Candidate Biomarkers for Genetic and Clinicopathological Diagnosis of Endometrial Cancer

The recent increase in the frequency of endometrial cancer has emphasized the need for accurate diagnosis and improved treatment. The current diagnosis is still based on conventional pathological indicators, such as clinical stage, tumor differentiation, invasion depth and vascular invasion. However, the genetic mechanisms underlying endometrial cancer have gradually been determined, due to developments in molecular biology, leading to the possibility of new methods of diagnosis and treatment planning. New candidate biomarkers for endometrial cancer include those for molecular epigenetic mutations, such as microRNAs. These biomarkers may permit earlier detection of endometrial cancer and prediction of outcomes and are likely to contribute to future personalized therapy for endometrial cancer.     

Improved performance of submicrometer-gate GaAs MESFETs with an Al0.3Ga0.7As buffer layer grown by metal organicvapor phase epitaxy

Submicrometer-gate MESFETs were fabricated with a GaAs active layer and an Al_xGa_1-xAs buffer layer grown by metalorganic vapor-phase epitaxy. To investigate the effect of buffer layer composition on device performance, microwave FETs with GaAs and Al _0.3Ga_0.7As buffer layers were compared. Electron Hall mobility in the n-GaAs active layer was found to be unaffected by the Al content or carrier concentration in the buffer layer. However, a considerable improvement in the maximum available gain to as much as 5.2 dB was obtained at 26.5 GHz for FETs with a p-Al_0.3Ga_0.7 As buffer layer; this was 1.5 dB higher than the gain obtained with a p-GaAs buffer layer. The improvement is due to a 20-30% reduction in both drain conductance and drain-gate capacitance     

A new self-alignment technology for sub-quarter-micron-gate FETsoperating in the Ka-band

A self-alignment technology is proposed that allows fabrication of gates of less than 100 nm using conventional optical lithography. An offset gate structure is realized using this method. The technology is applied to high-power GaAs MESFETs consisting of many individual FETs. The uniformity of the FET characteristics is checked to show reproducibility. The input-output power characteristics of a MESFET with a 3.6-mm gate width were measured at 28 GHz. A linear gain of 4.0 dB and a saturation power of 0.8 W were obtained, demonstrating the overall effectiveness of this technology. It is shown that a 50-nm gate can be fabricated with this technology. A MESFET with a 90-nm gate length that was fabricated and evaluated at high frequency to demonstrate the technology is discussed     

Pick-and-verify: verification-based highly reliable picking system for various target objects in clutter

The reliability of picking task for various objects in clutter, as measured on the Amazon Picking Challenge, is far from the expectations of automation companies. Even if the best-performed team, who run object detection before picking the object, had picked a wrong object in the competition. In this paper, we propose a practical method to compose a highly reliable picking system with verification-based approach to reduce the rate of wrong picking and raise the reliability of picking ordered objects. In our approach, which we call pick-and-verify, the robot recognizes object twice: in clutter scene to detect the target and in hand after picking an object with less time loss and rise of reliability of picking the target. For grasping the detected object we do not assume its pose and it is actually the target object, instead, we adopt vision-based grasp planning for vacuum gripper with sensed 3-D point cloud. With the presented approach, the reliability of picking target objects raised 50%, and the score in the APC2015 competition has been improved to be close to the best-performed team by picking 9 out of 12 objects in 10 min with the same hardware in our previous system.