Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing

Some physical and chemical characteristics of Jurf Al- Sakar drinking water plant in Babylon governorate have been studied. Seven locations for this plant were selected. These were the drinking water treatment plant source on Euphrates River before entering the plant, precipitation, filtration and collection tanks, and also after leaving the plant at distances of one meter, 4 and 8 km. The samples were collected bimonthly from October, 2002 to August, 2003. Some results match with the national and international standard characters while the other characters (Turbidity, total hardness, calcium, nitrate, phosphate and the biological oxygen demand values) were not match. The present study showed that drinking water treatment plant is undrinka

The imbalances and economic problems which it face the countries, it is a result of international economic developments or changes or global crises such as deterioration in trade, sharp changes in oil prices, increasing global indebtedness, sharp changes in foreign exchange rates and other changes, all that, they affect the economic features of any country. and These influences vary from one country to another according to the rigidity of its economy and its potential in maneuvering with economic plans and actions that would reduce the impact or avoidance with minimal damage. Therefore, the countries  that  suffer from accumulated economic problems as a result of mismanagement and poor planning or suffe

Background: Evaluation and measurement of primary stability could be achieved by several methods, including the resonance frequency analysis (RFA) and implant insertion torque (IT) values. The need for a sufficient primary stability, guaranteed by an adequate insertion torque and implant stability quotient values, increased its importance mainly in one stage implants or in immediate loading protocols. The aims of this study was to find if there is a correlation between the peak insertion torque (PIT) and ISQ values of implants inserted in the jaws of different bone quality which regarded as two important clinical determinant factors for prediction of implant primary stability, and to evaluate and compare whether an experienced clinician cou

2,2'-(1-(3,4-bis(carboxydichloromethoxy)-5-oxo-2,5-dihydrofuran-2-yl)ethane-1,2-diyl)bis(oxy)bis(2,2-dichloroacetic acid) a derivative of L-ascorbic acid was prepared by reaction of L-ascorbic acid with trichloroacetic acid (1:4) ratio, in the presence of potassium hydroxide. A series of new metal complexes of this ligand were prepared by a reaction with the chlorides of Cd(II), Co(II), Ni(II), Cu(II) and Zn(II). The new ligand and its complexes were identified by C.H.N., IR, UV-visible spectra, Thermogravimetric analysis (TGA), as well as 1H, 13C-NMR and Mass spectra for ligand L. The complexes were also identified by molar conductance, atomic absorption, magnetic susceptibility and X-ray diffraction for Cu (II) complex. FT-IR spectra

The aim of the present work is to develop a new class of natural fillers based polymer composites with sawdust (S.D) which used two particle sizes (1.2 μm & 2.3 μm) and different weight percentage from sawdust (10%, 15%, and 20%). The mechanical properties studied include hardness (shore D) for all samples at normal conditions (N.C). The unsaturated polyester (UPE) and its composites samples were immersed in water for  30 days to find the effect of particle size of sawdust (S.D) on the weight gain (Mt %) by water for all the samples, also to find the effect of water on their hardness. The results show that the composite materials of sawdust (S.D) fillers which has particle size (1.2 μm) better than (2.3 μm) particle size bef

The aim of this study was to isolate and identify the cyanobacterium Scytonema hofmanni Var. calcicolum from the domestic drinking tanks as a new record in Iraqi drinking water. Scytonema hofmanni var. calcicolum, a filamentous freshwater cyanobacterium (blue-green alga). This alga was isolated from the walls of the domestic plastic water tanks in Al- karkh/ Baghdad city on July 2014. The sampling was performed by collecting three samples from this tanks, the three examined samples microscopically revealed the dominance of this cyanobacterium as unialgal in the studied samples. The results showed this alga has the ability to tolerate high temperature up to 42 Cº and very low light intensity inside the tanks which up to 10 μE/m²/s.

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when