Detection of molecular interactions with modified ferrocene self-assembled monolayers.

Ferrocene-terminated self-assembled monolayers (Fc-SAMs) are one of the most studied molecular aggregates on metal electrodes. They are easy to fabricate and provide a stable and reproducible system to investigate the effect of the microenvironment on the electron transfer parameters. We propose a novel application for Fc-SAMs, the detection of molecular interactions, based on the modification of the SAM with target-specific receptors. Mixed SAMs were fabricated by coimmobilization on Au electrodes of thiolated alkane chains with three different head groups: hydroxy terminating head group, ferrocene head group, and a functional head group such as biotin. Upon binding, the intrinsic electric charge of the target (e.g., streptavidin) modifies the electrostatic potential at the plane of electron transfer, causing a shift in the formal potential E degrees '. The SAMs were characterized by AC voltammetry. The detection mechanism is confirmed by measurements of formal potential as a function of electrolyte pH.

Investigation of multilingual deep neural networks for spoken term detection

The development of high-performance speech processing systems for low-resource languages is a challenging area. One approach to address the lack of resources is to make use of data from multiple languages. A popular direction in recent years is to use bottleneck features, or hybrid systems, trained on multilingual data for speech-to-text (STT) systems. This paper presents an investigation into the application of these multilingual approaches to spoken term detection. Experiments were run using the IARPA Babel limited language pack corpora (∼10 hours/language) with 4 languages for initial multilingual system development and an additional held-out target language. STT gains achieved through using multilingual bottleneck features in a Tandem configuration are shown to also apply to keyword search (KWS). Further improvements in both STT and KWS were observed by incorporating language questions into the Tandem GMM-HMM decision trees for the training set languages. Adapted hybrid systems performed slightly worse on average than the adapted Tandem systems. A language independent acoustic model test on the target language showed that retraining or adapting of the acoustic models to the target language is currently minimally needed to achieve reasonable performance. © 2013 IEEE.