Spectrum sensing using two-stage detection to compensate for reduced primary user duty cycle

Spectrum sensing is considered to be one of the most important tasks in cognitive radio. One of the common assumption among current spectrum sensing detectors is the full presence or complete absence of the primary user within the sensing period. In reality, there are many situations where the primary user signal only occupies a portion of the observed signal and the assumption of primary user duty cycle not necessarily fulfilled. In this paper we show that the true detection performance can degrade from the assumed achievable values when the observed primary user exhibits a certain duty cycle. Therefore, a two-stage detection method incorporating primary user duty cycle that enhances the detection performance is proposed. The proposed detector can improve the probability of detection under low duty cycle at the expense of a small decrease in performance at high duty cycle.

Orthogonality defect and reduced search-space size for solving integer least-squares problems

In the context of ambiguity resolution (AR) of Global Navigation Satellite Systems (GNSS), decorrelation among entries of an ambiguity vector, integer ambiguity search and ambiguity validations are three standard procedures for solving integer least-squares problems. This paper contributes to AR issues from three aspects. Firstly, the orthogonality defect is introduced as a new measure of the performance of ambiguity decorrelation methods, and compared with the decorrelation number and with the condition number which are currently used as the judging criterion to measure the correlation of ambiguity variance-covariance matrix. Numerically, the orthogonality defect demonstrates slightly better performance as a measure of the correlation between decorrelation impact and computational efficiency than the condition number measure. Secondly, the paper examines the relationship of the decorrelation number, the condition number, the orthogonality defect and the size of the ambiguity search space with the ambiguity search candidates and search nodes. The size of the ambiguity search space can be properly estimated if the ambiguity matrix is decorrelated well, which is shown to be a significant parameter in the ambiguity search progress. Thirdly, a new ambiguity resolution scheme is proposed to improve ambiguity search efficiency through the control of the size of the ambiguity search space. The new AR scheme combines the LAMBDA search and validation procedures together, which results in a much smaller size of the search space and higher computational efficiency while retaining the same AR validation outcomes. In fact, the new scheme can deal with the case there are only one candidate, while the existing search methods require at least two candidates. If there are more than one candidate, the new scheme turns to the usual ratio-test procedure. Experimental results indicate that this combined method can indeed improve ambiguity search efficiency for both the single constellation and dual constellations respectively, showing the potential for processing high dimension integer parameters in multi-GNSS environment.

Reduced expression of retinoblastoma gene product (pRB) and high expression of p53 are associated with poor prognosis in ovarian cancer

Paraffin sections (n = 168, 27 benign, 16 low malignant potential [LMP] and 125 malignant tumours) from epithelial ovarian tumours were evaluated immunohistochemically for expression of retinoblastoma gene product (pRB) and p53 protein, and the relationship among pRB, p53 and cyclin-dependent kinase inhibitor 2 (CDKN2) gene product p16INK4A (p16) was analysed, following our previous study of p16. Forty-one percent of the benign, 50% of the LMP and most (71%) of the malignant tumours showed high pRB expression. High expression of pRB (>50% pRB-positive cells) significantly correlated with non-mucinous histological subtypes. Reduced pRB expression, substage and residual disease were significant predictors for poor prognosis in stage I patients. All the benign and most of the LMP (81%) tumours were in either the p53-negative or low p53-positive category, but nearly half of the malignant tumours had high p53 expression. High p53 accumulation was found in non-mucinous, high grade and late stage tumours. For well-differentiated carcinomas, high p53 expression was a predictor of poor prognosis. However, even though high p53 expression was not associated with histological subtype, stage or the presence of residual disease, high p53 expression was not an independent predictor when all clinical parameters were combined. For all ovarian cancers, a close correlation was found between high p53 and high p16 expression. The relationship between the expression of pRB and p16 depended on tumour stage. In stage I tumours, high pRB was associated with low p16 reactivity. On the other hand, most advanced tumours showed both high pRB and high p16 reactivity. Int. J. Cancer 74:407–415, 1997. © 1997 Wiley-Liss, Inc.

Reduced Il17a expression distinguishes a Ly6cloMHCIIhi macrophage population promoting wound healing

Macrophages are the main components of inflammation during skin wound healing. They are critical in wound closure and in excessive inflammation, resulting in defective healing observed in chronic wounds. Given the heterogeneity of macrophage phenotypes and functions, we here hypothesized that different subpopulations of macrophages would have different and sometimes opposing effects on wound healing. Using multimarker flow cytometry and RNA expression array analyses on macrophage subpopulations from wound granulation tissue, we identified a Ly6cloMHCIIhi “noninflammatory” subset that increased both in absolute number and proportion during normal wound healing and was missing in Ob/Ob and MYD88−/− models of delayed healing. We also identified IL17 as the main cytokine distinguishing this population from proinflammatory macrophages and demonstrated that inhibition of IL17 by blocking Ab or in IL17A−/− mice accelerated normal and delayed healing. These findings dissect the complexity of the role and activity of the macrophages during wound inflammation and may contribute to the development of therapeutic approaches to restore healing in chronic wounds.

Mechanical properties of graphene : effects of layer number, temperature and isotope

Herein the mechanical properties of graphene, including Young’s modulus, fracture stress and fracture strain have been investigated by molecular dynamics simulations. The simulation results show that the mechanical properties of graphene are sensitive to the temperature changes but insensitive to the layer numbers in the multilayer graphene. Increasing temperature exerts adverse and significant effects on the mechanical properties of graphene. However, the adverse effect produced by the increasing layer number is marginal. On the other hand, isotope substitutions in graphene play a negligible role in modifying the mechanical properties of graphene.

Recent advances in fabrication and characterization of graphene-polymer nanocomposites

Graphene has attracted considerable interest over recent years due to its intrinsic mechanical, thermal and electrical properties. Incorporation of small quantity of graphene fillers into polymer can create novel nanocomposites with improved structural and functional properties. This review introduced the recent progress in fabrication, properties and potential applications of graphene-polymer composites. Recent research clearly confirmed that graphene-polymer nanocomposites are promising materials with applications ranging from transportation, biomedical systems, sensors, electrodes for solar cells and electromagnetic interference. In addition to graphene-polymer nanocomposites, this article also introduced the synergistic effects of hybrid graphene-carbon nanotubes (CNTs) on the properties of composites. Finally, some technical problems associated with the development of these nanocomposites are discussed.

Molecular dynamics investigation on edge stress and shape transition in graphene nanoribbons

Graphene nanoribbon (GNR) with free edges demonstrates unique pre-existing edge energy and edge stress, leading to non-flat morphologies. Using molecular dynamics (MD) methods, we evaluated edge energies as well as edge stresses for four different edge types, including regular edges (armchair and zigzag), armchair edge terminated with hydrogen and reconstructed armchair. The results showed that compressive stress exists in the regular and hydrogen-terminated edges along the edge direction. In contrast, the reconstructed armchair edge is generally subject to tension. Furthermore, we also investigated shape transition between flat and rippled configurations of GNRs with different free edges. It was found that the pre-existing stress at free edges can greatly influence the initial energy state and the shape transition.

Graphene nanocomposites

Graphene, one of the allotropes (diamond, carbon nanotube, and fullerene) of carbon, is a monolayer of honeycomb lattice of carbon atoms discovered in 2004. The Nobel Prize in Physics 2010 was awarded to Andre Geim and Konstantin Novoselov for their ground breaking experiments on the twodimensional graphene [1]. Since its discovery, the research communities have shown a lot of interest in this novel material owing to its unique properties. As shown in Figure 1, the number of publications on graphene has dramatically increased in recent years. It has been confirmed that graphene possesses very peculiar electrical properties such as anomalous quantum hall effect, and high electron mobility at room temperature (250000 cm2/Vs). Graphene is also one of the stiffest (modulus ~1 TPa) and strongest (strength ~100 GPa) materials. In addition, it has exceptional thermal conductivity (5000 Wm-1K-1). Based on these exceptional properties, graphene has found its applications in various fields such as field effect devices, sensors, electrodes, solar cells, energy storage devices and nanocomposites. Only adding 1 volume per cent graphene into polymer (e.g. polystyrene), the nanocomposite has a conductivity of ~0.1 Sm-1 [2], sufficient for many electrical applications. Significant improvement in strength, fracture toughness and fatigue strength has also been achieved in these nanocomposites [3-5]. Therefore, graphene-polymer nanocomposites have demonstrated a great potential to serve as next generation functional or structural materials.

Numerical Modelling of Mechanical Behaviour of Graphene

Graphene, one of the allotropes (diamond, carbon nanotube, and fullerene) of element carbon, is a monolayer of honeycomb lattice of carbon atoms, which was discovered in 2004. The Nobel Prize in Physics 2010 was awarded to Andre Geim and Konstantin Novoselov for their ground breaking work on the two-dimensional (2D) graphene [1]. Since its discovery, the research communities have shown a lot of interest in this novel material owing to its intriguing electrical, mechanical and thermal properties. It has been confirmed that grapheme possesses very peculiar electrical properties such as anomalous quantum hall effect, and high electron mobility at room temperature (250000 cm2/Vs). Graphene also has exceptional mechanical properties. It is one of the stiffest (modulus ~1 TPa) and strongest (strength ~100 GPa) materials. In addition, it has exceptional thermal conductivity (5000 Wm-1K-1). Due to these exceptional properties, graphene has demonstrated its potential for broad applications in micro and nano devices, various sensors, electrodes, solar cells and energy storage devices and nanocomposites. In particular, the excellent mechanical properties of graphene make it more attractive for development next generation nanocomposites and hybrid materials...

Hybrid graphene and graphitic carbon nitride nanocomposite : gap opening, electron–hole puddle, interfacial charge transfer, and enhanced visible light response

Opening up a band gap and finding a suitable substrate material are two big challenges for building graphene-based nanodevices. Using state-of-the-art hybrid density functional theory incorporating long range dispersion corrections, we investigate the interface between optically active graphitic carbon nitride (g-C3N4) and electronically active graphene. We find an inhomogeneous planar substrate (g-C3N4) promotes electronrich and hole-rich regions, i.e., forming a well-defined electron−hole puddle, on the supported graphene layer. The composite displays significant charge transfer from graphene to the g-C3N4 substrate, which alters the electronic properties of both components. In particular, the strong electronic coupling at the graphene/g-C3N4 interface opens a 70 meV gap in g-C3N4-supported graphene, a feature that can potentially allow overcoming the graphene’s band gap hurdle in constructing field effect transistors. Additionally, the 2-D planar structure of g-C3N4 is free of dangling bonds, providing an ideal substrate for graphene to sit on. Furthermore, when compared to a pure g-C3N4 monolayer, the hybrid graphene/g-C3N4 complex displays an enhanced optical absorption in the visible region, a promising feature for novel photovoltaic and photocatalytic applications.

Multifunctional porous graphene for nanoelectronics and hydrogen storage : new properties revealed by first principle calculations

The lack of an obvious “band gap” is a formidable hurdle for making a nanotransistor from graphene. Here, we use density functional calculations to demonstrate for the first time that porosity such as evidenced in recently synthesized porous graphene (http://www.sciencedaily.com/releases/2009/11/091120084337.htm) opens a band gap. The size of the band gap (3.2 eV) is comparable to most popular photocatalytic titania and graphitic C3N4 materials. In addition, the adsorption of hydrogen on Li-decorated porous graphene is much stronger than that in regular Li-doped graphene due to the natural separation of Li cations, leading to a potential hydrogen storage gravimetric capacity of 12 wt %. In light of the most recent experimental progress on controlled synthesis, these results uncover new potential for the practical application of porous graphene in nanoelectronics and clean energy.

Electronic functionality in graphene-based nanoarchitectures : discovery and design via first-principles modeling

Graphene has promised many novel applications in nanoscale electronics and sustainable energy due to its novel electronic properties. Computational exploration of electronic functionality and how it varies with architecture and doping presently runs ahead of experimental synthesis yet provides insights into types of structures that may prove profitable for targeted experimental synthesis and characterization. We present here a summary of our understanding on the important aspects of dimension, band gap, defect, and interfacial engineering of graphene based on state-of-the-art ab initio approaches. Some most recent experimental achievements relevant for future theoretical exploration are also covered.

Hybrid graphene/titania nanocomposite : interface charge transfer, hole doping, and sensitization for visible light response

We demonstrated for the first time by large-scale ab initio calculations that a graphene/titania interface in the ground electronic state forms a charge-transfer complex due to the large difference of work functions between graphene and titania, leading to substantial hole doping in graphene. Interestingly, electrons in the upper valence band can be directly excited from graphene to the conduction band, that is, the 3d orbitals of titania, under visible light irradiation. This should yield well-separated electron−hole pairs, with potentially high photocatalytic or photovoltaic performance in hybrid graphene and titania nanocomposites. Experimental wavelength-dependent photocurrent generation of the graphene/titania photoanode demonstrated noticeable visible light response and evidently verified our ab initio prediction.

Formation of single-walled carbon nanotube via the interaction of graphene nanoribbons : ab initio density functional calculations

The interaction of bare graphene nanoribbons (GNRs) was investigated by ab initio density functional theory calculations with both the local density approximation (LDA) and the generalized gradient approximation (GGA). Remarkably, two bare 8-GNRs with zigzag-shaped edges are predicted to form an (8, 8) armchair single-wall carbon nanotube (SWCNT) without any obvious activation barrier. The formation of a (10, 0) zigzag SWCNT from two bare 10-GNRs with armchair-shaped edges has activation barriers of 0.23 and 0.61 eV for using the LDA and the revised PBE exchange correlation functional, respectively, Our results suggest a possible route to control the growth of specific types SWCNT via the interaction of GNRs.

Numerical analysis of shape transition in graphene nanoribbons

Graphene nanoribbon (GNR) with free edges can exhibit non-flat morphologies due to pre-existing edge stress. Using molecular dynamics (MD) simulations, we investigate the free-edge effect on the shape transition in GNRs with different edge types, including regular (armchair and zigzag), armchair terminated with hydrogen and reconstructed armchair. The results show that initial edge stress and energy are dependent on the edge configurations. It is confirmed that pre-strain on the free edges is a possible way to limit the random shape transition of GNRs. In addition, the influence of surface attachment on the shape transition is also investigated in this work. It is found that surface attachment can lead to periodic ripples in GNRs, dependent on the initial edge configurations.