The Impact of Macroeconomic Variables on the Fluctuation of Jakarta Composite Index (Jci) in Indonesia Stock Exchange (Study at Indonesia Stock Exchange for the Period of 2003-2012)

The purpose of this paper is to analyze the impact of macroeconomic variables on the fluctuation of Jakarta Composite Index (JCI) in Indonesia Stock Exchange. This research consists of four macroeconomic variables as independent variables; inflation, BI rate, exchange rate of rupiah against U.S. dollar and real GDP. The using of JCI as dependent variable is because of it reflects the price change in different types of stocks in the Indonesia capital market as generally. Ordinary Least Square (OLS) is used as data analysis technique. Quarterly data are obtained for the period of ten years starting from January 2003 until December 2012. Augmented Dickey Fuller (ADF) and Phillips-Perron (PP) Unit Root test is employed to check the stationary of data. The results show that data has autocorrelation problem, therefore modifying original equation is taken to take account of the serial correlation by transforming all the variables by r differencing using first differences (regressing yt – yt-1 and xt – xt-1). The result reveals that macroeconomic variables simultaneously have significant impact on JCI. In addition, there are significantly negative impact of BI rate and exchange rate on JCI. The result also reveals that inflation and real GDP do not have any significant impact on JCI

A new mechanism for a naturally small Dirac neutrino mass

A mechanism is proposed in which a right-handed neutrino zero mode and a right-handed charged lepton zero mode can be localized at the same place along an extra compact dimension while having markedly different spreads in their wave functions: a relatively narrow one for the neutrino and a rather broad one for the charged lepton. In their overlaps with the wave function for the left-handed zero modes, this mechanism could produce a natural large hierarchy in the effective Yukawa couplings in four dimensions, and hence a large disparity in masses.Comment: 6 pages (2 with figures), twocolumn forma

An artificial neural network model for rainfall forecasting in Bangkok, Thailand

This paper presents a new approach using an Artificial Neural Network technique to improve rainfall forecast performance. A real world case study was set up in Bangkok; 4 years of hourly data from 75 rain gauge stations in the area were used to develop the ANN model. The developed ANN model is being applied for real time rainfall forecasting and flood management in Bangkok, Thailand. Aimed at providing forecasts in a near real time schedule, different network types were tested with different kinds of input information. Preliminary tests showed that a generalized feedforward ANN model using hyperbolic tangent transfer function achieved the best generalization of rainfall. Especially, the use of a combination of meteorological parameters (relative humidity, air pressure, wet bulb temperature and cloudiness), the rainfall at the point of forecasting and rainfall at the surrounding stations, as an input data, advanced ANN model to apply with continuous data containing rainy and non-rainy period, allowed model to issue forecast at any moment. Additionally, forecasts by ANN model were compared to the convenient approach namely simple persistent method. Results show that ANN forecasts have superiority over the ones obtained by the persistent model. Rainfall forecasts for Bangkok from 1 to 3 h ahead were highly satisfactory. Sensitivity analysis indicated that the most important input parameter besides rainfall itself is the wet bulb temperature in forecasting rainfall

A Study on Tourism Development Strategy of Kaohsiung City in Taiwan after Urban Style Regeneration

Urban tourism has gradually been emphasized in past years; especially, it is regarded as a savior of urban regeneration in old industrial cities. When losing the competitive advantages and getting declined, old industrial cities are facing the challenge of transformation. The development of urban tourism is considered as the opportunity of industrial cities in dark recession that they start to involve in the development of tourism. Analytic Hierarchy Process (AHP) is applied in this study to evaluate key success factors in the tourism development strategy of Kaohsiung City after the urban style regeneration. AHP is used for confirming the levels of various evaluation factors. The first hierarchy contains four evaluation dimensions, and 14 evaluation standards are covered in the second hierarchy. The results reveal the important sequence of four evaluation factors in the second hierarchy as (1) marketing activity, (2) management strategy, (3) recreational environment, and (4) infrastructure, where the importance of evaluation factors in the third hierarchy is sequenced as (1) urban attraction, (2) environmental facility maintenance, (3) celebrations, (4) local characteristics, and (5) natural landscape. The research results and suggestions in this study are expected to enhance the tourism development of Kaohsiung City in Taiwan after the urban style regeneration.     Keywords: urban style, tourism development strategy, key success factors, Delphi method, AH

Entropy production and equilibration in Yang-Mills quantum mechanics

The Husimi distribution provides for a coarse grained representation of the phase space distribution of a quantum system, which may be used to track the growth of entropy of the system. We present a general and systematic method of solving the Husimi equation of motion for an isolated quantum system, and we construct a coarse grained Hamiltonian whose expectation value is exactly conserved. As an application, we numerically solve the Husimi equation of motion for two-dimensional Yang-Mills quantum mechanics (the x-y model) and calculate the time evolution of the coarse grained entropy of a highly excited state. We show that the coarse grained entropy saturates to a value that coincides with the microcanonical entropy corresponding to the energy of the system.Comment: 23 pages, 23 figure

Precision cancer monitoring using a novel, fully integrated, microfluidic array partitioning digital PCR platform.

A novel digital PCR (dPCR) platform combining off-the-shelf reagents, a micro-molded plastic microfluidic consumable with a fully integrated single dPCR instrument was developed to address the needs for routine clinical diagnostics. This new platform offers a simplified workflow that enables: rapid time-to-answer; low potential for cross contamination; minimal sample waste; all within a single integrated instrument. Here we showcase the capability of this fully integrated platform to detect and quantify non-small cell lung carcinoma (NSCLC) rare genetic mutants (EGFR T790M) with precision cell-free DNA (cfDNA) standards. Next, we validated the platform with an established chronic myeloid leukemia (CML) fusion gene (BCR-ABL1) assay down to 0.01% mutant allele frequency to highlight the platform's utility for precision cancer monitoring. Thirdly, using a juvenile myelomonocytic leukemia (JMML) patient-specific assay we demonstrate the ability to precisely track an individual cancer patient's response to therapy and show the patient's achievement of complete molecular remission. These three applications highlight the flexibility and utility of this novel fully integrated dPCR platform that has the potential to transform personalized medicine for cancer recurrence monitoring