BACKGROUND: Keratoconus is a progressive non inflammatory bilateral (usually asymmetric) ectatic corneal disease characterized by paraxial stromal thinning ,weakening that lead to corneal surface distortion ,vision loss primarily from irregular astigmatism and myopia and secondly from corneal scar. OBJECTIVE: To evaluate visual and refractive outcomes after intracorneal continuous ring (ICCR) implantation combined with intrapocket corneal collagen cross linking in patient with keratoconus. Setting: Eye Specialty Private Hospital, Baghdad, Iraq. METHODS: This study assessed the results of implantation of Myoring ICCR combined with CXL in 40 eyes with KC. Outcome measures include UDVA,CDVA(spectacle correction),refraction, complications and side effects. Postoperative follow- up was up to 1 year. RESULTS: The study evaluated 40 eyes of 34 patients with a mean age of 25.75 years. Preoperatively, the pachymetry at thinnest location range from (367_555ϻm) and the mean keratometry (K) readings 50.51± 3.94D. Post operatively ,there was statistically significant improvement in the UDVA,CDVA,K reading ,manifest spherical and cylindrical refractive errors ,and spherical equivalent (p<.05).The mean UDVA improved by 13 lines ,CDVA improved by 3.5 lines and the mean K reading decreased by 7.14 D .No serious intraoperative complications occurred .Side effects includes glare and night vision problems. CONCLUSION: Treatment of KC with simultaneous ICCR implantation and intrapocket collagen cross linking significantly improved visual and refractive outcomes .the UDVA and CDVA continuously improved during the 1st year postoperatively. KEYWORDS:kKerCa:tkoecroantousc,oinnutsra,cICorCnRea:linctoranctionrunoeualscroingti,nucoullsagrieng,croCsXs-Lli:nckoinllgagaennd:crimospsl-alintkaibnlge acnodllaImCLer:lIemnps.lantableCollamerLens
in this paper the collocation method will be solve ordinary differential equations of retarted arguments also some examples are presented in order to illustrate this approach
Background: Atherosclerosis is well known related to age and certain cardiovascular diseases. Aging is one reason of arteries function deterioration which can cause loss of compliance and plaque accumulation, this effect increases by the presence of certain diseases such as hypertension and diabetes disease. Aim: To investigate the reduction of blood supply to the brain in patients with diabetes and hypertension with age and the role of resistive index in the diagnosis of reduced blood flow. Method: Patients with both diseases diabetic and hypertension were classified according to their age to identify the progression of the disease and factors influencing the carotid artery blood flow. By using ultrasound and standard Doppler techniq
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Encryption of data is translating data to another shape or symbol which enables people only with an access to the secret key or a password that can read it. The data which are encrypted are generally referred to as cipher text, while data which are unencrypted are known plain text. Entropy can be used as a measure which gives the number of bits that are needed for coding the data of an image. As the values of pixel within an image are dispensed through further gray-levels, the entropy increases. The aim of this research is to compare between CAST-128 with proposed adaptive key and RSA encryption methods for video frames to determine the more accurate method with highest entropy. The first method is achieved by applying the "CAST-128" and
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This research includes the study of dual data models with mixed random parameters, which contain two types of parameters, the first is random and the other is fixed. For the random parameter, it is obtained as a result of differences in the marginal tendencies of the cross sections, and for the fixed parameter, it is obtained as a result of differences in fixed limits, and random errors for each section. Accidental bearing the characteristic of heterogeneity of variance in addition to the presence of serial correlation of the first degree, and the main objective in this research is the use of efficient methods commensurate with the paired data in the case of small samples, and to achieve this goal, the feasible general least squa
... Show MoreAutorías: Wafaa Sabah Mohammed Al-Khafaji, Fatimah Hameed Kzar Al-Masoodi, Suadad Ibrahim Suhail Al-Kinani. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 3, 2023. Artículo de Revista en Dialnet.
Re-use of the byproduct wastes resulting from different municipal and industrial activities in the reclamation of contaminated water is real application for green projects and sustainability concepts. In this direction, the synthesis of composite sorbent from the mixing of waterworks and sewage sludge coated with new nanoparticles named “siderite” (WSSS) is the novelty of this study. These particles can be precipitated from the iron(II) nitrate using waterworks sludge as alkaline agent and source of carbonate. Characterization tests using X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) mapping revealed that the coating process was c
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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