Showing papers by "University of Science and Technology of China published in 2015"
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TL;DR: Faster R-CNN as discussed by the authors proposes a Region Proposal Network (RPN) to generate high-quality region proposals, which are used by Fast R-NN for detection.
Abstract: State-of-the-art object detection networks depend on region proposal algorithms to hypothesize object locations. Advances like SPPnet and Fast R-CNN have reduced the running time of these detection networks, exposing region proposal computation as a bottleneck. In this work, we introduce a Region Proposal Network (RPN) that shares full-image convolutional features with the detection network, thus enabling nearly cost-free region proposals. An RPN is a fully convolutional network that simultaneously predicts object bounds and objectness scores at each position. The RPN is trained end-to-end to generate high-quality region proposals, which are used by Fast R-CNN for detection. We further merge RPN and Fast R-CNN into a single network by sharing their convolutional features---using the recently popular terminology of neural networks with 'attention' mechanisms, the RPN component tells the unified network where to look. For the very deep VGG-16 model, our detection system has a frame rate of 5fps (including all steps) on a GPU, while achieving state-of-the-art object detection accuracy on PASCAL VOC 2007, 2012, and MS COCO datasets with only 300 proposals per image. In ILSVRC and COCO 2015 competitions, Faster R-CNN and RPN are the foundations of the 1st-place winning entries in several tracks. Code has been made publicly available.
23,183 citations
TL;DR: This work equips the networks with another pooling strategy, "spatial pyramid pooling", to eliminate the above requirement, and develops a new network structure, called SPP-net, which can generate a fixed-length representation regardless of image size/scale.
Abstract: Existing deep convolutional neural networks (CNNs) require a fixed-size (e.g., 224 $\times$ 224) input image. This requirement is “artificial” and may reduce the recognition accuracy for the images or sub-images of an arbitrary size/scale. In this work, we equip the networks with another pooling strategy, “spatial pyramid pooling”, to eliminate the above requirement. The new network structure, called SPP-net, can generate a fixed-length representation regardless of image size/scale. Pyramid pooling is also robust to object deformations. With these advantages, SPP-net should in general improve all CNN-based image classification methods. On the ImageNet 2012 dataset, we demonstrate that SPP-net boosts the accuracy of a variety of CNN architectures despite their different designs. On the Pascal VOC 2007 and Caltech101 datasets, SPP-net achieves state-of-the-art classification results using a single full-image representation and no fine-tuning. The power of SPP-net is also significant in object detection. Using SPP-net, we compute the feature maps from the entire image only once, and then pool features in arbitrary regions (sub-images) to generate fixed-length representations for training the detectors. This method avoids repeatedly computing the convolutional features. In processing test images, our method is 24-102 $\times$ faster than the R-CNN method, while achieving better or comparable accuracy on Pascal VOC 2007. In ImageNet Large Scale Visual Recognition Challenge (ILSVRC) 2014, our methods rank #2 in object detection and #3 in image classification among all 38 teams. This manuscript also introduces the improvement made for this competition.
5,919 citations
TL;DR: A new role for circRNAs in regulating gene expression in the nucleus is revealed, in which EIciRNAs enhance the expression of their parental genes in cis, and a regulatory strategy for transcriptional control via specific RNA-RNA interaction between U1 snRNA and EICIRNAs is highlighted.
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
2,077 citations
TL;DR: 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.
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.
1,567 citations
TL;DR: The proposed DNN approach can well suppress highly nonstationary noise, which is tough to handle in general, and is effective in dealing with noisy speech data recorded in real-world scenarios without the generation of the annoying musical artifact commonly observed in conventional enhancement methods.
Abstract: In contrast to the conventional minimum mean square error (MMSE)-based noise reduction techniques, we propose a supervised method to enhance speech by means of finding a mapping function between noisy and clean speech signals based on deep neural networks (DNNs). In order to be able to handle a wide range of additive noises in real-world situations, a large training set that encompasses many possible combinations of speech and noise types, is first designed. A DNN architecture is then employed as a nonlinear regression function to ensure a powerful modeling capability. Several techniques have also been proposed to improve the DNN-based speech enhancement system, including global variance equalization to alleviate the over-smoothing problem of the regression model, and the dropout and noise-aware training strategies to further improve the generalization capability of DNNs to unseen noise conditions. Experimental results demonstrate that the proposed framework can achieve significant improvements in both objective and subjective measures over the conventional MMSE based technique. It is also interesting to observe that the proposed DNN approach can well suppress highly nonstationary noise, which is tough to handle in general. Furthermore, the resulting DNN model, trained with artificial synthesized data, is also effective in dealing with noisy speech data recorded in real-world scenarios without the generation of the annoying musical artifact commonly observed in conventional enhancement methods.
1,250 citations
TL;DR: The optimized carbon with additional phosphorus dopant exhibits excellent electrocatalytic performance for the oxygen reduction reaction, which is much better than the benchmark Pt/C in alkaline media.
Abstract: Bimetallic metal-organic frameworks are rationally synthesized as templates and employed for porous carbons with retained morphology, high graphitization degree, hierarchical porosity, high surface area, CoNx moiety and uniform N/Co dopant by pyrolysis. The optimized carbon with additional phosphorus dopant exhibits excellent electrocatalytic performance for the oxygen reduction reaction, which is much better than the benchmark Pt/C in alkaline media.
1,182 citations
TL;DR: A series of spinel-structured nanosheets with oxygen deficiencies and ultrathin thicknesses designed to increase the reactivity and the number of active sites of the catalysts were taken as an excellent platform for promoting the water oxidation process and should provide a new pathway for the design of advanced OER catalysts.
Abstract: Electrochemical water splitting is a clean technology for H2 fuels, but greatly hindered by the slow kinetics of the oxygen evolution reaction (OER). Herein, a series of spinel-structured nanosheets with oxygen deficiencies and ultrathin thicknesses were designed to increase the reactivity and the number of active sites of the catalysts, which were then taken as an excellent platform for promoting the water oxidation process. Theoretical investigations showed that the oxygen vacancies confined in the ultrathin nanosheet could lower the adsorption energy of H2O, leading to increased OER efficiency. As expected, the NiCo2O4 ultrathin nanosheets rich in oxygen vacancies exhibited a large current density of 285 mA cm−2 at 0.8 V and a small overpotential of 0.32 V, both of which are superior to the corresponding values of bulk samples or samples with few oxygen deficiencies and even higher than those of most reported non-precious-metal catalysts. This work should provide a new pathway for the design of advanced OER catalysts.
1,164 citations
1,062 citations
TL;DR: It is shown that penta-graphene, composed of only carbon pentagons and resembling Cairo pentagonal tiling, is dynamically, thermally, and mechanically stable, and exhibits negative Poisson's ratio, a large band gap, and an ultrahigh mechanical strength.
Abstract: A 2D metastable carbon allotrope, penta-graphene, composed entirely of carbon pentagons and resembling the Cairo pentagonal tiling, is proposed. State-of-the-art theoretical calculations confirm that the new carbon polymorph is not only dynamically and mechanically stable, but also can withstand temperatures as high as 1000 K. Due to its unique atomic configuration, penta-graphene has an unusual negative Poisson’s ratio and ultrahigh ideal strength that can even outperform graphene. Furthermore, unlike graphene that needs to be functionalized for opening a band gap, penta-graphene possesses an intrinsic quasi-direct band gap as large as 3.25 eV, close to that of ZnO and GaN. Equally important, penta-graphene can be exfoliated from T12-carbon. When rolled up, it can form pentagon-based nanotubes which are semiconducting, regardless of their chirality. When stacked in different patterns, stable 3D twin structures of T12-carbon are generated with band gaps even larger than that of T12-carbon. The versatility of penta-graphene and its derivatives are expected to have broad applications in nanoelectronics and nanomechanics.
1,060 citations
TL;DR: A broadband photodetector using a layered black phosphorus transistor that is polarization-sensitive over a bandwidth from ∼400 nm to 3,750‽nm is demonstrated and might provide new functionalities in novel optical and optoelectronic device applications.
Abstract: The ability to detect light over a broad spectral range is central to practical optoelectronic applications and has been successfully demonstrated with photodetectors of two-dimensional layered crystals such as graphene and MoS2. However, polarization sensitivity within such a photodetector remains elusive. Here, we demonstrate a broadband photodetector using a layered black phosphorus transistor that is polarization-sensitive over a bandwidth from ∼400 nm to 3,750 nm. The polarization sensitivity is due to the strong intrinsic linear dichroism, which arises from the in-plane optical anisotropy of this material. In this transistor geometry, a perpendicular built-in electric field induced by gating can spatially separate the photogenerated electrons and holes in the channel, effectively reducing their recombination rate and thus enhancing the performance for linear dichroism photodetection. The use of anisotropic layered black phosphorus in polarization-sensitive photodetection might provide new functionalities in novel optical and optoelectronic device applications. The anisotropic optical properties of black phosphorus can be exploited to fabricate photodetectors with linear dichroism operating over a broad spectral range.
973 citations
TL;DR: A general image fusion framework by combining MST and SR to simultaneously overcome the inherent defects of both the MST- and SR-based fusion methods is presented and experimental results demonstrate that the proposed fusion framework can obtain state-of-the-art performance.
TL;DR: The finding suggests that metallic nitride nanosheets could serve as a new group of OER electrocatalysts with excellent property, and benefitting from enhanced electrical conductivity with metallic behavior and atomically disordered structure compared with bulk Ni3N and NiO nanOSheets.
Abstract: Exploring efficient and inexpensive oxygen evolution reaction (OER) electrocatalysts is of great importance for various electrochemical energy storage and conversion technologies. Ni-based electrocatalysts have been actively pursued because of their promising activity and earth abundance. However, the OER efficiency for most of the developed Ni-based electrocatalysts has been intrinsically limited due to their low electrical conductivity and poor active site exposure yield. Herein, we report metallic Ni3N nanosheets as an efficient OER electrocatalyst for the first time. The first-principles calculations and electrical transport property measurements unravel that the Ni3N is intrinsically metallic, and the carrier concentration can be remarkably improved with dimensional confinement. The EXAFS spectra provide solid evidence that the Ni3N nanosheets have disordered structure resultant of dimensional reduction, which then could provide more active sites for OER. Benefiting from enhanced electrical conductiv...
TL;DR: A generally accepted definition for SDN is presented, including decoupling the control plane from the data plane and providing programmability for network application development, and its three-layer architecture is dwelled on, including an infrastructure layer, a control layer, and an application layer.
Abstract: Emerging mega-trends (e.g., mobile, social, cloud, and big data) in information and communication technologies (ICT) are commanding new challenges to future Internet, for which ubiquitous accessibility, high bandwidth, and dynamic management are crucial. However, traditional approaches based on manual configuration of proprietary devices are cumbersome and error-prone, and they cannot fully utilize the capability of physical network infrastructure. Recently, software-defined networking (SDN) has been touted as one of the most promising solutions for future Internet. SDN is characterized by its two distinguished features, including decoupling the control plane from the data plane and providing programmability for network application development. As a result, SDN is positioned to provide more efficient configuration, better performance, and higher flexibility to accommodate innovative network designs. This paper surveys latest developments in this active research area of SDN. We first present a generally accepted definition for SDN with the aforementioned two characteristic features and potential benefits of SDN. We then dwell on its three-layer architecture, including an infrastructure layer, a control layer, and an application layer, and substantiate each layer with existing research efforts and its related research areas. We follow that with an overview of the de facto SDN implementation (i.e., OpenFlow). Finally, we conclude this survey paper with some suggested open research challenges.
TL;DR: This review highlights the recent progress on probing and steering charge kinetics toward designing highly efficient photocatalysts and elucidate the fundamentals behind the combinative use of controlled synthesis, characterization techniques and theoretical simulations in photocatalysis studies.
Abstract: Charge kinetics is highly critical in determining the quantum efficiency of solar-to-chemical conversion in photocatalysis, and this includes, but is not limited to, the separation of photoexcited electron–hole pairs, utilization of plasmonic hot carriers and delivery of photo-induced charges to reaction sites, as well as activation of reactants by energized charges. In this review, we highlight the recent progress on probing and steering charge kinetics toward designing highly efficient photocatalysts and elucidate the fundamentals behind the combinative use of controlled synthesis, characterization techniques (with a focus on spectroscopic characterizations) and theoretical simulations in photocatalysis studies. We first introduce the principles of various processes associated with charge kinetics that account for or may affect photocatalysis, from which a set of parameters that are critical to photocatalyst design can be summarized. We then outline the design rules for photocatalyst structures and their corresponding synthetic approaches. The implementation of characterization techniques and theoretical simulations in different steps of photocatalysis, together with the associated fundamentals and working mechanisms, are also presented. Finally, we discuss the challenges and opportunities for photocatalysis research at this unique intersection as well as the potential impact on other research fields.
TL;DR: A new class of SQEs based on excitons that are spatially localized by defects in 2D tungsten-diselenide (WSe2) monolayers is reported, which could give rise to practical advantages in quantum-information processing, such as an efficient photon extraction and a high integratability and scalability.
Abstract: Emission of single photons can be achieved by using defects in two-dimensional crystals as a source of luminescence.
TL;DR: A robust and highly active catalyst for hydrogen evolution reaction that is constructed by in situ growth of molybdenum disulfide on the surface of cobalt diselenide, which is the best among the non-noble metal hydrogen evolution catalysts and even approaches to the commercial platinum/carbon catalyst.
Abstract: There is substantial research into new catalysts for electroreduction of water. Here, the authors report a robust and active molybdenum disulfide/cobalt diselenide hydrogen evolution catalyst with onset potential of 11 mV and Tafel slope of 36 mV per decade, approaching the activity of platinum.
TL;DR: The exfoliated black phosphorus nanosheets are demonstrated to be effective photosensitizers for the generation of singlet oxygen with a high quantum yield of about 0.91, rendering their attractive applications in catalysis and photodynamic therapy.
Abstract: Benefiting from its strong oxidizing properties, the singlet oxygen has garnered serious attentions in physical, chemical, as well as biological studies. However, the photosensitizers for the generation of singlet oxygen bear in low quantum yields, lack of long wavelength absorption band, poor biocompatibility, undegradable in living tissues, and so on. Here we first demonstrate the exfoliated black phosphorus nanosheets to be effective photosensitizers for the generation of singlet oxygen with a high quantum yield of about 0.91, rendering their attractive applications in catalysis and photodynamic therapy. Through in vitro and in vivo studies, the water dispersible black phosphorus nanosheets show notable cancer therapy ability. In addition, the photodegradable character of black phosphorus from element to biocompatible phosphorus oxides further highlights its therapeutic potential against cancer. This study will not only expand the breadth of study in black phosphorus but also offer an efficient catalys...
TL;DR: In this article, the atomically dispersed Pd on graphene can be fabricated using the atomic layer deposition technique, and the single-atom Pd1/graphene catalyst showed about 100% butenes selectivity at 95% conversion at a mild reaction condition of about 50 °C, likely due to the changes of 1,3-butadiene adsorption mode and enhanced steric effect on the isolated Pd atoms.
Abstract: We reported that atomically dispersed Pd on graphene can be fabricated using the atomic layer deposition technique. Aberration-corrected high-angle annular dark-field scanning transmission electron microscopy and X-ray absorption fine structure spectroscopy both confirmed that isolated Pd single atoms dominantly existed on the graphene support. In selective hydrogenation of 1,3-butadiene, the single-atom Pd1/graphene catalyst showed about 100% butenes selectivity at 95% conversion at a mild reaction condition of about 50 °C, which is likely due to the changes of 1,3-butadiene adsorption mode and enhanced steric effect on the isolated Pd atoms. More importantly, excellent durability against deactivation via either aggregation of metal atoms or carbonaceous deposits during a total 100 h of reaction time on stream was achieved. Therefore, the single-atom catalysts may open up more opportunities to optimize the activity, selectivity, and durability in selective hydrogenation reactions.
TL;DR: This tutorial review focuses on the recent progress in disclosing the factors that affect the activity of reactive sites, including characterization of atomic coordination number, structural defects and disorder in ultrathin two-dimensional sheets by X-ray absorption fine structure spectroscopy, positron annihilation spectroscopic, electron spin resonance and high resolution transmission electron microscopy.
Abstract: Catalysis can speed up chemical reactions and it usually occurs on the low coordinated steps, edges, terraces, kinks and corner atoms that are often called “active sites”. However, the atomic level interplay between active sites and catalytic activity is still an open question, owing to the large difference between idealized models and real catalysts. This stimulates us to pursue a suitable material model for studying the active sites–catalytic activity relationship, in which the atomically-thin two-dimensional sheets could serve as an ideal model, owing to their relatively simple type of active site and the ultrahigh fraction of active sites that are comparable to the overall atoms. In this tutorial review, we focus on the recent progress in disclosing the factors that affect the activity of reactive sites, including characterization of atomic coordination number, structural defects and disorder in ultrathin two-dimensional sheets by X-ray absorption fine structure spectroscopy, positron annihilation spectroscopy, electron spin resonance and high resolution transmission electron microscopy. Also, we overview their applications in CO catalytic oxidation, photocatalytic water splitting, electrocatalytic oxygen and hydrogen evolution reactions, and hence highlight the atomic level interplay among coordination number, structural defects/disorder, active sites and catalytic activity in the two-dimensional sheets with atomic thickness. Finally, we also present the major challenges and opportunities regarding the role of active sites in catalysis. We believe that this review provides critical insights for understanding the catalysis and hence helps to develop new catalysts with high catalytic activity.
TL;DR: DA and DRD1 signaling prevent NLRP3 inflammasome-dependent inflammation, including neurotoxin-induced neuroinflammation, LPS-induced systemic inflammation, and monosodium urate crystal (MSU)-induced peritoneal inflammation.
TL;DR: The role of torsion in gravity has been extensively investigated along the main direction of bringing gravity closer to its gauge formulation and incorporating spin in a geometric description, and various torsional constructions, from teleparallel, to Einstein-Cartan, and metric-affine gauge theories are reviewed.
Abstract: Over the past decades, the role of torsion in gravity has been extensively investigated along the main direction of bringing gravity closer to its gauge formulation and incorporating spin in a geometric description. Here we review various torsional constructions, from teleparallel, to Einstein-Cartan, and metric-affine gauge theories, resulting in extending torsional gravity in the paradigm of f(T) gravity, where f(T) is an arbitrary function of the torsion scalar. Based on this theory, we further review the corresponding cosmological and astrophysical applications. In particular, we study cosmological solutions arising from f(T) gravity, both at the background and perturbation levels, in different eras along the cosmic expansion. The f(T) gravity construction can provide a theoretical interpretation of the late-time universe acceleration, and it can easily accommodate with the regular thermal expanding history including the radiation and cold dark matter dominated phases. Furthermore, if one traces back to very early times, a sufficiently long period of inflation can be achieved and hence can be investigated by cosmic microwave background observations, or alternatively, the Big Bang singularity can be avoided due to the appearance of non-singular bounces. Various observational constraints, especially the bounds coming from the large-scale structure data in the case of f(T) cosmology, as well as the behavior of gravitational waves, are described in detail. Moreover, the spherically symmetric and black hole solutions of the theory are reviewed. Additionally, we discuss various extensions of the f(T) paradigm. Finally, we consider the relation with other modified gravitational theories, such as those based on curvature, like f(R) gravity, trying to enlighten the subject of which formulation might be more suitable for quantization ventures and cosmological applications.
TL;DR: This work developed metallic Co4N porous nanowire arrays directly grown on flexible substrates as highly active OER electrocatalysts for the first time, which is the best OER performance among reported Co-based electrocatalyst performance to date.
Abstract: Designing highly efficient electrocatalysts for oxygen evolution reaction (OER) plays a key role in the development of various renewable energy storage and conversion devices. In this work, we developed metallic Co4N porous nanowire arrays directly grown on flexible substrates as highly active OER electrocatalysts for the first time. Benefiting from the collaborative advantages of metallic character, 1D porous nanowire arrays, and unique 3D electrode configuration, surface oxidation activated Co4N porous nanowire arrays/carbon cloth achieved an extremely small overpotential of 257 mV at a current density of 10 mA cm(-2), and a low Tafel slope of 44 mV dec(-1) in an alkaline medium, which is the best OER performance among reported Co-based electrocatalysts to date. Moreover, in-depth mechanistic investigations demonstrate the active phases are the metallic Co4N core inside with a thin cobalt oxides/hydroxides shell during the OER process. Our finding introduces a new concept to explore the design of high-efficiency OER electrocatalysts.
TL;DR: In this article, the authors summarized the most current advances on novel design idea and new synthesis strategy for g-C 3 N 4 preparation, insightful ideas on extending optical absorption of pristine G-C3 N 4, overall water splitting and CO 2 photoreduction over g-c 3N 4 based systems.
TL;DR: It is demonstrated that methanol can affect the coordination mode of ZIF-67 in the presence of Co(2+) and induces a mild phase transformation under solvothermal conditions and a well-defined hollow Zn/Co ZIF rhombic dodecahedron can be obtained.
Abstract: The rational design of metal–organic frameworks (MOFs) with hollow features and tunable porosity at the nanoscale can enhance their intrinsic properties and stimulates increasing attentions. In this Communication, we demonstrate that methanol can affect the coordination mode of ZIF-67 in the presence of Co2+ and induces a mild phase transformation under solvothermal conditions. By applying this transformation process to the ZIF-67@ZIF-8 core–shell structures, a well-defined hollow Zn/Co ZIF rhombic dodecahedron can be obtained. The manufacturing of hollow MOFs enables us to prepare a noble metal@MOF yolk-shell composite with controlled spatial distribution and morphology. The enhanced gas storage and porous confinement that originate from the hollow interior and coating of ZIF-8 confers this unique catalyst with superior activity and selectivity toward the semi-hydrogenation of acetylene.
TL;DR: In this paper, the branching fraction ratio R(D)(()*()) of (B) over bar → D-(*())tau(-)(nu)over bar (tau) relative to (B), where l = e or mu, was measured using the full Belle data sample.
Abstract: We report a measurement of the branching fraction ratios R(D)(()*()) of (B) over bar -> D-(*())tau(-)(nu) over bar (tau) relative to (B) over bar -> D-(*())l(-)(nu) over barl (where l = e or mu) using the full Belle data sample of 772 x 10(6)B (B) over bar pairs collected at the Upsilon(4S) resonance with the Belle detector at the KEKB asymmetric-energy e(+)e(-) collider. The measured values are R(D) = 0.375 +/- 0.064(stat) +/- 0.026(syst) and R(D*) = 0.293 +/- 0.038 (stat) +/- 0.015 (syst). The analysis uses hadronic reconstruction of the tag-side B meson and purely leptonic t decays. The results are consistent with earlier measurements and do not show a significant deviation from the standard model prediction.
TL;DR: The Jiangmen Underground Neutrino Observatory (JUNO) as mentioned in this paper is a 20 kton multi-purpose underground liquid scintillator detector with the determination of the neutrino mass hierarchy as a primary physics goal.
Abstract: The Jiangmen Underground Neutrino Observatory (JUNO), a 20 kton multi-purpose underground liquid scintillator detector, was proposed with the determination of the neutrino mass hierarchy as a primary physics goal. It is also capable of observing neutrinos from terrestrial and extra-terrestrial sources, including supernova burst neutrinos, diffuse supernova neutrino background, geoneutrinos, atmospheric neutrinos, solar neutrinos, as well as exotic searches such as nucleon decays, dark matter, sterile neutrinos, etc. We present the physics motivations and the anticipated performance of the JUNO detector for various proposed measurements. By detecting reactor antineutrinos from two power plants at 53-km distance, JUNO will determine the neutrino mass hierarchy at a 3-4 sigma significance with six years of running. The measurement of antineutrino spectrum will also lead to the precise determination of three out of the six oscillation parameters to an accuracy of better than 1\%. Neutrino burst from a typical core-collapse supernova at 10 kpc would lead to ~5000 inverse-beta-decay events and ~2000 all-flavor neutrino-proton elastic scattering events in JUNO. Detection of DSNB would provide valuable information on the cosmic star-formation rate and the average core-collapsed neutrino energy spectrum. Geo-neutrinos can be detected in JUNO with a rate of ~400 events per year, significantly improving the statistics of existing geoneutrino samples. The JUNO detector is sensitive to several exotic searches, e.g. proton decay via the $p\to K^++\bar
u$ decay channel. The JUNO detector will provide a unique facility to address many outstanding crucial questions in particle and astrophysics. It holds the great potential for further advancing our quest to understanding the fundamental properties of neutrinos, one of the building blocks of our Universe.
TL;DR: A survey of MaOEAs is reported and seven classes of many-objective evolutionary algorithms proposed are categorized into seven classes: relaxed dominance based, diversity-based, aggregation- based, indicator-Based, reference set based, preference-based and dimensionality reduction approaches.
Abstract: Multiobjective evolutionary algorithms (MOEAs) have been widely used in real-world applications. However, most MOEAs based on Pareto-dominance handle many-objective problems (MaOPs) poorly due to a high proportion of incomparable and thus mutually nondominated solutions. Recently, a number of many-objective evolutionary algorithms (MaOEAs) have been proposed to deal with this scalability issue. In this article, a survey of MaOEAs is reported. According to the key ideas used, MaOEAs are categorized into seven classes: relaxed dominance based, diversity-based, aggregation-based, indicator-based, reference set based, preference-based, and dimensionality reduction approaches. Several future research directions in this field are also discussed.
TL;DR: A phase incorporation strategy to induce robust room-temperature ferromagnetism in a nonmagnetic MoS2 semiconductor nanosheets and opens up new possibility for effective manipulation of exchange interactions in two-dimensional nanostructures.
Abstract: Outstanding magnetic properties are highly desired for two-dimensional ultrathin semiconductor nanosheets. Here, we propose a phase incorporation strategy to induce robust room-temperature ferromagnetism in a nonmagnetic MoS2 semiconductor. A two-step hydrothermal method was used to intentionally introduce sulfur vacancies in a 2H-MoS2 ultrathin nanosheet host, which prompts the transformation of the surrounding 2H-MoS2 local lattice into a trigonal (1T-MoS2) phase. 25% 1T-MoS2 phase incorporation in 2H-MoS2 nanosheets can enhance the electron carrier concentration by an order, introduce a Mo4+ 4d energy state within the bandgap, and create a robust intrinsic ferromagnetic response of 0.25 mu(B)/Mo by the exchange interactions between sulfur vacancy and the Mo4+ 4d bandgap state at room temperature. This design opens up new possibility for effective manipulation of exchange interactions in two-dimensional nanostructures.
TL;DR: This work uses photon pairs entangled in both degrees of freedom (that is, hyper-entangled) as the quantum channel for teleportation, and develops a method to project and discriminate hyper-ENTangled Bell states by exploiting probabilistic quantum non-demolition measurement, which can be extended to more degrees offreedom.
Abstract: The quantum teleportation of composite quantum states of a single photon encoded in both spin and orbital angular momentum is achieved, with a teleportation fidelity above the classical limit, by quantum non-demolition measurement assisted discrimination of the Bell states describing the entanglement of the two degrees of freedom. In the process known as quantum teleportation, quantum information encoded in a quantum particle, for example a photon, is transferred from one place to the other without ever moving the photon. Although quantum teleportation has been demonstrated with a variety of different systems, all have so far been limited in one crucial aspect: they only allow teleporting one degree of freedom. Here, Nai-Le Liu and colleagues demonstrate quantum teleportation of two degrees of freedom — spin and orbital angular momentum — in a single photon. Their experimental implementation is very complex and entails various innovative techniques, most notably a hybrid Bell-state measurement scheme. The intricacy of this scheme illustrates how difficult it will be to implement quantum teleportation of more complex quantum systems with more degrees of freedom. But this work represents a first and significant step in this direction. Quantum teleportation1 provides a ‘disembodied’ way to transfer quantum states from one object to another at a distant location, assisted by previously shared entangled states and a classical communication channel. As well as being of fundamental interest, teleportation has been recognized as an important element in long-distance quantum communication2, distributed quantum networks3 and measurement-based quantum computation4,5. There have been numerous demonstrations of teleportation in different physical systems such as photons6,7,8, atoms9, ions10,11, electrons12 and superconducting circuits13. All the previous experiments were limited to the teleportation of one degree of freedom only. However, a single quantum particle can naturally possess various degrees of freedom—internal and external—and with coherent coupling among them. A fundamental open challenge is to teleport multiple degrees of freedom simultaneously, which is necessary to describe a quantum particle fully and, therefore, to teleport it intact. Here we demonstrate quantum teleportation of the composite quantum states of a single photon encoded in both spin and orbital angular momentum. We use photon pairs entangled in both degrees of freedom (that is, hyper-entangled) as the quantum channel for teleportation, and develop a method to project and discriminate hyper-entangled Bell states by exploiting probabilistic quantum non-demolition measurement, which can be extended to more degrees of freedom. We verify the teleportation for both spin–orbit product states and hybrid entangled states, and achieve a teleportation fidelity ranging from 0.57 to 0.68, above the classical limit. Our work is a step towards the teleportation of more complex quantum systems, and demonstrates an increase in our technical control of scalable quantum technologies.
TL;DR: High-resolution electron microscopy imaging of water locked between two graphene sheets is reported, an archetypal example of hydrophobic confinement, and shows that the nanoconfined water at room temperature forms ‘square ice’—a phase having symmetry qualitatively different from the conventional tetrahedral geometry of hydrogen bonding between water molecules.
Abstract: Bulk water exists in many forms, including liquid, vapour and numerous crystalline and amorphous phases of ice, with hexagonal ice being responsible for the fascinating variety of snowflakes Much less noticeable but equally ubiquitous is water adsorbed at interfaces and confined in microscopic pores Such low-dimensional water determines aspects of various phenomena in materials science, geology, biology, tribology and nanotechnology Theory suggests many possible phases for adsorbed and confined water, but it has proved challenging to assess its crystal structure experimentally Here we report high-resolution electron microscopy imaging of water locked between two graphene sheets, an archetypal example of hydrophobic confinement The observations show that the nanoconfined water at room temperature forms 'square ice'--a phase having symmetry qualitatively different from the conventional tetrahedral geometry of hydrogen bonding between water molecules Square ice has a high packing density with a lattice constant of 283 A and can assemble in bilayer and trilayer crystallites Molecular dynamics simulations indicate that square ice should be present inside hydrophobic nanochannels independently of their exact atomic nature