Development of a Reference Wafer for On-Wafer Testing of Extreme Impedance Devices

This paper describes the design, fabrication, and testing of an on-wafer substrate that has been developed specifically for measuring extreme impedance devices using an on-wafer probe station. Such devices include carbon nano-tubes (CNTs) and structures based on graphene which possess impedances in the κ Ω range and are generally realised on the nano-scale rather than the micro-scale that is used for conventional on-wafer measurement. These impedances are far removed from the conventional 50- reference impedance of the test equipment. The on-wafer substrate includes methods for transforming from the micro-scale towards the nano-scale and reference standards to enable calibrations for extreme impedance devices. The paper includes typical results obtained from the designed wafer

A Framework for Efficient N-Way Interaction Testing in Case/Control Studies with Categorical Data

Goal: Most common diseases are influenced by multiple gene interactions and interactions with the environment. Performing an exhaustive search to identify such interactions is computationally expensive and needs to address the multiple testing problem. A four-step framework is proposed for the efficient identification of n-Way interactions. Methods: The framework was applied on a Multiple Sclerosis dataset with 725 subjects and 147 tagging SNPs. The first two steps of the framework are quality control and feature selection. The next step uses clustering and binary encodes the features. The final step performs the n-Way interaction testing. Results: The feature space was reduced to 7 SNPs and using the proposed binary encoding, more 2-SNP and 3-SNP interactions were identified compared to using the initial encoding. Conclusions: The framework selects informative features and with the proposed binary encoding it is able to identify more n-way interactions by increasing the power of the statistical analysis. © 2020 IEEE