Showing papers by "University of Electronic Science and Technology of China published in 2015"

Supervised Discrete Hashing

Abstract: Recently, learning based hashing techniques have attracted broad research interests because they can support efficient storage and retrieval for high-dimensional data such as images, videos, documents, etc. However, a major difficulty of learning to hash lies in handling the discrete constraints imposed on the pursued hash codes, which typically makes hash optimizations very challenging (NP-hard in general). In this work, we propose a new supervised hashing framework, where the learning objective is to generate the optimal binary hash codes for linear classification. By introducing an auxiliary variable, we reformulate the objective such that it can be solved substantially efficiently by employing a regularization algorithm. One of the key steps in this algorithm is to solve a regularization sub-problem associated with the NP-hard binary optimization. We show that the sub-problem admits an analytical solution via cyclic coordinate descent. As such, a high-quality discrete solution can eventually be obtained in an efficient computing manner, therefore enabling to tackle massive datasets. We evaluate the proposed approach, dubbed Supervised Discrete Hashing (SDH), on four large image datasets and demonstrate its superiority to the state-of-the-art hashing methods in large-scale image retrieval.

Supervised Discrete Hashing

Abstract: Recently, learning based hashing techniques have attracted broad research interests because they can support efficient storage and retrieval for high-dimensional data such as images, videos, documents, etc. However, a major difficulty of learning to hash lies in handling the discrete constraints imposed on the pursued hash codes, which typically makes hash optimizations very challenging (NP-hard in general). In this work, we propose a new supervised hashing framework, where the learning objective is to generate the optimal binary hash codes for linear classification. By introducing an auxiliary variable, we reformulate the objective such that it can be solved substantially efficiently by employing a regularization algorithm. One of the key steps in this algorithm is to solve a regularization sub-problem associated with the NP-hard binary optimization. We show that the sub-problem admits an analytical solution via cyclic coordinate descent. As such, a high-quality discrete solution can eventually be obtained in an efficient computing manner, therefore enabling to tackle massive datasets. We evaluate the proposed approach, dubbed Supervised Discrete Hashing (SDH), on four large image datasets and demonstrate its superiority to the state-of-the-art hashing methods in large-scale image retrieval.

High-performance green flexible electronics based on biodegradable cellulose nanofibril paper

Abstract: The rapid evolution of consumer electronics means that out-of-date devices quickly end up in the scrap heap. Here, the authors fabricate electrical components using biodegradable and flexible cellulose nanofibril paper—a natural sustainable resource derived from wood.

Declining global warming effects on the phenology of spring leaf unfolding.

Abstract: Spring leaf unfolding has been occurring earlier in the year because of rising temperatures; however, long-term evidence in the field from 7 European tree species studied in 1,245 sites shows that this early unfolding effect is being reduced in recent years, possibly because the reducing chilling and/or insolation render trees less responsive to warming. Spring leaf unfolding has been occurring earlier in the year because of rising temperatures, but some experimental evidence has suggested that the effect is becoming less marked because trees are not receiving the necessary chilling required to trigger leaf unfolding. Shilong Piao and colleagues present evidence based on long-term field observations of seven European tree species studied in 1,245 locations across Europe confirming that a weakening of temperature sensitivity of leaf unfolding is indeed occurring. The authors provide model-based evidence that the chilling effect is at least partially responsible. Earlier spring leaf unfolding is a frequently observed response of plants to climate warming1,2,3,4. Many deciduous tree species require chilling for dormancy release, and warming-related reductions in chilling may counteract the advance of leaf unfolding in response to warming5,6. Empirical evidence for this, however, is limited to saplings or twigs in climate-controlled chambers7,8. Using long-term in situ observations of leaf unfolding for seven dominant European tree species at 1,245 sites, here we show that the apparent response of leaf unfolding to climate warming (ST, expressed in days advance of leaf unfolding per °C warming) has significantly decreased from 1980 to 2013 in all monitored tree species. Averaged across all species and sites, ST decreased by 40% from 4.0 ± 1.8 days °C−1 during 1980–1994 to 2.3 ± 1.6 days °C−1 during 1999–2013. The declining ST was also simulated by chilling-based phenology models, albeit with a weaker decline (24–30%) than observed in situ. The reduction in ST is likely to be partly attributable to reduced chilling. Nonetheless, other mechanisms may also have a role, such as ‘photoperiod limitation’ mechanisms that may become ultimately limiting when leaf unfolding dates occur too early in the season. Our results provide empirical evidence for a declining ST, but also suggest that the predicted strong winter warming in the future may further reduce ST and therefore result in a slowdown in the advance of tree spring phenology.

Design Guidelines for Spatial Modulation

Abstract: A new class of low-complexity, yet energy-efficient Multiple-Input Multiple-Output (MIMO) transmission techniques, namely, the family of Spatial Modulation (SM) aided MIMOs (SM-MIMO), has emerged. These systems are capable of exploiting the spatial dimensions (i.e., the antenna indices) as an additional dimension invoked for transmitting information, apart from the traditional Amplitude and Phase Modulation (APM). SM is capable of efficiently operating in diverse MIMO configurations in the context of future communication systems. It constitutes a promising transmission candidate for large-scale MIMO design and for the indoor optical wireless communication while relying on a single-Radio Frequency (RF) chain. Moreover, SM may be also viewed as an entirely new hybrid modulation scheme, which is still in its infancy. This paper aims for providing a general survey of the SM design framework as well as of its intrinsic limits. In particular, we focus our attention on the associated transceiver design, on spatial constellation optimization, on link adaptation techniques, on distributed/cooperative protocol design issues, and on their meritorious variants.

A CRISPR/Cas9 Toolbox for Multiplexed Plant Genome Editing and Transcriptional Regulation

Abstract: The relative ease, speed, and biological scope of clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated Protein9 (Cas9)-based reagents for genomic manipulations are revolutionizing virtually all areas of molecular biosciences, including functional genomics, genetics, applied biomedical research, and agricultural biotechnology. In plant systems, however, a number of hurdles currently exist that limit this technology from reaching its full potential. For example, significant plant molecular biology expertise and effort is still required to generate functional expression constructs that allow simultaneous editing, and especially transcriptional regulation, of multiple different genomic loci or multiplexing, which is a significant advantage of CRISPR/Cas9 versus other genome-editing systems. To streamline and facilitate rapid and wide-scale use of CRISPR/Cas9-based technologies for plant research, we developed and implemented a comprehensive molecular toolbox for multifaceted CRISPR/Cas9 applications in plants. This toolbox provides researchers with a protocol and reagents to quickly and efficiently assemble functional CRISPR/Cas9 transfer DNA constructs for monocots and dicots using Golden Gate and Gateway cloning methods. It comes with a full suite of capabilities, including multiplexed gene editing and transcriptional activation or repression of plant endogenous genes. We report the functionality and effectiveness of this toolbox in model plants such as tobacco (Nicotiana benthamiana), Arabidopsis (Arabidopsis thaliana), and rice (Oryza sativa), demonstrating its utility for basic and applied plant research.

High-frequency, precise modification of the tomato genome

Abstract: The use of homologous recombination to precisely modify plant genomes has been challenging, due to the lack of efficient methods for delivering DNA repair templates to plant cells. Even with the advent of sequence-specific nucleases, which stimulate homologous recombination at predefined genomic sites by creating targeted DNA double-strand breaks, there are only a handful of studies that report precise editing of endogenous genes in crop plants. More efficient methods are needed to modify plant genomes through homologous recombination, ideally without randomly integrating foreign DNA. Here, we use geminivirus replicons to create heritable modifications to the tomato genome at frequencies tenfold higher than traditional methods of DNA delivery (i.e., Agrobacterium). A strong promoter was inserted upstream of a gene controlling anthocyanin biosynthesis, resulting in overexpression and ectopic accumulation of pigments in tomato tissues. More than two-thirds of the insertions were precise, and had no unanticipated sequence modifications. Both TALENs and CRISPR/Cas9 achieved gene targeting at similar efficiencies. Further, the targeted modification was transmitted to progeny in a Mendelian fashion. Even though donor molecules were replicated in the vectors, no evidence was found of persistent extra-chromosomal replicons or off-target integration of T-DNA or replicon sequences. High-frequency, precise modification of the tomato genome was achieved using geminivirus replicons, suggesting that these vectors can overcome the efficiency barrier that has made gene targeting in plants challenging. This work provides a foundation for efficient genome editing of crop genomes without the random integration of foreign DNA.

High mobility emissive organic semiconductor

Abstract: The integration of high charge carrier mobility and high luminescence in an organic semiconductor is challenging. However, there is need of such materials for organic light-emitting transistors and organic electrically pumped lasers. Here we show a novel organic semiconductor, 2,6-diphenylanthracene (DPA), which exhibits not only high emission with single crystal absolute florescence quantum yield of 41.2% but also high charge carrier mobility with single crystal mobility of 34 cm(2) V(-1) s(-1). Organic light-emitting diodes (OLEDs) based on DPA give pure blue emission with brightness up to 6,627 cd m(-2) and turn-on voltage of 2.8 V. 2,6-Diphenylanthracene OLED arrays are successfully driven by DPA field-effect transistor arrays, demonstrating that DPA is a high mobility emissive organic semiconductor with potential in organic optoelectronics.

Toward link predictability of complex networks

Abstract: The organization of real networks usually embodies both regularities and irregularities, and, in principle, the former can be modeled. The extent to which the formation of a network can be explained coincides with our ability to predict missing links. To understand network organization, we should be able to estimate link predictability. We assume that the regularity of a network is reflected in the consistency of structural features before and after a random removal of a small set of links. Based on the perturbation of the adjacency matrix, we propose a universal structural consistency index that is free of prior knowledge of network organization. Extensive experiments on disparate real-world networks demonstrate that (i) structural consistency is a good estimation of link predictability and (ii) a derivative algorithm outperforms state-of-the-art link prediction methods in both accuracy and robustness. This analysis has further applications in evaluating link prediction algorithms and monitoring sudden changes in evolving network mechanisms. It will provide unique fundamental insights into the above-mentioned academic research fields, and will foster the development of advanced information filtering technologies of interest to information technology practitioners.

Facile Synthesis of Single Crystal Vanadium Disulfide Nanosheets by Chemical Vapor Deposition for Efficient Hydrogen Evolution Reaction

Abstract: A facile chemical vapor deposition method to prepare single-crystalline VS2 nanosheets for the hydrogen evolution reaction is reported. The electrocatalytic hydrogen evolution reaction (HER) activities of VS2 show an extremely low overpotential of -68 mV at 10 mA cm(-2), small Tafel slopes of ≈34 mV decade(-1), as well as high stability, demonstrating its potential as a candidate non-noble-metal catalyst for the HER.

Multivariate classification of social anxiety disorder using whole brain functional connectivity

Abstract: Recent research has shown that social anxiety disorder (SAD) is accompanied by abnormalities in brain functional connections. However, these findings are based on group comparisons, and, therefore, little is known about whether functional connections could be used in the diagnosis of an individual patient with SAD. Here, we explored the potential of the functional connectivity to be used for SAD diagnosis. Twenty patients with SAD and 20 healthy controls were scanned using resting-state functional magnetic resonance imaging. The whole brain was divided into 116 regions based on automated anatomical labeling atlas. The functional connectivity between each pair of regions was computed using Pearson’s correlation coefficient and used as classification feature. Multivariate pattern analysis was then used to classify patients from healthy controls. The pattern classifier was designed using linear support vector machine. Experimental results showed a correct classification rate of 82.5 % (p < 0.001) with sensitivity of 85.0 % and specificity of 80.0 %, using a leave-one-out cross-validation method. It was found that the consensus connections used to distinguish SAD were largely located within or across the default mode network, visual network, sensory-motor network, affective network, and cerebellar regions. Specifically, the right orbitofrontal region exhibited the highest weight in classification. The current study demonstrated that functional connectivity had good diagnostic potential for SAD, thus providing evidence for the possible use of whole brain functional connectivity as a complementary tool in clinical diagnosis. In addition, this study confirmed previous work and described novel pathophysiological mechanisms of SAD.

Long noncoding RNA UCA1 modulates breast cancer cell growth and apoptosis through decreasing tumor suppressive miR-143.

Abstract: Objective Long non coding RNA (LncRNA) urothelial carcinoma-associated 1 (UCA1) is an oncogene in breast cancer. However, the detailed mechanism has not been fully revealed. This study explored whether UCA1 can directly interact with miR-143, a tumor suppressor in breast cancer and whether the UCA1-miR-143 axis is involved in regulation of cancer cell growth and apoptosis. Patients and methods miRNA microarray was performed to identify the most dysregulated miRNAs between tumor and adjacent normal tissues of breast cancer. QRT-PCR analysis was performed to assess the expression of UCA1 and miR-143. The binding between UCA1 and miR-143 was verified using dual luciferase and RNA binding protein immunoprecipitation (RIP) assay. MTT assay and flow cytometry analysis were performed to study the role of UCA1-miR-143 axis in cell proliferation, cell cycle and apoptosis. Results UC1 was significantly upregulated, while miR-143 was significantly downregulated in the tumor tissues than in the adjacent normal tissues. There are direct interactions between miR-143 and the miRNA recognition sites of UCA1. UCA1 is present in Ago2-containing RNA-induced silencing complex (RISC), through association with miR-143. Through downregulating miR-143, UCA1 can modulate breast cancer cell growth and apoptosis. Conclusions UCA1 can directly interact with miR-143, lower its expression and affect its downstream regulation. Therefore, the UCA1-miR-143 axis constitutes a part of the oncogenic role of UCA1 in breast cancer.

Vibration Control of a Flexible Beam With Output Constraint

Abstract: In this paper, we present the vibration control design for a Euler–Bernoulli beam with the boundary output constraint. To prevent the constraint violation, a novel barrier Lyapunov function is employed for the control design and stability analysis. This paper represents an important step in extending the barrier Lyapunov function theory to distributed parameter systems. Model-based barrier control is proposed to suppress the vibration of a flexible Euler–Bernoulli beam under the boundary output constraint. Then, adaptive control is designed to handle the system parametric uncertainties. The vibration suppression is well achieved without violation of the constraint. Numerical simulations are provided to illustrate the performance of the control system.

Pseudo nucleotide composition or PseKNC: an effective formulation for analyzing genomic sequences

Abstract: With the avalanche of DNA/RNA sequences generated in the post-genomic age, it is urgent to develop automated methods for analyzing the relationship between the sequences and their functions. Towards this goal, a series of sequence-based methods have been proposed and applied to analyze various character-unknown DNA/RNA sequences in order for in-depth understanding their action mechanisms and processes. Compared with the classical sequence-based methods, the pseudo nucleotide composition or PseKNC approach developed very recently has the following advantages: (1) it can convert length-different DNA/RNA sequences into dimension-fixed digital vectors that can be directly handled by all the existing machine-learning algorithms or operation engines; (2) it can contain the desired features and properties according to the selection or definition of users; (3) it can cover considerable sequence pattern information, both local and global. This minireview is focused on the concept of pseudo nucleotide composition, its development and applications.

Evolution of Lattice Structure and Chemical Composition of the Surface Reconstruction Layer in Li1.2Ni0.2Mn0.6O2 Cathode Material for Lithium Ion Batteries

Abstract: Voltage and capacity fading of layer structured lithium and manganese rich (LMR) transition metal oxide is directly related to the structural and composition evolution of the material during the cycling of the battery. However, understanding such evolution at atomic level remains elusive. On the basis of atomic level structural imaging, elemental mapping of the pristine and cycled samples, and density functional theory calculations, it is found that accompanying the hoping of Li ions is the simultaneous migration of Ni ions toward the surface from the bulk lattice, leading to the gradual depletion of Ni in the bulk lattice and thickening of a Ni enriched surface reconstruction layer (SRL). Furthermore, Ni and Mn also exhibit concentration partitions within the thin layer of SRL in the cycled samples where Ni is almost depleted at the very surface of the SRL, indicating the preferential dissolution of Ni ions in the electrolyte. Accompanying the elemental composition evolution, significant structural evolu...

Recent advances in fundamentals and applications of random fiber lasers

Abstract: Random fiber lasers blend together attractive features of traditional random lasers, such as low cost and simplicity of fabrication, with high-performance characteristics of conventional fiber lasers, such as good directionality and high efficiency. Low coherence of random lasers is important for speckle-free imaging applications. The random fiber laser with distributed feedback proposed in 2010 led to a quickly developing class of light sources that utilize inherent optical fiber disorder in the form of the Rayleigh scattering and distributed Raman gain. The random fiber laser is an interesting and practically important example of a photonic device based on exploitation of optical medium disorder. We provide an overview of recent advances in this field, including high-power and high-efficiency generation, spectral and statistical properties of random fiber lasers, nonlinear kinetic theory of such systems, and emerging applications in telecommunications and distributed sensing.

Synthesis of Atomically Thin Boron Films on Copper Foils

Abstract: Two-dimensional boron materials have recently attracted extensive theoretical interest because of their exceptional structural complexity and remarkable physical and chemical properties. However, such 2D boron monolayers have still not been synthesized. In this report, the synthesis of atomically thin 2D γ-boron films on copper foils is achieved by chemical vapor deposition using a mixture of pure boron and boron oxide powders as the boron source and hydrogen gas as the carrier gas. Strikingly, the optical band gap of the boron film was measured to be around 2.25 eV, which is close to the value (2.07 eV) determined by first-principles calculations, suggesting that the γ-B28 monolayer is a fascinating direct band gap semiconductor. Furthermore, a strong photoluminescence emission band was observed at approximately 626 nm, which is again due to the direct band gap. This study could pave the way for applications of two-dimensional boron materials in electronic and photonic devices.

Isolation Enhancement of a Very Compact UWB-MIMO Slot Antenna With Two Defected Ground Structures

Abstract: A very compact ultrawideband (UWB) multiple-input multiple-output (MIMO) antenna with high isolation is presented in this letter. The proposed antenna, consisting of two UWB slot antennas, has a very compact size of $22 \times 26~\hbox{mm}^{2}$ , which is smaller than most of UWB antennas only with single antenna element. A T-shaped slot is etched on the ground to improve the impedance matching characteristic in the low-frequency and reduce the mutual coupling for the frequencies $ \geq 4~\hbox{GHz}$ . By etching a line slot to cancel out original coupling, isolation enhancement at the 3–4 GHz band is achieved. The antenna possesses a low mutual coupling of less than $ - 18~\hbox{dB}$ over the operating band from 3.1–10.6 GHz. The performance of this antenna both by simulation and by experiment indicates that the proposed antenna is a good candidate for UWB applications.

Broadband amplification of spoof surface plasmon polaritons at microwave frequencies

Abstract: Efficient amplification of spoof surface plasmon polaritons (SPPs) is proposed at microwave frequencies by using a subwavelength-scale amplifier For this purpose, a special plasmonic waveguide composed of two ultrathin corrugated metallic strips on top and bottom surfaces of a dielectric substrate with mirror symmetry is presented, which is easy to integrate with the amplifier It is shown that spoof SPPs are able to propagate on the plasmonic waveguide in broadband with low loss and strong subwavelength effect By loading a low-noise amplifier chip produced by the semiconductor technology, the first experiment is demonstrated to amplify spoof SPPs at microwave frequencies (from 6 to 20GHz) with high gain (around 20dB), which can be directly used as a SPP amplifier device The features of strong field confinement, high efficiency, broadband operation, and significant amplification of the spoof SPPs may advance a big step towards other active SPP components and integrated circuits

Asymmetrically interacting spreading dynamics on complex layered networks

Abstract: The spread of disease through a physical-contact network and the spread of information about the disease on a communication network are two intimately related dynamical processes. We investigate the asymmetrical interplay between the two types of spreading dynamics, each occurring on its own layer, by focusing on the two fundamental quantities underlying any spreading process: epidemic threshold and the final infection ratio. We find that an epidemic outbreak on the contact layer can induce an outbreak on the communication layer, and information spreading can effectively raise the epidemic threshold. When structural correlation exists between the two layers, the information threshold remains unchanged but the epidemic threshold can be enhanced, making the contact layer more resilient to epidemic outbreak. We develop a physical theory to understand the intricate interplay between the two types of spreading dynamics.

Large-area synthesis of monolayer WS2 and its ambient-sensitive photo-detecting performance

Abstract: We demonstrate the synthesis of large-area monolayer WS2 films by chemical vapor deposition (CVD) and investigate their photoresponse properties by fabricating n-type field effect transistors (FETs) with Al as the ohmic contact. Our CVD-grown monolayer WS2 shows an electron mobility of 0.91 cm2 V−1 s−1 and an ON/OFF ratio of 106, indicating its comparable electronic properties to the mechanically exfoliated flake sample. In a vacuum, by applying a gate bias (60 V), the responsivity of the monolayer WS2 phototransistor can increase up to 18.8 mA W−1 and a decent sub-second level response time can be maintained. In contrast, in air, it shows a very fast response time of less than 4.5 ms, but at the cost of responsivity reduction to 0.2 μA W−1. Such a distinctive ambient-sensitive photo-detecting performance can be well-explained by the pronounced effect of charge-acceptor-like O2/H2O molecule adsorption/desorption on the photocarrier transport. Our CVD-grown high quality monolayer WS2 may pave the way for developing industrial-scale optoelectronic devices for photo-detecting and chemical sensing applications.

Neural Network Control of a Rehabilitation Robot by State and Output Feedback

Abstract: In this paper, neural network control is presented for a rehabilitation robot with unknown system dynamics. To deal with the system uncertainties and improve the system robustness, adaptive neural networks are used to approximate the unknown model of the robot and adapt interactions between the robot and the patient. Both full state feedback control and output feedback control are considered in this paper. With the proposed control, uniform ultimate boundedness of the closed loop system is achieved in the context of Lyapunov's stability theory and its associated techniques. The state of the system is proven to converge to a small neighborhood of zero by appropriately choosing design parameters. Extensive simulations for a rehabilitation robot with constraints are carried out to illustrate the effectiveness of the proposed control.

Adaptive Multiobjective Particle Swarm Optimization Based on Parallel Cell Coordinate System

Abstract: Managing convergence and diversity is essential in the design of multiobjective particle swarm optimization (MOPSO) in search of an accurate and well distributed approximation of the true Pareto-optimal front. Largely due to its fast convergence, particle swarm optimization incurs a rapid loss of diversity during the evolutionary process. Many mechanisms have been proposed in existing MOPSOs in terms of leader selection, archive maintenance, and perturbation to tackle this deficiency. However, few MOPSOs are designed to dynamically adjust the balance in exploration and exploitation according to the feedback information detected from the evolutionary environment. In this paper, a novel method, named parallel cell coordinate system (PCCS), is proposed to assess the evolutionary environment including density, rank, and diversity indicators based on the measurements of parallel cell distance, potential, and distribution entropy, respectively. Based on PCCS, strategies proposed for selecting global best and personal best, maintaining archive, adjusting flight parameters, and perturbing stagnation are integrated into a self-adaptive MOPSO (pccsAMOPSO). The comparative experimental results show that the proposed pccsAMOPSO outperforms the other eight state-of-the-art competitors on ZDT and DTLZ test suites in terms of the chosen performance metrics. An additional experiment for density estimation in MOPSO illustrates that the performance of PCCS is superior to that of adaptive grid and crowding distance in terms of convergence and diversity.

PseKNC-General: A cross-platform package for generating various modes of pseudo nucleotide compositions

Abstract: Associate Editor: John HancockABSTRACTSummary: The avalanche of genomic sequences generated in thepost-genomic age requires efficient computational methods for rapidlyand accurately identifying biological features from sequence informa-tion. Towards this goal, we developed a freely available and open-source package, called PseKNC-General (the general form ofpseudo k-tuple nucleotide composition), that allows for fast and ac-curate computation of all the widely used nucleotide structural andphysicochemical properties of both DNA and RNA sequences.PseKNC-General can generate several modes of pseudo nucleotidecompositions, including conventional k-tuple nucleotide compositions,Moreau–Broto autocorrelation coefficient, Moran autocorrelation coef-ficient, Geary autocorrelation coefficient, Type I PseKNC and Type IIPseKNC. In every mode,4100 physicochemical properties are avail-able for choosing. Moreover, it is flexible enough to allow the users tocalculate PseKNC with user-defined properties. The package can berun on Linux, Mac and Windows systems and also provides a graph-ical user interface.Availability and implementation: The package is freely available at:http://lin.uestc.edu.cn/server/pseknc.Contact: chenweiimu@gmail.com or lqzhang@vt.edu or kcchou@gor-donlifescience.org.Supplementary information: Supplementary data are available atBioinformatics online.Received on July 22, 2014; revised on August 19, 2014; accepted onAugust 31, 2014

Top Tension Control of a Flexible Marine Riser by Using Integral-Barrier Lyapunov Function

Abstract: This paper presents a boundary controller for a flexible marine riser to suppress the riser's vibration with a top tension constraint. The flexible marine riser is described by a distributed parameter system with a partial differential equation and four ordinary differential equations. The boundary controller is designed at the top boundary of the riser based on an integral-barrier Lyapunov function to suppress the riser's tension at top. Adaptive control is designed when the system parametric uncertainty exists. With the proposed robust adaptive boundary control, uniformed boundedness under the ocean disturbance can be achieved. Stability analysis of the closed-loop system is given using the Lyapunov stability theory. Simulation results illustrate the effectiveness of the proposed boundary controller with top tension constraint.

Three-dimensional CNT/graphene–sulfur hybrid sponges with high sulfur loading as superior-capacity cathodes for lithium–sulfur batteries

Abstract: A facile method is presented to synthesize three-dimensional carbon nanotube/graphene–sulfur (3DCGS) sponge with a high sulfur loading of 80.1%. In the well-designed 3D architecture, the two-dimensional graphene nanosheets function as the 3D porous backbone and the one-dimensional (1D) highly conductive carbon nanotubes (CNTs) can not only significantly enhance the conductivity, but also effectively tune the mesoporous structure. Compared to the three-dimensional graphene–sulfur (3DGS) sponge without CNTs, the conductivity of 3DCGS is enhanced by 324.7%; most importantly, compared to the monomodal mesopores (with a size of 3.5 nm) formed in the 3DG, bimodal mesopores (with sizes of 3.5 and 32.1 nm) were formed in 3DCG; the bimodal mesopores, especially the newly formed 32.1 nm mesopores, provide abundant electrochemical nanoreactors, accommodate plenty of sulfur and polysulfides, and facilitate charge transportation and electrolyte penetration. The significantly enhanced conductivity and the unique bimodal-mesopore structure in 3DCGS result in its superior electrochemical performance. The reversible discharge capacity for sulfur is 1217 mA h g−1; the corresponding capacity for the whole electrode (including the 3DCGS, the conductive additive and the binder) is 877.4 mA h ge−1, which is the highest ever reported. In addition, the capacity decay is as low as 0.08% per cycle, and the high-rate capacity up to 4C is as large as 653.4 mA h g−1. The 3DCGS sponge with high sulfur loading is promising as a superior-capacity cathode for lithium–sulfur batteries.