved using metaheuristic and greedy techniques. Combining the greedy technique utilizing a metaheuristic search technique like hill climbing (HC), can produce feasible results for combinatorial tests. Methods based on metaheuristics are used to deal with tuples that may be left after redundancy using greedy strategies; then the result utilization is assured to be near-optimal using a metaheuristic algorithm. As a result, the use of both greedy and HC algorithms in a single test generation system is a good candidate if constructed correctly. T

Background: Tooth wear is one of the most concerning problems of the current dental practice especially among older subjects. The aim of this study is to determine the severity of tooth wear and its relation with selected salivary variables (salivary pH and vitamin C level) among a group of older adults in Mosul city/Iraq. Materials and methods: All subjects (30 subjects) of both gender tookpart in the current study; sixteen of them were older adults (55-65 years) and compared with fourteen middle-aged adults (30-40 years) at Textile factory in Mosul city/Iraq. Unstimulated salivary samples were collected and salivary pH was immediately measured. Salivary vitamin C level was determined colormetrically. Severity of tooth wear was determined

The aim of t his p aper is t o const ruct t he (k,r)-caps in t he p rojective 3-sp ace PG(3,p ) over Galois field GF(4). We found t hat t he maximum comp let e (k,2)-cap which is called an ovaloid, exist s in PG(3,4) when k = 13. Moreover t he maximum (k,3)-cap s, (k,4)-cap s and (k,5)-caps.

Background: Odontogenic cysts are characterized by their sluggish growth and ability to enlarge, primarily affecting the oral and maxillofacial tissues. Timely diagnosis and treatment are crucial to prevent potentially serious consequences. The present study aimed to evaluate and compare the immunohistochemical expression of cytokeratin 19 in the epithelium of odontogenic keratocyst, dentigerous, and radicular cysts.

Methods: This study analyzed forty-five formalin-fixed, paraffin-embedded tissue blocks containing odontogenic cysts. The sample consisted of fifteen odontogenic keratocysts, fifteen dentigerous cysts, and

This study was conducted to investigate phytoplasma causing a virescence disease on Arabic jasmine Jasminum sambac based on microscopy and molecular approaches. Samples were collected from symptomatic Arabic jasmine plants grown in nurseries in Baghdad-Iraq. Specimens from infected plants were prepared and Dienes stained for light microscopy examination. Phytoplasma were detected in infected plants by polymerase chain reaction (PCR) using P1/P7 and SecAfor1/SecArev3 Candidatus Phytoplasma specific primer sets. Light microscopy test showed symptomatic Arabic jasmine plants were phytoplasms infected when phloem tissues were stained with a dark blue color. PCR test confirmed the symptomatic plants were phytoplasms infected when SecAfor1/Sec

Cysteine-cysteine chemokine ligand 5 (CCL5) is known to play an important role with immunoregulatory and inflammatory activities in the formation of granuloma during infection with Mycobacterium tuberculosis. About 90 subjects, involving 50 patients with pulmonary TB and 40 apparently healthy individuals (as a control group) were collected from primary health care center\AL-Sadur city sector/ Baghdad City/ Iraq, and at specialized chest and respiratory diseases center in Wassit City /Iraq during the period from January 2019 to May 2019. The study was carried out to investigate serum level of CCL-5 of both patients and control by using enzyme linked immunosorbent assay (ELISA), and to determine the association between CCL5 genotypes with pul

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.