Showing papers by "Tsinghua University published in 2009"

Topological insulators in Bi2Se3, Bi2Te3 and Sb2Te3 with a single Dirac cone on the surface

Abstract: Topological insulators are new states of quantum matter in which surface states residing in the bulk insulating gap of such systems are protected by time-reversal symmetry. The study of such states was originally inspired by the robustness to scattering of conducting edge states in quantum Hall systems. Recently, such analogies have resulted in the discovery of topologically protected states in two-dimensional and three-dimensional band insulators with large spin–orbit coupling. So far, the only known three-dimensional topological insulator is BixSb1−x, which is an alloy with complex surface states. Here, we present the results of first-principles electronic structure calculations of the layered, stoichiometric crystals Sb2Te3, Sb2Se3, Bi2Te3 and Bi2Se3. Our calculations predict that Sb2Te3, Bi2Te3 and Bi2Se3 are topological insulators, whereas Sb2Se3 is not. These topological insulators have robust and simple surface states consisting of a single Dirac cone at the Γ point. In addition, we predict that Bi2Se3 has a topologically non-trivial energy gap of 0.3 eV, which is larger than the energy scale of room temperature. We further present a simple and unified continuum model that captures the salient topological features of this class of materials. First-principles calculations predict that Bi2Se3, Bi2Te3 and Sb2Te3 are topological insulators—three-dimensional semiconductors with unusual surface states generated by spin–orbit coupling—whose surface states are described by a single gapless Dirac cone. The calculations further predict that Bi2Se3 has a non-trivial energy gap larger than the energy scale kBT at room temperature.

Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review

Abstract: As a practical and effective tool for quantitative in-plane deformation measurement of a planar object surface, two-dimensional digital image correlation (2D DIC) is now widely accepted and commonly used in the field of experimental mechanics. It directly provides full-field displacements to sub-pixel accuracy and full-field strains by comparing the digital images of a test object surface acquired before and after deformation. In this review, methodologies of the 2D DIC technique for displacement field measurement and strain field estimation are systematically reviewed and discussed. Detailed analyses of the measurement accuracy considering the influences of both experimental conditions and algorithm details are provided. Measures for achieving high accuracy deformation measurement using the 2D DIC technique are also recommended. Since microscale and nanoscale deformation measurement can easily be realized by combining the 2D DIC technique with high-spatial-resolution microscopes, the 2D DIC technique should find more applications in broad areas.

Efficient influence maximization in social networks

Abstract: Influence maximization is the problem of finding a small subset of nodes (seed nodes) in a social network that could maximize the spread of influence. In this paper, we study the efficient influence maximization from two complementary directions. One is to improve the original greedy algorithm of [5] and its improvement [7] to further reduce its running time, and the second is to propose new degree discount heuristics that improves influence spread. We evaluate our algorithms by experiments on two large academic collaboration graphs obtained from the online archival database arXiv.org. Our experimental results show that (a) our improved greedy algorithm achieves better running time comparing with the improvement of [7] with matching influence spread, (b) our degree discount heuristics achieve much better influence spread than classic degree and centrality-based heuristics, and when tuned for a specific influence cascade model, it achieves almost matching influence thread with the greedy algorithm, and more importantly (c) the degree discount heuristics run only in milliseconds while even the improved greedy algorithms run in hours in our experiment graphs with a few tens of thousands of nodes.Based on our results, we believe that fine-tuned heuristics may provide truly scalable solutions to the influence maximization problem with satisfying influence spread and blazingly fast running time. Therefore, contrary to what implied by the conclusion of [5] that traditional heuristics are outperformed by the greedy approximation algorithm, our results shed new lights on the research of heuristic algorithms.

Asian emissions in 2006 for the NASA INTEX-B mission

Abstract: . A new inventory of air pollutant emissions in Asia in the year 2006 is developed to support the Intercontinental Chemical Transport Experiment-Phase B (INTEX-B) funded by the National Aeronautics and Space Administration (NASA). Emissions are estimated for all major anthropogenic sources, excluding biomass burning. We estimate total Asian anthropogenic emissions in the year 2006 as follows: 47.1 Tg SO2, 36.7 Tg NOx, 298.2 Tg CO, 54.6 Tg NMVOC, 29.2 Tg PM10, 22.2 Tg PM2.5, 2.97 Tg BC, and 6.57 Tg OC. We emphasize emissions from China because they dominate the Asia pollutant outflow to the Pacific and the increase of emissions from China since 2000 is of great concern. We have implemented a series of improved methodologies to gain a better understanding of emissions from China, including a detailed technology-based approach, a dynamic methodology representing rapid technology renewal, critical examination of energy statistics, and a new scheme of NMVOC speciation for model-ready emissions. We estimate China's anthropogenic emissions in the year 2006 to be as follows: 31.0 Tg SO2, 20.8 Tg NOx, 166.9 Tg CO, 23.2 Tg NMVOC, 18.2 Tg PM10, 13.3 Tg PM2.5, 1.8 Tg BC, and 3.2 Tg OC. We have also estimated 2001 emissions for China using the same methodology and found that all species show an increasing trend during 2001–2006: 36% increase for SO2, 55% for NOx, 18% for CO, 29% for VOC, 13% for PM10, and 14% for PM2.5, BC, and OC. Emissions are gridded at a resolution of 30 min×30 min and can be accessed at our web site ( http://mic.greenresource.cn/intex-b2006 ).

BCube: a high performance, server-centric network architecture for modular data centers

Abstract: This paper presents BCube, a new network architecture specifically designed for shipping-container based, modular data centers. At the core of the BCube architecture is its server-centric network structure, where servers with multiple network ports connect to multiple layers of COTS (commodity off-the-shelf) mini-switches. Servers act as not only end hosts, but also relay nodes for each other. BCube supports various bandwidth-intensive applications by speeding-up one-to-one, one-to-several, and one-to-all traffic patterns, and by providing high network capacity for all-to-all traffic.BCube exhibits graceful performance degradation as the server and/or switch failure rate increases. This property is of special importance for shipping-container data centers, since once the container is sealed and operational, it becomes very difficult to repair or replace its components.Our implementation experiences show that BCube can be seamlessly integrated with the TCP/IP protocol stack and BCube packet forwarding can be efficiently implemented in both hardware and software. Experiments in our testbed demonstrate that BCube is fault tolerant and load balancing and it significantly accelerates representative bandwidth-intensive applications.

Measurement of the quantum capacitance of graphene.

Abstract: Graphene has received widespread attention due to its unique electronic properties. Much of the research conducted so far has focused on electron mobility, which is determined by scattering from charged impurities and other inhomogeneities. However, another important quantity, the quantum capacitance, has been largely overlooked. Here, we report a direct measurement of the quantum capacitance of graphene as a function of gate potential using a three-electrode electrochemical configuration. The quantum capacitance has a non-zero minimum at the Dirac point and a linear increase on both sides of the minimum with relatively small slopes. Our findings -- which are not predicted by theory for ideal graphene -- suggest that charged impurities also influences the quantum capacitance. We also measured the capacitance in aqueous solutions at different ionic concentrations, and our results strongly indicate that the long-standing puzzle about the interfacial capacitance in carbon-based electrodes has a quantum origin.

Review: Application of data mining techniques in customer relationship management: A literature review and classification

Abstract: Despite the importance of data mining techniques to customer relationship management (CRM), there is a lack of a comprehensive literature review and a classification scheme for it. This is the first identifiable academic literature review of the application of data mining techniques to CRM. It provides an academic database of literature between the period of 2000-2006 covering 24 journals and proposes a classification scheme to classify the articles. Nine hundred articles were identified and reviewed for their direct relevance to applying data mining techniques to CRM. Eighty-seven articles were subsequently selected, reviewed and classified. Each of the 87 selected papers was categorized on four CRM dimensions (Customer Identification, Customer Attraction, Customer Retention and Customer Development) and seven data mining functions (Association, Classification, Clustering, Forecasting, Regression, Sequence Discovery and Visualization). Papers were further classified into nine sub-categories of CRM elements under different data mining techniques based on the major focus of each paper. The review and classification process was independently verified. Findings of this paper indicate that the research area of customer retention received most research attention. Of these, most are related to one-to-one marketing and loyalty programs respectively. On the other hand, classification and association models are the two commonly used models for data mining in CRM. Our analysis provides a roadmap to guide future research and facilitate knowledge accumulation and creation concerning the application of data mining techniques in CRM.

Preparation, Structure, and Electrochemical Properties of Reduced Graphene Sheet Films

Abstract: This paper describes the preparation, characterization, and electrochemical properties of reduced graphene sheet films (rGSFs), investigating especially their electrochemical behavior for several redox systems and electrocatalytic properties towards oxygen and some small molecules. The reduced graphene sheets (rGSs) are produced in high yield by a soft chemistry route involving graphite oxidation, ultrasonic exfoliation, and chemical reduction. Transmission electron microscopy (TEM), X-ray diffraction (XRD), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS) and Raman spectroscopy clearly demonstrate that graphene was successfully synthesized and modified at the surface of a glassy carbon electrode. Several redox species, such as Ru(NH3)63+/2+, Fe(CN)63−/4−, Fe3+/2+ and dopamine, are used to probe the electrochemical properties of these graphene films by using the cyclic voltammetry method. The rGSFs demonstrate fast electron-transfer (ET) kinetics and possess excellent electrocatalytic activity toward oxygen reduction and certain biomolecules. In our opinion, this microstructural and electrochemical information can serve as an important benchmark for graphene-based electrode performances.

Organosolv pretreatment of lignocellulosic biomass for enzymatic hydrolysis

Abstract: Production of ethanol by bioconversion of lignocellulosic biomass has attracted much interest in recent years. However, the pretreatment process for increasing the enzymatic digestibility of cellulose has become a key step in commercialized production of cellulosic ethanol. During the last decades, many pretreatment processes have been developed for decreasing the biomass recalcitrance, but only a few of them seem to be promising. From the point of view for integrated utilization of lignocellulosic biomass, organosolv pretreatment provides a pathway for biorefining of biomass. This review presents the progress of organosolv pretreatment of lignocellulosic biomass in recent decades, especially on alcohol, organic acid, organic peracid and acetone pretreatments, and corresponding action mechanisms. Evaluation and prospect of organosolv pretreatment were performed. Finally, some recommendations for future investigation of this pretreatment method were given.

A microbial polyhydroxyalkanoates (PHA) based bio- and materials industry

Abstract: Biopolyesters polyhydroxyalkanoates (PHA) produced by many bacteria have been investigated by microbiologists, molecular biologists, biochemists, chemical engineers, chemists, polymer experts and medical researchers. PHA applications as bioplastics, fine chemicals, implant biomaterials, medicines and biofuels have been developed and are covered in this critical review. Companies have been established or involved in PHA related R&D as well as large scale production. Recently, bacterial PHA synthesis has been found to be useful for improving robustness of industrial microorganisms and regulating bacterial metabolism, leading to yield improvement on some fermentation products. In addition, amphiphilic proteins related to PHA synthesis including PhaP, PhaZ or PhaC have been found to be useful for achieving protein purification and even specific drug targeting. It has become clear that PHA and its related technologies are forming an industrial value chain ranging from fermentation, materials, energy to medical fields (142 references).

Social influence analysis in large-scale networks

Abstract: In large social networks, nodes (users, entities) are influenced by others for various reasons. For example, the colleagues have strong influence on one's work, while the friends have strong influence on one's daily life. How to differentiate the social influences from different angles(topics)? How to quantify the strength of those social influences? How to estimate the model on real large networks?To address these fundamental questions, we propose Topical Affinity Propagation (TAP) to model the topic-level social influence on large networks. In particular, TAP can take results of any topic modeling and the existing network structure to perform topic-level influence propagation. With the help of the influence analysis, we present several important applications on real data sets such as 1) what are the representative nodes on a given topic? 2) how to identify the social influences of neighboring nodes on a particular node?To scale to real large networks, TAP is designed with efficient distributed learning algorithms that is implemented and tested under the Map-Reduce framework. We further present the common characteristics of distributed learning algorithms for Map-Reduce. Finally, we demonstrate the effectiveness and efficiency of TAP on real large data sets.

A water-soluble cationic oligopyrene derivative : Spectroscopic studies and sensing applications

Abstract: A water-soluble cationic conjugated oligomer, oligo(2-(4-(1-pyrenyl)butanoyloxy)ethyltrimethylammonium bromide) (OPBEAB) was synthesized by the combination of chemical and electrochemical synthesis techniques. The oligomer has an average repeat unit of 4 and a high quantum yield ( Ф ) of 0.7 in an aqueous solution containing 5.91 × 10 −3 mol L −1 sodium dodecyl sulfate (SDS). In this medium, surfactant molecules formed shielding layers along the OPBEAB chains and prevented aggregation of the oligomer and also improved its fluorescence stability. The fluorescence quenching of cationic oligomer (OPBEAB) depends strongly on the mixing sequence of the probe molecule (OPBEAB), analyte (TNT), and anionic surfactant (SDS). A molecule probe based on OPBEAB can rapidly detect ultra-trace TNT in both pure aqueous solution and environmental ground water with high sensitivity. The Stern–Volmer constant ( K SV ) of the probe in aqueous solution was measured to be as high as 5.30 × 10 5 mol −1 L and the limit of detection was about 7.0 × 10 −8 mol L −1 (70 ppb) under optimized conditions.

Printed assemblies of inorganic light-emitting diodes for deformable and semitransparent displays.

Abstract: We have developed methods for creating microscale inorganic light-emitting diodes (LEDs) and for assembling and interconnecting them into unusual display and lighting systems. The LEDs use specialized epitaxial semiconductor layers that allow delineation and release of large collections of ultrathin devices. Diverse shapes are possible, with dimensions from micrometers to millimeters, in either flat or “wavy” configurations. Printing-based assembly methods can deposit these devices on substrates of glass, plastic, or rubber, in arbitrary spatial layouts and over areas that can be much larger than those of the growth wafer. The thin geometries of these LEDs enable them to be interconnected by conventional planar processing techniques. Displays, lighting elements, and related systems formed in this manner can offer interesting mechanical and optical properties.

Fully room-temperature-fabricated nonvolatile resistive memory for ultrafast and high-density memory application.

Abstract: Through a simple industrialized technique which was completely fulfilled at room temperature, we have developed a kind of promising nonvolatile resistive switching memory consisting of Ag/ZnO:Mn/Pt with ultrafast programming speed of 5 ns, an ultrahigh R(OFF)/R(ON) ratio of 10(7), long retention time of more than 10(7) s, good endurance, and high reliability at elevated temperatures. Furthermore, we have successfully captured clear visualization of nanoscale Ag bridges penetrating through the storage medium, which could account for the high conductivity in the ON-state device. A model concerning redox reaction mediated formation and rupture of Ag bridges is therefore suggested to explain the memory effect. The Ag/ZnO:Mn/Pt device represents an ultrafast and highly scalable (down to sub-100-nm range) memory element for developing next generation nonvolatile memories.

Systematic measurements of identified particle spectra in pp, d+Au, and Au+Au collisions at the star detector.

Abstract: Identified charged-particle spectra of pi(+/-), K(+/-), p, and (p) over bar at midrapidity (vertical bar y vertical bar < 0.1) measured by the dE/dx method in the STAR (solenoidal tracker at the BNL Relativistic Heavy Ion Collider) time projection chamber are reported for pp and d + Au collisions at root s(NN) = 200 GeV and for Au + Au collisions at 62.4, 130, and 200 GeV. Average transverse momenta, total particle production, particle yield ratios, strangeness, and baryon production rates are investigated as a function of the collision system and centrality. The transverse momentum spectra are found to be flatter for heavy particles than for light particles in all collision systems; the effect is more prominent for more central collisions. The extracted average transverse momentum of each particle species follows a trend determined by the total charged-particle multiplicity density. The Bjorken energy density estimate is at least several GeV/fm(3) for a formation time less than 1 fm/c. A significantly larger net-baryon density and a stronger increase of the net-baryon density with centrality are found in Au + Au collisions at 62.4 GeV than at the two higher energies. Antibaryon production relative to total particle multiplicity is found to be constant over centrality, but increases with the collision energy. Strangeness production relative to total particle multiplicity is similar at the three measured RHIC energies. Relative strangeness production increases quickly with centrality in peripheral Au + Au collisions, to a value about 50% above the pp value, and remains rather constant in more central collisions. Bulk freeze-out properties are extracted from thermal equilibrium model and hydrodynamics-motivated blast-wave model fits to the data. Resonance decays are found to have little effect on the extracted kinetic freeze-out parameters because of the transverse momentum range of our measurements. The extracted chemical freeze-out temperature is constant, independent of collision system or centrality; its value is close to the predicted phase-transition temperature, suggesting that chemical freeze-out happens in the vicinity of hadronization and the chemical freeze-out temperature is universal despite the vastly different initial conditions in the collision systems. The extracted kinetic freeze-out temperature, while similar to the chemical freeze-out temperature in pp, d + Au, and peripheral Au + Au collisions, drops significantly with centrality in Au + Au collisions, whereas the extracted transverse radial flow velocity increases rapidly with centrality. There appears to be a prolonged period of particle elastic scatterings from chemical to kinetic freeze-out in central Au + Au collisions. The bulk properties extracted at chemical and kinetic freeze-out are observed to evolve smoothly over the measured energy range, collision systems, and collision centralities.

The Search for Heavy Majorana Neutrinos

Abstract: The Majorana nature of neutrinos can be experimentally verified only via lepton-number violating processes involving charged leptons. We study 36 lepton-number violating (LV ) processes from the decays of tau leptons and pseudoscalar mesons. These decays are absent in the Standard Model but, in presence of Majorana neutrinos in the mass range ∼ 100 MeV to 5 GeV, the rates for these processes would be enhanced due to their resonant contribution. We calculate the transition rates and branching fractions and compare them to the current bounds from direct experimental searches forL = 2 tau and rare meson decays. The experimental non-observation of such LV processes places stringent bounds on the Majorana neutrino mass and mixing and we summarize the existing limits. We also extend the search to hadron collider experiments. We find that, at the Tevatron with 8 fb −1 integrated luminosity, there could be 2σ (5σ) sensitivity for resonant production of a Majorana neutrino in the � ± � ± modes in the mass range of ∼ 10 − 180 GeV (10 − 120 GeV). This reach can be extended to ∼ 10 − 375 GeV (10 − 250 GeV) at the LHC of 14TeV with 100 fb −1 . The production cross section at the LHC of 10TeV is also presented for comparison. We study the � ± e ± modes as well and find that the signal could be large enough even taking into account the current bound from neutrinoless double-beta decay. The signal from the gauge boson fusion channel W + W + → l + l + at the LHC is found to be very weak given the rather small mixing parameters. We comment on the search strategy when a τ lepton is involved in the final state.

An online multi-channel SSVEP-based brain–computer interface using a canonical correlation analysis method

Abstract: In recent years, there has been increasing interest in using steady-state visual evoked potential (SSVEP) in brain–computer interface (BCI) systems. However, several aspects of current SSVEP-based BCI systems need improvement, specifically in relation to speed, user variation and ease of use. With these improvements in mind, this paper presents an online multi-channel SSVEP-based BCI system using a canonical correlation analysis (CCA) method for extraction of frequency information associated with the SSVEP. The key parameters, channel location, window length and the number of harmonics, are investigated using offline data, and the result used to guide the design of the online system. An SSVEP-based BCI system with six targets, which use nine channel locations in the occipital and parietal lobes, a window length of 2 s and the first harmonic, is used for online testing on 12 subjects. The results show that the proposed BCI system has a high performance, achieving an average accuracy of 95.3% and an information transfer rate of 58 ± 9.6 bit min−1. The positive characteristics of the proposed system are that channel selection and parameter optimization are not required, the possible use of harmonic frequencies, low user variation and easy setup.

MicroRNA-146a Feedback Inhibits RIG-I-Dependent Type I IFN Production in Macrophages by Targeting TRAF6, IRAK1, and IRAK2

Abstract: Upon recognition of viral components by pattern recognition receptors, including TLRs and retinoic acid-inducible gene I (RIG-I)- like helicases, cells are activated to produce type I IFN and proinflammatory cytokines. These pathways are tightly regulated by host to prevent inappropriate cellular response, but viruses can down-regulate these pathways for their survival. Recently, identification of negative regulators for cytoplasmic RNA-mediated antiviral signaling, especially the RIG-I pathway, attract much attention. However, there is no report about negative regulation of RIG-I antiviral pathway by microRNAs (miRNA) to date. We found that vesicular stomatitis virus (VSV) infection up-regulated miR-146a expression in mouse macrophages in TLR-myeloid differentiation factor 88-independent but RIG-I-NF-kappaB-dependent manner. In turn, miR-146a negatively regulated VSV-triggered type I IFN production, thus promoting VSV replication in macrophages. In addition to two known miR-146a targets, TRAF6 and IRAK1, we proved that IRAK2 was another target of miR-146a, which also participated in VSV-induced type I IFN production. Furthermore, IRAK1 and IRAK2 participated in VSV-induced type I IFN production by associating with Fas-associated death domain protein, an important adaptor in RIG-I signaling, in a VSV infection-inducible manner. Therefore, we demonstrate that miR-146a, up-regulated during viral infection, is a negative regulator of the RIG-I-dependent antiviral pathway by targeting TRAF6, IRAK1, and IRAK2.

Sparse LMS for system identification

Abstract: We propose a new approach to adaptive system identification when the system model is sparse. The approach applies l 1 relaxation, common in compressive sensing, to improve the performance of LMS-type adaptive methods. This results in two new algorithms, the zero-attracting LMS (ZA-LMS) and the reweighted zero-attracting LMS (RZA-LMS). The ZA-LMS is derived via combining a l 1 norm penalty on the coefficients into the quadratic LMS cost function, which generates a zero attractor in the LMS iteration. The zero attractor promotes sparsity in taps during the filtering process, and therefore accelerates convergence when identifying sparse systems. We prove that the ZA-LMS can achieve lower mean square error than the standard LMS. To further improve the filtering performance, the RZA-LMS is developed using a reweighted zero attractor. The performance of the RZA-LMS is superior to that of the ZA-LMS numerically. Experiments demonstrate the advantages of the proposed filters in both convergence rate and steady-state behavior under sparsity assumptions on the true coefficient vector. The RZA-LMS is also shown to be robust when the number of non-zero taps increases.

A new method for water desalination using microbial desalination cells.

Abstract: Current water desalination techniques are energy intensive and some use membranes operated at high pressures. It is shown here that water desalination can be accomplished without electrical energy input or high water pressure by using a source of organic matter as the fuel to desalinate water. A microbial fuel cell was modified by placing two membranes between the anode and cathode, creating a middle chamber for water desalination between the membranes. An anion exchange membrane was placed adjacent to the anode, and a cation exchange membrane was positioned next to the cathode. When current was produced by bacteria on the anode, ionic species in the middle chamber were transferred into the two electrode chambers, desalinating the water in the middle chamber. Proof-of-concept experiments for this approach, using what we call a microbial desalination cell (MDC), was demonstrated using water at different initial salt concentrations (5, 20, and 35 g/L) with acetate used as the substrate for the bacteria. The...

Sketch2Photo: internet image montage

Abstract: We present a system that composes a realistic picture from a simple freehand sketch annotated with text labels. The composed picture is generated by seamlessly stitching several photographs in agreement with the sketch and text labels; these are found by searching the Internet. Although online image search generates many inappropriate results, our system is able to automatically select suitable photographs to generate a high quality composition, using a filtering scheme to exclude undesirable images. We also provide a novel image blending algorithm to allow seamless image composition. Each blending result is given a numeric score, allowing us to find an optimal combination of discovered images. Experimental results show the method is very successful; we also evaluate our system using the results from two user studies.