Electronic structures of [001]- and [111]-oriented InSb and GaSb free-standing nanowires

We report on a theoretical study of the electronic structures of InSb and GaSb nanowires oriented along the [001] and [111] crystallographic directions. The nanowires are described by atomistic, spin-orbit inteaction included, tight-binding models, and the band structures and the wave functions of the nanowires are calculated by means of a Lanczos iteration algorithm. For the [001]-oriented InSb and GaSb nanowires, the systems with both square and rectangular cross sections are considered. Here, it is found that all the energy bands are double degenerate. Furthermore, although the lowest conduction bands in these nanowires show good parabolic dispersions, the top valence bands show rich and complex structures. In particular, the topmost valence bands of these nanowires with a square cross section show a double maximum structure. In the nanowires with a rectangular cross section, this double maximum structure is suppressed and top valence bands gradually develop into parabolic bands as the aspect ratio of the cross section is increased. For the [111]-oriented InSb and GaSb nanowires, the systems with hexagonal cross sections are considered. It is found that all the bands at the \Gamma-point are again double degenerate. However, some of them will split into non-degenerate bands when the wave vector moves away from the \Gamma-point. Furthermore, although the lowest conduction bands again show good parabolic dispersions, the topmost valence bands do not show the double maximum structure but, instead, a single maximum structure with its maximum at a wave vector slightly away from the \Gamma-point. We also investigate the effects of quantum confinement on the band structures of the [001]- and [111]-oriented InSb and GaSb nanowires and present an empirical formula for the description of quantization energies of the band edge states in the nanowires.Comment: 17 pages, 19 figure

Effect of a combination of general anesthesia and superficial cervical plexus block with ropivacaine on patients undergoing thyroidectomy

Purpose: To investigate the effect of a combination of general anesthesia and superficial cervical plexus block (SCPB) with ropivacaine on patients undergoing thyroidectomy. Methods: Ninety-six (96) patients undergoing thyroidectomy were randomly divided into control and study group. Both groups were subjected to SCPB in combination with general anesthesia. Ropivacaine was used for SCPB in the study group. Vital signs, visual analogue scale (VAS) scores, and serum interleukin 1β (IL-1β) levels were determined at various time points (T) after tracheal intubation. Occurrence of adverse reactions was recorded. Results: Compared with the control group, mean arterial pressure (MAP), heart rate (HR), diastolic blood pressure (DBP), and systolic blood pressure (SBP) levels from T1 to T5 were declined in study group (p < 0.01). VAS scores of study group were significantly lower at 12, 24, and 48 h after thyroidectomy than in control group (p < 0.05). At 5, 10 and 15 h after surgery, serum IL-1β level in study group was down-regulated (p < 0.05). Moreover, a marked decrease in the incidence of adverse reactions was also found in the study group post-surgery (p < 0.05). Conclusion: Ropivacaine is effective for SCPB in combination with general anesthesia in patients undergoing thyroidectomy. It is safer and more feasible in SCPB when combined with general anesthesia. However, further clinical trials are required to validate this technique

Depth from Refraction Using a Transparent Medium with Unknown Pose and Refractive Index

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P53 and Pten control neural and glioma stem/progenitor cell renewal and differentiation

Glioblastoma (GBM) is a highly lethal brain tumor presenting as one of two subtypes with distinct clinical histories and molecular profiles. The primary GBM subtype presents acutely as high-grade disease that typically harbors EGFR, Pten and Ink4a/Arf mutations, and the secondary GBM subtype evolves from the slow progression of low-grade disease that classically possesses PDGF and p53 events1–3. Here, we show that concomitant CNS-specific deletion of p53 and Pten in the mouse CNS generates a penetrant acute-onset high-grade malignant glioma phenotype with striking clinical, pathological and molecular resemblance to primary GBM in humans. This genetic observation prompted p53 and Pten mutational analysis in human primary GBM, demonstrating unexpectedly frequent inactivating mutations of p53 as well the expected Pten mutations. Integrated transcriptomic profiling, in silico promoter analysis and functional studies of murine neural stem cells (NSCs) established that dual, but not singular, inactivation of p53 and Pten promotes an undifferentiated state with high renewal potential and drives elevated c-Myc levels and its associated signature. Functional studies validated increased c-Myc activity as a potent contributor to the impaired differentiation and enhanced renewal of p53-Pten null NSCs as well as tumor neurospheres (TNSs) derived from this model. c-Myc also serves to maintain robust tumorigenic potential of p53-Pten null TNSs. These murine modeling studies, together with confirmatory transcriptomic/promoter studies in human primary GBM, validate a pathogenetic role of a common tumor suppressor mutation profile in human primary GBM and establish c-Myc as a key target for cooperative actions of p53 and Pten in the regulation of normal and malignant stem/progenitor cell differentiation, self-renewal and tumorigenic potential

BRAF Activation Initiates but Does Not Maintain Invasive Prostate Adenocarcinoma

Prostate cancer is the second leading cause of cancer-related deaths in men. Activation of MAP kinase signaling pathway has been implicated in advanced and androgen-independent prostate cancers, although formal genetic proof has been lacking. In the course of modeling malignant melanoma in a tyrosinase promoter transgenic system, we developed a genetically-engineered mouse (GEM) model of invasive prostate cancers, whereby an activating mutation of BRAFV600E–a mutation found in ∼10% of human prostate tumors–was targeted to the epithelial compartment of the prostate gland on the background of Ink4a/Arf deficiency. These GEM mice developed prostate gland hyperplasia with progression to rapidly growing invasive adenocarcinoma without evidence of AKT activation, providing genetic proof that activation of MAP kinase signaling is sufficient to drive prostate tumorigenesis. Importantly, genetic extinction of BRAFV600E in established prostate tumors did not lead to tumor regression, indicating that while sufficient to initiate development of invasive prostate adenocarcinoma, BRAFV600E is not required for its maintenance

Design and Characterization of a Human Monoclonal Antibody that Modulates Mutant Connexin 26 Hemichannels Implicated in Deafness and Skin Disorders

Background: Mutations leading to changes in properties, regulation, or expression of connexin-made channels have been implicated in 28 distinct human hereditary diseases. Eight of these result from variants of connexin 26 (Cx26), a protein critically involved in cell-cell signaling in the inner ear and skin. Lack of non-toxic drugs with defined mechanisms of action poses a serious obstacle to therapeutic interventions for diseases caused by mutant connexins. In particular, molecules that specifically modulate connexin hemichannel function without affecting gap junction channels are considered of primary importance for the study of connexin hemichannel role in physiological as well as pathological conditions. Monoclonal antibodies developed in the last three decades have become the most important class of therapeutic biologicals. Recombinant methods permit rapid selection and improvement of monoclonal antibodies from libraries with large diversity.Methods: By screening a combinatorial library of human single-chain fragment variable (scFv) antibodies expressed in phage, we identified a candidate that binds an extracellular epitope of Cx26. We characterized antibody action using a variety of biochemical and biophysical assays in HeLa cells, organotypic cultures of mouse cochlea and human keratinocyte-derived cells.Results: We determined that the antibody is a remarkably efficient, non-toxic, and completely reversible inhibitor of hemichannels formed by connexin 26 and does not affect direct cell-cell communication via gap junction channels. Importantly, we also demonstrate that the antibody efficiently inhibits hyperative mutant Cx26 hemichannels implicated in autosomal dominant non-syndromic hearing impairment accompanied by keratitis and hystrix-like ichthyosis-deafness (KID/HID) syndrome. We solved the crystal structure of the antibody, identified residues that are critical for binding and used molecular dynamics to uncover its mechanism of action.Conclusions: Although further studies will be necessary to validate the effect of the antibody in vivo, the methodology described here can be extended to select antibodies against hemichannels composed by other connexin isoforms and, consequently, to target other pathologies associated with hyperactive hemichannels. Our study highlights the potential of this approach and identifies connexins as therapeutic targets addressable by screening phage display libraries expressing human randomized antibodies

3D shape recovery under multiple viewpoints and single viewpoint

This thesis introduces novel algorithms for 3D shape recovery under multiple viewpoints and single viewpoint. Surface of a 3D object is reconstructed by either graph-cuts using images under multiple viewpoints, depth from reflection under a fixed viewpoint, or depth from refraction under a fixed viewpoint. The first part of this thesis revisits the graph-cuts based approach for solving the multi-view stereo problem and proposes a novel foreground / background energy. Unlike traditional graph-cuts based methods which focus on the photo-consistency energy, this thesis targets at deriving a robust and unbiased foreground / background energy which depends on data. It is shown that by using the proposed foreground / background energy, it is possible to recover the object surface from noisy depth maps even in the absence of the photo-consistency energy, which demonstrates the effectiveness of the proposed energy. In the second part of this thesis, a novel method for shape recovery is proposed based on reflection of light using a spherical mirror. Unlike other existing methods which require the prior knowledge of the position and the radius of the spherical mirror, it is shown in this thesis that the object can be reconstructed up to an unknown scale using an unknown spherical mirror. This thesis finally considers recovering object surfaces based on refraction of light and presents a novel depth from refraction method. A scene is captured several times by a fixed camera, with the first image (referred to as the direct image) captured directly by the camera and the others (referred to as the refracted images) by placing a transparent medium with two parallel planar faces between the scene and the camera. With a known pose and refractive index of the medium, a depth map of the scene is then recovered from the displacements of scene points in the images. Unlike traditional depth from refraction methods which require extra steps to estimate the pose and the refractive index of the medium, this thesis presents a novel method to estimate them from the direct and refracted images of the scene. It is shown that the pose of the medium can be recovered from one direct image and one refracted image. It is also shown that the refractive index of the medium can be recovered with a third image captured with the medium placed in a different pose.published_or_final_versionComputer ScienceDoctoralDoctor of Philosoph

Automatic Detection of Display Defects for Smart Meters based on Deep Learning

The smart meter is an essential part of an intelligent grid system. Defects in the LCD screen the smart meters affect their use. Therefore, detection of LCD screen defects of smart meters is of great significance for management and use of smart electricity meters. At present, detection methods are mainly realized by manual detection and automatic detection based on machine vision. However, performance of these two methods is not satisfactory. The fault detection task of a smart meter LCD screen can be divided into two parts: smart meter LCD localization and LCD fault detection. Therefore, this paper proposes a twostage system based on deep learning, which combines YOLOv5 with ResNet34. YOLOv5 is used for smart meter LCD localization and the classification network based on ResNet34 for LCD fault detection. We have constructed an LCD screen localization dataset and an LCD screen defect detection dataset to train and test our model. As a result, our model achieves a defect detection accuracy of 98.9% on the dataset proposed in this paper and can accurately detect the common defects of an LCD screen