Empirical analysis of the US swap curve

This paper provides an empirical analysis of the US swap rate curve using principal components analysis (PCA) to identify the factors which explain the variation in the data. We also investigate the forecasting performance of different econometric models for individual maturities across the curve using daily data over the period 1998 to 2011. The PCA analysis indicates that the first two factors explain approximately 99.76% of the cumulative variation in the sample. We also find that a continuous time modelling approach has a satisfactory performance across the curve based on the RMSE

Studies on blood protein and enzyme polymorphisms in the european moose (Alces Alces)

International audienc

Effect of grape seed extract on heat resistance of Clostridium perfringens vegetative cells in sous vide processed ground beef

PMID = 3100024

US and Canadian term structures of interest rates: A forecasting comparison

This paper provides empirical evidence for the US and Canadian yield curves using a one- and two-factor Generalised Vasicek model, using a data set comprised of daily panel data over the period between 2003 and 2011, which includes the recent global financial crisis. The two-factor model is found to have a good fit for both the US and Canadian yield curves. We also compare the forecasting performance of the term structure model with those from ARIMA, ARFIMA and Nelson-Siegel models. We find that for Canada the Nelson-Siegel model dominates, while for the US the ARFIMA model has a satisfactory performance

Deriving functional astrocytes from mouse embryonic stem cells with a fast and efficient protocol

A growing number of studies highlight the structural and functional diversity of astrocytes throughout the central nervous system. These cells are now seen as heterogeneous as neurons and are implicated in a number of neurological and psychiatric diseases. Efficient generation of diverse subtypes of astrocytes can be a useful tool in investigating synaptogenesis and patterns of activity in developing neural networks. In this study, we developed a protocol for the fast and efficient differentiation of astrocytes from mouse embryonic stem cells, as evidenced by the upregulation of genes related to astrocytic development (Gfap, Aldh1l1). Generated astrocytes exhibit phenotypic diversity, which is demonstrated by the variant expression of markers such as GFAP, ALDH1L1, AQP4 and S100β, amongst subgroups within the same cell population. In addition, astrocytes exhibited differential calcium transients upon stimulation with ATP. Our protocol will facilitate investigations, regarding the involvement of astrocytes in the structural and functional connectivity of neural networks

Identifying Appliances using NIALM with Minimum Features

Government of India has decided to install smart meters in fourteen states. Smart meters are required to identify home appliances to fulfill various tasks in the smart grid environment. Both intrusive and non-intrusive methods have been suggested for identification. However, intrusive method is not suitable for cost and privacy reasons. On the other hand, techniques using non-intrusive appliance load monitoring (NIALM) are yet to result in meaningful practical implementation. Two major challenges in NIALM research are the choice of features (load signatures of appliances), and the appropriate algorithm. Both have a direct impact on the cost of the smart meter. In this paper, we address the two issues and propose a procedure with only four features and a simple algorithm to identify appliances. Our experimental setup, on the recommended specifications of the internal electrical wiring in Indian residences, used common household appliances’ load signatures of active and reactive powers, harmonic components and their magnitudes. We show that these four features are essential and sufficient for implementation of NIALM with a simple algorithm. We have introduced a new approach of ‘multi point sensing’ and ‘group control’ rather than the ‘single point sensing’ and ‘individual control’, used so far in NIALM techniques.DOI:http://dx.doi.org/10.11591/ijece.v4i6.671