Objectives: The present study aims at detecting the depression among nurses who provide care for infected patients with corona virus phenomenon and to find out relationships between the depression and their demographic characteristics of age, gender, marital status, type of family, education, and years of experience of nurses in heath institutions, infection by corona virus, and their participation in training courses.
Methodology: A descriptive study is established for a period from October 10th, 2020 to April 15th, 2021. The study is conducted on a purposive (non-probability) sample of (100) nurse who are providing care for patients with COVID-19 and they are selected from the isolation wards. The instrument of the study is developed from Patients’ Health Questionnaire (PHQ) to achieve the study objectives. Content validity of the instrument is determined through panel of experts and internal consistency reliability is obtained through pilot study. Data are collected through the use of the questionnaire and analyzed through the application of descriptive and inferential statistical approaches which are applied by using SPSS version 22.
Results: The results of the present study showed that nurses who were providing care for patients with COVID-19 age group (30-39 years) )37%(, males constituent the higher percentage than female 87%, (77%) of them is married, (59%) Small family of Nurses, )64%( level of education among nurses have diploma in nursing, and they have (1-5) years of experience in heath institutions among nurses about (40%), also (61%) of nurses not sharing in epidemiological training courses, and (58%) of nurses had previous work in isolation wards, (39%) of nurses have source of information from network, duration of work in isolation wards is (83%) of nurses who are work for more than four weeks, (70%) of nurses are not infected with corona virus, (96%) of nurses are having no history of mental disorders, (54%) of nurses are not drinking alcohol and having no problem with drug abuse. By using PHQ-9, the study finds that depression among nurses is (43%).
Recommendations: Psychological care counseling and guidance are necessary to increase nurses’ vulnerability and strengthen their mental health which helps to encounter any psychological burden caused by COVID 19 pandemic.
Background: Obesity is considered an important risk factor for periodontal disease. It has been reported that reactive oxygen species linking both diseases, systemic melatonin supplementation as antioxidant therapy, was addressed as an adjuvant to scaling and root surface debridement (SRP) to enhance the treatment of periodontitis. Objective: To investigate the efficacy of systemic melatonin administration in periodontitis-obese patients as an adjuvant to scaling and root surface debridement (SRP). Methods: A randomized clinical trial was conducted at a dental-specialized center. Eighty subjects were included and allocated into group-I: twenty periodontium-healthy, normal-weight people; group-II: 30 obese patients with stage-III tre
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Background: The present study aimed to assess the distribution, prevalence, severity of malocclusion in Baghdad governorate in relation to gender and residency Materials and Methods: A multi-stage stratified sampling technique was used in this investigation to make the sample a representative of target population. The sample consisted of 2700 (1349 males and 1351 females) intermediate school students aged 13 years representing 3% of the total target population. A questionnaire was used to determine the perception of occlusion and orthodontic treatment demand of the students and the assessment procedures for occlusal features by direct intraoral measurement using veriner and an instrument to measure the rotated and displaced teeth. Results a
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Plagiarism is becoming more of a problem in academics. It’s made worse by the ease with which a wide range of resources can be found on the internet, as well as the ease with which they can be copied and pasted. It is academic theft since the perpetrator has ”taken” and presented the work of others as his or her own. Manual detection of plagiarism by a human being is difficult, imprecise, and time-consuming because it is difficult for anyone to compare their work to current data. Plagiarism is a big problem in higher education, and it can happen on any topic. Plagiarism detection has been studied in many scientific articles, and methods for recognition have been created utilizing the Plagiarism analysis, Authorship identification, and
... Show MoreIndividuals across different industries, including but not limited to agriculture, drones, pharmaceuticals and manufacturing, are increasingly using thermal cameras to achieve various safety and security goals. This widespread adoption is made possible by advancements in thermal imaging sensor technology. The current literature provides an in-depth exploration of thermography camera applications for detecting faults in sectors such as fire protection, manufacturing, aerospace, automotive, non-destructive testing and structural material industries. The current discussion builds on previous studies, emphasising the effectiveness of thermography cameras in distinguishing undetectable defects by the human eye. Various methods for defect
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For several applications, it is very important to have an edge detection technique matching human visual contour perception and less sensitive to noise. The edge detection algorithm describes in this paper based on the results obtained by Maximum a posteriori (MAP) and Maximum Entropy (ME) deblurring algorithms. The technique makes a trade-off between sharpening and smoothing the noisy image. One of the advantages of the described algorithm is less sensitive to noise than that given by Marr and Geuen techniques that considered to be the best edge detection algorithms in terms of matching human visual contour perception.
Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, auto
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The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz
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