Showing papers by "Southeast University published in 2010"

Toward discovery science of human brain function

Abstract: Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual's "functional connectome." Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon_1000/.

The sequence and de novo assembly of the giant panda genome

Abstract: Using next-generation sequencing technology alone, we have successfully generated and assembled a draft sequence of the giant panda genome. The assembled contigs (2.25 gigabases (Gb)) cover approximately 94% of the whole genome, and the remaining gaps (0.05 Gb) seem to contain carnivore-specific repeats and tandem repeats. Comparisons with the dog and human showed that the panda genome has a lower divergence rate. The assessment of panda genes potentially underlying some of its unique traits indicated that its bamboo diet might be more dependent on its gut microbiome than its own genetic composition. We also identified more than 2.7 million heterozygous single nucleotide polymorphisms in the diploid genome. Our data and analyses provide a foundation for promoting mammalian genetic research, and demonstrate the feasibility for using next-generation sequencing technologies for accurate, cost-effective and rapid de novo assembly of large eukaryotic genomes.

Renewable Chemical Commodity Feedstocks from Integrated Catalytic Processing of Pyrolysis Oils

Abstract: Fast pyrolysis of lignocellulosic biomass produces a renewable liquid fuel called pyrolysis oil that is the cheapest liquid fuel produced from biomass today Here we show that pyrolysis oils can be converted into industrial commodity chemical feedstocks using an integrated catalytic approach that combines hydroprocessing with zeolite catalysis The hydroprocessing increases the intrinsic hydrogen content of the pyrolysis oil, producing polyols and alcohols The zeolite catalyst then converts these hydrogenated products into light olefins and aromatic hydrocarbons in a yield as much as three times higher than that produced with the pure pyrolysis oil The yield of aromatic hydrocarbons and light olefins from the biomass conversion over zeolite is proportional to the intrinsic amount of hydrogen added to the biomass feedstock during hydroprocessing The total product yield can be adjusted depending on market values of the chemical feedstocks and the relative prices of the hydrogen and biomass

Three-dimensional broadband ground-plane cloak made of metamaterials

Abstract: Optical cloaking has already been demonstrated in two dimensions, and also in three dimensions for a limited range of angles. Now, Ma and Cui present a metamaterial-based cloaking device that can shield an object lying on the ground plane from all viewing angles at microwave frequencies.

Multi-label learning by exploiting label dependency

Abstract: In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (exponential) number of possible label sets, the task of learning from multi-label examples is rather challenging. Therefore, the key to successful multi-label learning is how to effectively exploit correlations between different labels to facilitate the learning process. In this paper, we propose to use a Bayesian network structure to efficiently encode the conditional dependencies of the labels as well as the feature set, with the feature set as the common parent of all labels. To make it practical, we give an approximate yet efficient procedure to find such a network structure. With the help of this network, multi-label learning is decomposed into a series of single-label classification problems, where a classifier is constructed for each label by incorporating its parental labels as additional features. Label sets of unseen examples are predicted recursively according to the label ordering given by the network. Extensive experiments on a broad range of data sets validate the effectiveness of our approach against other well-established methods.

Three-dimensional broadband and broad-angle transformation-optics lens

Abstract: Lenses with superior performance with respect to conventional uniform materials are desirable. The authors show a three-dimensional lens, made of multilayered metamaterials and based on approximate transformation optics, which works in different polarizations at broad viewing angles and with wide bandwidth.

On Pinning Synchronization of Directed and Undirected Complex Dynamical Networks

Abstract: This paper presents some low-dimensional pinning criteria for global synchronization of both directed and undirected complex networks, and proposes specifically pinning schemes to select pinned nodes by investigating the relationship among pinning synchronization, network topology, and the coupling strength. The paper answers the challenging questions in pinning control of complex networks: 1) what sufficient conditions can guarantee global asymptotic stability of the pinning process; 2) what nodes should be chosen as pinned candidates; and 3) how many nodes are needed to be pinned for a fixed coupling strength? Furthermore, an adaptive pinning control scheme is developed to achieve synchronization of general complex networks. Numerical examples are given to verify our theoretical analysis.

Visualizing of the cellular uptake and intracellular trafficking of exosomes by live-cell microscopy.

Abstract: Cells release exosomes to transfer various molecules to other cells. Exosomes are involved in a number of physiological and pathological processes. They are emerging great potential utility for diseases diagnosis and treatment recently. However, the internalization and intracellular trafficking of exosomes have not been described clearly. In this work, exosomes were isolated from the culture medium of PC12 cells, labeled by lipophilic dye and amino-reactive fluorophore, incubated with resting PC12 cells. The results of live-cell microscopy indicated that exosomes were internalized through endocytosis pathway, trapped in vesicles, and transported to perinuclear region. Particle tracking fluorescent vesicles suggested that the active transport of exosomes may be mediated by cytoskeleton. The proteins on exosome membrane were found to be released from exosomes and trapped in lysosome. The inverted transport of lipophilic dye from perinuclear region to cell peripheries was revealed, possibly caused by recycling of the exosome lipids. This study provides new sight into the mechanisms of exosome uptake and intracellular fate.

Preparation of Gold Nanoparticle/Graphene Composites with Controlled Weight Contents and Their Application in Biosensors

Abstract: Positively charged gold nanoparticles (GNPs) with diameters of 2−6 nm were self-assembled onto the surfaces of 1-pyrene butyric acid functionalized graphene (PFG) sheets simply by mixing their aqueous dispersions. The amount of GNPs assembled on PFG sheets can be easily modulated by controlling the feeding weight ratio of both components. Furthermore, it was found that PFG sheets had a high loading capability of GNPs, and the maximum value was determined to be about 300 times the PFG’s own weight. Glassy carbon (GC) electrodes modified with the composite of GNPs and PFG (GNP−PFG composite) showed strong electrocatalytic activity and high electrochemical stability. A uric acid electrochemical sensor based on the composite modified electrode exhibited rapid response and high sensitivity.

Mobile phone based drunk driving detection

Abstract: Drunk driving, or officially Driving Under the Influence (DUI) of alcohol, is a major cause of traffic accidents throughout the world. In this paper, we propose a highly efficient system aimed at early detection and alert of dangerous vehicle maneuvers typically related to drunk driving. The entire solution requires only a mobile phone placed in vehicle and with accelerometer and orientation sensor. A program installed on the mobile phone computes accelerations based on sensor readings, and compares them with typical drunk driving patterns extracted from real driving tests. Once any evidence of drunk driving is present, the mobile phone will automatically alert the driver or call the police for help well before accident actually happens. We implement the detection system on Android G1 phone and have it tested with different kinds of driving behaviors. The results show that the system achieves high accuracy and energy efficiency.

Prussian blue modified iron oxide magnetic nanoparticles and their high peroxidase-like activity

Abstract: Prussian blue (PB) modified γ-Fe2O3 magnetic nanoparticles (MNPs) featuring varying PB proportions were synthesized and characterized by TEM, FTIR, UV-vis, EDS, XRD and XPS. The magnetic properties and peroxidase-like catalytic activity of the synthesized nanoparticles were investigated. With increasing PB content, the magnetism could still maintain a high level. Peroxidase-like activity was enhanced as the PB proportion increased. Catalysis was found to follow Michaelis–Menten kinetics. The calculated kinetic parameters exhibited strong affinity with substrates and high catalytic activity, which are three orders of magnitudes larger than that for magnetite nanoparticles of similar size. Based on the high activity, an enzyme immunoassay model was established: staphylococcal protein A (SPA) was conjugated onto the surface of the nanoparticles to construct a new nanoprobe which was employed to detect IgG immobilized to 96-well plates. The results presented a linear absorbance enhancement with concentration of IgG, suggesting that PBMNPs serve as an inexpensive horseradish peroxidase (HRP) mimic enzyme with potential applications in bio-detection.

A Universal Trend of Reduced mRNA Stability near the Translation-Initiation Site in Prokaryotes and Eukaryotes

Abstract: Recent studies have suggested that the thermodynamic stability of mRNA secondary structure near the start codon can regulate translation efficiency in Escherichia coli, and that translation is more efficient the less stable the secondary structure. We survey the complete genomes of 340 species for signals of reduced mRNA secondary structure near the start codon. Our analysis includes bacteria, archaea, fungi, plants, insects, fishes, birds, and mammals. We find that nearly all species show evidence for reduced mRNA stability near the start codon. The reduction in stability generally increases with increasing genomic GC content. In prokaryotes, the reduction also increases with decreasing optimal growth temperature. Within genomes, there is variation in the stability among genes, and this variation correlates with gene GC content, codon bias, and gene expression level. For birds and mammals, however, we do not find a genome-wide trend of reduced mRNA stability near the start codon. Yet the most GC rich genes in these organisms do show such a signal. We conclude that reduced stability of the mRNA secondary structure near the start codon is a universal feature of all cellular life. We suggest that the origin of this reduction is selection for efficient recognition of the start codon by initiator-tRNA.

Migration and localization of metal atoms on strained graphene.

Abstract: Reconstructed point defects in graphene are created by electron irradiation and annealing. By applying electron microscopy and density functional theory, it is shown that the strain field around these defects reaches far into the unperturbed hexagonal network and that metal atoms have a high affinity to the nonperfect and strained regions of graphene. Metal atoms are attracted by reconstructed defects and bonded with energies of about 2 eV. The increased reactivity of the distorted � -electron system in strained graphene allows us to attach metal atoms and to tailor the properties of graphene.

Nitrogen-doped carbon nanotubes: high electrocatalytic activity toward the oxidation of hydrogen peroxide and its application for biosensing.

Abstract: This study compares the electrocatalytic activity of nitrogen-doped carbon nanotubes (NCNTs) with multiwalled carbon nanotubes (MWCNTs). Results indicate that NCNTs possess a marked electrocatalytic activity toward oxygen reduction reaction (ORR) by an efficient four-electron process in the alkaline condition, while the process of MWCNTs is through a two-electron pathway. Meanwhile, NCNTs show a very attractive electrochemical performance for the redox reaction of hydrogen peroxide (H2O2) and could be employed as a H2O2 sensor at a low potential of +0.3 V. The sensitivity of the NCNT-based biosensor reaches 24.5 microA/mM, more than 87 times that of the MWCNT-based one. Moreover, NCNTs exhibit striking analytical stability and reproducibility, which enables a reliable and sensitive determination of glucose by monitoring H2O2 produced by an enzymatic reaction between glucose oxidase/glucose or choline oxidase/choline at +0.3 V without the help of the electron mediator. The NCNT-based glucose biosensor has a linear range from 2 to 140 microM with an extremely high sensitivity of 14.9 microA/mM, and the detection limit is estimated to be 1.2 microM at a signal-to-noise ratio of 3. The results indicate that the NCNTs are good nanostructured materials for potential application in biosensors.

Robust Exponential Stability of Markovian Jump Impulsive Stochastic Cohen-Grossberg Neural Networks With Mixed Time Delays

Abstract: This paper is concerned with the problem of exponential stability for a class of Markovian jump impulsive stochastic Cohen-Grossberg neural networks with mixed time delays and known or unknown parameters. The jumping parameters are determined by a continuous-time, discrete-state Markov chain, and the mixed time delays under consideration comprise both time-varying delays and continuously distributed delays. To the best of the authors' knowledge, till now, the exponential stability problem for this class of generalized neural networks has not yet been solved since continuously distributed delays are considered in this paper. The main objective of this paper is to fill this gap. By constructing a novel Lyapunov-Krasovskii functional, and using some new approaches and techniques, several novel sufficient conditions are obtained to ensure the exponential stability of the trivial solution in the mean square. The results presented in this paper generalize and improve many known results. Finally, two numerical examples and their simulations are given to show the effectiveness of the theoretical results.

Exceptional dielectric phase transitions in a perovskite-type cage compound.

Abstract: Progress in metal–organic framework (MOF) research has recently opened up new possibilities to realize hybrid materials with unique solid-state electric properties, such as ferroelectricity, piezoelectricity, and dielectricity. Compared with conventional pure inorganic/organic compounds, MOFs take advantage of structural tunability and multifunctionality to develop polarizable molecular materials with rich dielectric properties. Among them, switchable molecular dielectrics, which undergo transitions between high and low dielectric states, are promising materials with potential applications especially in data communication, signal processing, and sensing. However, reports of such MOFs have remained scarce owing to a lack of knowledge regarding control of the motions of the dipole moments in the crystal lattice. From the microscopic point of view, the tunable dielectric permittivity closely relates to the positional freedom of molecular dipole moments. For instance, polar molecules in the liquid state show larger dielectric permittivities than in the solid state owing to the “melting” and “freezing” of the molecular reorientations. With regard to MOFs, the dipole moments are rigidly fixed in the crystal structures in most cases, usually resulting in small and almost temperatureindependent dielectric permittivities. Fortunately, there is still much room for the integration of flexible units into the frameworks; that is, the introduction of a polarization rotation unit in the form of a solid-state molecular rotator or host–guest systems, such as porous compounds. Cage compounds, which are assembled by the inclusion of guest species into the well-matched host cages, is a very promising class of switchable molecular dielectrics. The reorientations of the polar guests in the carefully designed cage compounds may give rise to large dielectric permittivities, which are characterized by a multidimensional liquidlike state, and their freezing will lead to low-dielectric systems. Herein, we present a novel organic–inorganic hybrid cage compound (HIm)2[KFe(CN)6] (1; HIm = imidazolium) with a perovskite-type structure, in which the order– disorder behavior of the HIm polar guests give rise to striking dielectric anomalies. The (HIm)2[KFe(CN)6] crystals were grown from an aqueous solution of K3[Fe(CN)6] and (HIm)Cl salts by slow evaporation at room temperature as large red hexagonal plate perpendicular to the c axis. The existence of HIm and CN groups in 1 is verified by IR spectra. The CN group in 1 exhibits several vibrations in the range 2102–2143 cm , distinct from a single peak of 2118 cm 1 in K3[Fe(CN)6]. Thermal analysis reveals that 1 undergoes two phase transitions, at 187 K (T1) and 158 K (T2). For convenience, we label the phase above T1 as the high-temperature phase (HTP), the phase between T1 and T2 as intermediate-temperature phase (ITP), and the phase below T2 as low-temperature phase (LTP). Variable-temperature X-ray diffraction analysis reveals that 1 crystallizes in the centrosymmetric space group R3̄m at 293 K and 173 K as the HTP and ITP, respectively, and in C2/c at 83 K as the LTP. The common structural feature of the compound is the anionic cage formed by Fe CN K units in which the HIm cation resides. The metal–cyanide bond is strong and covalent in the fragment {Fe(CN)6} (Fe C = 1.9 ) and much weaker and ionic in the fragment {K(NC)6} (K N = 2.9 ; Figure 1). In the HTP, the cation reorients around the threefold c axis perpendicular to the ring plane. The cation consists of three carbon and two nitrogen atoms, which were all refined as carbon atoms. The five atoms of the

Resting brain connectivity: changes during the progress of Alzheimer disease.

Abstract: Our study results demonstrate that abnormal posterior cingulate cortex connectivity modulation of the default mode could change along with Alzheimer disease stage progression.

An omnidirectional electromagnetic absorber made of metamaterials

Abstract: In a recent theoretical work by Narimanov and Kildishev (2009 Appl. Phys. Lett. 95 041106) an optical omnidirectional light absorber based on metamaterials was proposed, in which theoretical analysis and numerical simulations showed that all optical waves hitting the absorber are trapped and absorbed. Here we report the first experimental demonstration of an omnidirectional electromagnetic absorber in the microwave frequency. The proposed device is composed of non-resonant and resonant metamaterial structures, which can trap and absorb electromagnetic waves coming from all directions spirally inwards without any reflections due to the local control of electromagnetic fields. It is shown that the absorption rate can reach 99 per cent in the microwave frequency. The all-directional full absorption property makes the device behave like an 'electromagnetic black body', and the wave trapping and absorbing properties simulate, to some extent, an 'electromagnetic black hole.' We expect that such a device could be used as a thermal emitting source and to harvest electromagnetic waves.

Group IV nanoparticles: synthesis, properties, and biological applications.

Abstract: In this review, the emerging roles of group IV nanoparticles including silicon, diamond, silicon carbide, and germanium are summarized and discussed from the perspective of biologists, engineers, and medical practitioners. The synthesis, properties, and biological applications of these new nanomaterials have attracted great interest in the past few years. They have gradually evolved into promising biomaterials due to their innate biocompatibility; toxic ions are not released when they are used in vitro or in vivo, and their wide fluorescence spectral regions span the near-infrared, visible, and near-ultraviolet ranges. Additionally, they generally have good resistance against photobleaching and have lifetimes on the order of nanoseconds to microseconds, which are suitable for bioimaging. Some of the materials possess unique mechanical, chemical, or physical properties, such as ultrachemical and thermal stability, high hardness, high photostability, and no blinking. Recent data have revealed the superiority of these nanoparticles in biological imaging and drug delivery.

Anisotropic mechanical properties of graphene sheets from molecular dynamics

Abstract: Anisotropic mechanical properties are observed for a sheet of graphene along different load directions. The anisotropic mechanical properties are attributed to the hexagonal structure of the unit cells of the graphene. Under the same tensile loads, the edge bonds bear larger load in the longitudinal mode (LM) than in the transverse mode (TM), which causes fracture sooner in LM than in TM. The Young's modulus and the third order elastic modulus for the LM are slightly larger than that for the TM. Simulation also demonstrates that, for both LM and TM, the loading and unloading stress–strain response curves overlap as long as the graphene is unloaded before the fracture point. This confirms that graphene sustains complete elastic and reversible deformation in the elongation process.

PerFallD: A pervasive fall detection system using mobile phones

Abstract: Falls are a major health risk that diminish the quality of life among elderly people With the elderly population surging, especially with aging “baby boomers”, fall detection becomes increasingly important However, existing commercial products and academic solutions struggle to achieve pervasive fall detection In this paper, we propose utilizing mobile phones as a platform for pervasive fall detection system development To our knowledge, we are the first to do so We design a detection algorithm based on mobile phone platforms We propose PerFallD, a pervasive fall detection system implemented on mobile phones We implement a prototype system on the Android G1 phone and conduct experiments to evaluate our system In particular, we compare PerFallD's performance with that of existing work and a commercial product Experimental results show that PerFallD achieves strong detection performance and power efficiency

Projection models for intuitionistic fuzzy multiple attribute decision making

Abstract: The aim of this paper is to investigate the intuitionistic fuzzy multiple attribute decision-making problems where the attribute values are expressed in intuitionistic fuzzy numbers or interval-val...