Ultrafast Electron–Phonon Coupling at Metal-Dielectric Interface

Energy transfer from photo-excited electrons in a metal thin film to the dielectric substrate is important for understanding the ultrafast heat transfer process across the two materials. Substantial research has been conducted to investigate heat transfer in a metal-dielectric structure. In this work, a two-temperature model in metal was used to analyze the interface electron and dielectric substrate coupling. An improved temperature and wavelength-dependent Drude–Lorentz model was implemented to interpret the signals obtained in optical measurements. Ultrafast pump-and-probe measurements on Au-Si samples were carried out, where the probe photon energy was chosen to be close to the interband transition threshold of gold to minimize the influence of non-equilibrium electrons on the optical response and maximize the thermal modulation to the optical reflectance. Electron-substrate interface thermal conductance at different pump laser fluences was obtained, and was found to increase with the interface temperature.     

Low temperature crystallographic data on Kevlar 49 fibres

Using X-ray diffraction data, the behaviour of Kevlar 49 fibres at low temperatures, up to –100°C, has been analysed. During cooling, the basal plane of the monoclinic unit cell shrinks whereas the c- (unique, chain axis) length is not significantly affected. In contrast, in the return heating cycle to ambient temperature, the basal plane expands and contraction occurs along the chain direction. The unit cell registers a reduction in volume in both the cooling and heating cycles. Conspicuously, after a cycle of cooling and heating, the unit cell does not return to its initial volume.     

Reducing cycle times in manufacturing and supply chains by input and service rate smoothing

A key performance parameter of a manufacturing network or supply chain is its cycle time; the time that a typical item spends in the network. A previous simulation study on a semiconductor assembly and test facility showed that cycle times could be reduced by having smooth input and service rates. This suggested that there is a “cycle time principle” that, for a system with a specified throughput or input rate, the shortest cycle times are obtained when the input and service rates do not vary over time. We prove that this principle is true for the M/G/1 and M/M/s queueing systems and Jackson networks. The analysis involves establishing several results on the concavity of waiting time probabilities and the convexity of expected waiting times and queue lengths, as functions of input and service rates. These results also have natural uses in other optimization problems.     

CMV colitis masquerading as colon cancer--an unusual presentation of acquired immunodeficiency syndrome

To determine whether there is any correlation between sudden decrease in barometric pressure and onset of labor, a non-experimental, retrospective study at a 948-bed tertiary care hospital was done. Pregnant patients of 36 weeks gestation or more who presented with spontaneous onset of labor during the 48 hours surrounding the 12 occurrences of significant drop in barometric pressure in 1992 were included in the study. Significantly more occurrences of onset of labor were identified in the 24 hours after a drop in barometric pressure than were identified in the 24 hours prior to the drop in barometric pressure (P < 0.05). Therefore, the overall number of labor onsets increased in the 24 hours following a significant drop in barometric pressure.     

Development of Stretch Solder Interconnections for Wafer Level Packaging

A wafer level packaging technique has been developed with an inherent advantage of good solder joint co-planarity suitable for wafer level testing. A suitable weak metallization scheme has also been established for the detachment process. During the fabrication process, the compliancy of the solder joint is enhanced through stretching to achieve a small shape factor. Thermal cycling reliability of these hourglass-shaped, stretch solder interconnections has been found to be considerably better than that of the conventional spherical-shaped solder bumps.     

A new method to estimate parameters of linear compartmental models using artificial neural networks

At present, the preferred tool for parameter estimation in compartmental analysis is an iterative procedure; weighted nonlinear regression. For a large number of applications, observed data can be fitted to sums of exponentials whose parameters are directly related to the rate constants/coefficients of the compartmental models. Since weighted nonlinear regression often has to be repeated for many different data sets, the process of fitting data from compartmental systems can be very time consuming. Furthermore the minimization routine often converges to a local (as opposed to global) minimum. In this paper, we examine the possibility of using artificial neural networks instead of weighted nonlinear regression in order to estimate model parameters. We train simple feed-forward neural networks to produce as outputs the parameter values of a given model when kinetic data are fed to the networks' input layer. The artificial neural networks produce unbiased estimates and are orders of magnitude faster than regression algorithms. At noise levels typical of many real applications, the neural networks are found to produce lower variance estimates than weighted nonlinear regression in the estimation of parameters from mono- and biexponential models. These results are primarily due to the inability of weighted nonlinear regression to converge. These results establish that artificial neural networks are powerful tools for estimating parameters for simple compartmental models.