Showing papers by "University of Illinois at Urbana–Champaign published in 2017"
TL;DR: The association of GRB 170817A, detected by Fermi-GBM 1.7 s after the coalescence, corroborates the hypothesis of a neutron star merger and provides the first direct evidence of a link between these mergers and short γ-ray bursts.
Abstract: On August 17, 2017 at 12∶41:04 UTC the Advanced LIGO and Advanced Virgo gravitational-wave detectors made their first observation of a binary neutron star inspiral. The signal, GW170817, was detected with a combined signal-to-noise ratio of 32.4 and a false-alarm-rate estimate of less than one per 8.0×10^{4} years. We infer the component masses of the binary to be between 0.86 and 2.26 M_{⊙}, in agreement with masses of known neutron stars. Restricting the component spins to the range inferred in binary neutron stars, we find the component masses to be in the range 1.17-1.60 M_{⊙}, with the total mass of the system 2.74_{-0.01}^{+0.04}M_{⊙}. The source was localized within a sky region of 28 deg^{2} (90% probability) and had a luminosity distance of 40_{-14}^{+8} Mpc, the closest and most precisely localized gravitational-wave signal yet. The association with the γ-ray burst GRB 170817A, detected by Fermi-GBM 1.7 s after the coalescence, corroborates the hypothesis of a neutron star merger and provides the first direct evidence of a link between these mergers and short γ-ray bursts. Subsequent identification of transient counterparts across the electromagnetic spectrum in the same location further supports the interpretation of this event as a neutron star merger. This unprecedented joint gravitational and electromagnetic observation provides insight into astrophysics, dense matter, gravitation, and cosmology.
7,327 citations
TL;DR: The goal of this Consensus Statement is to engender appropriate use of the term 'prebiotic' by relevant stakeholders so that consistency and clarity can be achieved in research reports, product marketing and regulatory oversight of the category.
Abstract: With the continued interest in the role of the gut microbiota in health, attention has now turned to how to harness the microbiota for the benefit of the host. This Consensus Statement outlines the definition and scope of the term 'prebiotic' as determined by an expert panel convened by the International Scientific Association for Probiotics and Prebiotics in December 2016. In December 2016, a panel of experts in microbiology, nutrition and clinical research was convened by the International Scientific Association for Probiotics and Prebiotics to review the definition and scope of prebiotics. Consistent with the original embodiment of prebiotics, but aware of the latest scientific and clinical developments, the panel updated the definition of a prebiotic: a substrate that is selectively utilized by host microorganisms conferring a health benefit. This definition expands the concept of prebiotics to possibly include non-carbohydrate substances, applications to body sites other than the gastrointestinal tract, and diverse categories other than food. The requirement for selective microbiota-mediated mechanisms was retained. Beneficial health effects must be documented for a substance to be considered a prebiotic. The consensus definition applies also to prebiotics for use by animals, in which microbiota-focused strategies to maintain health and prevent disease is as relevant as for humans. Ultimately, the goal of this Consensus Statement is to engender appropriate use of the term 'prebiotic' by relevant stakeholders so that consistency and clarity can be achieved in research reports, product marketing and regulatory oversight of the category. To this end, we have reviewed several aspects of prebiotic science including its development, health benefits and legislation.
2,863 citations
TL;DR: In this paper, the authors used the observed time delay of $(+1.74\pm 0.05)\,{\rm{s}}$ between GRB 170817A and GW170817 to constrain the difference between the speed of gravity and speed of light to be between $-3
Abstract: On 2017 August 17, the gravitational-wave event GW170817 was observed by the Advanced LIGO and Virgo detectors, and the gamma-ray burst (GRB) GRB 170817A was observed independently by the Fermi Gamma-ray Burst Monitor, and the Anti-Coincidence Shield for the Spectrometer for the International Gamma-Ray Astrophysics Laboratory. The probability of the near-simultaneous temporal and spatial observation of GRB 170817A and GW170817 occurring by chance is $5.0\times {10}^{-8}$. We therefore confirm binary neutron star mergers as a progenitor of short GRBs. The association of GW170817 and GRB 170817A provides new insight into fundamental physics and the origin of short GRBs. We use the observed time delay of $(+1.74\pm 0.05)\,{\rm{s}}$ between GRB 170817A and GW170817 to: (i) constrain the difference between the speed of gravity and the speed of light to be between $-3\times {10}^{-15}$ and $+7\times {10}^{-16}$ times the speed of light, (ii) place new bounds on the violation of Lorentz invariance, (iii) present a new test of the equivalence principle by constraining the Shapiro delay between gravitational and electromagnetic radiation. We also use the time delay to constrain the size and bulk Lorentz factor of the region emitting the gamma-rays. GRB 170817A is the closest short GRB with a known distance, but is between 2 and 6 orders of magnitude less energetic than other bursts with measured redshift. A new generation of gamma-ray detectors, and subthreshold searches in existing detectors, will be essential to detect similar short bursts at greater distances. Finally, we predict a joint detection rate for the Fermi Gamma-ray Burst Monitor and the Advanced LIGO and Virgo detectors of 0.1–1.4 per year during the 2018–2019 observing run and 0.3–1.7 per year at design sensitivity.
2,633 citations
TL;DR: The magnitude of modifications to the gravitational-wave dispersion relation is constrain, the graviton mass is bound to m_{g}≤7.7×10^{-23} eV/c^{2} and null tests of general relativity are performed, finding that GW170104 is consistent with general relativity.
Abstract: We describe the observation of GW170104, a gravitational-wave signal produced by the coalescence of a pair of stellar-mass black holes. The signal was measured on January 4, 2017 at 10∶11:58.6 UTC by the twin advanced detectors of the Laser Interferometer Gravitational-Wave Observatory during their second observing run, with a network signal-to-noise ratio of 13 and a false alarm rate less than 1 in 70 000 years. The inferred component black hole masses are 31.2^(8.4) _(−6.0)M_⊙ and 19.4^(5.3)_( −5.9)M_⊙ (at the 90% credible level). The black hole spins are best constrained through measurement of the effective inspiral spin parameter, a mass-weighted combination of the spin components perpendicular to the orbital plane, χ_(eff) = −0.12^(0.21)_( −0.30). This result implies that spin configurations with both component spins positively aligned with the orbital angular momentum are disfavored. The source luminosity distance is 880^(450)_(−390) Mpc corresponding to a redshift of z = 0.18^(0.08)_( −0.07) . We constrain the magnitude of modifications to the gravitational-wave dispersion relation and perform null tests of general relativity. Assuming that gravitons are dispersed in vacuum like massive particles, we bound the graviton mass to m_g ≤ 7.7 × 10^(−23) eV/c^2. In all cases, we find that GW170104 is consistent with general relativity.
2,569 citations
TL;DR: For the first time, the nature of gravitational-wave polarizations from the antenna response of the LIGO-Virgo network is tested, thus enabling a new class of phenomenological tests of gravity.
Abstract: On August 14, 2017 at 10∶30:43 UTC, the Advanced Virgo detector and the two Advanced LIGO detectors coherently observed a transient gravitational-wave signal produced by the coalescence of two stellar mass black holes, with a false-alarm rate of ≲1 in 27 000 years. The signal was observed with a three-detector network matched-filter signal-to-noise ratio of 18. The inferred masses of the initial black holes are 30.5-3.0+5.7M⊙ and 25.3-4.2+2.8M⊙ (at the 90% credible level). The luminosity distance of the source is 540-210+130 Mpc, corresponding to a redshift of z=0.11-0.04+0.03. A network of three detectors improves the sky localization of the source, reducing the area of the 90% credible region from 1160 deg2 using only the two LIGO detectors to 60 deg2 using all three detectors. For the first time, we can test the nature of gravitational-wave polarizations from the antenna response of the LIGO-Virgo network, thus enabling a new class of phenomenological tests of gravity.
1,979 citations
Imperial College London1, Anglia Ruskin University2, University of New South Wales3, Brien Holden Vision Institute4, International Agency for the Prevention of Blindness5, Moorfields Eye Hospital6, York Hospital7, Heidelberg University8, L V Prasad Eye Institute9, Massachusetts Eye and Ear Infirmary10, Nova Southeastern University11, University of KwaZulu-Natal12, National Health and Medical Research Council13, World Health Organization14, National University of Singapore15, University of Melbourne16, Selçuk University17, University of Miami18, University of Adelaide19, Queen's University Belfast20, Harvard University21, The George Institute for Global Health22, University of Washington23, University of Michigan24, Universiti Tunku Abdul Rahman25, University of Alabama at Birmingham26, National Institutes of Health27, Johns Hopkins University28, University of São Paulo29, Henry Ford Health System30, University College London31, Sankara Nethralaya32, University of Nairobi33, University of Georgia34, University of Utah35, Federal University of São Paulo36, Yale University37, Alberta Children's Hospital38, University of Illinois at Chicago39, Medical College of Wisconsin40, Novartis41, University of Udine42, University of Illinois at Urbana–Champaign43, Royal Children's Hospital44, University of Missouri45, Centers for Disease Control and Prevention46, University of Milan47, Icahn School of Medicine at Mount Sinai48, Mayo Clinic49, Pan American Health Organization50, University of Indonesia51, University of Pennsylvania52, University of Crete53, University of Southern California54, University of Florence55, Capital Medical University56, Leipzig University57
TL;DR: A series of regression models were fitted to estimate the proportion of moderate or severe vision impairment and blindness by cause, age, region, and year, and found that world regions varied markedly in the causes of blindness and vision impairment in this age group.
1,909 citations
12 Apr 2017
TL;DR: In this paper, the Laplacian pyramid super-resolution network (LapSRN) is proposed to progressively reconstruct the sub-band residuals of high-resolution images.
Abstract: Convolutional neural networks have recently demonstrated high-quality reconstruction for single-image super-resolution. In this paper, we propose the Laplacian Pyramid Super-Resolution Network (LapSRN) to progressively reconstruct the sub-band residuals of high-resolution images. At each pyramid level, our model takes coarse-resolution feature maps as input, predicts the high-frequency residuals, and uses transposed convolutions for upsampling to the finer level. Our method does not require the bicubic interpolation as the pre-processing step and thus dramatically reduces the computational complexity. We train the proposed LapSRN with deep supervision using a robust Charbonnier loss function and achieve high-quality reconstruction. Furthermore, our network generates multi-scale predictions in one feed-forward pass through the progressive reconstruction, thereby facilitates resource-aware applications. Extensive quantitative and qualitative evaluations on benchmark datasets show that the proposed algorithm performs favorably against the state-of-the-art methods in terms of speed and accuracy.
1,651 citations
Anglia Ruskin University1, University of Oxford2, Heidelberg University3, L V Prasad Eye Institute4, Massachusetts Eye and Ear Infirmary5, Nova Southeastern University6, Brien Holden Vision Institute7, University of KwaZulu-Natal8, Flinders University9, University of New South Wales10, Royal Liverpool University Hospital11, World Health Organization12, National University of Singapore13, University of Melbourne14, Selçuk University15, University of Burgundy16, University of Miami17, University of Adelaide18, Queen's University Belfast19, Harvard University20, The George Institute for Global Health21, University of Washington22, University of Michigan23, Universiti Tunku Abdul Rahman24, University of Alabama25, National Institutes of Health26, Johns Hopkins University27, University of São Paulo28, Henry Ford Health System29, University College London30, University of Nairobi31, University of Georgia32, University of Utah33, Federal University of São Paulo34, Yale University35, Alberta Children's Hospital36, University of Pennsylvania37, Medical College of Wisconsin38, Novartis39, University of Udine40, University of Illinois at Urbana–Champaign41, Royal Children's Hospital42, University of Missouri43, University of Milan44, Centers for Disease Control and Prevention45, Singapore National Eye Center46, Icahn School of Medicine at Mount Sinai47, Mayo Clinic48, Pan American Health Organization49, University of Indonesia50, University of Crete51, Erasmus University Rotterdam52, University of Southern California53, University of Florence54, Stellenbosch University55, Capital Medical University56, Leipzig University57, Moorfields Eye Hospital58
TL;DR: There is an ongoing reduction in the age-standardised prevalence of blindness and visual impairment, yet the growth and ageing of the world's population is causing a substantial increase in number of people affected, highlighting the need to scale up vision impairment alleviation efforts at all levels.
1,473 citations
Posted Content•
TL;DR: This paper proposes the Laplacian Pyramid Super-Resolution Network (LapSRN) to progressively reconstruct the sub-band residuals of high-resolution images and generates multi-scale predictions in one feed-forward pass through the progressive reconstruction, thereby facilitates resource-aware applications.
Abstract: Convolutional neural networks have recently demonstrated high-quality reconstruction for single-image super-resolution. In this paper, we propose the Laplacian Pyramid Super-Resolution Network (LapSRN) to progressively reconstruct the sub-band residuals of high-resolution images. At each pyramid level, our model takes coarse-resolution feature maps as input, predicts the high-frequency residuals, and uses transposed convolutions for upsampling to the finer level. Our method does not require the bicubic interpolation as the pre-processing step and thus dramatically reduces the computational complexity. We train the proposed LapSRN with deep supervision using a robust Charbonnier loss function and achieve high-quality reconstruction. Furthermore, our network generates multi-scale predictions in one feed-forward pass through the progressive reconstruction, thereby facilitates resource-aware applications. Extensive quantitative and qualitative evaluations on benchmark datasets show that the proposed algorithm performs favorably against the state-of-the-art methods in terms of speed and accuracy.
1,417 citations
TL;DR: This work introduces a paradigm in which “nested” Wilson loops give rise to topological invariants that have been overlooked and opens a venue for the expansion of the classification of topological phases of matter.
Abstract: The Berry phase provides a modern formulation of electric polarization in crystals. We extend this concept to higher electric multipole moments and determine the necessary conditions and minimal models for which the quadrupole and octupole moments are topologically quantized electromagnetic observables. Such systems exhibit gapped boundaries that are themselves lower-dimensional topological phases. Furthermore, they host topologically protected corner states carrying fractional charge, exhibiting fractionalization at the boundary of the boundary. To characterize these insulating phases of matter, we introduce a paradigm in which “nested” Wilson loops give rise to topological invariants that have been overlooked. We propose three realistic experimental implementations of this topological behavior that can be immediately tested. Our work opens a venue for the expansion of the classification of topological phases of matter.
1,319 citations
TL;DR: In this article, a GW signal from the merger of two stellar-mass black holes was observed by the two Advanced Laser Interferometer Gravitational-Wave Observatory detectors with a network signal-to-noise ratio of 13.5%.
Abstract: On 2017 June 8 at 02:01:16.49 UTC, a gravitational-wave (GW) signal from the merger of two stellar-mass black holes was observed by the two Advanced Laser Interferometer Gravitational-Wave Observatory detectors with a network signal-to-noise ratio of 13. This system is the lightest black hole binary so far observed, with component masses of ${12}_{-2}^{+7}\,{M}_{\odot }$ and ${7}_{-2}^{+2}\,{M}_{\odot }$ (90% credible intervals). These lie in the range of measured black hole masses in low-mass X-ray binaries, thus allowing us to compare black holes detected through GWs with electromagnetic observations. The source's luminosity distance is ${340}_{-140}^{+140}\,\mathrm{Mpc}$, corresponding to redshift ${0.07}_{-0.03}^{+0.03}$. We verify that the signal waveform is consistent with the predictions of general relativity.
01 Jul 2017
TL;DR: A novel method for semantic image inpainting, which generates the missing content by conditioning on the available data, and successfully predicts information in large missing regions and achieves pixel-level photorealism, significantly outperforming the state-of-the-art methods.
Abstract: Semantic image inpainting is a challenging task where large missing regions have to be filled based on the available visual data. Existing methods which extract information from only a single image generally produce unsatisfactory results due to the lack of high level context. In this paper, we propose a novel method for semantic image inpainting, which generates the missing content by conditioning on the available data. Given a trained generative model, we search for the closest encoding of the corrupted image in the latent image manifold using our context and prior losses. This encoding is then passed through the generative model to infer the missing content. In our method, inference is possible irrespective of how the missing content is structured, while the state-of-the-art learning based method requires specific information about the holes in the training phase. Experiments on three datasets show that our method successfully predicts information in large missing regions and achieves pixel-level photorealism, significantly outperforming the state-of-the-art methods.
ETH Zurich1, University of California, Merced2, University of Hong Kong3, Seoul National University4, The Chinese University of Hong Kong5, Chinese Academy of Sciences6, KAIST7, University of Illinois at Urbana–Champaign8, Harbin Institute of Technology9, Xiamen University10, Peking University11, University of Missouri12, University of Sydney13, Beijing University of Posts and Telecommunications14, Shandong University15, Australian National University16, Sejong University17, Pennsylvania State University18, Tampere University of Technology19, Indian Institute of Technology Kharagpur20, École Polytechnique Fédérale de Lausanne21, University of Electronic Science and Technology of China22
TL;DR: This paper reviews the first challenge on single image super-resolution (restoration of rich details in an low resolution image) with focus on proposed solutions and results and gauges the state-of-the-art in single imagesuper-resolution.
Abstract: This paper reviews the first challenge on single image super-resolution (restoration of rich details in an low resolution image) with focus on proposed solutions and results. A new DIVerse 2K resolution image dataset (DIV2K) was employed. The challenge had 6 competitions divided into 2 tracks with 3 magnification factors each. Track 1 employed the standard bicubic downscaling setup, while Track 2 had unknown downscaling operators (blur kernel and decimation) but learnable through low and high res train images. Each competition had ∽100 registered participants and 20 teams competed in the final testing phase. They gauge the state-of-the-art in single image super-resolution.
Proceedings Article•
16 Aug 2017
TL;DR: It is argued that Mirai may represent a sea change in the evolutionary development of botnets--the simplicity through which devices were infected and its precipitous growth, and that novice malicious techniques can compromise enough low-end devices to threaten even some of the best-defended targets.
Abstract: The Mirai botnet, composed primarily of embedded and IoT devices, took the Internet by storm in late 2016 when it overwhelmed several high-profile targets with massive distributed denial-of-service (DDoS) attacks. In this paper, we provide a seven-month retrospective analysis of Mirai's growth to a peak of 600k infections and a history of its DDoS victims. By combining a variety of measurement perspectives, we analyze how the botnet emerged, what classes of devices were affected, and how Mirai variants evolved and competed for vulnerable hosts. Our measurements serve as a lens into the fragile ecosystem of IoT devices. We argue that Mirai may represent a sea change in the evolutionary development of botnets--the simplicity through which devices were infected and its precipitous growth, demonstrate that novice malicious techniques can compromise enough low-end devices to threaten even some of the best-defended targets. To address this risk, we recommend technical and nontechnical interventions, as well as propose future research directions.
TL;DR: The Pathosystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center, which provides services for RNA-Seq, variation, model reconstruction and differential expression analysis, all delivered through an updated private workspace.
Abstract: The Pathosystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center (https://www.patricbrc.org). Recent changes to PATRIC include a redesign of the web interface and some new services that provide users with a platform that takes them from raw reads to an integrated analysis experience. The redesigned interface allows researchers direct access to tools and data, and the emphasis has changed to user-created genome-groups, with detailed summaries and views of the data that researchers have selected. Perhaps the biggest change has been the enhanced capability for researchers to analyze their private data and compare it to the available public data. Researchers can assemble their raw sequence reads and annotate the contigs using RASTtk. PATRIC also provides services for RNA-Seq, variation, model reconstruction and differential expression analysis, all delivered through an updated private workspace. Private data can be compared by 'virtual integration' to any of PATRIC's public data. The number of genomes available for comparison in PATRIC has expanded to over 80 000, with a special emphasis on genomes with antimicrobial resistance data. PATRIC uses this data to improve both subsystem annotation and k-mer classification, and tags new genomes as having signatures that indicate susceptibility or resistance to specific antibiotics.
University of South Carolina1, Los Alamos National Laboratory2, Moscow State University3, Delhi Technological University4, University of Paris5, University of California, Davis6, Indian Institute of Technology (BHU) Varanasi7, University of Moratuwa8, University of Illinois at Urbana–Champaign9, California Polytechnic State University10, Sandia National Laboratories11, Max Planck Society12, Indian Institute of Technology Kharagpur13, French Institute for Research in Computer Science and Automation14, University of New Mexico15, Charles University in Prague16, Birla Institute of Technology and Science17, Indian Institute of Technology Bombay18, University of West Bohemia19
TL;DR: The architecture of SymPy is presented, a description of its features, and a discussion of select domain specific submodules are discussed, to become the standard symbolic library for the scientific Python ecosystem.
Abstract: SymPy is an open source computer algebra system written in pure Python. It is built with a focus on extensibility and ease of use, through both interactive and programmatic applications. These characteristics have led SymPy to become a popular symbolic library for the scientific Python ecosystem. This paper presents the architecture of SymPy, a description of its features, and a discussion of select submodules. The supplementary material provide additional examples and further outline details of the architecture and features of SymPy.
TL;DR: The term "lab-on-skin" is introduced to describe a set of electronic devices that have physical properties, such as thickness, thermal mass, elastic modulus, and water-vapor permeability, which resemble those of the skin, which provide accurate, non-invasive, long-term, and continuous health monitoring.
Abstract: Skin is the largest organ of the human body, and it offers a diagnostic interface rich with vital biological signals from the inner organs, blood vessels, muscles, and dermis/epidermis. Soft, flexible, and stretchable electronic devices provide a novel platform to interface with soft tissues for robotic feedback and control, regenerative medicine, and continuous health monitoring. Here, we introduce the term “lab-on-skin” to describe a set of electronic devices that have physical properties, such as thickness, thermal mass, elastic modulus, and water-vapor permeability, which resemble those of the skin. These devices can conformally laminate on the epidermis to mitigate motion artifacts and mismatches in mechanical properties created by conventional, rigid electronics while simultaneously providing accurate, non-invasive, long-term, and continuous health monitoring. Recent progress in the design and fabrication of soft sensors with more advanced capabilities and enhanced reliability suggest an impending t...
TL;DR: In this paper, the authors extend the theory of dipole moments in crystalline insulators to higher multipole moments, and describe the topological invariants that protect these moments.
Abstract: We extend the theory of dipole moments in crystalline insulators to higher multipole moments. In this paper, we expand in great detail the theory presented in Ref. 1, and extend it to cover associated topological pumping phenomena, and a novel class of 3D insulator with chiral hinge states. In quantum-mechanical crystalline insulators, higher multipole bulk moments manifest themselves by the presence of boundary-localized moments of lower dimension, in exact correspondence with the electromagnetic theory of classical continuous dielectrics. In the presence of certain symmetries, these moments are quantized, and their boundary signatures are fractionalized. These multipole moments then correspond to new SPT phases. The topological structure of these phases is described by "nested" Wilson loops, which reflect the bulk-boundary correspondence in a way that makes evident a hierarchical classification of the multipole moments. Just as a varying dipole generates charge pumping, a varying quadrupole generates dipole pumping, and a varying octupole generates quadrupole pumping. For non-trivial adiabatic cycles, the transport of these moments is quantized. An analysis of these interconnected phenomena leads to the conclusion that a new kind of Chern-type insulator exists, which has chiral, hinge-localized modes in 3D. We provide the minimal models for the quantized multipole moments, the non-trivial pumping processes and the hinge Chern insulator, and describe the topological invariants that protect them.
TL;DR: The thoroughly updated antiSMASH version 4 is presented, which adds several novel features, including prediction of gene cluster boundaries using the ClusterFinder method or the newly integrated CASSIS algorithm, improved substrate specificity prediction for non-ribosomal peptide synthetase adenylation domains based on the new SANDPUMA algorithm, and several usability features have been updated and improved.
Abstract: Many antibiotics, chemotherapeutics, crop protection agents and food preservatives originate from molecules produced by bacteria, fungi or plants. In recent years, genome mining methodologies have been widely adopted to identify and characterize the biosynthetic gene clusters encoding the production of such compounds. Since 2011, the â € antibiotics and secondary metabolite analysis shell - antiSMASH' has assisted researchers in efficiently performing this, both as a web server and a standalone tool. Here, we present the thoroughly updated antiSMASH version 4, which adds several novel features, including prediction of gene cluster boundaries using the ClusterFinder method or the newly integrated CASSIS algorithm, improved substrate specificity prediction for non-ribosomal peptide synthetase adenylation domains based on the new SANDPUMA algorithm, improved predictions for terpene and ribosomally synthesized and post-translationally modified peptides cluster products, reporting of sequence similarity to proteins encoded in experimentally characterized gene clusters on a per-protein basis and a domain-level alignment tool for comparative analysis of trans-AT polyketide synthase assembly line architectures. Additionally, several usability features have been updated and improved. Together, these improvements make antiSMASH up-to-date with the latest developments in natural product research and will further facilitate computational genome mining for the discovery of novel bioactive molecules.
TL;DR: In this paper, the authors present a new data set of annual historical (1750-2014) anthropogenic chemically reactive gases (CO, CH4, NH3, NOx, SO2, NMVOCs), carbonaceous aerosols (black carbon BC, and organic carbon OC), and CO2 developed with the Community Emissions Data System (CEDS).
Abstract: . We present a new data set of annual historical (1750–2014) anthropogenic chemically reactive gases (CO, CH4, NH3, NOx, SO2, NMVOCs), carbonaceous aerosols (black carbon – BC, and organic carbon – OC), and CO2 developed with the Community Emissions Data System (CEDS). We improve upon existing inventories with a more consistent and reproducible methodology applied to all emission species, updated emission factors, and recent estimates through 2014. The data system relies on existing energy consumption data sets and regional and country-specific inventories to produce trends over recent decades. All emission species are consistently estimated using the same activity data over all time periods. Emissions are provided on an annual basis at the level of country and sector and gridded with monthly seasonality. These estimates are comparable to, but generally slightly higher than, existing global inventories. Emissions over the most recent years are more uncertain, particularly in low- and middle-income regions where country-specific emission inventories are less available. Future work will involve refining and updating these emission estimates, estimating emissions' uncertainty, and publication of the system as open-source software.
Posted Content•
TL;DR: The proposed ODIN method, based on the observation that using temperature scaling and adding small perturbations to the input can separate the softmax score distributions between in- and out-of-distribution images, allowing for more effective detection, consistently outperforms the baseline approach by a large margin.
Abstract: We consider the problem of detecting out-of-distribution images in neural networks. We propose ODIN, a simple and effective method that does not require any change to a pre-trained neural network. Our method is based on the observation that using temperature scaling and adding small perturbations to the input can separate the softmax score distributions between in- and out-of-distribution images, allowing for more effective detection. We show in a series of experiments that ODIN is compatible with diverse network architectures and datasets. It consistently outperforms the baseline approach by a large margin, establishing a new state-of-the-art performance on this task. For example, ODIN reduces the false positive rate from the baseline 34.7% to 4.3% on the DenseNet (applied to CIFAR-10) when the true positive rate is 95%.
TL;DR: The current knowledge of the impact of fiber and prebiotic consumption on the composition and metabolic function of the human gastrointestinal microbiota is reviewed, including the effects of physiochemical properties of complex carbohydrates, adequate intake and treatment dosages, and the phenotypic responses related to the composition of thehuman microbiota.
Abstract: The gastrointestinal microbiota has an important role in human health, and there is increasing interest in utilizing dietary approaches to modulate the composition and metabolic function of the mic...
National Autonomous University of Mexico1, University of Illinois at Urbana–Champaign2, Conservation International3, German Primate Center4, Yale University5, University of Texas at Austin6, Oxford Brookes University7, Leibniz Institute for Neurobiology8, University of Colorado Boulder9, Durham University10, Emory University11, Naturhistorisches Museum12, Universidade Federal de Sergipe13, Federal University of Bahia14, Rhodes College15, University of Notre Dame16, Saint Louis University17, Northwestern University18, Federal University of Paraná19, Liverpool John Moores University20, University of Amsterdam21, Washington University in St. Louis22, University of Western Australia23, Chinese Academy of Sciences24
TL;DR: Raising global scientific and public awareness of the plight of the world’s primates and the costs of their loss to ecosystem health and human society is imperative.
Abstract: Nonhuman primates, our closest biological relatives, play important roles in the livelihoods, cultures, and religions of many societies and offer unique insights into human evolution, biology, behavior, and the threat of emerging diseases. They are an essential component of tropical biodiversity, contributing to forest regeneration and ecosystem health. Current information shows the existence of 504 species in 79 genera distributed in the Neotropics, mainland Africa, Madagascar, and Asia. Alarmingly, ~60% of primate species are now threatened with extinction and ~75% have declining populations. This situation is the result of escalating anthropogenic pressures on primates and their habitats—mainly global and local market demands, leading to extensive habitat loss through the expansion of industrial agriculture, large-scale cattle ranching, logging, oil and gas drilling, mining, dam building, and the construction of new road networks in primate range regions. Other important drivers are increased bushmeat hunting and the illegal trade of primates as pets and primate body parts, along with emerging threats, such as climate change and anthroponotic diseases. Often, these pressures act in synergy, exacerbating primate population declines. Given that primate range regions overlap extensively with a large, and rapidly growing, human population characterized by high levels of poverty, global attention is needed immediately to reverse the looming risk of primate extinctions and to attend to local human needs in sustainable ways. Raising global scientific and public awareness of the plight of the world’s primates and the costs of their loss to ecosystem health and human society is imperative.
TL;DR: A measurement of the Hubble constant is reported that combines the distance to the source inferred purely from the gravitational-wave signal with the recession velocity inferred from measurements of the redshift using the electromagnetic data.
Abstract: On 17 August 2017, the Advanced LIGO1 and Virgo2 detectors observed the gravitational-wave event GW170817—a strong signal from the merger of a binary neutron-star system3. Less than two seconds after the merger, a γ-ray burst (GRB 170817A) was detected within a region of the sky consistent with the LIGO–Virgo-derived location of the gravitational-wave source4, 5, 6. This sky region was subsequently observed by optical astronomy facilities7, resulting in the identification8, 9, 10, 11, 12, 13 of an optical transient signal within about ten arcseconds of the galaxy NGC 4993. This detection of GW170817 in both gravitational waves and electromagnetic waves represents the first ‘multi-messenger’ astronomical observation. Such observations enable GW170817 to be used as a ‘standard siren’14, 15, 16, 17, 18 (meaning that the absolute distance to the source can be determined directly from the gravitational-wave measurements) to measure the Hubble constant. This quantity represents the local expansion rate of the Universe, sets the overall scale of the Universe and is of fundamental importance to cosmology. Here we report a measurement of the Hubble constant that combines the distance to the source inferred purely from the gravitational-wave signal with the recession velocity inferred from measurements of the redshift using the electromagnetic data. In contrast to previous measurements, ours does not require the use of a cosmic ‘distance ladder’19: the gravitational-wave analysis can be used to estimate the luminosity distance out to cosmological scales directly, without the use of intermediate astronomical distance measurements. We determine the Hubble constant to be about 70 kilometres per second per megaparsec. This value is consistent with existing measurements20, 21, while being completely independent of them. Additional standard siren measurements from future gravitational-wave sources will enable the Hubble constant to be constrained to high precision.
University of East Anglia1, University of Exeter2, Max Planck Society3, Commonwealth Scientific and Industrial Research Organisation4, Stanford University5, Oak Ridge National Laboratory6, National Oceanic and Atmospheric Administration7, Atlantic Oceanographic and Meteorological Laboratory8, Cooperative Institute for Marine and Atmospheric Studies9, Bjerknes Centre for Climate Research10, Geophysical Institute, University of Bergen11, Met Office12, École Normale Supérieure13, Centre national de la recherche scientifique14, University of Maryland, College Park15, National Institute of Water and Atmospheric Research16, International Institute for Applied Systems Analysis17, Alfred Wegener Institute for Polar and Marine Research18, Woods Hole Oceanographic Institution19, University of New Hampshire20, University of Illinois at Urbana–Champaign21, Karlsruhe Institute of Technology22, University of California, San Diego23, Utrecht University24, Netherlands Environmental Assessment Agency25, Leibniz Institute of Marine Sciences26, University of Paris27, Cooperative Research Centre28, Hobart Corporation29, Oeschger Centre for Climate Change Research30, University of Bern31, National Center for Atmospheric Research32, University of Miami33, Council of Scientific and Industrial Research34, Institute of Arctic and Alpine Research35, National Institute for Environmental Studies36, Spanish National Research Council37, Montana State University38, Goddard Space Flight Center39, Leibniz Institute for Baltic Sea Research40, University of Delaware41, Auburn University42, Food and Agriculture Organization43, Wageningen University and Research Centre44, VU University Amsterdam45, University of Groningen46
TL;DR: In this paper, the authors quantify the five major components of the global carbon budget and their uncertainties, and the resulting carbon budget imbalance (BIM) is a measure of imperfect data and understanding of the contemporary carbon cycle.
Abstract: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the "global carbon budget" – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2007–2016), EFF was 9.4 ± 0.5 GtC yr−1, ELUC 1.3 ± 0.7 GtC yr−1, GATM 4.7 ± 0.1 GtC yr−1, SOCEAN 2.4 ± 0.5 GtC yr−1, and SLAND 3.0 ± 0.8 GtC yr−1, with a budget imbalance BIM of 0.6 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1. Also for 2016, ELUC was 1.3 ± 0.7 GtC yr−1, GATM was 6.1 ± 0.2 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1, and SLAND was 2.7 ± 1.0 GtC yr−1, with a small BIM of −0.3 GtC. GATM continued to be higher in 2016 compared to the past decade (2007–2016), reflecting in part the high fossil emissions and the small SLAND consistent with El Nino conditions. The global atmospheric CO2 concentration reached 402.8 ± 0.1 ppm averaged over 2016. For 2017, preliminary data for the first 6–9 months indicate a renewed growth in EFF of +2.0 % (range of 0.8 to 3.0 %) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Quere et al., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017).
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TL;DR: In this paper, a combination of exhaustive and reinforcement learning-based search is proposed to discover multiple novel activation functions, including Swish, which is the most successful and widely used activation function in deep networks.
Abstract: The choice of activation functions in deep networks has a significant effect on the training dynamics and task performance. Currently, the most successful and widely-used activation function is the Rectified Linear Unit (ReLU). Although various hand-designed alternatives to ReLU have been proposed, none have managed to replace it due to inconsistent gains. In this work, we propose to leverage automatic search techniques to discover new activation functions. Using a combination of exhaustive and reinforcement learning-based search, we discover multiple novel activation functions. We verify the effectiveness of the searches by conducting an empirical evaluation with the best discovered activation function. Our experiments show that the best discovered activation function, $f(x) = x \cdot \text{sigmoid}(\beta x)$, which we name Swish, tends to work better than ReLU on deeper models across a number of challenging datasets. For example, simply replacing ReLUs with Swish units improves top-1 classification accuracy on ImageNet by 0.9\% for Mobile NASNet-A and 0.6\% for Inception-ResNet-v2. The simplicity of Swish and its similarity to ReLU make it easy for practitioners to replace ReLUs with Swish units in any neural network.
Abstract: The second-generation of gravitational-wave detectors are just starting operation, and have already yielding their first detections. Research is now concentrated on how to maximize the scientific potential of gravitational-wave astronomy. To support this effort, we present here design targets for a new generation of detectors, which will be capable of observing compact binary sources with high signal-to-noise ratio throughout the Universe.
TL;DR: In this article, the Gordon and Betty Moore Foundation (GBMF5076) and the Heising-Simons Foundation (HSPF) have contributed to the creation of the DES-Brazil Consortium.
Abstract: NSF [AST-1411763, AST-1714498, DGE 1144152, PHY-1707954, AST-1518052]; NASA [NNX15AE50G, NNX16AC22G]; National Science Foundation; Kavli Foundation; Danish National Research Foundation; Niels Bohr International Academy; DARK Cosmology Centre; Gordon & Betty Moore Foundation; Heising-Simons Foundation; UCSC; Alfred P. Sloan Foundation; David and Lucile Packard Foundation; European Research Council [ERC-StG-335936]; Gordon and Betty Moore Foundation [GBMF5076]; DOE (USA); NSF (USA); MISE (Spain); STFC (UK); HEFCE (UK); NCSA (UIUC); KICP (U. Chicago); CCAPP (Ohio State); MIFPA (Texas AM); MINECO (Spain); DFG (Germany); CNPQ (Brazil); FAPERJ (Brazil); FINEP (Brazil); Argonne Lab; UC Santa Cruz; University of Cambridge; CIEMAT-Madrid; University of Chicago; University College London; DES-Brazil Consortium; University of Edinburgh; ETH Zurich; Fermilab; University of Illinois; ICE (IEEC-CSIC); IFAE Barcelona; Lawrence Berkeley Lab; LMU Munchen; Excellence Cluster Universe; University of Michigan; NOAO; University of Nottingham; Ohio State University; University of Pennsylvania; University of Portsmouth; SLAC National Lab; Stanford University; University of Sussex; Texas AM University; Gemini Observatory [GS-2017B-Q-8, GS-2017B-DD-4]
TL;DR: The properties of LADs, the molecular mechanisms that determine their association with the nuclear lamina, their dynamic links with other nuclear compartments, and their proposed roles in gene regulation are discussed.
TL;DR: The description of energy transfer, in particular multichromophoric antenna structures, is shown to vary depending on the spatial and energetic landscape, which dictates the relative coupling strength between constituent pigment molecules.
Abstract: The process of photosynthesis is initiated by the capture of sunlight by a network of light-absorbing molecules (chromophores), which are also responsible for the subsequent funneling of the excitation energy to the reaction centers. Through evolution, genetic drift, and speciation, photosynthetic organisms have discovered many solutions for light harvesting. In this review, we describe the underlying photophysical principles by which this energy is absorbed, as well as the mechanisms of electronic excitation energy transfer (EET). First, optical properties of the individual pigment chromophores present in light-harvesting antenna complexes are introduced, and then we examine the collective behavior of pigment−pigment and pigment−protein interactions. The description of energy transfer, in particular multichromophoric antenna structures, is shown to vary depending on the spatial and energetic landscape, which dictates the relative coupling strength between constituent pigment molecules. In the latter half...