Showing papers by "Chinese Academy of Sciences published in 2015"

Cleavage of GSDMD by inflammatory caspases determines pyroptotic cell death

Abstract: Inflammatory caspases (caspase-1, -4, -5 and -11) are critical for innate defences. Caspase-1 is activated by ligands of various canonical inflammasomes, and caspase-4, -5 and -11 directly recognize bacterial lipopolysaccharide, both of which trigger pyroptosis. Despite the crucial role in immunity and endotoxic shock, the mechanism for pyroptosis induction by inflammatory caspases is unknown. Here we identify gasdermin D (Gsdmd) by genome-wide clustered regularly interspaced palindromic repeat (CRISPR)-Cas9 nuclease screens of caspase-11- and caspase-1-mediated pyroptosis in mouse bone marrow macrophages. GSDMD-deficient cells resisted the induction of pyroptosis by cytosolic lipopolysaccharide and known canonical inflammasome ligands. Interleukin-1β release was also diminished in Gsdmd(-/-) cells, despite intact processing by caspase-1. Caspase-1 and caspase-4/5/11 specifically cleaved the linker between the amino-terminal gasdermin-N and carboxy-terminal gasdermin-C domains in GSDMD, which was required and sufficient for pyroptosis. The cleavage released the intramolecular inhibition on the gasdermin-N domain that showed intrinsic pyroptosis-inducing activity. Other gasdermin family members were not cleaved by inflammatory caspases but shared the autoinhibition; gain-of-function mutations in Gsdma3 that cause alopecia and skin defects disrupted the autoinhibition, allowing its gasdermin-N domain to trigger pyroptosis. These findings offer insight into inflammasome-mediated immunity/diseases and also change our understanding of pyroptosis and programmed necrosis.

An electron acceptor challenging fullerenes for efficient polymer solar cells.

Abstract: A novel non-fullerene electron acceptor (ITIC) that overcomes some of the shortcomings of fullerene acceptors, for example, weak absorption in the visible spectral region and limited energy-level variability, is designed and synthesized. Fullerene-free polymer solar cells (PSCs) based on the ITIC acceptor are demonstrated to exhibit power conversion effi ciencies of up to 6.8%, a record for fullerene-free PSCs.

Comprehensive evaluation of antibiotics emission and fate in the river basins of China: source analysis, multimedia modeling, and linkage to bacterial resistance.

Abstract: Antibiotics are widely used in humans and animals, but there is a big concern about their negative impacts on ecosystem and human health after use. So far there is a lack of information on emission inventory and environmental fate of antibiotics in China. We studied national consumption, emissions, and multimedia fate of 36 frequently detected antibiotics in China by market survey, data analysis, and level III fugacity modeling tools. Based on our survey, the total usage for the 36 chemicals was 92700 tons in 2013, an estimated 54000 tons of the antibiotics was excreted by human and animals, and eventually 53800 tons of them entered into the receiving environment following various wastewater treatments. The fugacity model successfully predicted environmental concentrations (PECs) in all 58 river basins of China, which are comparable to the reported measured environmental concentrations (MECs) available in some basins. The bacterial resistance rates in the hospitals and aquatic environments were found to b...

The eleventh and twelfth data releases of the Sloan Digital Sky Survey: final data from SDSS-III

Abstract: The third generation of the Sloan Digital Sky Survey (SDSS-III) took data from 2008 to 2014 using the original SDSS wide-field imager, the original and an upgraded multi-object fiber-fed optical spectrograph, a new near-infrared high-resolution spectrograph, and a novel optical interferometer. All the data from SDSS-III are now made public. In particular, this paper describes Data Release 11 (DR11) including all data acquired through 2013 July, and Data Release 12 (DR12) adding data acquired through 2014 July (including all data included in previous data releases), marking the end of SDSS-III observing. Relative to our previous public release (DR10), DR12 adds one million new spectra of galaxies and quasars from the Baryon Oscillation Spectroscopic Survey (BOSS) over an additional 3000 sq. deg of sky, more than triples the number of H-band spectra of stars as part of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE), and includes repeated accurate radial velocity measurements of 5500 stars from the Multi-Object APO Radial Velocity Exoplanet Large-area Survey (MARVELS). The APOGEE outputs now include measured abundances of 15 different elements for each star. In total, SDSS-III added 2350 sq. deg of ugriz imaging; 155,520 spectra of 138,099 stars as part of the Sloan Exploration of Galactic Understanding and Evolution 2 (SEGUE-2) survey; 2,497,484 BOSS spectra of 1,372,737 galaxies, 294,512 quasars, and 247,216 stars over 9376 sq. deg; 618,080 APOGEE spectra of 156,593 stars; and 197,040 MARVELS spectra of 5,513 stars. Since its first light in 1998, SDSS has imaged over 1/3 of the Celestial sphere in five bands and obtained over five million astronomical spectra.

Person re-identification by Local Maximal Occurrence representation and metric learning

Abstract: Person re-identification is an important technique towards automatic search of a person's presence in a surveillance video. Two fundamental problems are critical for person re-identification, feature representation and metric learning. An effective feature representation should be robust to illumination and viewpoint changes, and a discriminant metric should be learned to match various person images. In this paper, we propose an effective feature representation called Local Maximal Occurrence (LOMO), and a subspace and metric learning method called Cross-view Quadratic Discriminant Analysis (XQDA). The LOMO feature analyzes the horizontal occurrence of local features, and maximizes the occurrence to make a stable representation against viewpoint changes. Besides, to handle illumination variations, we apply the Retinex transform and a scale invariant texture operator. To learn a discriminant metric, we propose to learn a discriminant low dimensional subspace by cross-view quadratic discriminant analysis, and simultaneously, a QDA metric is learned on the derived subspace. We also present a practical computation method for XQDA, as well as its regularization. Experiments on four challenging person re-identification databases, VIPeR, QMUL GRID, CUHK Campus, and CUHK03, show that the proposed method improves the state-of-the-art rank-1 identification rates by 2.2%, 4.88%, 28.91%, and 31.55% on the four databases, respectively.

Exon-intron circular RNAs regulate transcription in the nucleus

Abstract: Noncoding RNAs (ncRNAs) have numerous roles in development and disease, and one of the prominent roles is to regulate gene expression A vast number of circular RNAs (circRNAs) have been identified, and some have been shown to function as microRNA sponges in animal cells Here, we report a class of circRNAs associated with RNA polymerase II in human cells In these circRNAs, exons are circularized with introns 'retained' between exons; we term them exon-intron circRNAs or EIciRNAs EIciRNAs predominantly localize in the nucleus, interact with U1 snRNP and promote transcription of their parental genes Our findings reveal a new role for circRNAs in regulating gene expression in the nucleus, in which EIciRNAs enhance the expression of their parental genes in cis, and highlight a regulatory strategy for transcriptional control via specific RNA-RNA interaction between U1 snRNA and EIciRNAs

Type-II Weyl semimetals.

Abstract: Fermions--elementary particles such as electrons--are classified as Dirac, Majorana or Weyl. Majorana and Weyl fermions had not been observed experimentally until the recent discovery of condensed matter systems such as topological superconductors and semimetals, in which they arise as low-energy excitations. Here we propose the existence of a previously overlooked type of Weyl fermion that emerges at the boundary between electron and hole pockets in a new phase of matter. This particle was missed by Weyl because it breaks the stringent Lorentz symmetry in high-energy physics. Lorentz invariance, however, is not present in condensed matter physics, and by generalizing the Dirac equation, we find the new type of Weyl fermion. In particular, whereas Weyl semimetals--materials hosting Weyl fermions--were previously thought to have standard Weyl points with a point-like Fermi surface (which we refer to as type-I), we discover a type-II Weyl point, which is still a protected crossing, but appears at the contact of electron and hole pockets in type-II Weyl semimetals. We predict that WTe2 is an example of a topological semimetal hosting the new particle as a low-energy excitation around such a type-II Weyl point. The existence of type-II Weyl points in WTe2 means that many of its physical properties are very different to those of standard Weyl semimetals with point-like Fermi surfaces.

Recent Advances in Two-Dimensional Materials beyond Graphene

Abstract: The isolation of graphene in 2004 from graphite was a defining moment for the “birth” of a field: two-dimensional (2D) materials In recent years, there has been a rapidly increasing number of papers focusing on non-graphene layered materials, including transition-metal dichalcogenides (TMDs), because of the new properties and applications that emerge upon 2D confinement Here, we review significant recent advances and important new developments in 2D materials “beyond graphene” We provide insight into the theoretical modeling and understanding of the van der Waals (vdW) forces that hold together the 2D layers in bulk solids, as well as their excitonic properties and growth morphologies Additionally, we highlight recent breakthroughs in TMD synthesis and characterization and discuss the newest families of 2D materials, including monoelement 2D materials (ie, silicene, phosphorene, etc) and transition metal carbide- and carbon nitride-based MXenes We then discuss the doping and functionalization of 2

Recurrent convolutional neural networks for text classification

Abstract: Text classification is a foundational task in many NLP applications. Traditional text classifiers often rely on many human-designed features, such as dictionaries, knowledge bases and special tree kernels. In contrast to traditional methods, we introduce a recurrent convolutional neural network for text classification without human-designed features. In our model, we apply a recurrent structure to capture contextual information as far as possible when learning word representations, which may introduce considerably less noise compared to traditional window-based neural networks. We also employ a max-pooling layer that automatically judges which words play key roles in text classification to capture the key components in texts. We conduct experiments on four commonly used datasets. The experimental results show that the proposed method outperforms the state-of-the-art methods on several datasets, particularly on document-level datasets.

Nitrogen-doped mesoporous carbon of extraordinary capacitance for electrochemical energy storage

Abstract: Carbon-based supercapacitors can provide high electrical power, but they do not have sufficient energy density to directly compete with batteries. We found that a nitrogen-doped ordered mesoporous few-layer carbon has a capacitance of 855 farads per gram in aqueous electrolytes and can be bipolarly charged or discharged at a fast, carbon-like speed. The improvement mostly stems from robust redox reactions at nitrogen-associated defects that transform inert graphene-like layered carbon into an electrochemically active substance without affecting its electric conductivity. These bipolar aqueous-electrolyte electrochemical cells offer power densities and lifetimes similar to those of carbon-based supercapacitors and can store a specific energy of 41 watt-hours per kilogram (19.5 watt-hours per liter).

Hierarchical recurrent neural network for skeleton based action recognition

Abstract: Human actions can be represented by the trajectories of skeleton joints. Traditional methods generally model the spatial structure and temporal dynamics of human skeleton with hand-crafted features and recognize human actions by well-designed classifiers. In this paper, considering that recurrent neural network (RNN) can model the long-term contextual information of temporal sequences well, we propose an end-to-end hierarchical RNN for skeleton based action recognition. Instead of taking the whole skeleton as the input, we divide the human skeleton into five parts according to human physical structure, and then separately feed them to five subnets. As the number of layers increases, the representations extracted by the subnets are hierarchically fused to be the inputs of higher layers. The final representations of the skeleton sequences are fed into a single-layer perceptron, and the temporally accumulated output of the perceptron is the final decision. We compare with five other deep RNN architectures derived from our model to verify the effectiveness of the proposed network, and also compare with several other methods on three publicly available datasets. Experimental results demonstrate that our model achieves the state-of-the-art performance with high computational efficiency.

Elevation-dependent warming in mountain regions of the world

Abstract: There is growing evidence that the rate of warming is amplified with elevation, such that high-mountain environments experience more rapid changes in temperature than environments at lower elevations. Elevation-dependent warming (EDW) can accelerate the rate of change in mountain ecosystems, cryospheric systems, hydrological regimes and biodiversity. Here we review important mechanisms that contribute towards EDW: snow albedo and surface-based feedbacks; water vapour changes and latent heat release; surface water vapour and radiative flux changes; surface heat loss and temperature change; and aerosols. All lead to enhanced warming with elevation (or at a critical elevation), and it is believed that combinations of these mechanisms may account for contrasting regional patterns of EDW. We discuss future needs to increase knowledge of mountain temperature trends and their controlling mechanisms through improved observations, satellite-based remote sensing and model simulations.

Experimental Discovery of Weyl Semimetal TaAs

Abstract: Weyl fermions possess exotic properties and can act like magnetic monopoles. Researchers show that TaAs is a Weyl semimetal, demonstrating for the first time that Weyl semimetals can be identified experimentally.

Progress in triboelectric nanogenerators as a new energy technology and self-powered sensors

Abstract: Ever since the first report of the triboelectric nanogenerator (TENG) in January 2012, its output area power density has reached 500 W m−2, and an instantaneous conversion efficiency of ∼70% and a total energy conversion efficiency of up to 85% have been demonstrated. We provide a comprehensive review of the four modes, their theoretical modelling, and the applications of TENGs for harvesting energy from human motion, walking, vibration, mechanical triggering, rotating tire, wind, flowing water and more as well as self-powered sensors.

Combined Measurement of the Higgs Boson Mass in pp Collisions at √s=7 and 8 TeV with the ATLAS and CMS Experiments

Abstract: A measurement of the Higgs boson mass is presented based on the combined data samples of the ATLAS and CMS experiments at the CERN LHC in the H→γγ and H→ZZ→4l decay channels. The results are obtained from a simultaneous fit to the reconstructed invariant mass peaks in the two channels and for the two experiments. The measured masses from the individual channels and the two experiments are found to be consistent among themselves. The combined measured mass of the Higgs boson is mH=125.09±0.21 (stat)±0.11 (syst) GeV.

Red, Green, and Blue Luminescence by Carbon Dots: Full‐Color Emission Tuning and Multicolor Cellular Imaging

Abstract: A facile approach for preparation of photoluminescent (PL) carbon dots (CDs) is reported. The three resulting CDs emit bright and stable red, green and blue (RGB) colors of luminescence, under a single ultraviolet-light excitation. Alterations of PL emission of these CDs are tentatively proposed to result from the difference in their particle size and nitrogen content. Interestingly, up-conversion (UC)PL of these CDs is also observed. Moreover, flexible full-color emissive PVA films can be achieved through mixing two or three CDs in the appropriate ratios. These CDs also show low cytotoxicity and excellent cellular imaging capability. The facile preparation and unique optical features make these CDs potentially useful in numerous applications such as light-emitting diodes, full-color displays, and multiplexed (UC)PL bioimaging.

A Fast Single Image Haze Removal Algorithm Using Color Attenuation Prior

Abstract: Single image haze removal has been a challenging problem due to its ill-posed nature. In this paper, we propose a simple but powerful color attenuation prior for haze removal from a single input hazy image. By creating a linear model for modeling the scene depth of the hazy image under this novel prior and learning the parameters of the model with a supervised learning method, the depth information can be well recovered. With the depth map of the hazy image, we can easily estimate the transmission and restore the scene radiance via the atmospheric scattering model, and thus effectively remove the haze from a single image. Experimental results show that the proposed approach outperforms state-of-the-art haze removal algorithms in terms of both efficiency and the dehazing effect.

Rising Temperatures Reduce Global Wheat Production

Abstract: Crop models are essential tools for assessing the threat of climate change to local and global food production(1). Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature(2). Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 degrees C to 32 degrees C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each degrees C of further temperature increase and become more variable over space and time.

Knowledge Graph Embedding via Dynamic Mapping Matrix

Abstract: Knowledge graphs are useful resources for numerous AI applications, but they are far from completeness. Previous work such as TransE, TransH and TransR/CTransR regard a relation as translation from head entity to tail entity and the CTransR achieves state-of-the-art performance. In this paper, we propose a more fine-grained model named TransD, which is an improvement of TransR/CTransR. In TransD, we use two vectors to represent a named symbol object (entity and relation). The first one represents the meaning of a(n) entity (relation), the other one is used to construct mapping matrix dynamically. Compared with TransR/CTransR, TransD not only considers the diversity of relations, but also entities. TransD has less parameters and has no matrix-vector multiplication operations, which makes it can be applied on large scale graphs. In Experiments, we evaluate our model on two typical tasks including triplets classification and link prediction. Evaluation results show that our approach outperforms state-of-the-art methods.

NiSe Nanowire Film Supported on Nickel Foam: An Efficient and Stable 3D Bifunctional Electrode for Full Water Splitting

Abstract: Active and stable electrocatalysts made from earth-abundant elements are key to water splitting for hydrogen production through electrolysis. The growth of NiSe nanowire film on nickel foam (NiSe/NF) insitu by hydrothermal treatment of NF using NaHSe as Se source is presented. When used as a 3D oxygen evolution electrode, the NiSe/NF exhibits high activity with an overpotential of 270mV required to achieve 20mAcm(-2) and strong durability in 1.0M KOH, and the NiOOH species formed at the NiSe surface serves as the actual catalytic site. The system is also highly efficient for catalyzing the hydrogen evolution reaction in basic media. This bifunctional electrode enables a high-performance alkaline water electrolyzer with 10mAcm(-2) at a cell voltage of 1.63V.

Soil Contamination in China: Current Status and Mitigation Strategies

Abstract: China faces great challenges in protecting its soil from contamination caused by rapid industrialization and urbanization over the last three decades. Recent nationwide surveys show that 16% of the soil samples, 19% for the agricultural soils, are contaminated based on China’s soil environmental quality limits, mainly with heavy metals and metalloids. Comparisons with other regions of the world show that the current status of soil contamination, based on the total contaminant concentrations, is not worse in China. However, the concentrations of some heavy metals in Chinese soils appear to be increasing at much greater rates. Exceedance of the contaminant limits in food crops is widespread in some areas, especially southern China, due to elevated inputs of contaminants, acidic nature of the soil and crop species or cultivars prone to heavy metal accumulation. Minimizing the transfer of contaminants from soil to the food chain is a top priority. A number of options are proposed, including identification of the sources of contaminants to agricultural systems, minimization of contaminant inputs, reduction of heavy metal phytoavailability in soil with liming or other immobilizing materials, selection and breeding of low accumulating crop cultivars, adoption of appropriate water and fertilizer management, bioremediation, and change of land use to grow nonfood crops. Implementation of these strategies requires not only technological advances, but also social-economic evaluation and effective enforcement of environmental protection law.

Weyl Semimetal Phase in Noncentrosymmetric Transition-Metal Monophosphides

Abstract: So-called Weyl points can be thought of as magnetic monopoles in momentum space. Researchers show that certain transition-metal monophosphides are characterized by Weyl points.

Atomic cobalt on nitrogen-doped graphene for hydrogen generation

Abstract: Reduction of water to hydrogen through electrocatalysis holds great promise for clean energy, but its large-scale application relies on the development of inexpensive and efficient catalysts to replace precious platinum catalysts. Here we report an electrocatalyst for hydrogen generation based on very small amounts of cobalt dispersed as individual atoms on nitrogen-doped graphene. This catalyst is robust and highly active in aqueous media with very low overpotentials (30 mV). A variety of analytical techniques and electrochemical measurements suggest that the catalytically active sites are associated with the metal centres coordinated to nitrogen. This unusual atomic constitution of supported metals is suggestive of a new approach to preparing extremely efficient single-atom catalysts.

Biomimetic super-lyophobic and super-lyophilic materials applied for oil/water separation: a new strategy beyond nature

Abstract: Oil spills and industrial organic pollutants have induced severe water pollution and threatened every species in the ecological system. To deal with oily water, special wettability stimulated materials have been developed over the past decade to separate oil-and-water mixtures. Basically, synergy between the surface chemical composition and surface topography are commonly known as the key factors to realize the opposite wettability to oils and water and dominate the selective wetting or absorption of oils/water. In this review, we mainly focus on the development of materials with either super-lyophobicity or super-lyophilicity properties in oil/water separation applications where they can be classified into four kinds as follows (in terms of the surface wettability of water and oils): (i) superhydrophobic and superoleophilic materials, (ii) superhydrophilic and under water superoleophobic materials, (iii) superhydrophilic and superoleophobic materials, and (iv) smart oil/water separation materials with switchable wettability. These materials have already been applied to the separation of oil-and-water mixtures: from simple oil/water layered mixtures to oil/water emulsions (including oil-in-water emulsions and water-in-oil emulsions), and from non-intelligent materials to intelligent materials. Moreover, they also exhibit high absorption capacity or separation efficiency and selectivity, simple and fast separation/absorption ability, excellent recyclability, economical efficiency and outstanding durability under harsh conditions. Then, related theories are proposed to understand the physical mechanisms that occur during the oil/water separation process. Finally, some challenges and promising breakthroughs in this field are also discussed. It is expected that special wettability stimulated oil/water separation materials can achieve industrial scale production and be put into use for oil spills and industrial oily wastewater treatment in the near future.

A Comprehensive Survey of Clustering Algorithms

Abstract: Data analysis is used as a common method in modern science research, which is across communication science, computer science and biology science. Clustering, as the basic composition of data analysis, plays a significant role. On one hand, many tools for cluster analysis have been created, along with the information increase and subject intersection. On the other hand, each clustering algorithm has its own strengths and weaknesses, due to the complexity of information. In this review paper, we begin at the definition of clustering, take the basic elements involved in the clustering process, such as the distance or similarity measurement and evaluation indicators, into consideration, and analyze the clustering algorithms from two perspectives, the traditional ones and the modern ones. All the discussed clustering algorithms will be compared in detail and comprehensively shown in Appendix Table 22.