The influence of substrate surface roughness on microstrip transmission line loss using conventional analyses and length‐scale fractal analysis

Two components of conductor topography can impact conductor loss for signals in the GHz frequency range: conductor–ceramic interface roughness and conductor edge angle. This study is an experimental investigation of the influence of these conductor topographies on conductor loss in microstrip circuits produced by thick‐film technology. The aluminum nitride ceramic substrates have different surface roughnesses due to different surface finish processes. The substrate surfaces were characterized using conventional and length‐scale fractal analysis. The conductor–ceramic interface was measured with a contact profilometer. The conductor edge angle and conductor edge profile were measured optically. It was found that there is a direct correlation between conductor loss and conductor edge angle, whereas there is an inverse correlation between loss and substrate roughness or relative length of the conductor–ceramic interface. This is the opposite result to the conventional expectation of surface roughness effects on conductor loss. There is also a negative correlation between conductor edge angle and surface roughness or relative length. The loss behavior can be explained by the interaction of the conductor paste with the surfaces during processing. The paste tends to spread more on the smoother surfaces, and thus creates an elongated edge of diminishing cross‐section and a small edge angle. This leads to greater conductor loss. Copyright © 2009 John Wiley & Sons, Ltd.     

Exponential family mixed membership models for soft clustering of multivariate data

For several years, model-based clustering methods have successfully tackled many of the challenges presented by data-analysts. However, as the scope of data analysis has evolved, some problems may be beyond the standard mixture model framework. One such problem is when observations in a dataset come from overlapping clusters, whereby different clusters will possess similar parameters for multiple variables. In this setting, mixed membership models, a soft clustering approach whereby observations are not restricted to single cluster membership, have proved to be an effective tool. In this paper, a method for fitting mixed membership models to data generated by a member of an exponential family is outlined. The method is applied to count data obtained from an ultra running competition, and compared with a standard mixture model approach.     

Effects of word frequency, contextual diversity, and semantic distinctiveness on spoken word recognition

The relative abilities of word frequency, contextual diversity, and semantic distinctiveness to predict accuracy of spoken word recognition in noise were compared using two data sets. Word frequency is the number of times a word appears in a corpus of text. Contextual diversity is the number of different documents in which the word appears in that corpus. Semantic distinctiveness takes into account the number of different semantic contexts in which the word appears. Semantic distinctiveness and contextual diversity were both able to explain variance above and beyond that explained by word frequency, which by itself explained little unique variance.     

Demonstration of a 100 Hz repetition rate gain-saturated diode-pumped table-top soft x-ray laser

We demonstrate the operation of a gain-saturated table-top soft x-ray laser at 100?Hz repetition rate. The laser generates an average power of 0.15?mW at λ=18.9 nm, the highest laser power reported to date from a sub-20-nm wavelength compact source. Picosecond laser pulses of 1.5?μJ energy were produced at λ=18.9 nm by amplification in a Mo plasma created by tailoring the temporal intensity profile of single pump pulses with 1?J energy produced by a diode-pumped chirped pulse amplification Yb:YAG laser. Lasing was also obtained in the 13.9?nm line of Ni-like Ag. These results increase by an order of magnitude the repetition rate of plasma-based soft x-ray lasers opening the path to milliwatt average power table-top lasers at sub-20?nm wavelengths.     

Modeling texture evolution in equal channel angular extrusion using crystal plasticity finite element models

A new approach to modeling crystallographic texture evolution in Equal Channel Angular Extrusion (ECAE) is presented in this paper. The proposed approach utilizes an elastic–viscoplastic single crystal constitutive model implemented in a finite element framework. A representative volume element of the polycrystal is subjected to boundary conditions that simulate the approximate deformation history experienced by different regions of the sample (at different through-thickness depths) in both Route A and Route C processing. The proposed approach aims to capture the influence of the complex interactions that ensue among the constituent individual crystals of a polycrystal in controlling the texture evolution in the sample, while capturing the boundary conditions inherent to ECAE deformation. The predictions from the proposed approach are compared against previously reported experimental measurements in ECAE of copper. It is observed that the proposed approach provides significantly better agreement with the measurements when compared against previously reported model predictions.