. 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

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

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

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

The utilization of targeted therapy for programmed death ligand 1 (PD‑L1) has emerged as a prominent focus in contemporary clinical trials, particularly in the context of immune checkpoint inhibitors. The prognostic significance of the expression of PD‑L1 in invasive mammary cancer remains a subject of discussion in clinical oncology, requiring further exploration, despite its recognition as a biomarker for responsiveness to anti‑PDL1 immunotherapy. The present study was conducted to investigate the immunohistological expression of PD‑L1 in women with triple‑negative breast cancer (TNBC), with a particular focus for searching for the associated clinical and pathological characteristics. The present retrospective study examined the

Type 2 diabetes mellitus (DM) is a group of metabolic disorder disease. The inflammatory markers act as a new risk factor for development of type 2 diabetes with a possible association with ABO/Rh blood groups. Human ABO genes are located on chromosome 9q34.1-q34.2. The aim of this study was to investigate the possible association between inflammatory markers, interleukin (IL) -18 and IL-33 in type 2DM and ABO blood groups. Sixty four patients with newly diagnosed type2 DM and control group consist of twenty healthy Iraqi individual. Laboratory test were include ABO blood groups using standard serological procedures and detection IL-18 and IL-33 in serum by ELISA kits. The Present data showed a significant increase i

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

The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode