Background: The aim of this national oral health survey was to determine the prevalence of malocclusions due to some anomalies in the dentition among the 13 years old Kurdish students in sulaimani intermediate school. Materials and methods: The total sample was 950 (455 males and 495 females) which assessed by diagnostic set and special instrument. The clinical examination was mainly based on the definitions of Björk et al. Some variables were recorded as present or absent sometimes denoting the tooth or the teeth involved in malocclusion and their distribution according to the whole sample. Results: The results showed that 1)The most common extracted tooth was the mandibular first molar (2.9%). 2) At this age group the most common partially erupted tooth was the maxillary canine (4.2%). 3) The most common unerupted tooth was the maxillary second molars. 4) The most common retained deciduous tooth was the maxillary canine (6.8%), then the maxillary second molars (5.4%).5) Hypodontia as judged clinically was found in 2.1% of the sample affecting one or more permanent teeth. The most common congenitally missing tooth was the maxillary lateral incisor (0.9%), mandibular second premolars (0.4%), and then maxillary second premolar (0.2%). 6) 29.2 % of the sample had one or more rotated teeth. The most common rotated tooth was the mandibular second premolars (5.3%). 7). The sample showed 30.4% with one or more displaced teeth. The most common displaced tooth was the maxillary lateral incisor (8.8%), then the maxillary canine (7.2%). Conclusion: At the age of 13 both males and females show large range of dental anomalies that are better to be controlled.
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
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Inventory or inventories are stocks of goods being held for future use or sale. The demand for a product in is the number of units that will need to be removed from inventory for use or sale during a specific period. If the demand for future periods can be predicted with considerable precision, it will be reasonable to use an inventory rule that assumes that all predictions will always be completely accurate. This is the case where we say that demand is deterministic.
The timing of an order can be periodic (placing an order every days) or perpetual (placing an order whenever the inventory declines to units).
in this research we discuss how to formulating inv
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Spelling correction is considered a challenging task for resource-scarce languages. The Arabic language is one of these resource-scarce languages, which suffers from the absence of a large spelling correction dataset, thus datasets injected with artificial errors are used to overcome this problem. In this paper, we trained the Text-to-Text Transfer Transformer (T5) model using artificial errors to correct Arabic soft spelling mistakes. Our T5 model can correct 97.8% of the artificial errors that were injected into the test set. Additionally, our T5 model achieves a character error rate (CER) of 0.77% on a set that contains real soft spelling mistakes. We achieved these results using a 4-layer T5 model trained with a 90% error inject
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Background: Pervasive Developmental Disorder (PDD) is a term refers to the overarching group of conditions to which autism spectrum disorder (ASD) belongs .
Objective: This study was designed to determine the existing behavior of children with autism in dental sitting, the behavior improvements in recall dental visits and evaluate the improvement in oral hygiene with using specific visual pedagogy chart.
Type of the study: Cross-sectional study.
Methods: Forty children of both genders, ages ranged from 4 – 6 years having primary teeth only were selected whose medical history included a diagnosis
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Transactions on Engineering and Sciences
. 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
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Background: Anterior disc displacement with reduction (ADDWR) is the most common form of the internal derangement (ID) of temporomandibular joint (TMJ). It is a painful progressive dysfunction and clinically characterized by reciprocal clicking due to shift in the disc anteriorly in relation to the condyle and fossa during mandible elevation. Minimally invasive therapy such as intra-articular injection of platelet-rich plasma (PRP) has been used. PRP is a natural autologous product with a high platelet concentration obtained by centrifugation process to enhance tissue healing through several growth factors (GFs), which are released after endogenous activation. The aim of this study is to assess this technique which is increasingly used toda
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In the present article, mixed ligand metal (II) complexes have been synthesized with Schiff base (1E, 5Z, 6E)-1,7 bis (4-hydroxy-3- methoxyphenyl)-5-(3-hydroxyphenyl) imino) hepta-1,6-dien-3-one derived from Curcumin and 3-aminophenol as primary ligand and L-dopa as a secondary ligand. The Schiff base act as bidentate and arrange to the metals through the azomethine (C=N) nitrogen and (C=O) oxygen atom. The mode of bonding of the Schiff base has been affirmed on the infrared by the UV-Visible, 1H, and 13C NMR spectroscopic techniques. The magnetic susceptibility and the UV-Vis data of the complexes propose octahedral geometry around the central metal ion. The information appears that the complexes have the structure of [L-M-(L-dopa)] system
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