Observation of Quantum Capacitance of individual single walled carbon nanotubes

We report a measurement on quantum capacitance of individual semiconducting and small band gap SWNTs. The observed quantum capacitance is remarkably smaller than that originating from density of states and it implies a strong electron correlation in SWNTs

The Fast Medical Image Segmentation of Target Region Based on Improved FM Algorithm

AbstractThis paper studies several kinds of image segmentation algorithm,and region-growing algorithm and fast level set matching algorithm FM are programmed by VC and verified,thereinto,the speed of segmentation of region-growing algorithm is fast.It is primarily affected by the identity of gray level of object region, for the inconsistent object region, excessive segmentation and missing segmentation will happen.The fast matching method can easily handle the geometric objects which topological structure is complex or changing, but the evolving curve also easily leak from the boundary, if there are holes in an object which has been segmented, it will not quite separate the interior outline of the object,so,aiming at the characteristics of medical image,an improved fast matching algorithm is presented in this paper, it can effectively enhance the image segmentation effect and prevent the loss of details of lines, and the internal change of topological structures of the objects can also be segmented better by it

Determination of the Sign of g factors for Conduction Electrons Using Time-resolved Kerr Rotation

The knowledge of electron g factor is essential for spin manipulation in the field of spintronics and quantum computing. While there exist technical difficulties in determining the sign of g factor in semiconductors by the established magneto-optical spectroscopic methods. We develop a time resolved Kerr rotation technique to precisely measure the sign and the amplitude of electron g factor in semiconductors

Anomalously Robust Valley Polarization and Valley Coherence in Bilayer WS2

Coherence is a crucial requirement to realize quantum manipulation through light-matter interactions. Here we report the observation of anomalously robust valley polarization and valley coherence in bilayer WS2. The polarization of the photoluminescence from bilayer WS2 inherits that of the excitation source with both circularly and linearly polarized and retains even at room temperature. The near unity circular polarization of the luminescence reveals the coupling of spin, layer and valley degree of freedom in bilayer system, while the linear polarized photoluminescence manifests quantum coherence between the two inequivalent band extrema in momentum space, namely, the valley quantum coherence in atomically thin bilayer WS2. This observation opens new perspectives for quantum manipulation in atomically thin semiconductors

A case with sarcomatoid hepatocellular carcinoma and literature review

Sarcomatoid hepatocellular carcinoma (SHC) is a relatively rare subtype of liver cancer reported in 1.8–2.0% of surgically resected cases. Previous studies have found that SHC was more likely to occur in patients who received repeated anticancer therapies, but the underlying mechanism has not been exactly illustrated. We report a case of a 62-year-old man with SHC. With the initial implication of abscess suspected liver mass by radiological exams (enhanced Computed Tomography and liver Magnetic Resonance Imaging), the patient underwent a laparoscopic pus debridement and biopsy. The diagnosis of SHC was considered by pathologists. After a short recovery, a second radical resection of the liver tumor and hepatic hilar lymph node dissection were conducted. Postoperative pathology revealed a tumor-free incisal margin and negative lymph node. The recovery of the patient was uneventful. When confronting an occasional liver mass with previous Hepatitis B virus infection, SHC should be included for a candidate diagnosis. If diagnosis is confirmed, high biological malignancy and poor survival should be expected. Surgery is still a main option to treat SHC

Small datasets for fruit detection with transfer learning

A common approach to the problem of fruit detection in images is to design a deep learning network and train a model to locate objects, using bounding boxes to identify regions containing fruit. However, this requires sufficient data and presents challenges for small datasets. Transfer learning, which acquires knowledge from a source domain and brings that to a new target domain, can produce improved performance in the target domain. The work discussed in this paper shows the application of transfer learning for fruit detection with small datasets and presents analysis between the number of training images in source and target domains