Scrutinizing Various Phenomenological Interactions In The Context Of Holographic Ricci Dark Energy Models

In this paper, we examine two types of interacting holographic dark energy model using Pantheon supernova data, BAO BOSS DR12, CMB Planck 2015, fgas (gas mass fraction) and SZ/Xray (Sunyaev-Zeldovich effect and X-ray emission) data from galaxy clusters (GC). In particular, we considered the Holographic Ricci dark energy and Extended holographic Ricci dark energy models. During this analysis we considered seven type of phenomenological interaction terms (three linear and four non-linear) $Q_1=3Hb\rho_{D}$, $Q_2=3Hb\rho_{m}$, $Q_3=3Hb\left(\rho_{D}+\rho_m\right)$, $Q_4=3Hb\left(\rho_{D}+\frac{\rho_{D}^2}{\rho_{D}+\rho_m}\right)$, $Q_5=3Hb\left(\rho_{m}+\frac{\rho_{m}^2}{\rho_{D}+\rho_m}\right)$, $Q_6=3Hb\left(\rho_{D}+\rho_{m}+\frac{\rho_{D}^2}{\rho_{D}+\rho_m}\right)$, $Q_7=3Hb\left(\rho_{D}+\rho_{m}+\frac{\rho_{m}^2}{\rho_{D}+\rho_m}\right)$ respectively. To find the best model we apply Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) and use the $\Lambda$CDM as the referring model for comparison. Using AIC and BIC models selection method we note that the $Q_1$ and $Q_4$ interaction terms are favored by observational data within the context of the holographic Ricci dark energy models. The obtained results also demonstrated that the considered types of holographic Ricci dark energy model are not favored by observational data since the $\Lambda$CDM is considered as the reference model. We also observed that the values of the deceleration parameter and the transition redshift for all models are compatible with the latest observational data and Planck 2015. In addition, we studied the jerk parameter for all models. Using our modified CAMB code, we observed that the interacting models suppress the CMB spectrum at low multi-poles and enhances the acoustic peaks.Comment: 27 pages, 60 figure

Cyclic Fatigue Resistance of Five Different Glidepath Files in Double Curved Artificial Canals

Introduction: The aim of this study was to examine the cyclic fatigue resistances #16 ProGlider, #15.02 Scout RaCe, #15.03 NeoNiti, One G and Path-File NiTi glide path files in S-shaped artificial canals. Materials and Methods: Twenty files from each group were tested. An artificial groove simulating double (S-shaped) curved canal measuring 1.5 mm in width at the top level decreasing towards the apical reaching 0.3 mm at the tip having a 0.06 taper, 18 mm in length, and 1.5 in depth machined in a stainless steel block was used in this study. Resistance to cyclic fatigue was determined by counting the numbers of cycles to failure (NCF). Furthermore, the fragment length of the fractured tips and angle and radius of curvature formed by each file in each trajectory were evaluated. The data were analyzed using the one-way analysis of variance and Tukey’s HSD test and the level of significance was set at 5%. Results: NeoNiti GPS and Scout RaCe glide path files showed significantly higher NCF values compared to other evaluated glide path files (P<0.001) but no significant difference when compared with each other (P=0.67). Conclusion: Based on this in vitro study NeoNiti GPS and Scout RaCe glide path files had the highest cyclic fatigue resistance in simulated double (S-shaped) curved artificial canals among the evaluated path finding files. Therefore, it seems that they can be used with more confidence in endodontic treatment of S-shaped canals clinically

Evaluation of apical foramen distance in relation to the anatomical apex of mandibular molars by cone-beam computed tomography (CBCT) in a selected Iranian population

Introduction: Knowledge of the internal anatomy and apical foramen of a tooth has always been a fundamental prerequisite for root canal therapy. Aim of the present study was to evaluate the distance of apical foramen in relation to the anatomical apex of mandibular molars by cone beam computed tomography (CBCT) in a selected Iranian population. Material & Methods: In this cross- sectional study, 97 CBCT images of 25-50 years old patients were evaluated .the teeth were assessed in coronal plan. Results: Average (±SD) distance from apical foramen to the anatomical apex in the mesio-buccal and mesio-lingual, distal canal were [0.938 (±0.294)mm], [0.964 (±0.315)mm] and [0.982 (±0.322)mm] respectively. No statistical difference was found between right and left quadrant. Conclusion: This study demonstrated that 1mm distance from radiographic apex in mandibular molars could be appropriate for root canal therapy

Evaluation of the Fractured Surface of Five Endodontic Rotary Instruments: A Metallurgical Study

Introduction: The aim of this study was to compare several metallurgic properties of Neoniti instrument with four other commonly used endodontic rotary files. Methods and Materials: Neoniti A1 (25/0.08), RaCe (25/0.06), Mtwo (25/0.06), Twisted file (25/0.06) and ProTaper Next X2 (25/0.06) were examined by differential scanning calorimetry (DSC) before and after heat treatment at 500°C. X-ray diffraction (XRD) was also performed on the specimens. Furthermore, scanning electron microscopy (SEM) and x-ray energy-dispersive spectrometric (EDS) analyses were carried out on randomly selected fractured files. Results: In SEM tests, dimpled ruptures, characteristic of ductile fracture, were seen in all evaluated cross sections of all files. The SEM results of all evaluated files were alike. EDS results revealed higher proportions of Nickel (Ni) rich intermetallic compounds in Neoniti; whereas, in all the other files the proportion of Titanium (Ti) rich precipitates was higher. DSC results indicated that the temperature present in the oral environment, the austenite phase existed in all files. Mtwo and RaCe files did not show austenite transformation in the temperature range evaluated in this study. Only Neoniti revealed rhombohedal phase (R-phase) transformation. After heat treatment. No significant difference was seen in the transformation temperatures of all evaluated files. XRD evaluations revealed that Neoniti contained both Ni-rich and Ti-rich precipitates. The amount of the martensite phase was higher in ProTaper Next. Conclusion: The metallurgic properties of Neoniti files were different from other evaluated rotary files. This file contained higher proportions of Ni-rich precipitates.Keywords: Differential Scanning Calorimetry; Instrumentation; Nickel-Titanium; Root Canal Preparation; Scanning Electron Microscopy ; Transition Temperatures; X-ray Diffractio

Observational constraints on interacting Tsallis holographic dark energy model

In this paper, we investigate a recent proposed model – so called the Tsallis holographic dark energy (THDE) model with consideration of the Hubble and the event future horizon as IR cutoffs. In this case, we consider the non-gravitational and phenomenological interaction between dark sectors. We fit the free parameters of the model using Pantheon Supernovae Type Ia data, Baryon Acoustic Oscillations, Cosmic Microwave Background, Gamma-Ray burst and the the local value of the Hubble constant. We examine the THDE model to check its compatibility with observational data using objective Information Criterion (IC). We find that the THDE models cannot be supported by observational data once the $$\Lambda$$CDM is considered as the referring model. Therefore we re-examine the analysis with the standard holographic dark energy model (HDE) as another reference. Changing the $$\Lambda$$CDM to main standard dark energy model (HDE), we observe the compatibility of the THDE models. Using the Alcock–Paczynski (AP) test we check the deviation of the model compared to $$\Lambda$$CDM and HDE. Surveying the evolution of squared of sound speed $$v^2_s$$ as an another test we check the stability of the interacting and non-interacting THDE models and we find that while the THDE model with the Hubble horizon as IR cutoff is unstable against the background perturbation, the future event horizon as IR cutoff show stability at the late time. In addition, using the modified version of the CAMB package, we observe the suppressing the CMB spectrum at small K-modes and large scale

Comparison of Cyclic Fatigue Resistance of Five Nickel Titanium Rotary File Systems with Different Manufacturing Techniques

Objectives: The purpose of this study was to evaluate the resistance to fatigue failure of five different nickel-titanium rotary files in three different curved trajectories. Materials and Methods: A total of 150 Neoniti A1, RaCe 25.06, Mtwo 25.06, Twisted file 25.06 and ProTaper Next X2 files with the tip size of 25 were tested (n=30 for each group). Three groove types simulating curved canals were used differing in radius, arc length and position of the arc, each measuring 1.5 mm in width, 20 mm in total length and 2.5 in depth. Resistance to cyclic fatigue was determined by counting the numbers of cycles to failure. Furthermore, the fragment length of the fractured tips and angle and radius of curvature formed by each file in each trajectory were evaluated. The data were analyzed by t-test, one way ANOVA and Tukey’s HSD test. Results: Neoniti showed the highest and RaCe showed the lowest number of cycles to fracture (NCF) values (P<0.05), indicating the highest and lowest fatigue resistance, respectively. The highest and lowest curvature angles were seen in RaCe and Neoniti, respectively. Regarding the radius of curvature, Twisted file had the lowest and Neoniti had the highest values. The mean NCF of all rotary files was lower in the more coronally curved trajectory. Conclusion: The fatigue resistance of the evaluated rotary files was lower in more coronally located curvatures. Neoniti exhibited the highest and RaCe exhibited the lowest fatigue resistance compared to other evaluated files

Prediction of Dead Oil Viscosity: Machine Learning vs. Classical Correlations

Dead oil viscosity is a critical parameter to solve numerous reservoir engineering problems and one of the most unreliable properties to predict with classical black oil correlations. Determination of dead oil viscosity by experiments is expensive and time-consuming, which means developing an accurate and quick prediction model is required. This paper implements six machine learning models: random forest (RF), lightgbm, XGBoost, multilayer perceptron (MLP) neural network, stochastic real-valued (SRV) and SuperLearner to predict dead oil viscosity. More than 2000 pressure–volume–temperature (PVT) data were used for developing and testing these models. A huge range of viscosity data were used, from light intermediate to heavy oil. In this study, we give insight into the performance of different functional forms that have been used in the literature to formulate dead oil viscosity. The results show that the functional form f(γAPI,T), has the best performance, and additional correlating parameters might be unnecessary. Furthermore, SuperLearner outperformed other machine learning (ML) algorithms as well as common correlations that are based on the metric analysis. The SuperLearner model can potentially replace the empirical models for viscosity predictions on a wide range of viscosities (any oil type). Ultimately, the proposed model is capable of simulating the true physical trend of the dead oil viscosity with variations of oil API gravity, temperature and shear rate