Background: Poly (methylmethacrylate) is not ideal in every aspect and has disadvantages such as insufficient surface hardness, increase water sorption and poor impact resistance and the latter being the primary cause of fracture of denture base resins. The aim of this study was to evaluate the effect of addition of silanized nano- hydroxyapatite (HA) on some properties of heat cured acrylic denture base material. Materials and methods: HA nano particles were first silanized with MPS (tri methacryloxypropyletrimethoxy silane coupling agent) then ultrasonicated with methylmethacrylate (monomer) to disperse agglomerated nano particles and mixed with polymer. 2% by wt of HA nano particles was selected as the best concentration that add

Thin films of the blended solution of (NiPc/C60) on glass substrates were prepared by spin-coated method for three different ratios (100/1, 100/10 and 100/100). The effects of annealing temperature and C60 concentration on the optical properties of the samples were studied using the UV-Vis absorption spectroscopy and FTIR spectra. The optical absorption spectrum consists of two main bands, Q and B band, with maxima at about (602-632) nm and (700-730) nm for Q1 and Q2 respectively, and (340-375) nm for B band. The optical energy gap were determined from optical absorption spectra, The variation of optical energy gap with annealing temperature was nonsystematic and this may be due to the improvement in crystal structure for thin films. Whi

Background: For decades, the use of naturally accessible materials in treating human disease has been widespread. The goal of this study was to determine the anti-fungal effectiveness /of the lemongrass essential oil (LGEO) versus Candida albicans (C. albicans) adhesion to polymethylmethacrylate (PMMA) materials. Material and methods: LGEO's anti-fungal activity was tested against C. albicans adhesion using the following concentration of LGEO in PMMA monomer (2.5 vol. %, 5 vol. % LGEO) selected from the pilot study as the best two effective concentrations. A total of 40 specimens were fabricated for the candida adherence test and were subdivided into four equal groups: negative control 0 vol. % addition, experimental with 2.5 vol. % and

Background: Denture cleansing was an important step that could prevent the spread of infection and improve a patient's health, the durability of the dentures, and the overall quality of life; therefore, it was necessary to choose a suitable cleanser that, in addition to being effective, did not have an unfavorable effect on the qualities of the denture base resin itself when used for an extended period. For this purpose, this study aimed to evaluate the effect of tea tree oil (TTO) on Candida albicans adhesion and the surface roughness property of poly(methyl methacrylate) denture material after immersion in TTO. Methods: A total of 55 heat-cured acrylic resin specimens were used for C. albicans adherence and surface roughness tests. The

The world's renewable energy sources have taken on great importance, for its cleanness and its environmental effects as well as being a renewable source, Increased demand for fossil energy sources is also causing global warming and climate change. Iraq is an appropriate area for renewable energy This study shows that renewable alternative energy has not been used sufficiently enough at present. But this energy can play an important role in the future of renewable energy in Iraq. This research aims to study the renewable energy in Iraq (solar energy) and it is appropriate to develop this alternative energy for crude oil, which is characterized by the use of the most appropriate and less economical and more environmentally friendly. Solar

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

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

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

Currently, there is an intensive development of bipedal walking robots. The most known solutions are based on the use of the principles of human gait created in nature during evolution. Modernbipedal robots are also based on the locomotion manners of birds. This review presents the current state of the art of bipedal walking robots based on natural bipedal movements (human and bird) as well as on innovative synthetic solutions. Firstly, an overview of the scientific analysis of human gait is provided as a basis for the design of bipedal robots. The full human gait cycle that consists of two main phases is analysed and the attention is paid to the problem of balance and stability, especially in the single support phase when the biped