Diabetic retinopathy is one of most important complications of diabetes mellitus that can be treated by Nd:YAG laser. Laser is used in ophthalmic practice for photocoagulation and photodisruption. The purpose of this study is to evaluate changes in immunological ,hematological and biochemical values after treatment of diabetic retinopathy by laser. Blood samples from 10 patients suffering from diabetic retinopathy were taken before and after laser treatment to coagulate retina to prevent leakage and hemorraghe to avoid deterioration of vision.In group one (4 patients = 40%), blood tests were done one day after treatment. In group two (6 patients =60%) tests were done 7 days after treatment with laser. The study showed no clear changes in the values of biochemical tests(except glucouse is already high) and hemtologyical tests (except PT, PTT, clotting time and bleeding time for those patients taking l00mg acetylsalicylic acid or warfarin) after irradiation with laser, probably because that main organs that affecting these tests or the elements that involve in these tests have not been irradiated directly. The main changes were in mmunoglobulin values which increased as noticed in both groups, because all light- induced biological effects depend on the parameters of irradiation, the results suggest that the laser irradiation may play two principal roles in immunological changes. First, is stimulation of cellular proliferation, and stimulation of cellular differentiation that is responsible for different types of immunoglobulin.The other suggestion is that laser is acting as a triggering factor which induces systematic effects through the circulation when laser interacts with living cells so it has systemic effects through circulating blood.
This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.
The drug promethazine hydrochloride (PRZH) forms with rhodium (II) a colored chelate (?max = 472 nm) complex at (pH = 2.1) which is extractable with benzyl alcohol as organic solvent. Under the appropriate experimental conditions a calibration plot was set up from which some analytical parameter were derived and deduced by regression. Standard addition procedure was also adopted. It has been estimated that the concentration of the drug PRZH to be 24.89 mg per unit and 24.19 mg per unit for both calibrations. Under optimal conditions, the developed method has been achieved the following characteristics: LDR (30 – 150 µg ml-1 ) PRZH , RSD % ( 0.6 – 2.47 ) , sandell sensitivity( 0.0844 µg. cm -2 ) , LOD ( 1.66 µgml-1 ) , recovery
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In this work, we construct projectively distinct (k,3)-arcs in the projective plane PG(2,9) by applying a geometrical method. The cubic curves have been been constructed by using the general equation of the cubic. We found that there are complete (13,3)-arcs, complete (15,3)-arcs and we found that the only (16,3)-arcs lead to maximum completeness
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The research aimed to modeling a structural equation for tourist attraction factors in Asir Region. The research population is the people in the region, and a simple random sample of 332 individuals were selected. The factor analysis as a reliable statistical method in this phenomenon was used to modeling and testing the structural model of tourism, and analyzing the data by using SPSS and AMOS statistical computerized programs. The study reached a number of results, the most important of them are: the tourist attraction factors model consists of five factors which explain 69.3% of the total variance. These are: the provision of tourist services, social and historic factors, mountains, weather and natural parks. And the differenc
... Show MoreIn this work, an enhanced Photonic Crystal Fiber (PCF) based on Surface Plasmon Resonance (SPR) sensor using a sided polished structure for the detection of toxic ions Arsenic in water was designed and implemented. The SPR curve can be obtained by polishing the side of the PCF after coating the Au film on the side of the polished area, the SPR curve can be obtained. The proposed sensor has a clear SPR effect, according to the findings of the experiments. The estimated signal to Noise Ratio (SNR), sensitivity (S), resolution (R), and Figures of merit (FOM) are approaching; the SNR is 0.0125, S is 11.11 μm/RIU, the resolution is 1.8x〖10〗^(-4), and the FOM is 13.88 for Single-mode Fiber- Photonic Crystal Fiber- single mode Fiber (SMF-P
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The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow
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KE Sharquie, HR Al-Hamamy, AA Noaimi, KA Ali, Journal of Cosmetics, Dermatological Sciences and Applications, 2015 - Cited by 3