Diabetes imposes a substantial public health burden; according to the International Diabetes Federation, there were about 3.4 million diabetes related deaths worldwide in 2024, and in Iraq, the Federation reports that one in nine adults lives with diabetes in 2024, with 14,683 adult deaths attributable to diabetes and a total diabetes related health expenditure of 2,078 million United States dollars. The dataset analyzed in this study contains 1,000 records collected in 2020 from two Iraqi teaching hospitals and includes multiple clinical and laboratory measurements with three outcome classes, namely Non diabetic, Pre diabetic, and Diabetic, with a low prevalence of the Pre diabetic class and an imbalanced overall class distribution; the data are challenging because they contain many outliers, non homogeneous covariance matrices across classes, exact duplicate rows that were removed before modelling, and linear correlations among certain variables. The study objective was to train and evaluate models that discriminate among the three classes and yield accurate, well calibrated predictions for future cases in similar clinical settings, but the diagnostic properties of the data limited the applicability of classical discriminant functions; therefore two supervised learners were employed: Classification and Regression Trees (CART) and Extreme Gradient Boosting (XGBoost), together with preprocessing that removed exact duplicate rows and excluded VLDL because it is algebraically derived from triglycerides in mmol per liter as VLDL equals triglycerides divided by 2.2, which would introduce redundancy and multicollinearity. On the heldout test set, XGBoost achieved higher Accuracy at 98.18 percent compared with 97.58 percent for CART and higher Balanced Accuracy at 93.84 percent compared with 88.16 percent for CART, indicating that XGBoost provided the strongest overall operating point for this three-class task while CART remains useful when simple and transparent rules are required.
The manufacturing industry in Iraq has faced, during the time stages, several obstacles that have had devastating effects on the Iraqi economy. These obstacles are represented by political events and wars that have led to the depletion of most human and material resources and the suspension of most vital industrial facilities from working, And the occurrence of this major deviation in the process of economic development, For the same reasons, the contributions of the manufacturing sector to the gross domestic product varied fluctuatingly, indicating instability in the growth rates of this sector, On the other hand, the supremacy of the belief that the dominance of oil resources as a main source for creating economic growth and achieving a h
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In the current review, an updated list of dark beetle species (Coleoptera, Tenebrionidae) recorded in Iraq was given. The current paper is based on previous studies in the literature and contains all dark beetles referred to in Iraq, except for the species within the Pimelinae subfamily. The investigation of this review showed the presence of 89 species belonging to 34 genera within five subfamilies. This work included mentioning the basionyms and synonyms for genera and species with their global distribution, as well as, correcting the scientific names that were mentioned in the previous checklists.
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Studies were conducted from 1980 to 1989 to determine the insect pests infested animal museum collections in Iraq. Twelve species of Coleoptera were recovered, eleven belonged to the Dermestidae, and one to the Tenebrionidae. Of these Anthrenus coloratus Reitt. and Phradonoma nobile (Reitt.) were the most commonest and widely distributed species. Trogoderma bactrianum Zhant. and Orphilus niger (Rossi) were recorded here for the first time in Iraq.
The study aimed to survey mushroom species from fields among herbs, palm trunks, and trees in central Iraq and to identify them on the basis of morphological and molecular characteristics. As a molecular identification result with polymerase chain reaction six species were recorded (with eight isolates): Agaricus bitorquis (Quéllt) Saccardo. 1887 (SHA14); Candolleomyces candolleanus (Fr.) D. Wächter & Melzer, 2020 (SHA15); Cyclocybe cylindracea (D.C.) Vizzini & Angelini, 2014 (SHA13); Leucoagaricus hesperius Vellinga, 2010 (SHA16); Volvariella sp. (SHA17), and Volvopluteus gloiocephalus (D. C.) Vizzini, Contu & Justo, 2011 (SHA10, SHA101 and SHA12), belonging to four families of Basidiomycetes: Agaricaceae, Pluteaceae,
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Iraq is Suffering nowadays from the criminal triad represented by the fiscal and administrative corruption, money laundering and terrorism, which are intertwined in a very related relations, as each of them support the other . Since the over growth has been one of its characteristics leaving behind a very dangerous negative effects whether it was social , economic or even political impacts . As a result , this trial is now represents a high risk that threatens the present and the future of Iraq . On the political , economic and social level , it is well to mention that the poor direct investment , the increasing rates of poverty , unemployment , inflation as well as the smuggling of goreign currency an
... Show MoreThe guava plant, Psidium guajava L., serves as proof of the abundant donations of nature, providing a delicious guava fruit; this plant is rich in groups of medicinal and nutritional benefits. Guava belonging to the Myrtaceae family, many previous studies reported many phytochemical constituents in its leaves that have many pharmacological activities and medicinal properties; this study focuses on the isolation, structural elucidation and calculation concentration of flavonoids, assessment of the cytotoxic activityof hyperin from Psidium guajava leaves newly cultivated in Iraq. The isolation process involved the use of thin-layer chromatography (TLC) and preparative high-performance liquid chromatography (PHPLC) and structural eluci
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This research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012),
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