Low short term timing jitter in an integrated monolithic extended cavity semiconductor mode-locked laser

Jitter measurements were performed on a monolithically integrated active/passive cavity multiple quantum well laser, actively mode-locked at 10 GHz via modulation of an absorber section. Sub-10 ps pulses were produced upon optimization of the drive conditions to the gain, distributed Bragg reflector, and absorber sections. A model was also developed using travelling wave rate equations. Simulation results suggest that spontaneous emission is the dominant cause of jitter, with carrier dynamics having a time constant of the order of 1 ns.

Short-channel polymer field-effect-transistor fabrication using spin-coating-induced edge template and ink-jet printing

A method to fabricate polymer field-effect transistors with submicron channel lengths is described. A thin polymer film is spin coated on a prepatterned resist with a low resolution to create a thickness contrast in the overcoated polymer layer. After plasma and solvent etching, a submicron-sized line structure, which templates the contour of the prepattern, is obtained. A further lift-off process is applied to define source-drain electrodes of transistors. With a combination of ink-jet printing, transistors with channel length down to 400 nm have been fabricated by this method. We show that drive current density increases as expected, while the on/off current ratio 106 is achieved. © 2005 American Institute of Physics.

Short- and long-term changes in joint co-contraction associated with motor learning as revealed from surface EMG.

In the field of motor control, two hypotheses have been controversial: whether the brain acquires internal models that generate accurate motor commands, or whether the brain avoids this by using the viscoelasticity of musculoskeletal system. Recent observations on relatively low stiffness during trained movements support the existence of internal models. However, no study has revealed the decrease in viscoelasticity associated with learning that would imply improvement of internal models as well as synergy between the two hypothetical mechanisms. Previously observed decreases in electromyogram (EMG) might have other explanations, such as trajectory modifications that reduce joint torques. To circumvent such complications, we required strict trajectory control and examined only successful trials having identical trajectory and torque profiles. Subjects were asked to perform a hand movement in unison with a target moving along a specified and unusual trajectory, with shoulder and elbow in the horizontal plane at the shoulder level. To evaluate joint viscoelasticity during the learning of this movement, we proposed an index of muscle co-contraction around the joint (IMCJ). The IMCJ was defined as the summation of the absolute values of antagonistic muscle torques around the joint and computed from the linear relation between surface EMG and joint torque. The IMCJ during isometric contraction, as well as during movements, was confirmed to correlate well with joint stiffness estimated using the conventional method, i.e., applying mechanical perturbations. Accordingly, the IMCJ during the learning of the movement was computed for each joint of each trial using estimated EMG-torque relationship. At the same time, the performance error for each trial was specified as the root mean square of the distance between the target and hand at each time step over the entire trajectory. The time-series data of IMCJ and performance error were decomposed into long-term components that showed decreases in IMCJ in accordance with learning with little change in the trajectory and short-term interactions between the IMCJ and performance error. A cross-correlation analysis and impulse responses both suggested that higher IMCJs follow poor performances, and lower IMCJs follow good performances within a few successive trials. Our results support the hypothesis that viscoelasticity contributes more when internal models are inaccurate, while internal models contribute more after the completion of learning. It is demonstrated that the CNS regulates viscoelasticity on a short- and long-term basis depending on performance error and finally acquires smooth and accurate movements while maintaining stability during the entire learning process.

Air stable complementary polymer circuits fabricated in ambient condition by inkjet printing

Air stable complementary polymer inverters were demonstrated by inkjet printing of both top-gate electrodes and the semiconductors in ambient conditions. The p-type and n-type polymer semiconductors were also thermally annealed in ambient conditions after printing. The good performance of circuits in ambient condition shows that the transistors are not only air-stable in term of ambient humidity and oxygen, but also inert to ion migration through dielectrics from the printed gate. The result obtained here has further confirmed the feasibility of fabrication of low-cost polymer complementary circuits in a practical environment. © 2011 Elsevier B.V. All rights reserved.

Fast-switching phase gratings using in-plane addressed short-pitch polymer stabilized chiral nematic liquid crystals

We demonstrate a fast-switching (sub-millisecond) phase grating based upon a polymer stabilized short-pitch chiral nematic liquid crystal that is electrically addressed using in-plane electric fields. The combination of the short-pitch and the polymer stabilization enables the diffraction pattern to be switched “on” and “off” reversibly in 600 µs. Results are presented on the far-field diffraction pattern along with the intensity of the diffraction orders as a function of the applied electric field and the response times.

BarraCUDA - a fast short read sequence aligner using graphics processing units.

BACKGROUND: With the maturation of next-generation DNA sequencing (NGS) technologies, the throughput of DNA sequencing reads has soared to over 600 gigabases from a single instrument run. General purpose computing on graphics processing units (GPGPU), extracts the computing power from hundreds of parallel stream processors within graphics processing cores and provides a cost-effective and energy efficient alternative to traditional high-performance computing (HPC) clusters. In this article, we describe the implementation of BarraCUDA, a GPGPU sequence alignment software that is based on BWA, to accelerate the alignment of sequencing reads generated by these instruments to a reference DNA sequence. FINDINGS: Using the NVIDIA Compute Unified Device Architecture (CUDA) software development environment, we ported the most computational-intensive alignment component of BWA to GPU to take advantage of the massive parallelism. As a result, BarraCUDA offers a magnitude of performance boost in alignment throughput when compared to a CPU core while delivering the same level of alignment fidelity. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the alignment throughput. CONCLUSIONS: BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the alignment of millions of sequencing reads generated by NGS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology.BarraCUDA is currently available from http://seqbarracuda.sf.net.