Flexible electronic‐paper active‐matrix displays

Abstract— A100‐μm‐thick 320 × 240‐pixel active‐matrix display integrated into a functional‐device prototype is presented. The active matrix is composed of alternating layers of organic materials and gold. A six‐mask photolithographic process is used. An electrophoretic electronic imaging film is laminated on top of the active matrix. The display is bendable to a radius of 7.5 mm for more than 30,000 repetitions.     

基于ARM的32位MCU提供SoC设计参考

随着制造工艺的迅猛发展,MCU在外设集成、性能、功耗及降低成本方面都有了长足的进展,几乎能提供与SoC相类似的性能,而且应用数量正日趋增长。特别是基于ARM的32位MCU,为SoC设计人员提供了快速低廉的设计参考。     

Electrocorticography-based brain computer interface--the Seattle experience.

Electrocorticography (ECoG) has been demonstrated to be an effective modality as a platform for brain-computer interfaces (BCIs). Through our experience with ten subjects, we further demonstrate evidence to support the power and flexibility of this signal for BCI usage. In a subset of four patients, closed-loop BCI experiments were attempted with the patient receiving online feedback that consisted of one-dimensional cursor movement controlled by ECoG features that had shown correlation with various real and imagined motor and speech tasks. All four achieved control, with final target accuracies between 73%-100%. We assess the methods for achieving control and the manner in which enhancing online control can be accomplished by rescreening during online tasks. Additionally, we assess the relevant issues of the current experimental paradigm in light of their clinical constraints.     

Design and realization of a flexible QQVGA AMOLED display with organic TFTs

We present a QQVGA top emitting monochrome AMOLED display with 85dpi resolution using an organic TFT backplane on low temperature PEN-foil. The backplane process flow is based on a 7 layer photolithography process that yields a final mobility of the OTFT of ～0.4 cm²/Vs. The aperture ratio of the top-emitting OLEDs is over 75%. For operation at 10 V supply voltage (V_DD), the brightness of the display using red and green OLEDs exceeds 200 cd/m².     

Discrimination between nontumor bladder tissue and tumor by Raman spectroscopy

We have applied Raman spectroscopy to discriminate between nontumor and tumor bladder tissue and to determine the biochemical differences therein. Tissue samples from 15 patients were collected, and frozen sections were made for Raman spectroscopy and histology. Twenty-five pseudocolor Raman maps were created in which each color represents a cluster of spectra measured on tissue areas of similar biochemical composition. For each cluster, the cluster-averaged spectrum (CAS) was calculated and classified as tumor and nontumor in accordance to pathohistology. Unguided hierarchical clustering was applied to display heterogeneity between and within groups of nontumor and tumor CAS. A linear discriminant analysis model was developed to discriminate between CAS from tumor and nontumor. The model was tested by a leave-one-patient-out validation, 84 of the 90 CAS (93%) were correctly classified with 94% sensitivity and 92% specificity. Biochemical differences between tumor and nontumor CAS areas were analyzed by fitting spectra of pure compounds to the CAS. Nontumor CAS showed higher collagen content while tumor CAS were characterized by higher lipid, nucleic acid, protein, and glycogen content. Raman spectroscopy enabled effective discrimination between tumor and nontumor bladder tissue based on characterized biochemical differences, despite heterogeneity expressed in both tumor and nontumor CAS.     

The BCI competition. III: Validating alternative approaches to actual BCI problems.

A brain-computer interface (BCI) is a system that allows its users to control external devices with brain activity. Although the proof-of-concept was given decades ago, the reliable translation of user intent into device control commands is still a major challenge. Success requires the effective interaction of two adaptive controllers: the user's brain, which produces brain activity that encodes intent, and the BCI system, which translates that activity into device control commands. In order to facilitate this interaction, many laboratories are exploring a variety of signal analysis techniques to improve the adaptation of the BCI system to the user. In the literature, many machine learning and pattern classification algorithms have been reported to give impressive results when applied to BCI data in offline analyses. However, it is more difficult to evaluate their relative value for actual online use. BCI data competitions have been organized to provide objective formal evaluations of alternative methods. Prompted by the great interest in the first two BCI Competitions, we organized the third BCI Competition to address several of the most difficult and important analysis problems in BCI research. The paper describes the data sets that were provided to the competitors and gives an overview of the results.     

n-Type self-assembled monolayer field-effect transistors for flexible organic electronics

Within this work we present n-type self-assembled monolayer field-effect transistors (SAMFETs) based on a novel perylene bisimide. The molecule spontaneously forms a covalently fixed monolayer on top of an aluminium oxide dielectric via a phosphonic acid anchor group. Detailed studies revealed an amorphous, two-dimensional semiconducting sheet on top of the dielectric. Reliable transistors with electron mobilities on the order of 10^?3 cm²/V s with limited hysteresis were achieved on rigid as well on flexible substrates. Furthermore, a flexible NMOS-bias inverter based on SAMFETs is demonstrated for the first time.