Abstract: An organic transistor includes a semiconductor section that includes a thin-film laminate in which a first organic thin film and a second organic thin film are alternately stacked. The thin-film laminate includes at least two layers of the first organic thin film. The first organic thin film is a pentacene thin film, and the second organic thin film is an amorphous organic thin film. The pentacene thin film may be a pentacene bilayer thin film, and the amorphous organic thin film may be a tetraaryldiamine thin film. The tetraaryldiamine thin film may be an ?-NPD thin film. The organic transistor has improved transistor characteristics (e.g., mobility, ON/OFF ratio, or threshold value control).

Abstract: A digital microphone comprises a ?? modulator. The ?? modulator has a resonator including a membrane which vibrates by receiving a sound wave and a wiring pattern disposed opposite to the membrane, an oscillator, including the resonator, for outputting an FM signal according to the vibration of the membrane, and a one-bit quantizer for outputting a one-bit quantized signal by sampling the FM signal with a high-frequency clock.

Abstract: A system rapidly detects and identifies pathogenic bacteria responsible for infection (particularly septicemia), and selects an appropriate antimicrobial drug. A method according to the present invention for detecting and identifying pathogenic bacteria includes performing gene amplification such as real-time PCR, and analyzing the combination of the melting temperatures (Tm values) determined by gene amplification product melting curve analysis or the difference between the Tm values. Specifically, real-time PCR is performed using 4 to 16 primer sets including 1 to 7 primer sets for the 16S ribosomal RNA of bacteria, 1 to 6 primer sets for the 18S ribosomal RNA of fungi, and one primer set respectively for the spa gene and the mecA gene specific to MRSA, and the combination of the Tm values of the amplification product or the combination of the differences between the Tm values is compared with a database to identify pathogenic bacteria responsible for septicemia.