Abstract Objective: The objective of this study was to explore in-depth the impact of after-hours academic work at home on the wellbeing of college pharmacy faculty members. Methods: This qualitative study was conducted through face-to-face individual-based interview with faculty members at the College of Pharmacy, University of Baghdad in Iraq. A purposive sampling was used to enroll faculty with different levels in their academic carrier. Interviews were conducted till reaching the point of saturation. The interviews were conducted from Nov 7 through December 6, 2023. All interviews were audio-recorded. Qualitative interview data were analyzed using thematic analysis. Findings: Twenty faculty members participated in the study: 16 have a P

The objective of this review was to describe the COVID-19 complications after recovery.

Background: Lymphomas are group of diseases caused by malignant lymphocytes that accumulate in lymph nodes and caused the characteristics lymphadenopathy. Occasionally, they may spill over into blood or infiltrate organs outside the lymphoid tissue. The major subdivision of lymphomas is into Hodgkin lymphoma and non–Hodgkin lymphoma and this is based on the histologic presence of Reed-Sternberg cells in Hodgkin lymphoma. Salivary immunoglobulin A is the prominent immunoglobulin and is considered to be the main specific defense mechanism in oral cavity. The aim of this study was to determine the level of salivary immunoglobulin A in lymphoma patients before and after chemotherapy treatment. Subjects, materials and methods: The study i

Background: Since the periodontal disease Index of Ramfjord (Ramfjord index) can potentially shorten the examination time by almost half, many studies evaluated Ramfjord teeth in predicting full-mouth periodontal status of an adult population. The aim of this study was to evaluate the benefit of Ramfjord teeth in predicting the full-mouth clinical attachment level of an adult population in patients attending the college of dentistry- Baghdad University. Materials and methods: The study participants were 100 patients with age range from 30-60 years old which represent group zero. The patients were divided into three main groups according to the age of the patients. Group I and group II each of them composed of 30 patients while group III co

The purpose of this study was to evaluate the anesthetic effectiveness of a buccal infiltration technique combined with local massage (using 2% lidocaine) in the extraction of mandibular premolars to be utilized as an alternative to the conventional inferior alveolar nerve block.

Organic light emitting diodes (OLEDs) were fabricated containing host molecule of conjugated polymer MEH-PPV poly (2-methoxy-5-(2'-ethylhexyloxy)-1,4-phenlenevinylene) which was dissolved in chloroform solvent and doped with guest molecules MWCNTs that were dissolved in DMF solvent with different volume ratios 0.05 and 0.15, nanocomposite system which acts as active layer in OLEDs device. The Poly(3,4-ethylenedioxythiophene):poly-(styrenesulfonate) "PEDOT:PSS" and Tris98-hydroxyquinoline) aluminum "Alq3" as hole transport layer HTL and electron transport layer ETL were used respectively, to enhanced the injection charge from the electrodes to the active layer. Spin coating method used for achieving facile and low cost OLED. The absorption s

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class