Generalized ridge regression,least squares with stochastic prior information,and Bayesian estimators

The ridge estimator of the usual linear model is generalized by the introduction of an a priori vector r and an associated positive semidefinite matrix S. It is then shown that the generalized ridge estimator can be justified in two ways: (a) by the minimization of the residual sum of squares subject to a constraint on the length, in the metric S, of the vector of differences between r and the estimated linear model coefficients, (b) by incorporating prior knowledge, r playing the role of the vector of means and S proportional to the precision matrix. Both a Bayesian and an Aitken generalized least squares frameworks are used for the latter. The properties of the new estimator are derived and compared to the ordinary least squares estimator. The new method is illustrated with different assumptions on the form of the S matrix.     

Pearling instabilities of membrane tubes with anchored polymers

We have studied the pearling instability induced on hollow tubular lipid vesicles by hydrophilic polymers with hydrophobic side groups along the backbone. The results show that the polymer concentration is coupled to local membrane curvature. The relaxation of a pearled tube is characterized by two different well-separated time scales, indicating two physical mechanisms. We present a model, which explains the observed phenomena and predicts polymer segregation according to local membrane curvature at late stages.     

Both-end opened nanostructure holes by embedded carbon nanotubes realized on thinned membranes on (1 0 0) silicon substrates

Vertically aligned carbon nanotubes (CNT) have been grown in a DC-PECVD apparatus on quartz membranes. 1 0 0-oriented Si wafer has been anisotropically etched in a KOH solution. A mixture of acetylene and hydrogen gases is used to grow CNT while Ni acts as the catalyst layer. As-grown structures have been coated by titanium dioxide using chemical vapor deposition at atmospheric pressure. By means of a polishing and ashing process steps followed by total removing of the quartz membrane both ends of CNTs are opened and nano holes are obtained. SEM analysis is used to study the evolution of such nanostructures.     

Model for cost estimation in a finite-capacity stochastic environment based on shop floor optimization combined with simulation

In recent years several researchers suggested cost estimation models that consider limited capacity. These researchers ignored the stochastic nature of the shop floor. This paper presents a cost estimation model that takes into account the stochastic environment. It is based on marginal analysis – the difference between the total cost without the new order and the total cost with the new order. The proposed model is based on the integration of simulation and optimization. Data generated by the simulation is inserted into the optimization procedure that finds good feasible solutions quickly. A significant advantage of the proposed stochastic cost estimation over an existing deterministic approach is shown. A computational study is performed to test different factors affecting the proposed model.     

Intensity based erbium distribution for erbium doped fiber amplifiers

A method to calculate an optimum Erbium distribution to enhance the gain efficiency in EDFA is proposed. This method calculates Erbium distribution based on optical pump envelop, pump power and optical properties of Erbium ion. The intensity-based Erbium distribution is obtained for single-mode fiber and dispersion-shifted fiber types EDFA for pump power from 10 to 40 mW. All of the profiles have a Gaussian-like shape. For single-mode fiber type EDFA, high gain enhancement is obtained in a relatively short optimal length of fiber. Optimal length of EDFA, using intensity-based Erbium distribution, is increased by a factor of 1.5–3 with respect to the one using stepwise. This optimal length increasing factor is considerably smaller than that of the EDFA, using the one-fourth confinement Erbium profile.     

Modeling catalyst nucleation for carbon nanotube growth by chemical-vapor and plasma-enhanced chemical-vapor deposition methods

The nucleation of the nickel nanoparticles on substrates, a critical process in the growth of carbon nanotubes, has been modeled analytically using thermodynamic and statistical theories. It was hypothesized that during the initial stages of the annealing process smaller nanoparticles with the size of about 5 nm form and, subsequently, randomly hop to make larger nanoparticles. The minimum and maximum diameter of the nickel nanoparticles can be obtained from the derived expressions. In addition, the size-dependent probability of forming the nanoparticles was examined at various temperatures and plasma power densities in chemical-vapor deposition and plasma-enhanced chemical-vapor deposition methods, respectively. The theoretical results presented agreed very well with experimental data.     

Budding and tubulation in highly oblate vesicles by anchored amphiphilic molecules

We studied local budding and tubulation induced in highly oblate lipid vesicles by the anchoring of either polymers having a hydrophilic backbone and grafted hydrophobic anchor groups, or by oleoyl-coenzyme A, an amphiphilic molecule important in lipid metabolism. The dynamics of bud formation, shrinkage, and readsorption is consistent with an induced spontaneous curvature coupled with local amphiphile diffusion on the membrane. We report a novel metastable state prior to bud readsorption.     

Synthesis and Characterization of Carbon-Stabilized Magnesium Nanoparticles

Magnesium nanopowder has attracted many interests in the recent years, which has a very difficult and costly synthesis process because of its high activity. In this work, magnesium nanoparticles stabilized with amorphous carbon (Mg–C nanoparticles) were synthesized by submerged arc discharge technique in kerosene. The arc discharge was generated between two electrodes of magnesium at the arc current of 1 A and arc voltage of 50 V. Mg–C nanoparticles were characterized by various techniques. Dynamic light scattering result indicated that size of magnesium nanoparticles is about 35 nm. X-ray diffraction showed that the produced sample consisted of hexagonal magnesium and amorphous carbon and there was no presence of magnesium oxides in the pattern. Field emission scanning electron microscopy and transmission electron microscopy results illustrated that the sample has morphology of agglomerated nanospheres. Energy dispersive X-ray spectroscopy demonstrated formation of 57 percent magnesium and 43 percent carbon. Differential scanning calorimetry analysis showed that the amorphous carbon increased ignition temperature of nanoparticles by 180 °C compared to pure magnesium micron-sized powder. Therefore, Mg–C nanoparticles can have many applications in different fields similar to magnesium nanopowders. However, by producing Mg–C nanoparticles, there is no need for vacuum chamber or inert gases during production and after that, since amorphous carbon protects magnesium nanoparticles from oxidation.     

Formation of well-packed TiO<Subscript>2</Subscript> nanoparticles on multiwall carbon nanotubes using CVD method to fabricate high sensitive gas sensors

Titanium oxide nanoparticles were coated on multiwall carbon nanotubes (MWCNTs) using an atmospheric pressure chemical vapor deposition (CVD) to achieve highly compact nanoparticles of about 5 nm on CNT structure. The CNTs with a diameter of about 50 nm were grown by plasma enhanced CVD. Gas sensitivity of the fabricated structure was investigated and compared with TiO₂/CNT composite-based gas sensors. The effect of the structural interaction between the nanoparticles and the CNT wall on sensing mechanism of the as-prepared gas sensors was investigated. Ultrasensitive gas sensors were obtained by TiO₂/CNT nanostructures with strong interaction between the MWCNT and the TiO₂ nanoparticles. The measurements show high chemical activity and exceptional electrical response of the as-prepared structure being exposed to gases. Scanning and transmission electron microscopy and X-ray diffraction analysis were used to obtain structural information.