A Flexible Functional Form Approach To Mortality Modeling: Do We Need Additional Cohort Dummies?

The increasing amount of attention paid to longevity risk and funding for old age has created the need for precise mortality models and accurate future mortality forecasts. Orthogonal polynomials have been widely used in technical fields and there have also been applications in mortality modeling. In this paper we adopt a flexible functional form approach using two‐dimensional Legendre orthogonal polynomials to fit and forecast mortality rates. Unlike some of the existing mortality models in the literature, the model we propose does not impose any restrictions on the age, time or cohort structure of the data and thus allows for different model designs for different countries' mortality experience. We conduct an empirical study using male mortality data from a range of developed countries and explore the possibility of using age–time effects to capture cohort effects in the underlying mortality data. It is found that, for some countries, cohort dummies still need to be incorporated into the model. Moreover, when comparing the proposed model with well‐known mortality models in the literature, we find that our model provides comparable fitting but with a much smaller number of parameters. Based on 5‐year‐ahead mortality forecasts, it can be concluded that the proposed model improves the overall accuracy of the future mortality projection. Copyright © 2016 John Wiley & Sons, Ltd.     

Two‐Dimensional Kernel Smoothing of Mortality Surface: An Evaluation of Cohort Strength

Accurate mortality forecasts are of primary interest to insurance companies, pension providers and government welfare systems owing to the rapid increase in life expectancy during the past few decades. Existing mortality models in the literature tend to project future mortality rates by extracting the observed patterns in the mortality surface. Patterns found in the cohort dimension have received a considerable amount of attention and are included in many models of mortality. However, to our knowledge very few studies have considered an evaluation and comparison of cohort patterns across different countries. Moreover, the answer to the question of how the incorporation of the cohort effect affects the forecasting performance of mortality models still remains unclear. In this paper we introduce a new way of incorporating the cohort effect at the beginning of the estimation stage via the implementation of kernel smoothing techniques. Bivariate standard normal kernel density is used and we capture the cohort effect by assigning greater weights along the diagonals of the mortality surface. Based on the results from our empirical study, we compare and discuss the differences in cohort strength across a range of developed countries. Further, the fitting and forecasting results demonstrate the superior performance of our model when compared to some well‐known mortality models in the literature under a majority of circumstances. Copyright © 2016 John Wiley & Sons, Ltd.     

Effect of CNTs and nano ZnO on physical and mechanical properties of polyaniline composites applicable in energy devices

Polyaniline was synthesized chemically in an acidic medium in the presence of Ammonium Peroxydisulphate (APS) as an oxidizing agent. PANI(Polyaniline) nanocomposites were prepared in the presence of various amount of carbon nanotube and zinc oxide (from 1 to 5 wt%) by solution casting method. The free-standing film of polyaniline and its nanocomposites were obtained by vaporization of solvent content. The composition, morphology and structure of the polymer and the nanocomposites were characterized by Fourier transform infrared spectroscopy FT-IR spectra, scanning electron microscopy (SEM) image and XRD pattern. In addition, thermal stability was studied by TGA analysis, electrical conductivity was measured by four-point probe technique and mechanical properties were studied by tensile strength test. The characteristic FTIR peaks of PANI were found to shift to lower wave number in nanocomposites due to the formation of H-bonding. XRD results revealed that the crystallinity of PANI was more noticeable after addition of nano-ZnO, while the intensity of the peaks increased by the addition of ZnO nanoparticles. Furthermore, TGA results showed that the decomposition of the nanocomposite was less than that of pure polyaniline which confirms the successful fabrication of products. Young''s modulus and strength at break point were increased in the case of the nanocomposite, in addition, the electrical conductivity of the PANI/ZnO nanocomposite film was found to be smaller than that of the PANI film while CNTs increase the conductivity of polyaniline.     

Geometry-induced electrostatic trapping of nanometric objects in a fluid

The ability to trap an object-whether a single atom or a macroscopic entity-affects fields as diverse as quantum optics, soft condensed-matter physics, biophysics and clinical medicine. Many sophisticated methodologies have been developed to counter the randomizing effect of Brownian motion in solution, but stable trapping of nanometre-sized objects remains challenging. Optical tweezers are widely used traps, but require sufficiently polarizable objects and thus are unable to manipulate small macromolecules. Confinement of single molecules has been achieved using electrokinetic feedback guided by tracking of a fluorescent label, but photophysical constraints limit the trap stiffness and lifetime. Here we show that a fluidic slit with appropriately tailored topography has a spatially modulated electrostatic potential that can trap and levitate charged objects in solution for up to several hours. We illustrate this principle with gold particles, polymer beads and lipid vesicles with diameters of tens of nanometres, which are all trapped without external intervention and independently of their mass and dielectric function. The stiffness and stability of our electrostatic trap is easily tuned by adjusting the system geometry and the ionic strength of the solution, and it lends itself to integration with other manipulation mechanisms. We anticipate that these features will allow its use for contact-free confinement of single proteins and macromolecules, and the sorting and fractionation of nanometre-sized objects or their assembly into high-density arrays.