Одной из активно развивающихся отраслей лексикологии является неология, объект её изучения - новое слово или неологизм. В задачу неологии входит выявление новых слов и новых значений у уже существующих в языке слов, анализ причин и способов их появления, описание факторов, влияющих на появление нового в лексической системе языка, разработка языковой политики в отношении новых номинаций. Лексикографическим описанием неологизмов занимается неография. В русистике активное изучение неологизмов началось во второй половине XX века, однако интерес к новым номинациям в языке появился значительно раньше. Впервые определение термина неологизм было дано в «Настольном словаре для справок по всем отраслям знания» под ред. Ф.Толля (1864 г.): «Неологизм (греч.), страсть вводить в язык слова бесполезные, т.е. назначенные для выражения идей, ясно передаваемых другими словами, уже вошедшими в употребление» [Алаторцева, 1999 с. 11]. Само же слово неологизм использовалось и ранее, например, П. Я Вяземский пишет: «Позволю себе неологизмы, т.е. прибавления к Словарю Российской Академии» [там же, с. 11].
Background: Odontogenic cysts include a group of osseodestructive lesions that frequently affect the jaws. Those cysts could derive from odontogenic epithelium and occur in the tooth-bearing regions of the jaws. The aims of this study were to evaluate the immunohistochemical expression of Cyclin D1 in Keratocystic Odontogenic Tumor, Dentigerous cyst and Radicular cyst in epithelium and connective tissue capsule. Materials and Methods: In this study, thirty formalin fixed paraffin embedded tissue blocks of Odontogenic cysts and Tumor, consist of 14 Keratocystic Odontogenic Tumor, 8 dentigerous cysts and 8 radicular cysts were analyzed immunohistochemically for the presence of Cyclin D1 proteins. Results: Strong to moderate expression of Cy
... Show MoreThe purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreDeep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
... Show MoreImproving" Jackknife Instrumental Variable Estimation method" using A class of immun algorithm with practical application
Background :Infectious disorders in general have high morbidity and mortality.. CNS infections include many disorders like bacterial meningitis, tuberculous and other subacute and chronic meningitis, viral meningitis, cerebral abscess, spinal cord infections, and others.
Objective: To assess our locality about prevalence of CNS infections , to have more awareness regarding CNS infections, and to try to find the proper way to reduce their prevalence and to treat them in appropriate way.
Method :We revised the records of all the cases of CNS infections excluding cases of spinal cord infections who were admitted in the wards of neuroscience hospital over the previous two years ( from July/2010 to June 2012 ),those were 132 cases.Seaso
تناولنا في هذه الدراسة التأكيد على تطوير المناهج الدراسية بأتجاه تنمية قيم التسامح والتعايش السلمي ، لان ثقافة التسامح باتت من الضرورات الملحة التي يفرضها الواقع الراهن لمواجهة العنف المجتمعي ، مما يوجب الحرص على ترسيخ القيم الانسانية ، لان التسامح من الصفات التي تحبها النفوس وتنجذب اليها القلوب .
والقيم الاخلاقية والسلوكية كالتسامح وغيرها ، من الامور الرئيسية لعمليتي التربية والتعليم في المدارس وال
... Show MoreCase Report.
To present a case of a previous complicated mandibular orthognathic surgery that aimed to setback the mandible in a female cleft lip and palate (CLP) patient, which led to bone necrosis on one side with subsequent severe mandibular deviation and facial asymmetry. We additionally reviewed the previous reports of similar complications, the pathophysiology and the factors that could lead to this dreadful result.
A 27-year-old female patient presented with a severe dentofacial deformity secondary to a complicated bilateral sagittal spli
This work presents a computer studying to simulate the charging process of a dust grain immersed in plasma with negative ions. The study based on the discrete charging model. The model was developed to take into account the effect of negative ions on charging process of dust grain.
The model was translated to a numerical calculation by using computer programs. The program of model has been written with FORTRAN programming language to calculate the charging process for a dust particle in plasma with negative ion, the time distribution of a dust charge, number charge equilibrium and charging time for different value of ηe (ratio of number density of electron to number density of positive ion).