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Showing papers by "Shanghai University published in 2016"


Journal ArticleDOI
Daniel J. Klionsky1, Kotb Abdelmohsen2, Akihisa Abe3, Joynal Abedin4  +2519 moreInstitutions (695)
TL;DR: In this paper, the authors present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macro-autophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes.
Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagy-related protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.

5,187 citations


Journal ArticleDOI
06 Oct 2016-Nature
TL;DR: Detailed catalyst characterization during the initial reaction stage and theoretical calculations indicate that preferentially exposed {101} and {020} facets play a pivotal role during syngas conversion, in that they favour olefin production and inhibit methane formation, and thereby render cobalt carbide nanoprisms a promising new catalyst system for directly converting syng as into lower olefins.
Abstract: Lower olefins-generally referring to ethylene, propylene and butylene-are basic carbon-based building blocks that are widely used in the chemical industry, and are traditionally produced through thermal or catalytic cracking of a range of hydrocarbon feedstocks, such as naphtha, gas oil, condensates and light alkanes. With the rapid depletion of the limited petroleum reserves that serve as the source of these hydrocarbons, there is an urgent need for processes that can produce lower olefins from alternative feedstocks. The 'Fischer-Tropsch to olefins' (FTO) process has long offered a way of producing lower olefins directly from syngas-a mixture of hydrogen and carbon monoxide that is readily derived from coal, biomass and natural gas. But the hydrocarbons obtained with the FTO process typically follow the so-called Anderson-Schulz-Flory distribution, which is characterized by a maximum C2-C4 hydrocarbon fraction of about 56.7 per cent and an undesired methane fraction of about 29.2 per cent (refs 1, 10, 11, 12). Here we show that, under mild reaction conditions, cobalt carbide quadrangular nanoprisms catalyse the FTO conversion of syngas with high selectivity for the production of lower olefins (constituting around 60.8 per cent of the carbon products), while generating little methane (about 5.0 per cent), with the ratio of desired unsaturated hydrocarbons to less valuable saturated hydrocarbons amongst the C2-C4 products being as high as 30. Detailed catalyst characterization during the initial reaction stage and theoretical calculations indicate that preferentially exposed {101} and {020} facets play a pivotal role during syngas conversion, in that they favour olefin production and inhibit methane formation, and thereby render cobalt carbide nanoprisms a promising new catalyst system for directly converting syngas into lower olefins.

578 citations



Journal ArticleDOI
TL;DR: In this paper, the various RDH algorithms and researches have been classified into the following six categories: 1) RDH into image spatial domain; 2) RD h into image compressed domain (e.g., JPEG); 3) RDh suitable for image semi-fragile authentication; 4)RDH with image contrast enhancement; 5) RD H into encrypted images, which is expected to have wide application in the cloud computation; and 6) RDD into video and into audio.
Abstract: In the past two decades, reversible data hiding (RDH), also referred to as lossless or invertible data hiding, has gradually become a very active research area in the field of data hiding. This has been verified by more and more papers on increasingly wide-spread subjects in the field of RDH research that have been published these days. In this paper, the various RDH algorithms and researches have been classified into the following six categories: 1) RDH into image spatial domain; 2) RDH into image compressed domain (e.g., JPEG); 3) RDH suitable for image semi-fragile authentication; 4) RDH with image contrast enhancement; 5) RDH into encrypted images, which is expected to have wide application in the cloud computation; and 6) RDH into video and into audio. For each of these six categories, the history of technical developments, the current state of the arts, and the possible future researches are presented and discussed. It is expected that the RDH technology and its applications in the real word will continue to move ahead.

432 citations


Proceedings ArticleDOI
01 Jun 2016
TL;DR: A novel approach for text detection in natural images that consistently achieves the state-of-the-art performance on three text detection benchmarks: MSRA-TD500, I CDAR2015 and ICDAR2013.
Abstract: In this paper, we propose a novel approach for text detection in natural images. Both local and global cues are taken into account for localizing text lines in a coarse-to-fine procedure. First, a Fully Convolutional Network (FCN) model is trained to predict the salient map of text regions in a holistic manner. Then, text line hypotheses are estimated by combining the salient map and character components. Finally, another FCN classifier is used to predict the centroid of each character, in order to remove the false hypotheses. The framework is general for handling text in multiple orientations, languages and fonts. The proposed method consistently achieves the state-of-the-art performance on three text detection benchmarks: MSRA-TD500, ICDAR2015 and ICDAR2013.

389 citations


Journal ArticleDOI
26 Feb 2016
TL;DR: In this paper, the authors provide a summary of achievements made in recent studies of thermoelectric transport properties, and demonstrate how they have led to improvements in thermal performance by the integration of modern theory and experiment.
Abstract: During the last two decades, we have witnessed great progress in research on thermoelectrics. There are two primary focuses. One is the fundamental understanding of electrical and thermal transport, enabled by the interplay of theory and experiment; the other is the substantial enhancement of the performance of various thermoelectric materials, through synergistic optimisation of those intercorrelated transport parameters. Here we review some of the successful strategies for tuning electrical and thermal transport. For electrical transport, we start from the classical but still very active strategy of tuning band degeneracy (or band convergence), then discuss the engineering of carrier scattering, and finally address the concept of conduction channels and conductive networks that emerge in complex thermoelectric materials. For thermal transport, we summarise the approaches for studying thermal transport based on phonon–phonon interactions valid for conventional solids, as well as some quantitative efforts for nanostructures. We also discuss the thermal transport in complex materials with chemical-bond hierarchy, in which a portion of the atoms (or subunits) are weakly bonded to the rest of the structure, leading to an intrinsic manifestation of part-crystalline part-liquid state at elevated temperatures. In this review, we provide a summary of achievements made in recent studies of thermoelectric transport properties, and demonstrate how they have led to improvements in thermoelectric performance by the integration of modern theory and experiment, and point out some challenges and possible directions.

386 citations


Posted Content
TL;DR: In this article, a Fully Convolutional Network (FCN) model is trained to predict the salient map of text regions in a holistic manner, and text line hypotheses are estimated by combining the saliency map and character components.
Abstract: In this paper, we propose a novel approach for text detec- tion in natural images. Both local and global cues are taken into account for localizing text lines in a coarse-to-fine pro- cedure. First, a Fully Convolutional Network (FCN) model is trained to predict the salient map of text regions in a holistic manner. Then, text line hypotheses are estimated by combining the salient map and character components. Fi- nally, another FCN classifier is used to predict the centroid of each character, in order to remove the false hypotheses. The framework is general for handling text in multiple ori- entations, languages and fonts. The proposed method con- sistently achieves the state-of-the-art performance on three text detection benchmarks: MSRA-TD500, ICDAR2015 and ICDAR2013.

363 citations


Journal ArticleDOI
TL;DR: In this article, the authors describe the combine effects of thermo-diffusion and thermal radiation on Williamson nanofluid over a porous stretching sheet and apply successive linearization method (SLM) and Chebyshev spectral collocation method (CSC) to solve the resulting coupled ordinary nonlinear differential equations.

279 citations


Journal ArticleDOI
TL;DR: A novel scheme of reversible data hiding in encrypted images using distributed source coding using Slepian-Wolf encoded using low-density parity check codes that outperforms the previously published ones.
Abstract: This paper proposes a novel scheme of reversible data hiding in encrypted images using distributed source coding. After the original image is encrypted by the content owner using a stream cipher, the data-hider compresses a series of selected bits taken from the encrypted image to make room for the secret data. The selected bit series is Slepian–Wolf encoded using low-density parity check codes. On the receiver side, the secret bits can be extracted if the image receiver has the embedding key only. In case the receiver has the encryption key only, he/she can recover the original image approximately with high quality using an image estimation algorithm. If the receiver has both the embedding and encryption keys, he/she can extract the secret data and perfectly recover the original image using the distributed source decoding. The proposed method outperforms the previously published ones.

241 citations


Journal ArticleDOI
TL;DR: Compared to its individual components or current therapeutic formulations, iNPG-pDox shows enhanced efficacy in MDA-MB-231 and 4T1 mouse models of metastatic breast cancer, including functional cures in 40–50% of treated mice.
Abstract: The efficacy of cancer drugs is often limited because only a small fraction of the administered dose accumulates in tumors. Here we report an injectable nanoparticle generator (iNPG) that overcomes multiple biological barriers to cancer drug delivery. The iNPG is a discoidal micrometer-sized particle that can be loaded with chemotherapeutics. We conjugate doxorubicin to poly(L-glutamic acid) by means of a pH-sensitive cleavable linker, and load the polymeric drug (pDox) into iNPG to assemble iNPG-pDox. Once released from iNPG, pDox spontaneously forms nanometer-sized particles in aqueous solution. Intravenously injected iNPG-pDox accumulates at tumors due to natural tropism and enhanced vascular dynamics and releases pDox nanoparticles that are internalized by tumor cells. Intracellularly, pDox nanoparticles are transported to the perinuclear region and cleaved into Dox, thereby avoiding excretion by drug efflux pumps. Compared to its individual components or current therapeutic formulations, iNPG-pDox shows enhanced efficacy in MDA-MB-231 and 4T1 mouse models of metastatic breast cancer, including functional cures in 40-50% of treated mice.

241 citations


Journal ArticleDOI
TL;DR: The results indicate that Cu(2+) ions released from Cu-BG/ESM nanocomposite films play an important role for improving both angiogenesis and antibacterial activity and the prepared nanocomPOSite films combined Cu-containing BG nanocoatings with ESM are a promising biomaterial for wound healing application.

Journal ArticleDOI
TL;DR: This paper proposes lossless, reversible, and combined data hiding schemes for ciphertext images encrypted by public-key cryptosystems with probabilistic and homomorphic properties.
Abstract: This paper proposes lossless, reversible, and combined data hiding schemes for ciphertext images encrypted by public-key cryptosystems with probabilistic and homomorphic properties. In the lossless scheme, the ciphertext pixels are replaced with new values to embed the additional data into several least significant bit planes of ciphertext pixels by multilayer wet paper coding. Then, the embedded data can be directly extracted from the encrypted domain, and the data-embedding operation does not affect the decryption of original plaintext image. In the reversible scheme, a preprocessing is employed to shrink the image histogram before image encryption, so that the modification on encrypted images for data embedding will not cause any pixel oversaturation in plaintext domain. Although a slight distortion is introduced, the embedded data can be extracted and the original image can be recovered from the directly decrypted image. Due to the compatibility between the lossless and reversible schemes, the data-embedding operations in the two manners can be simultaneously performed in an encrypted image. With the combined technique, a receiver may extract a part of embedded data before decryption, and extract another part of embedded data and recover the original plaintext image after decryption.

Journal ArticleDOI
TL;DR: In this paper, metal oxides and metal hydroxides have been developed and investigated for phosphorus removal, which is important for eutrophication control of water bodies, and they have been applied to wastewater.
Abstract: Phosphorus removal from wastewater is important for eutrophication control of water bodies. Metal oxides and metal hydroxides have always been developed and investigated for phosphorus removal, bec...

Journal ArticleDOI
TL;DR: A detailed summary of the molecular recognition of P5As and neutral guests is provided, where the driving forces, binding mechanisms, and binding selectivities are comprehensively discussed.

Journal ArticleDOI
TL;DR: The synergism of high special surface to volume ratio, mesoporous structure, graphene-based conduction paths, and Fe3O4 nanoparticles provided a high surface area of ion-accessibility, high electric conductivity, and the utmost utilization of Fe3 O4 and resulted in excellent specific capacitance, outstanding rate capability and cycling life as all-solid-state supercapacitor electrodes.
Abstract: Fe3O4@carbon nanosheet composites were synthesized using ammonium ferric citrate as the Fe3O4/carbon precursor and graphene oxide as the structure-directing agent under a hydrothermal process. The surface chemical compositions, pore structures, and morphology of the composite were analyzed and characterized by nitrogen adsorption isotherms, TG analysis, FT-IR, X-ray photoelectron energy spectrum, transmission electron microscopy, and scanning electron microscopy. The composites showed excellent specific capacitance of 586 F/g, 340 F/g at 0.5 A/g and 10 A/g. The all-solid-state asymmetric supercapacitor device assembled using carbon nanosheets in situ embedded Fe3O4 composite and porous carbon showed a largest energy density of 18.3 Wh/kg at power density of 351 W/kg in KOH/PVA gel electrolyte. The synergism of high special surface to volume ratio, mesoporous structure, graphene-based conduction paths, and Fe3O4 nanoparticles provided a high surface area of ion-accessibility, high electric conductivity, an...

Journal ArticleDOI
TL;DR: Wang et al. as mentioned in this paper found that workplace ostracism was positively related to hospitality employees' evasive hiding and playing dumb, but not related to rationalized hiding, while negative reciprocity beliefs and moral disengagement were high.

Journal ArticleDOI
TL;DR: A review of the assumptions and derivation steps of the kinetic models, summarization of corresponding analysis methods, and introduction of some recently proposed kinetic models and analysis methods for hydrogen storage materials can be found in this paper.

Journal ArticleDOI
Shifu Zhou1, Wei Shen1, Dan Zeng1, Mei Fang1, Yuanwang Wei1, Zhijiang Zhang1 
TL;DR: The proposed method for detecting and locating anomalous activities in video sequences of crowded scenes is a coupling of anomaly detection with a spatial-temporal Convolutional Neural Networks (CNN), which to the best of the knowledge has not been previously done.
Abstract: Abnormal behavior detection in crowded scenes is extremely challenging in the field of computer vision due to severe inter-object occlusions, varying crowd densities and the complex mechanics of a human crowd. We propose a method for detecting and locating anomalous activities in video sequences of crowded scenes. The key novelty of our method is the coupling of anomaly detection with a spatial-temporal Convolutional Neural Networks (CNN), which to the best of our knowledge has not been previously done. This architecture allows us to capture features from both spatial and temporal dimensions by performing spatial-temporal convolutions, thereby, both the appearance and motion information encoded in continuous frames are extracted. The spatial-temporal convolutions are only performed within spatial-temporal volumes of moving pixels to ensure robustness to local noise, and increase detection accuracy. We experimentally evaluate our model on benchmark datasets containing various situations with human crowds, and the results demonstrate that the proposed approach surpass state-of-the-art methods. HighlightsA mechanism for localizing dynamic regions in crowded scenes is proposed.A spatial-temporal Convolutional Neural Network is designed to automatically extract spatial-temporal features of the crowd.The performance of anomaly detection is improved when the analysis is concentrated on the dynamic regions only.The anomaly events that take place in small regions are effectively detected and localized by the spatial-temporal Convolutional Neural Network.

Journal ArticleDOI
TL;DR: This chapter first emphasizes the recent progress on the Ni-catalyzed alkylation, arylation/vinylation, and acylation of alkyl electrophiles, and the coupling of aryl halides with other C(sp2)–electrophiles.
Abstract: The Ni-catalyzed reductive coupling of alkyl/aryl with other electrophiles has evolved to be an important protocol for the construction of C–C bonds. This chapter first emphasizes the recent progress on the Ni-catalyzed alkylation, arylation/ vinylation, and acylation of alkyl electrophiles. A brief overview of CO2 fixation is also addressed. The chemoselectivity between the electrophiles and the reactivity of the alkyl substrates will be detailed on the basis of different Nicatalyzed conditions and mechanistic perspective. The asymmetric formation of C(sp3)–C(sp2) bonds arising from activated alkyl halides is next depicted followed by allylic carbonylation. Finally, the coupling of aryl halides with other C(sp2)– electrophiles is detailed at the end of this chapter.

Journal ArticleDOI
TL;DR: The cyclometalated iridium(III) complexes are considered as the most attractive candidates for electroluminescent devices owing to their stable chemical structure, high luminescent effiency, and tunable emission wavelength over the whole visible region as discussed by the authors.
Abstract: © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim 881 wileyonlinelibrary.com for organic light-emitting diodes (OLEDs) that are regarded as potential replacements in future display and solid-state lighting techniques. [ 1–15 ] The phosphorescent transition-metal complexes harness both singlet and triplet excitons to improve device effi ciency greatly compared with electrofl uorescent emitters. [ 16–20 ] To meet the target of full-color fl at-panel displays and low-cost lighting sources, recent efforts have been devoted to the color tuning of these complexes. [ 21–27 ] Among all kinds of transition-metal complexes, the cyclometalated iridium(III) complexes are considered as the most attractive candidates for electroluminescent devices owing to their stable chemical structure, high luminescent effi ciency, and tunable emission wavelength over the whole visible region. [ 28–32 ]

Journal ArticleDOI
TL;DR: By modifying the shapes of the Raman pulses, this work theoretically proposes and experimentally demonstrates a shortcut-to-adiabatic protocol that is robust against control parameter variations and provides an efficient and practical way to control quantum systems.
Abstract: Accurate control of a quantum system is a fundamental requirement in many areas of modern science ranging from quantum information processing to high-precision measurements. A significantly important goal in quantum control is preparing a desired state as fast as possible, with sufficiently high fidelity allowed by available resources and experimental constraints. Stimulated Raman adiabatic passage (STIRAP) is a robust way to realize high-fidelity state transfer but it requires a sufficiently long operation time to satisfy the adiabatic criteria. Here we theoretically propose and then experimentally demonstrate a shortcut-to-adiabatic protocol to speed-up the STIRAP. By modifying the shapes of the Raman pulses, we experimentally realize a fast and high-fidelity stimulated Raman shortcut-to-adiabatic passage that is robust against control parameter variations. The all-optical, robust and fast protocol demonstrated here provides an efficient and practical way to control quantum systems.

Journal ArticleDOI
TL;DR: Adsorption energy markedly increased with increasing number of the π rings by using the density functional theory (DFT), showing the particular importance of π-π interactions in the adsorption process.
Abstract: The use of carbon based materials on the removal of antibiotics with high concentrations has been well studied, however the effect of this removal method is not clear on the actual concentration of environments, such as the hospital wastewater, sewage treatment plants and aquaculture wastewater. In this study, experimental studies on the adsorption of 7 antibiotics in environmental concentration of aqueous solutions by carbon based materials have been observed. Three kinds of carbon materials have shown very fast adsorption to antibiotics by liquid chromatography-tandem mass spectrometry (LC-MS-MS) detection, and the highest removal efficiency of antibiotics could reach to 100% within the range of detection limit. Surprisedly, the adsorption rate of graphene with small specific surface area was stronger than other two biochar, and adsorption rate of the two biochar which have approximate specific surface and different carbonization degree, was significantly different. The key point to the present observation were the π-π interactions between aromatic rings on adsorbed substance and carbon based materials by confocal laser scanning microscope observation. Moreover, adsorption energy markedly increased with increasing number of the π rings by using the density functional theory (DFT), showing the particular importance of π-π interactions in the adsorption process.

Journal ArticleDOI
TL;DR: This work demonstrates not only the guiding principle of low sound velocity for minimal lattice thermal conductivity and therefore high zT, but also argyrodite compounds as promising thermoelectric materials with weak chemical bonds and heavy constituent elements.
Abstract: Conventional strategies for advancing thermoelectrics by minimizing the lattice thermal conductivity focus on phonon scattering for a short mean free path. Here, a design of slow phonon propagation as an effective approach for high-performance thermoelectrics is shown. Taking Ag8SnSe6 as an example, which shows one of the lowest sound velocities among known thermoelectric semiconductors, the lattice thermal conductivity is found to be as low as 0.2 W m-1 K-1 in the entire temperature range. As a result, a peak thermoelectric figure of merit zT > 1.2 and an average zT as high as ≈0.8 are achieved in Nb-doped materials, without relying on a high thermoelectric power factor. This work demonstrates not only a guiding principle of low sound velocity for minimal lattice thermal conductivity and therefore high zT, but also argyrodite compounds as promising thermoelectric materials with weak chemical bonds and heavy constituent elements.

Journal ArticleDOI
TL;DR: In this article, the performance of Fe2O3/CeO2 catalysts for the selective catalytic reduction of NO with NH3 (NH3-SCR) has been investigated using combined experimental and density functional theory (DFT) methods.
Abstract: The facet-dependent catalytic performance of Fe2O3/CeO2 catalysts for the selective catalytic reduction of NO with NH3 (NH3–SCR) has been investigated using combined experimental and density functional theory (DFT) methods. The structure and surface characteristics of the synthesized samples were characterized by XRD, XPS, TEM, ICP–AES, N2 sorption isotherms, Raman spectra, photoluminescence spectra, H2–TPR, NH3–TPD and NO + O2–TPD. It is found that the CeO2 nanorods and Fe2O3/CeO2 nanorods predominately exposed {110} and {100} facets rather than the stable {111} facets on CeO2 nanopolyhedra and Fe2O3/CeO2 nanopolyhedra. The influence of the micromorphologies and surface properties of CeO2 supports on the NO conversion and N2 selectivity has been compared. The Fe2O3/CeO2 nanorods achieve higher catalytic activity than the Fe2O3/CeO2 nanopolyhedra for NH3–SCR of NO. The synergetic effect between CeO2 supports and Fe2O3 species has been demonstrated. The insight into molecular facet dependence by the DFT me...

Journal ArticleDOI
TL;DR: In this article, a novel eco-friendly approach involving hydrazine hydrate-assisted hydrothermal cutting followed by functionalization with poly (ethylene imine) (PEI) for fabricating highly fluorescent graphene quantum dots from coffee grounds was developed.

Journal ArticleDOI
TL;DR: The crystal chemistry, kinetics and electrochemical performance of the present study on various morphologies of LiNi(0.5)Mn(1.5).5)O4 spinel materials have implications for understanding the complex impacts of electrode interface and electrolyte and rational design of rechargeable electrode materials for lithium-ion batteries.
Abstract: An evolution panorama of morphology and surface orientation of high-voltage spinel LiNi0.5Mn1.5O4 cathode materials synthesized by the combination of the microwave-assisted hydrothermal technique and a postcalcination process is presented. Nanoparticles, octahedral and truncated octahedral particles with different preferential growth of surface orientations are obtained. The structures of different materials are studied by X-ray diffraction (XRD), Raman spectroscopy, X-ray absorption near edge spectroscopy (XANES), and transmission electron microscopy (TEM). The influence of various morphologies (including surface orientations and particle size) on kinetic parameters, such as electronic conductivity and Li+ diffusion coefficients, are investigated as well. Moreover, electrochemical measurements indicate that the morphological differences result in divergent rate capabilities and cycling performances. They reveal that appropriate surface-tailoring can satisfy simultaneously the compatibility of power capab...

Journal ArticleDOI
TL;DR: In this paper, a bimetal-organic-frameworks synthesis of Co0.4Zn0.19S@N and S codoped carbon dodecahedron is shown with rooted carbon nanotubes (Co-Zn-S@ N-S-C-CNT) for high-performance Li-ion battery application.
Abstract: Lithium ion battery is the predominant power source for portable electronic devices, electrical vehicles, and back-up electricity storage units for clean and renewable energies. High-capacity and long-life electrode materials are essential for the next-generation Li-ion battery with high energy density. Here bimetal-organic-frameworks synthesis of Co0.4Zn0.19S@N and S codoped carbon dodecahedron is shown with rooted carbon nanotubes (Co-Zn-S@N-S-C-CNT) for high-performance Li-ion battery application. Benefiting from the synergetic effect of two metal sulfide species for Li-storage at different voltages, mesoporous dodecahedron structure, N and S codoped carbon overlayer and deep-rooted CNTs network, the product exhibits a larger-than-theoretical reversible Li-storage capacity of 941 mAh g−1 after 250 cycles at 100 mA g−1 and excellent high-rate capability (734, 591, 505 mAh g−1 after 500 cycles at large current densities of 1, 2, and 5 A g−1 , respectively).

Journal ArticleDOI
TL;DR: An overview of the recent development and application of FBG based sensors for health monitoring of several key geotechnical structures, including soil nail systems, slopes, and piles are reviewed in this paper.
Abstract: Fiber Bragg grating (FBG) sensor has been considered as a reliable sensor for health monitoring of structural and geotechnical projects. Various types of FBG based sensors have been proposed in past few decades and employed for health monitoring of many geotechnical structures. This paper presents an overview of the recent development and application of FBG based sensors for health monitoring of several key geotechnical structures, including soil nail systems, slopes, and piles. Different sensor design, implementation and packaging methods, advantages and limitations of using FBG based sensors in different projects are reviewed. Comparative analysis of using two mathematical methods for the prediction of ground movement using FBG sensor data are also carried out. The two typical mathematical methods include Finite Difference Method (FDM) and Numerical Integration method (NIM). Possible technical challenges of applying FBG sensors for geotechnical monitoring are discussed.

Journal ArticleDOI
TL;DR: In this paper, a fabricated sensor based on 3.8 wt% reduced graphene oxide/hexagonal WO3 (rGO/h-WO3) nanosheets composites was synthesized through hydrothermal method and post-calcination treatment.
Abstract: Reduced graphene oxide/hexagonal WO3 (rGO/h-WO3) nanosheets composites were synthesized through hydrothermal method and post-calcination treatment. The products were characterized by powder X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), N2 adsorption-desorption, Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR) and Thermogravimetric analysis (TGA). The results showed that two-dimensional (2D) h-WO3 nanosheets with porous structure were attached on rGO to construct 3D rGO/h-WO3 hybrid nanocomposites. This 3D hybrid nanostructure provided many channels for gas diffusion. The fabricated sensor based on 3.8 wt% rGO/h-WO3 composites showed good gas sensing response to H2S. The sensitivity of the sensor was about 168.58 toward 40 ppm H2S, which was 3.7 times higher than that of pure WO3, and the response time was 7 s when exposed to 10 ppm H2S. Moreover, the sensor showed low detection limit (10 ppb), wide linear range and high selectivity to H2S. The improved gas sensing properties of 3.8 wt% rGO/h-WO3 composites may be attributed to the formation of hetero-junctions, good accepting/transporting electrons properties of rGO and effective gas transport channels in 3D hybrid nanostructure.

Posted Content
TL;DR: This paper forms a fixed-point model which uses a predicted segmentation mask to shrink the input region and outperform the state-of-the-art by more than \(4\%\), measured by the average Dice-Sorensen Coefficient (DSC).
Abstract: Deep neural networks have been widely adopted for automatic organ segmentation from abdominal CT scans. However, the segmentation accuracy of some small organs (e.g., the pancreas) is sometimes below satisfaction, arguably because deep networks are easily disrupted by the complex and variable background regions which occupies a large fraction of the input volume. In this paper, we formulate this problem into a fixed-point model which uses a predicted segmentation mask to shrink the input region. This is motivated by the fact that a smaller input region often leads to more accurate segmentation. In the training process, we use the ground-truth annotation to generate accurate input regions and optimize network weights. On the testing stage, we fix the network parameters and update the segmentation results in an iterative manner. We evaluate our approach on the NIH pancreas segmentation dataset, and outperform the state-of-the-art by more than 4%, measured by the average Dice-Sorensen Coefficient (DSC). In addition, we report 62.43% DSC in the worst case, which guarantees the reliability of our approach in clinical applications.