A Two-Dimensional Carbon Semiconductor

We show that patterned defects can be used to disrupt the sub-lattice symmetry of graphene so as to open up a band gap. This way of modifying graphene's electronic structure does not rely on external agencies, the addition of new elements or special boundaries. The method is used to predict a planar, low energy, graphene allotrope with a band gap of 1.2 eV. This defect engineering also allows semiconducting ribbons of carbon to be fabricated within graphene. Linear arrangements of defects lead to naturally embedded ribbons of the semiconducting material in graphene, offering the prospect of two-dimensional circuit logic composed entirely of carbon.Comment: 4 pages, 5 figure

Novel Si(1-x)Ge(x)/Si heterojunction internal photoemission long wavelength infrared detectors

There is a major need for long-wavelength-infrared (LWIR) detector arrays in the range of 8 to 16 microns which operate with close-cycle cryocoolers above 65 K. In addition, it would be very attractive to have Si-based infrared (IR) detectors that can be easily integrated with Si readout circuitry and have good pixel-to-pixel uniformity, which is critical for focal plane array (FPA) applications. Here, researchers report a novel Si(1-x)Ge(x)/Si heterojunction internal photoemission (HIP) detector approach with a tailorable long wavelength infrared cutoff wavelength, based on internal photoemission over the Si(1-x)Ge(x)/Si heterojunction. The HIP detectors were grown by molecular beam epitaxy (MBE), which allows one to optimize the device structure with precise control of doping profiles, layer thickness and composition. The feasibility of a novel Si(1-x)Ge(x)/Si HIP detector has been demonstrated with tailorable cutoff wavelength in the LWIR region. Photoresponse at wavelengths 2 to 10 microns are obtained with quantum efficiency (QE) above approx. 1 percent in these non-optimized device structures. It should be possible to significantly improve the QE of the HIP detectors by optimizing the thickness, composition, and doping concentration of the Si(1-x)Ge(x) layers and by configuring the detector for maximum absorption such as the use of a cavity structure. With optimization of the QE and by matching the barrier energy to the desired wavelength cutoff to minimize the thermionic current, researchers predict near background limited performance in the LWIR region with operating temperatures above 65K. Finally, with mature Si processing, the relatively simple device structure offers potential for low-cost producible arrays with excellent uniformity

Engaging Diverse Secondary Students in International Collaborative Networked Learning

This study examines the processes of engaging a group of highly diverse 7th and 8th grade students in the utilization of information and communication technology (ICT) for collaborative activities through a global networked learning environment called APEC Cyber Academy. Thirty-six middle school students went through a nine-week project-based learning program that aimed at improving ICT skills and promoting international peer learning. Although students showed strong interest in learning about ICT, the findings suggest that students need to be coached in collaboration skills, given appropriate roles to ensure proper division of labor, and supervised closely to ensure the completion of tasks

Electroluminescence from Strained Ge membranes and Implications for an Efficient Si-Compatible Laser

We demonstrate room-temperature electroluminescence (EL) from light-emitting diodes (LED) on highly strained germanium (Ge) membranes. An external stressor technique was employed to introduce a 0.76% bi-axial tensile strain in the active region of a vertical PN junction. Electrical measurements show an on-off ratio increase of one order of magnitude in membrane LEDs compared to bulk. The EL spectrum from the 0.76% strained Ge LED shows a 100nm redshift of the center wavelength because of the strain-induced direct band gap reduction. Finally, using tight-binding and FDTD simulations, we discuss the implications for highly efficient Ge lasers.Comment: 4 Pages, 5 figure

Integrating biological knowledge into variable selection : an empirical Bayes approach with an application in cancer biology

Background: An important question in the analysis of biochemical data is that of identifying subsets of molecular variables that may jointly influence a biological response. Statistical variable selection methods have been widely used for this purpose. In many settings, it may be important to incorporate ancillary biological information concerning the variables of interest. Pathway and network maps are one example of a source of such information. However, although ancillary information is increasingly available, it is not always clear how it should be used nor how it should be weighted in relation to primary data. Results: We put forward an approach in which biological knowledge is incorporated using informative prior distributions over variable subsets, with prior information selected and weighted in an automated, objective manner using an empirical Bayes formulation. We employ continuous, linear models with interaction terms and exploit biochemically-motivated sparsity constraints to permit exact inference. We show an example of priors for pathway- and network-based information and illustrate our proposed method on both synthetic response data and by an application to cancer drug response data. Comparisons are also made to alternative Bayesian and frequentist penalised-likelihood methods for incorporating network-based information. Conclusions: The empirical Bayes method proposed here can aid prior elicitation for Bayesian variable selection studies and help to guard against mis-specification of priors. Empirical Bayes, together with the proposed pathway-based priors, results in an approach with a competitive variable selection performance. In addition, the overall procedure is fast, deterministic, and has very few user-set parameters, yet is capable of capturing interplay between molecular players. The approach presented is general and readily applicable in any setting with multiple sources of biological prior knowledge

Receptive Field Block Net for Accurate and Fast Object Detection

Current top-performing object detectors depend on deep CNN backbones, such as ResNet-101 and Inception, benefiting from their powerful feature representations but suffering from high computational costs. Conversely, some lightweight model based detectors fulfil real time processing, while their accuracies are often criticized. In this paper, we explore an alternative to build a fast and accurate detector by strengthening lightweight features using a hand-crafted mechanism. Inspired by the structure of Receptive Fields (RFs) in human visual systems, we propose a novel RF Block (RFB) module, which takes the relationship between the size and eccentricity of RFs into account, to enhance the feature discriminability and robustness. We further assemble RFB to the top of SSD, constructing the RFB Net detector. To evaluate its effectiveness, experiments are conducted on two major benchmarks and the results show that RFB Net is able to reach the performance of advanced very deep detectors while keeping the real-time speed. Code is available at https://github.com/ruinmessi/RFBNet.Comment: Accepted by ECCV 201

O-GlcNAc modification blocks the aggregation and toxicity of the protein α-synuclein associated with Parkinson's disease.

Several aggregation-prone proteins associated with neurodegenerative diseases can be modified by O-linked N-acetyl-glucosamine (O-GlcNAc) in vivo. One of these proteins, α-synuclein, is a toxic aggregating protein associated with synucleinopathies, including Parkinson's disease. However, the effect of O-GlcNAcylation on α-synuclein is not clear. Here, we use synthetic protein chemistry to generate both unmodified α-synuclein and α-synuclein bearing a site-specific O-GlcNAc modification at the physiologically relevant threonine residue 72. We show that this single modification has a notable and substoichiometric inhibitory effect on α-synuclein aggregation, while not affecting the membrane binding or bending properties of α-synuclein. O-GlcNAcylation is also shown to affect the phosphorylation of α-synuclein in vitro and block the toxicity of α-synuclein that was exogenously added to cells in culture. These results suggest that increasing O-GlcNAcylation may slow the progression of synucleinopathies and further support a general function for O-GlcNAc in preventing protein aggregation

Atomic resolution experimental phase information reveals extensive disorder and bound 2-methyl-2,4-pentanediol in Ca\u3csup\u3e2+\u3c/sup\u3e-calmodulin

Calmodulin (CaM) is the primary calcium signaling protein in eukaryotes and has been extensively studied using various biophysical techniques. Prior crystal structures have noted the presence of ambiguous electron density in both hydrophobic binding pockets of Ca2+-CaM, but no assignment of these features has been made. In addition, Ca2+-CaM samples many conformational substates in the crystal and accurately modeling the full range of this functionally important disorder is challenging. In order to characterize these features in a minimally biased manner, a 1.0 A resolution single-wavelength anomalous diffraction data set was measured for selenomethionine-substituted Ca2+-CaM. Density-modified electron-density maps enabled the accurate assignment of Ca2+-CaM main-chain and side-chain disorder. These experimental maps also substantiate complex disorder models that were automatically built using lowcontour features of model-phased electron density. Furthermore, experimental electron-density maps reveal that 2-methyl-2,4-pentanediol (MPD) is present in the C-terminal domain, mediates a lattice contact between N-terminal domains and may occupy the N-terminal binding pocket. The majority of the crystal structures of target-free Ca2+-CaM have been derived from crystals grown using MPD as a precipitant, and thus MPD is likely to be bound in functionally critical regions of Ca2+-CaM in most of these structures. The adventitious binding of MPD helps to explain differences between the Ca2+-CaM crystal and solution structures and is likely to favor more open conformations of the EF-hands in the crystal

Atomic resolution experimental phase information reveals extensive disorder and bound 2-methyl-2,4-pentanediol in Ca\u3csup\u3e2+\u3c/sup\u3e-calmodulin

Calmodulin (CaM) is the primary calcium signaling protein in eukaryotes and has been extensively studied using various biophysical techniques. Prior crystal structures have noted the presence of ambiguous electron density in both hydrophobic binding pockets of Ca2+-CaM, but no assignment of these features has been made. In addition, Ca2+-CaM samples many conformational substates in the crystal and accurately modeling the full range of this functionally important disorder is challenging. In order to characterize these features in a minimally biased manner, a 1.0 A resolution single-wavelength anomalous diffraction data set was measured for selenomethionine-substituted Ca2+-CaM. Density-modified electron-density maps enabled the accurate assignment of Ca2+-CaM main-chain and side-chain disorder. These experimental maps also substantiate complex disorder models that were automatically built using lowcontour features of model-phased electron density. Furthermore, experimental electron-density maps reveal that 2-methyl-2,4-pentanediol (MPD) is present in the C-terminal domain, mediates a lattice contact between N-terminal domains and may occupy the N-terminal binding pocket. The majority of the crystal structures of target-free Ca2+-CaM have been derived from crystals grown using MPD as a precipitant, and thus MPD is likely to be bound in functionally critical regions of Ca2+-CaM in most of these structures. The adventitious binding of MPD helps to explain differences between the Ca2+-CaM crystal and solution structures and is likely to favor more open conformations of the EF-hands in the crystal