The goals of endodontic preparation were to shape and clean the space of the root canal and remove microorganisms, affected dentin and pulp, the apical foramen and the canal curve should be protected from being transported during endodontic canal preparation. The aim of this study was to evaluate the curve straightening of curved root canals and apical transportation after preparation with four rotary systems. Forty mesial roots of the lower 1st molars teeth only the mesiobuccal canals were used, these roots were immersed into cold clear acrylic , the teeth roots divided into four groups according to rotary system used for preparation of the canals (ten roots for each group):. group I: ProTaper Next rotary system, group II: IRaCe Plus rotary system, group III: HeroShaper rotary system, group IV: ProTaper rotary system, instrumentation were done to size 30 master apical file and with copious irrigation, total amount of 10 ml of 2.5% of sodium hypochlorite (NaOCl) then rinsed the canals with distilled water 5 ml. radiograph was taken for all roots before and after instrumentation in one direction buccolingual using digital radiograph system. The degree of curve straightening of the root canal and the apical transportation were measured using Image J software and Adobe photoshop CS6 software. Statistical analysis was done and the result showed that group IV had the highest mean values in curve straightening and apical transportation, there were significant difference between group IV and all of the other groups and there were non- significant difference between group I , group II and group . All the four used rotary systems produced adequate geometry during canal preparations. However, some apical transportation in ProTaper group was seen, which might need a caution when used protaper in instrumentation of curved canal.
This research include the designation of newly instrument (Turbidmeter) depending on using photo voltaic detector (8.5mm.*8.5mm.).These dimensions have large area which increases the scattering rays with a variable intensity. The properties of this design are local mode and the used tools are a available in the local markets as well as its less cost light weight system. It is worth mentioning that the possibility of its application in many fields such as: Clinical, Laboratory, Industrial and Fuel fields. This designation, applied to estimate Barium Sulphate in turbidity method. The analytical results show high accuracy and repetition, also the linearity ranges from (4-180) ppm. At the detection limit (0.05) ppm. With correlation coefficient
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Objective: A descriptive design, using the methodological approach, is carried throughout the present
study from April 1st 2012 to May 20th 2013 to construct the school physical environment standardized
features tool.
Methodology: An instrument of (141) item is constructed for the purpose of the study. A purposive
sample of (44) school; (22) public and (22) private ones is selected. Content Validity of the instrument is
determined through the use of panel of (11) expert who are specialists in Community Health Nursing and
Community Medicine. Internal consistency reliability, using the split-half technique, is employed through
the computation of Cronbach alpha correlation coefficient of (0.93) for internal scale. Data
Changing oil-wet surfaces toward higher water wettability is of key importance in subsurface engineering applications. This includes petroleum recovery from fractured limestone reservoirs, which are typically mixed or oil-wet, resulting in poor productivity as conventional waterflooding techniques are inefficient. A wettability change toward more water-wet would significantly improve oil displacement efficiency, and thus productivity. Another area where such a wettability shift would be highly beneficial is carbon geo-sequestration, where compressed CO2 is pumped underground for storage. It has recently been identified that more water-wet formations can store more CO2. We thus examined how silica based nanofluids can induce such a wettabil
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This research suggests a robust and systematic way for Arabic Sentiment Analysis using a vast dataset of 66,666 text reviews. One of the main advantages of this study is that the dataset was perfectly balanced (33,333 positive samples and 33,333 negative samples). In machine learning, this 50/50 split is important because it eliminates class bias and enables the predictive model to treat both sentiment classes equally. As shown in the values of the metrics — overall accuracy, weighted precision, weighted recall, and F1 score — there is great similarity among them, indicating a stable and reliable assessment of the model's real potential throughout the Arabic dataset. Based on data profile, the average word count per review is 42.3
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The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T