Evidences on Jumps in Industrialization

In this paper we show jumps in industrialization path of newly industrialized countries. Wavelet coefficients method is used for detecting jumps. The wavelet result is consistent with graphical examination. The jump is the way of passing the bad structure trap.

A Matlab Code for Univariate Time Series Forecasting

This M-File forecasts univariate time series such as stock prices with a feedforward neural networks. It finds best (minimume RMSE) network automatically and uses early stopping method for solving overfitting problem.Neural Networks, Time Series, Early Stopping, Forecasting

Structural Changes in NICs: Some Evidences on Attractor Points

In this paper we develop a regression and a kernel density based model for finding fixed points and attractors of dynamical systems to explore attractors of structural change for NICs. The results show that countries consume longer time in some structures than the others. This can be interpreted as existence of attractors that pull countries to themselves in the first stage of the development. In the other words one attractor (low level attractor) prevent countries to reach industrial structure. Awareness of this can be helpful in policymaking for transition from one structure to another. This analysis shades light on the problem that 'why some countries can not get ride of traditional structure?' or bad structure phenomena.Attractors, Structural changes, Fixed Points, Multidimensional Kernel Density, Regression Analysis.

Structural Changes in NICs: Some Evidences on Attractor Points

In this paper we develop a regression and a kernel density based model for finding fixed points and attractors of dynamical systems to explore attractors of structural change for NICs. The results show that countries consume longer time in some structures than the others. This can be interpreted as existence of attractors that pull countries to themselves in the first stage of the development. In the other words one attractor (low level attractor) prevent countries to reach industrial structure. Awareness of this can be helpful in policymaking for transition from one structure to another. This analysis shades light on the problem that 'why some countries can not get ride of traditional structure?' or bad structure phenomena.Attractors, Structural changes, Fixed Points, Multidimensional Kernel Density, Regression Analysis.

An Intelligent technical analysis using neural network

Technical analysis has been one of the most popular methods for stock market predictions for the past few decades. There have been enormous technical analysis methods to study the behavior of stock market for different kinds of trading markets such as currency, commodity or stock. In this paper, we propose two different methods based on volume adjusted moving average and ease of movement for stock trading. These methods are used with and without generalized regression neural network methods and the results are compared with each other. The preliminary results on historical stock price of 20 firms indicate that there is no meaningful difference between various proposed models of this paper

Root Canal Irrigants and Dentin Bonding: An Update

The purpose of the review was to assess the effect of root canal irrigants on dentin bonding. A PubMed-based search was conducted on the articles published from 1980 to 2016. A brief overview and reviewing the effect on dentin bonding of common root canal irrigation solutions such as sodium hypochlorite (NaOCl), chlorhexidine (CHX), ethylenediaminetetraacetic acid (EDTA), mixture of a tetracycline, acid and a detergent (MTAD) and ozone was conducted. Findings showed that, depending on the type of dentin bonding, using NaOCl may decrease, increase or not affect the bond strength. In addition, due to its broad-spectrum matrix metalloproteinase-inhibitoryeffect, CHX as well as MTAD can significantly improve the resin-dentin bondstability. However, the effect of ozone therapy on bond strength was controversial.Keywords: Bond Strength; Chlorhexidine; EDTA; MTAD; Ozone; Sodium Hypochlorit

A Review on Triple Antibiotic Paste as a Suitable Material Used in Regenerative Endodontics

As the root canal system shows different and complicated anatomies, mechanical instrumentation alone has not the ability to provide a bacteria-free environment in root canals. On the other aspect, necrotic tissue remaining can decrease the effects of root canal irrigants and medicaments and also interfere with the adaptation of root canal fillings to dentin. As a result, certain disinfection and irrigation procedures are required to remove the remaining tissues from the root canal area thoroughly and also be able to eliminate the microorganisms. Triple antibiotic paste (TAP) containing metronidazole, ciprofloxacin and minocycline has been proposed as a root canal medicament due to its antimicrobial effects in endodontic regenerative procedures. The purposes of this review were to determine the properties of TAP drugs and to evaluate the efficiency of TAP on the root canal disinfection, in primary and permanent teeth, along with its affection in regeneration/revascularization procedures. The biocompatibility and disadvantages of this medicament were also discussed.Keywords: Endodontics; Intra-canal Medicament; Regeneration; Triple Antibiotic Past

NONPARAMREG: MATLAB function to estimate nonparametric regression

The code estimates nonparametric multivariate regression by rank regression method. Inputs of the function are x(a matrix of independent variables without vector of ones as intercept) and y(a vector of dependent variable). The output is coefficient t stats, F stat and p value. Also a complete report is placed in command window.

ANNLYAP: MATLAB function to calculate Lyapunov exponents

This M-file calculates Lyapunov exponents with minimum RMSE neural network. After estimation of network weights and finding network with minimum BIC, derivatives are calculated. Sum of logarithm of QR decomposition on Jacobian matrix for observations gives spectrum of Lyapunov Exponents. Using the code is very simple, it needs only an scalar time series, number of lags and number of hidden unites. Higher number of hidden units leads to more precise estimation of Lyapunov exponent, but it is time consuming for less powerful personal computers. Number of lags determines number of embedding dimensions. Therefore, please give number of lags equal to number of embedding dimension. The codes creates networks with various neurons up to user supplied value for neurons and lags up to user specified number lags. Total number of networks are equal to number of neurons times number of lags. this modeling strategy is complex but helps to user select embedding dimension based on minimum BIC.Lyapunov Exponents, Chaos, Time Series, Neural Networks, Jaccobian Method

SSAVGDENOIS: MATLAB function to denoise a time series

This code uses state space averaging method for denoising of time series. Running the code is time consuming but its result is precise.Denoising, state space averaging, time series, chaos