Pub Date : 2023-02-04DOI: 10.24017/science.2023.1.2
Yousif Abdalla Qadr, Azad A. Ismail
This study aimed to find out the level of stress and coping methods among elderly in Sulaimanya city during the pandemic COVID-19. Through the snowballing sampling method, 394 elders were included to this study. After validation, two scales were used in this study; stress subscale from Depression, Anxiety and Stress Scale (DASS-21) and a culture-bound scale for determining coping methods. The results of this study showed that participants experienced a mild level of stress. Male participants, elders who live with their family, unvaccinated elders, physically passive elders have had higher stress level than female, elderly home, vaccinated, physical active elders. The findings also indicated that spiritual connection was the most common coping method used by the sample. Results of this study are the first and foremost way to share elder's unexpressed messages; it also can be a way for verbalizing their unspoken feelings. These results may also inform the elder's caregivers that elder's stress level and illness anxiety was not very high, strengthening their social support and spiritual connection may help them to reduce their distress into a lesser degree.
{"title":"Stress and Coping Among Elderly During The COVID-19 Pandemic in Sulaimanya City in Kurdistan Region of Iraq","authors":"Yousif Abdalla Qadr, Azad A. Ismail","doi":"10.24017/science.2023.1.2","DOIUrl":"https://doi.org/10.24017/science.2023.1.2","url":null,"abstract":"This study aimed to find out the level of stress and coping methods among elderly in Sulaimanya city during the pandemic COVID-19. Through the snowballing sampling method, 394 elders were included to this study. After validation, two scales were used in this study; stress subscale from Depression, Anxiety and Stress Scale (DASS-21) and a culture-bound scale for determining coping methods. The results of this study showed that participants experienced a mild level of stress. Male participants, elders who live with their family, unvaccinated elders, physically passive elders have had higher stress level than female, elderly home, vaccinated, physical active elders. The findings also indicated that spiritual connection was the most common coping method used by the sample. Results of this study are the first and foremost way to share elder's unexpressed messages; it also can be a way for verbalizing their unspoken feelings. These results may also inform the elder's caregivers that elder's stress level and illness anxiety was not very high, strengthening their social support and spiritual connection may help them to reduce their distress into a lesser degree.","PeriodicalId":17866,"journal":{"name":"Kurdistan Journal of Applied Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42148432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-03DOI: 10.24017/science.2023.1.1
Soma I. Majeed, Sulaf Mustafa Mohammed, Ali Mustafa Mohammad
In the recent years, MgO nanoparticles (MgO NPs) have been one of the metal oxide nanoparticles that used in various medicinal fields. Despite MgO NPs' widespread use, a little is known regarding their cytotoxic effects on health. The purpose of this study was to determine the toxic dose of MgO NPs that prepared by the sol-gel method and the roles of vitamins E and C in the toxicity that is produced by MgO NPs. The MgO NPs were characterized and several amounts (62.5, 125, 250, and 500 mg/kg BW) were orally administrated for 28 days to male Wister rats. Toxic dosimetry was evaluated using metal content analysis, hematological, biochemical, histopathological, and serum ROS estimation. Then toxic doses of MgO NPs were administered orally with vitamins E and C, or a combination of them for six weeks, twice a week. The result showed 500 mg/kg bw/day MgO NPs is considered as a toxic and leads to a significant Mg bioaccumulation in the liver (P < 0.001) and significantly increased serum ROS (P<0.001) and histopathological damage in the liver and kidney with an immunologic response. Administration of vitamin E with MgO NPs significantly increased serum ROS and adversely affected blood parameters and histological damage to the liver and kidney. The combination of vitamins E and C with MgO NPs significantly reduced the immunologic response to MgO NPs, but serum ROS levels increased significantly with histopathological damage in vital organs. Vitamin C significantly reduced MgO NPs-induced damage in kidney and liver tissues. In the conclusion, MgO NPs are toxic at high doses. Administration of vitamin E alone or combined vitamin E and C with toxic doses of MgO NPs increases their toxicity. However, vitamin C was shown to be histopathologically protective. Therefore, a serious caution should be considered when vitamins are administered with nanoparticles.
{"title":"Bioaccumulation and Evaluation of Magnesium Oxide Nanoparticles Toxicity and Combination Effects of Vitamin E and C with it on Exposed Male Rats","authors":"Soma I. Majeed, Sulaf Mustafa Mohammed, Ali Mustafa Mohammad","doi":"10.24017/science.2023.1.1","DOIUrl":"https://doi.org/10.24017/science.2023.1.1","url":null,"abstract":"In the recent years, MgO nanoparticles (MgO NPs) have been one of the metal oxide nanoparticles that used in various medicinal fields. Despite MgO NPs' widespread use, a little is known regarding their cytotoxic effects on health. The purpose of this study was to determine the toxic dose of MgO NPs that prepared by the sol-gel method and the roles of vitamins E and C in the toxicity that is produced by MgO NPs. The MgO NPs were characterized and several amounts (62.5, 125, 250, and 500 mg/kg BW) were orally administrated for 28 days to male Wister rats. Toxic dosimetry was evaluated using metal content analysis, hematological, biochemical, histopathological, and serum ROS estimation. Then toxic doses of MgO NPs were administered orally with vitamins E and C, or a combination of them for six weeks, twice a week. The result showed 500 mg/kg bw/day MgO NPs is considered as a toxic and leads to a significant Mg bioaccumulation in the liver (P < 0.001) and significantly increased serum ROS (P<0.001) and histopathological damage in the liver and kidney with an immunologic response. Administration of vitamin E with MgO NPs significantly increased serum ROS and adversely affected blood parameters and histological damage to the liver and kidney. The combination of vitamins E and C with MgO NPs significantly reduced the immunologic response to MgO NPs, but serum ROS levels increased significantly with histopathological damage in vital organs. Vitamin C significantly reduced MgO NPs-induced damage in kidney and liver tissues. In the conclusion, MgO NPs are toxic at high doses. Administration of vitamin E alone or combined vitamin E and C with toxic doses of MgO NPs increases their toxicity. However, vitamin C was shown to be histopathologically protective. Therefore, a serious caution should be considered when vitamins are administered with nanoparticles.","PeriodicalId":17866,"journal":{"name":"Kurdistan Journal of Applied Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49669810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-15DOI: 10.24017/science.2022.2.10
Chra Ali Kamal, Manal Ali Atiyah
Today, diabetes is one of the most common chronic diseases in the world due to the people’s sedentary lifestyle which led to many health issues like heart attack, kidney frailer and blindness. Additionally, most of the people are unrealizable about the early-stage diabetes symptoms to prevent it. The above reasons were encouraging to develop a diabetes prediction system using machine learning techniques. The Pima Indian Diabetes Dataset (PIDD) was utilized for this framework as it is common and appropriate dataset in .CSV format. While there were not any duplicate or null values, however, some zero values were replaced, four outlier records were removed and data standardization were performed in the dataset. In addition, this project methodology divided into two phases of model selection. In the first phase, two different hyper parameter techniques (Randomized Search and TPOT(autoML)) were used to increase the accuracy level for each algorithm. Then six different algorithms (Logistic Regression, Decision Tree, Random Forest, K-nearest neighbor, Support Vector Machine and Naïve Bayes) were applied. In the second phase, the four best performed algorithms (with best estimated parameters for each of them) were chosen and used as an input for the voting classifier, because it applies to find the best algorithm between a group of multiple options. The result was satisfying, and Random Forest was achieved 98.69% in second stage, while its accuracy level was 81.04% in the previous one and it utilized to predict diabetes via a simple graphic user interface.
{"title":"Predict Diabetes Using Voting Classifier and Hyper Tuning Technique","authors":"Chra Ali Kamal, Manal Ali Atiyah","doi":"10.24017/science.2022.2.10","DOIUrl":"https://doi.org/10.24017/science.2022.2.10","url":null,"abstract":"Today, diabetes is one of the most common chronic diseases in the world due to the people’s sedentary lifestyle which led to many health issues like heart attack, kidney frailer and blindness. Additionally, most of the people are unrealizable about the early-stage diabetes symptoms to prevent it. The above reasons were encouraging to develop a diabetes prediction system using machine learning techniques. The Pima Indian Diabetes Dataset (PIDD) was utilized for this framework as it is common and appropriate dataset in .CSV format. While there were not any duplicate or null values, however, some zero values were replaced, four outlier records were removed and data standardization were performed in the dataset. In addition, this project methodology divided into two phases of model selection. In the first phase, two different hyper parameter techniques (Randomized Search and TPOT(autoML)) were used to increase the accuracy level for each algorithm. Then six different algorithms (Logistic Regression, Decision Tree, Random Forest, K-nearest neighbor, Support Vector Machine and Naïve Bayes) were applied. In the second phase, the four best performed algorithms (with best estimated parameters for each of them) were chosen and used as an input for the voting classifier, because it applies to find the best algorithm between a group of multiple options. The result was satisfying, and Random Forest was achieved 98.69% in second stage, while its accuracy level was 81.04% in the previous one and it utilized to predict diabetes via a simple graphic user interface. ","PeriodicalId":17866,"journal":{"name":"Kurdistan Journal of Applied Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47377436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-15DOI: 10.24017/science.2022.2.11
Abdalbasit Mohammed Qadir, Dana Faiq Abd
There are several disease kinds in global populations that may be related to human lifestyles, social, genetic, economic, and other factors related to the nature of the country they live in. Most of the recent studies have focused on investigating prevalent diseases that spread in the population in order to minimize mortality risks, choose the best method for treatment, and improve community healthcare. Kidney disease is one of the most widespread health problems in modern society. This study focuses on kidney stones, cysts, and tumors, the three most common types of renal illness, using a dataset of 12,446 CT urogram and whole abdomen images, aiming to move toward an AI-based kidney disease diagnosis system while contributing to the wider field of artificial intelligence research. In this study, a hybrid technique is used by utilizing both pre-train models for feature extraction and classification using machine learning algorithms for the task of kidney disease image diagnosis. The pre-trained model used in this study is the Densenet-201 model. As well as using Random Forest for classification, the Densenet-201-Random-Forest approach has outperformed many of the previous models used in other studies, having an accuracy rate of 99.719 percent.
{"title":"Kidney Diseases Classification using Hybrid Transfer-Learning DenseNet201-Based and Random Forest Classifier","authors":"Abdalbasit Mohammed Qadir, Dana Faiq Abd","doi":"10.24017/science.2022.2.11","DOIUrl":"https://doi.org/10.24017/science.2022.2.11","url":null,"abstract":"There are several disease kinds in global populations that may be related to human lifestyles, social, genetic, economic, and other factors related to the nature of the country they live in. Most of the recent studies have focused on investigating prevalent diseases that spread in the population in order to minimize mortality risks, choose the best method for treatment, and improve community healthcare. Kidney disease is one of the most widespread health problems in modern society. This study focuses on kidney stones, cysts, and tumors, the three most common types of renal illness, using a dataset of 12,446 CT urogram and whole abdomen images, aiming to move toward an AI-based kidney disease diagnosis system while contributing to the wider field of artificial intelligence research. In this study, a hybrid technique is used by utilizing both pre-train models for feature extraction and classification using machine learning algorithms for the task of kidney disease image diagnosis. The pre-trained model used in this study is the Densenet-201 model. As well as using Random Forest for classification, the Densenet-201-Random-Forest approach has outperformed many of the previous models used in other studies, having an accuracy rate of 99.719 percent.","PeriodicalId":17866,"journal":{"name":"Kurdistan Journal of Applied Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44879080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-09DOI: 10.24017/science.2022.2.9
Dashne Abdulla Salih, K. Karim
Spermatogenesis and male phenotypic development during puberty are mainly done by androgen and their function is regulated by the androgen receptor (AR) gene. This gene has a polymorphism site in Exon1 which encode androgen receptor and have various length of CAG trinucleotide repeat which causes the production of polyglutamine chain in different length of the N-terminal domain of AR protein which reduces producing sperm by disrupting spermatogenesis. The aim is to determine the relation of infertility in male with the increased frequency of CAG repeats in the AR gene, and the correlation between CAG repetition and hormonal changes. The case-control research was carried out in the Immunogene center and IVF center in the maternity teaching hospital Erbil-Kurdistan region-Iraq. The convenience sample included 50 men, 30 infertile and 20 fertile over one year starting from March 2021 to March 2022. Men with infertility had CAG repeats in their AR gene, ranging from (17-26) repeats, with a mean (21.3 ±0.16). In infertile men, CAG expansion was longer than the fertile men. The motility and normal morphology of sperm in infertile men have negative relation while sperm count and concentration have a positive relation with CAG expansion. The relation of hormones (Testosterone, LH, and FSH) with CAG repetition was statistically not significant. In conclusion, CAG expansion was longer in infertile (case) men compared with fertile (control) men. Polyglutamine effect on increasing sperm abnormal morphology and immotility which is the reason for infertility but statistically not significant and it will not affect hormonal assay in infertile men.
{"title":"CAG Expansion in Androgen Receptor Gene of Infertile Men in Erbil Governorate","authors":"Dashne Abdulla Salih, K. Karim","doi":"10.24017/science.2022.2.9","DOIUrl":"https://doi.org/10.24017/science.2022.2.9","url":null,"abstract":"Spermatogenesis and male phenotypic development during puberty are mainly done by androgen and their function is regulated by the androgen receptor (AR) gene. This gene has a polymorphism site in Exon1 which encode androgen receptor and have various length of CAG trinucleotide repeat which causes the production of polyglutamine chain in different length of the N-terminal domain of AR protein which reduces producing sperm by disrupting spermatogenesis. \u0000The aim is to determine the relation of infertility in male with the increased frequency of CAG repeats in the AR gene, and the correlation between CAG repetition and hormonal changes. \u0000The case-control research was carried out in the Immunogene center and IVF center in the maternity teaching hospital Erbil-Kurdistan region-Iraq. The convenience sample included 50 men, 30 infertile and 20 fertile over one year starting from March 2021 to March 2022. \u0000Men with infertility had CAG repeats in their AR gene, ranging from (17-26) repeats, with a mean (21.3 ±0.16). In infertile men, CAG expansion was longer than the fertile men. The motility and normal morphology of sperm in infertile men have negative relation while sperm count and concentration have a positive relation with CAG expansion. The relation of hormones (Testosterone, LH, and FSH) with CAG repetition was statistically not significant. \u0000In conclusion, CAG expansion was longer in infertile (case) men compared with fertile (control) men. Polyglutamine effect on increasing sperm abnormal morphology and immotility which is the reason for infertility but statistically not significant and it will not affect hormonal assay in infertile men.","PeriodicalId":17866,"journal":{"name":"Kurdistan Journal of Applied Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49025260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-03DOI: 10.24017/science.2022.2.8
Shaho Muhammad Wstabdullah, H. Hamarashid, Muhammed Ali Kamal
Autoregressive Distributed Lag (ARDL) is possible when cointegration analysis is applied to experimentally to shape the relationship between the variables without considering the regressors are stationary at its first difference or level, there is an integration of order one or both of the variables are mixed. Being based on one equation framework is a benefit of using the ARDL model, in order to take sufficient lags’ number and directing process data generation process in a modelling framework that goes from general to specific. The aim of this study is to focus on the trend of the relation between the GBP/USD rate and Brent Oil prices, which is done through the adoption of dependent variable which the oil price and the independent variable which is the dollar exchange rate. Another target of the research is to show the relationship between gold price and oil prices. The result shows that there are a number of likely influenced variable through by which the dollar-pound rate has effects on the demand and supply of oil as a result of its prices. That is done through the analysis of the relations between the variables of the study. Moreover, correlation coefficient values are given that there exists a positive explanatory correlation between the variables of the study. On the whole, there exists a positive long-term equilibrium relation between the GBP/USD exchange rate, price of oil and price of gold. Any change in the exchange rate of GBP/USD is causing the changes in prices of Brent oil.
{"title":"An Approach To Study The Effects of GBP/USD Exchange Rate and Gold Prices on Brent Oil Prices Using Autoregressive Distributed Lag (ARDL)","authors":"Shaho Muhammad Wstabdullah, H. Hamarashid, Muhammed Ali Kamal","doi":"10.24017/science.2022.2.8","DOIUrl":"https://doi.org/10.24017/science.2022.2.8","url":null,"abstract":"Autoregressive Distributed Lag (ARDL) is possible when cointegration analysis is applied to experimentally to shape the relationship between the variables without considering the regressors are stationary at its first difference or level, there is an integration of order one or both of the variables are mixed. Being based on one equation framework is a benefit of using the ARDL model, in order to take sufficient lags’ number and directing process data generation process in a modelling framework that goes from general to specific. The aim of this study is to focus on the trend of the relation between the GBP/USD rate and Brent Oil prices, which is done through the adoption of dependent variable which the oil price and the independent variable which is the dollar exchange rate. Another target of the research is to show the relationship between gold price and oil prices. The result shows that there are a number of likely influenced variable through by which the dollar-pound rate has effects on the demand and supply of oil as a result of its prices. That is done through the analysis of the relations between the variables of the study. Moreover, correlation coefficient values are given that there exists a positive explanatory correlation between the variables of the study. On the whole, there exists a positive long-term equilibrium relation between the GBP/USD exchange rate, price of oil and price of gold. Any change in the exchange rate of GBP/USD is causing the changes in prices of Brent oil.","PeriodicalId":17866,"journal":{"name":"Kurdistan Journal of Applied Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44118928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.24017/science.2023.1.5
Mohammed Bahi, Khattab Mustafa Shekhany
andida species are considered the most common opportunistic human fungal pathogen due to the presence of various virulence factors, including its ability to form a biofilm that aids in oral candidiasis. Pediatric patients are more susceptible to oral candidiasis than healthy pediatric because of the factors that encourage Candida oral carriage. This current study aims to isolate, evaluated the antifungal effect on Candida spp. and participated in oral candidiasis of pediatric patients in Sulaymaniyah and Kirkuk city. The study was performed from September 2021 to February 2022 on two groups of pediatrics which including pediatric patients (n=160) and healthy pediatric (n=50) as a control group. Oral swabs were obtained from 210 participants in the Kurdistan Region of Iraq at the Pediatric teaching hospital of the Sulaymaneyah and Kirkuk governorates. To culture the swabs, Sabouraud dextrose agar (SDA) medium was used. HiCrome™ Candida Differential agar used to identify Candida isolated, then depending on the internal transcribed spacer (ITS) region using confirmed polymerase chain reaction. Antifungal sensitivity was done for all C. albicans and non-albicans isolates using five common antifungal disks. Among of the 160 sample of pediatric patient 62 (38.8%) positive for Candida spp. which it is including 17 (27.4 %) and 26 (41.9%), 19 (30.6%) breast feeding, bottle feeding and mixing respectively. While within 50 samples of control group 13 (26%) were positive for Candida spp. which including 2 (15.4%), 9(69.2%), 2(15.4%) of same respectively feeding types. Regarding to the antifungal susceptibility the results showed that C. albicans had higher resistance rates against itraconazole, ketoconazole, and clotrimazole than the non-albicans Candida species However, highly resistant rate were detected in Itraconazole and Ketoconazole with 23.7% and 54.4% respectively, for all Candida species. The Current study concluded that oral candidiasis was more predominant in pediatric patients in compare to healthy pediatric also, and C. albicans is the most prevalent etiologic agent. However, higher rate of sensitivity were detected between Candida species for nystatin, which may suggest as the main treatment for oral Candida infections.
念珠菌被认为是最常见的机会性人类真菌病原体，因为存在各种毒力因素，包括其形成生物膜的能力，导致口腔念珠菌病。儿科患者比健康的儿童更容易患口腔念珠菌病，因为这些因素鼓励念珠菌的口腔传播。本研究旨在对苏莱曼尼亚和基尔库克市儿童口腔念珠菌病患者进行分离、抑菌效果评估和口腔念珠菌感染调查。该研究于2021年9月至2022年2月在两组儿科中进行，其中包括儿科患者(n=160)和健康儿科(n=50)作为对照组。从伊拉克库尔德斯坦地区苏莱曼尼亚省和基尔库克省儿科教学医院的210名参与者获得了口腔拭子。用Sabouraud dextrose agar (SDA)培养基培养拭子。HiCrome™念珠菌鉴别琼脂用于鉴定分离的念珠菌，然后根据内部转录间隔区(ITS)使用确认的聚合酶链反应。使用五种常见的抗真菌圆盘对所有白色念珠菌和非白色念珠菌分离株进行抗真菌敏感性试验。160例患儿中念珠菌阳性62例(38.8%)，其中母乳喂养17例(27.4%)，奶瓶喂养26例(41.9%)，混合喂养19例(30.6%)。对照组50只样品中念珠菌阳性13只(26%)，分别为2只(15.4%)、9只(69.2%)、2只(15.4%)。结果表明，白色念珠菌对伊曲康唑、酮康唑和克霉唑的耐药率均高于非白色念珠菌，但对伊曲康唑和酮康唑的高耐药率分别为23.7%和54.4%。目前的研究表明，与健康儿童相比，口腔念珠菌病在儿科患者中更为突出，白色念珠菌是最常见的病因。制霉菌素在不同种类念珠菌间的敏感性较高，可作为口腔念珠菌感染的主要治疗药物。
{"title":"Isolation and Antifungal Susceptibility of Candida spp. from Pediatric Patients in Kurdistan of Iraq","authors":"Mohammed Bahi, Khattab Mustafa Shekhany","doi":"10.24017/science.2023.1.5","DOIUrl":"https://doi.org/10.24017/science.2023.1.5","url":null,"abstract":"andida species are considered the most common opportunistic human fungal pathogen due to the presence of various virulence factors, including its ability to form a biofilm that aids in oral candidiasis. Pediatric patients are more susceptible to oral candidiasis than healthy pediatric because of the factors that encourage Candida oral carriage. This current study aims to isolate, evaluated the antifungal effect on Candida spp. and participated in oral candidiasis of pediatric patients in Sulaymaniyah and Kirkuk city. The study was performed from September 2021 to February 2022 on two groups of pediatrics which including pediatric patients (n=160) and healthy pediatric (n=50) as a control group. Oral swabs were obtained from 210 participants in the Kurdistan Region of Iraq at the Pediatric teaching hospital of the Sulaymaneyah and Kirkuk governorates. To culture the swabs, Sabouraud dextrose agar (SDA) medium was used. HiCrome™ Candida Differential agar used to identify Candida isolated, then depending on the internal transcribed spacer (ITS) region using confirmed polymerase chain reaction. Antifungal sensitivity was done for all C. albicans and non-albicans isolates using five common antifungal disks. Among of the 160 sample of pediatric patient 62 (38.8%) positive for Candida spp. which it is including 17 (27.4 %) and 26 (41.9%), 19 (30.6%) breast feeding, bottle feeding and mixing respectively. While within 50 samples of control group 13 (26%) were positive for Candida spp. which including 2 (15.4%), 9(69.2%), 2(15.4%) of same respectively feeding types. Regarding to the antifungal susceptibility the results showed that C. albicans had higher resistance rates against itraconazole, ketoconazole, and clotrimazole than the non-albicans Candida species However, highly resistant rate were detected in Itraconazole and Ketoconazole with 23.7% and 54.4% respectively, for all Candida species. The Current study concluded that oral candidiasis was more predominant in pediatric patients in compare to healthy pediatric also, and C. albicans is the most prevalent etiologic agent. However, higher rate of sensitivity were detected between Candida species for nystatin, which may suggest as the main treatment for oral Candida infections.","PeriodicalId":17866,"journal":{"name":"Kurdistan Journal of Applied Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68819502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-25DOI: 10.24017/science.2022.2.7
Miran Othman Tofiq, Kawa Muhammad Jamal Rasheed
In this research, we made use of the principal component analysis (PCA) technique, which is a multivariate statistical method that transforms a fixed number of correlated variables into a fixed number of orthogonal, uncorrelated axes known as principal components by making use of orthogonal transformation. In other words, the PCA technique converts correlated variables into uncorrelated axes. To minimize the dimensionality of a data set that included a large range of connected variables while yet keeping as much variance within the data set as possible, we employed a method called principal component analysis (PCA). This allowed us to analyze eleven steel components. This is accomplished by reworking the unique variables into a brand new set of uncorrelated variables known as principal components (PC). The principal components are ordered in such a way that they preserve the majority of the variation that is found in all of the unique variables. This is done by reworking the unique variables into a brand new set of uncorrelated variables called principal components (PC). We are able to come to the conclusion that the five principal components that collectively account for approximately sixty-seven percent of the variance in all of the data are the best principal components because this percentage represents the best principal aspect of all of the 11 principal components.
{"title":"Application of Principal Component Analysis for Steel Material Components","authors":"Miran Othman Tofiq, Kawa Muhammad Jamal Rasheed","doi":"10.24017/science.2022.2.7","DOIUrl":"https://doi.org/10.24017/science.2022.2.7","url":null,"abstract":"In this research, we made use of the principal component analysis (PCA) technique, which is a multivariate statistical method that transforms a fixed number of correlated variables into a fixed number of orthogonal, uncorrelated axes known as principal components by making use of orthogonal transformation. In other words, the PCA technique converts correlated variables into uncorrelated axes. To minimize the dimensionality of a data set that included a large range of connected variables while yet keeping as much variance within the data set as possible, we employed a method called principal component analysis (PCA). This allowed us to analyze eleven steel components. This is accomplished by reworking the unique variables into a brand new set of uncorrelated variables known as principal components (PC). The principal components are ordered in such a way that they preserve the majority of the variation that is found in all of the unique variables. This is done by reworking the unique variables into a brand new set of uncorrelated variables called principal components (PC). We are able to come to the conclusion that the five principal components that collectively account for approximately sixty-seven percent of the variance in all of the data are the best principal components because this percentage represents the best principal aspect of all of the 11 principal components.","PeriodicalId":17866,"journal":{"name":"Kurdistan Journal of Applied Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42006151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-28DOI: 10.24017/science.2022.2.6
Ahlam Mohamad Shakoor, Hersh Hasan Taha
The most popular type of renewable energy is photovoltaic (PV) because it is a sustainable source and environmentally friendly. The power generated by a PV system varies with changes in ambient conditions such as temperature and sun radiation; therefore, tracking the maximum power generation from a photovoltaic system independent of temperature and radiation factors is very important. In the literature, a number of techniques for achieving the maximum power point have been presented. In this work, the maximum power point tracking (MPPT) system employing perturb and observe (P&O) algorithm is implemented based on the Proportional and Integral (PI) controller on the proposed PV system to achieve the highest power production from photovoltaic (PV) system and enhance the system performance. The proposed PV system is composed of a Photovoltaic array, DC to DC boost type converter and an MPPT algorithm using perturb and observe method. 1Soltech 1STH-220-P module type was chosen in this study for the simulation and proposed PV The array consists of 40 rows of PV modules connected in parallel, while each row consists of 10 modules connected in a series. All elements of the PV system were simulated using MATLAB/Simulink. The proposed model is used to simulate and optimize the photovoltaic array output current, voltage and power features under various environmental conditions including solar temperature and radiation. The simulation results showed that maximum power point tracking approach using perturbation and observation provide high efficiency to get the highest energy from the PV system regardless of variations in environmental conditions. DC to DC boost converter with perfect performance and high voltage gain is also successfully simulated on the developed PV system.
{"title":"Modelling and simulation of Perturb and Observe MPPT algorithm based on the PI Controller for Photovoltaic system","authors":"Ahlam Mohamad Shakoor, Hersh Hasan Taha","doi":"10.24017/science.2022.2.6","DOIUrl":"https://doi.org/10.24017/science.2022.2.6","url":null,"abstract":"\u0000 \u0000 \u0000 \u0000 \u0000 \u0000 \u0000 \u0000 \u0000The most popular type of renewable energy is photovoltaic (PV) because it is a sustainable source and environmentally friendly. The power generated by a PV system varies with changes in ambient conditions such as temperature and sun radiation; therefore, tracking the maximum power generation from a photovoltaic system independent of temperature and radiation factors is very important. In the literature, a number of techniques for achieving the maximum power point have been presented. In this work, the maximum power point tracking (MPPT) system employing perturb and observe (P&O) algorithm is implemented based on the Proportional and Integral (PI) controller on the proposed PV system to achieve the highest power production from photovoltaic (PV) system and enhance the system performance. The proposed PV system is composed of a Photovoltaic array, DC to DC boost type converter and an MPPT algorithm using perturb and observe method. 1Soltech 1STH-220-P module type was chosen in this study for the simulation and proposed PV The array consists of 40 rows of PV modules connected in parallel, while each row consists of 10 modules connected in a series. All elements of the PV system were simulated using MATLAB/Simulink. The proposed model is used to simulate and optimize the photovoltaic array output current, voltage and power features under various environmental conditions including solar temperature and radiation. The simulation results showed that maximum power point tracking approach using perturbation and observation provide high efficiency to get the highest energy from the PV system regardless of variations in environmental conditions. DC to DC boost converter with perfect performance and high voltage gain is also successfully simulated on the developed PV system. \u0000 \u0000 \u0000 \u0000 \u0000 \u0000 \u0000 \u0000 \u0000 ","PeriodicalId":17866,"journal":{"name":"Kurdistan Journal of Applied Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48570242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-27DOI: 10.24017/science.2022.2.5
Tahsin Ali Mohammed Amin, S. Mahmood, Rebar Dara Mohammed, P. J. Karim
There are many potential sources of data uncertainty, such as imperfect measurement or sampling, intrusive environmental monitoring, unreliable sensor networks, and inaccurate medical diagnoses. To avoid unintended results, data mining from new applications like sensors and location-based services needs to be done with care. When attempting to classify data with a high degree of uncertainty, many researchers have turned to heuristic approaches and machine learning (ML) methods. We propose an entirely new ML method in this paper by fusing the Radial Basis Function (RBF) network based on ant colony optimization (ACO). After introducing a large amount of uncertainty into a dataset, we normalize the data and finish training on clean data. The ant colony optimization algorithm is then used to train a recurrent neural network. Finally, we evaluate our proposed method against some of the most popular ML methods, including a k-nearest neighbor, support vector machine, random forest, decision tree, logistic regression, and extreme gradient boosting (Xgboost). Error metrics show that our model significantly outperforms the gold standard and other popular ML methods. Using industry-standard performance metrics, the results of our experiments show that our proposed method does a better job of classifying uncertain data than other methods
{"title":"A Novel Classification of Uncertain Stream Data using Ant Colony Optimization Based on Radial Basis Function","authors":"Tahsin Ali Mohammed Amin, S. Mahmood, Rebar Dara Mohammed, P. J. Karim","doi":"10.24017/science.2022.2.5","DOIUrl":"https://doi.org/10.24017/science.2022.2.5","url":null,"abstract":"There are many potential sources of data uncertainty, such as imperfect measurement or sampling, intrusive environmental monitoring, unreliable sensor networks, and inaccurate medical diagnoses. To avoid unintended results, data mining from new applications like sensors and location-based services needs to be done with care. When attempting to classify data with a high degree of uncertainty, many researchers have turned to heuristic approaches and machine learning (ML) methods. We propose an entirely new ML method in this paper by fusing the Radial Basis Function (RBF) network based on ant colony optimization (ACO). After introducing a large amount of uncertainty into a dataset, we normalize the data and finish training on clean data. The ant colony optimization algorithm is then used to train a recurrent neural network. Finally, we evaluate our proposed method against some of the most popular ML methods, including a k-nearest neighbor, support vector machine, random forest, decision tree, logistic regression, and extreme gradient boosting (Xgboost). Error metrics show that our model significantly outperforms the gold standard and other popular ML methods. Using industry-standard performance metrics, the results of our experiments show that our proposed method does a better job of classifying uncertain data than other methods","PeriodicalId":17866,"journal":{"name":"Kurdistan Journal of Applied Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49557911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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