Showing papers by "University of Waterloo published in 2019"

An Introduction to Kolmogorov Complexity and Its Applications

Abstract: The book is outstanding and admirable in many respects. ... is necessary reading for all kinds of readers from undergraduate students to top authorities in the field. Journal of Symbolic Logic Written by two experts in the field, this is the only comprehensive and unified treatment of the central ideas and their applications of Kolmogorov complexity. The book presents a thorough treatment of the subject with a wide range of illustrative applications. Such applications include the randomness of finite objects or infinite sequences, Martin-Loef tests for randomness, information theory, computational learning theory, the complexity of algorithms, and the thermodynamics of computing. It will be ideal for advanced undergraduate students, graduate students, and researchers in computer science, mathematics, cognitive sciences, philosophy, artificial intelligence, statistics, and physics. The book is self-contained in that it contains the basic requirements from mathematics and computer science. Included are also numerous problem sets, comments, source references, and hints to solutions of problems. New topics in this edition include Omega numbers, KolmogorovLoveland randomness, universal learning, communication complexity, Kolmogorov's random graphs, time-limited universal distribution, Shannon information and others.

First M87 Event Horizon Telescope Results. I. The Shadow of the Supermassive Black Hole

Abstract: When surrounded by a transparent emission region, black holes are expected to reveal a dark shadow caused by gravitational light bending and photon capture at the event horizon. To image and study this phenomenon, we have assembled the Event Horizon Telescope, a global very long baseline interferometry array observing at a wavelength of 1.3 mm. This allows us to reconstruct event-horizon-scale images of the supermassive black hole candidate in the center of the giant elliptical galaxy M87. We have resolved the central compact radio source as an asymmetric bright emission ring with a diameter of 42 +/- 3 mu as, which is circular and encompasses a central depression in brightness with a flux ratio greater than or similar to 10: 1. The emission ring is recovered using different calibration and imaging schemes, with its diameter and width remaining stable over four different observations carried out in different days. Overall, the observed image is consistent with expectations for the shadow of a Kerr black hole as predicted by general relativity. The asymmetry in brightness in the ring can be explained in terms of relativistic beaming of the emission from a plasma rotating close to the speed of light around a black hole. We compare our images to an extensive library of ray-traced general-relativistic magnetohydrodynamic simulations of black holes and derive a central mass of M = (6.5 +/- 0.7) x 10(9) M-circle dot. Our radio-wave observations thus provide powerful evidence for the presence of supermassive black holes in centers of galaxies and as the central engines of active galactic nuclei. They also present a new tool to explore gravity in its most extreme limit and on a mass scale that was so far not accessible.

First M87 Event Horizon Telescope Results. VI. The Shadow and Mass of the Central Black Hole

Abstract: We present measurements of the properties of the central radio source in M87 using Event Horizon Telescope data obtained during the 2017 campaign. We develop and fit geometric crescent models (asymmetric rings with interior brightness depressions) using two independent sampling algorithms that consider distinct representations of the visibility data. We show that the crescent family of models is statistically preferred over other comparably complex geometric models that we explore. We calibrate the geometric model parameters using general relativistic magnetohydrodynamic (GRMHD) models of the emission region and estimate physical properties of the source. We further fit images generated from GRMHD models directly to the data. We compare the derived emission region and black hole parameters from these analyses with those recovered from reconstructed images. There is a remarkable consistency among all methods and data sets. We find that >50% of the total flux at arcsecond scales comes from near the horizon, and that the emission is dramatically suppressed interior to this region by a factor >10, providing direct evidence of the predicted shadow of a black hole. Across all methods, we measure a crescent diameter of 42 ± 3 μas and constrain its fractional width to be <0.5. Associating the crescent feature with the emission surrounding the black hole shadow, we infer an angular gravitational radius of GM/Dc2 = 3.8 ± 0.4 μas. Folding in a distance measurement of ${16.8}_{-0.7}^{+0.8}\,\mathrm{Mpc}$ gives a black hole mass of $M=6.5\pm 0.2{| }_{\mathrm{stat}}\pm 0.7{| }_{\mathrm{sys}}\times {10}^{9}\hspace{2pt}{M}_{\odot }$. This measurement from lensed emission near the event horizon is consistent with the presence of a central Kerr black hole, as predicted by the general theory of relativity.

First M87 Event Horizon Telescope Results. IV. Imaging the Central Supermassive Black Hole

Abstract: We present the first Event Horizon Telescope (EHT) images of M87, using observations from April 2017 at 1.3 mm wavelength. These images show a prominent ring with a diameter of ~40 μas, consistent with the size and shape of the lensed photon orbit encircling the "shadow" of a supermassive black hole. The ring is persistent across four observing nights and shows enhanced brightness in the south. To assess the reliability of these results, we implemented a two-stage imaging procedure. In the first stage, four teams, each blind to the others' work, produced images of M87 using both an established method (CLEAN) and a newer technique (regularized maximum likelihood). This stage allowed us to avoid shared human bias and to assess common features among independent reconstructions. In the second stage, we reconstructed synthetic data from a large survey of imaging parameters and then compared the results with the corresponding ground truth images. This stage allowed us to select parameters objectively to use when reconstructing images of M87. Across all tests in both stages, the ring diameter and asymmetry remained stable, insensitive to the choice of imaging technique. We describe the EHT imaging procedures, the primary image features in M87, and the dependence of these features on imaging assumptions.

Quantum Chemistry in the Age of Quantum Computing.

Abstract: Practical challenges in simulating quantum systems on classical computers have been widely recognized in the quantum physics and quantum chemistry communities over the past century. Although many approximation methods have been introduced, the complexity of quantum mechanics remains hard to appease. The advent of quantum computation brings new pathways to navigate this challenging and complex landscape. By manipulating quantum states of matter and taking advantage of their unique features such as superposition and entanglement, quantum computers promise to efficiently deliver accurate results for many important problems in quantum chemistry, such as the electronic structure of molecules. In the past two decades, significant advances have been made in developing algorithms and physical hardware for quantum computing, heralding a revolution in simulation of quantum systems. This Review provides an overview of the algorithms and results that are relevant for quantum chemistry. The intended audience is both quantum chemists who seek to learn more about quantum computing and quantum computing researchers who would like to explore applications in quantum chemistry.

GLIM Criteria for the Diagnosis of Malnutrition: A Consensus Report From the Global Clinical Nutrition Community

Abstract: Summary Rationale This initiative is focused on building a global consensus around core diagnostic criteria for malnutrition in adults in clinical settings Methods In January 2016, the Global Leadership Initiative on Malnutrition (GLIM) was convened by several of the major global clinical nutrition societies GLIM appointed a core leadership committee and a supporting working group with representatives bringing additional global diversity and expertise Empirical consensus was reached through a series of face-to-face meetings, telephone conferences, and e-mail communications Results A two-step approach for the malnutrition diagnosis was selected, ie, first screening to identify “at risk” status by the use of any validated screening tool, and second, assessment for diagnosis and grading the severity of malnutrition The malnutrition criteria for consideration were retrieved from existing approaches for screening and assessment Potential criteria were subjected to a ballot among the GLIM core and supporting working group members The top five ranked criteria included three phenotypic criteria (non-volitional weight loss, low body mass index, and reduced muscle mass) and two etiologic criteria (reduced food intake or assimilation, and inflammation or disease burden) To diagnose malnutrition at least one phenotypic criterion and one etiologic criterion should be present Phenotypic metrics for grading severity as Stage 1 (moderate) and Stage 2 (severe) malnutrition are proposed It is recommended that the etiologic criteria be used to guide intervention and anticipated outcomes The recommended approach supports classification of malnutrition into four etiology-related diagnosis categories Conclusion A consensus scheme for diagnosing malnutrition in adults in clinical settings on a global scale is proposed Next steps are to secure further collaboration and endorsements from leading nutrition professional societies, to identify overlaps with syndromes like cachexia and sarcopenia, and to promote dissemination, validation studies, and feedback The diagnostic construct should be re-considered every 3–5 years

GLIM criteria for the diagnosis of malnutrition - A consensus report from the global clinical nutrition community.

Abstract: Rationale This initiative is focused on building a global consensus around core diagnostic criteria for malnutrition in adults in clinical settings.

First M87 Event Horizon Telescope Results. V. Physical Origin of the Asymmetric Ring

Abstract: The Event Horizon Telescope (EHT) has mapped the central compact radio source of the elliptical galaxy M87 at 1.3 mm with unprecedented angular resolution. Here we consider the physical implications of the asymmetric ring seen in the 2017 EHT data. To this end, we construct a large library of models based on general relativistic magnetohydrodynamic (GRMHD) simulations and synthetic images produced by general relativistic ray tracing. We compare the observed visibilities with this library and confirm that the asymmetric ring is consistent with earlier predictions of strong gravitational lensing of synchrotron emission from a hot plasma orbiting near the black hole event horizon. The ring radius and ring asymmetry depend on black hole mass and spin, respectively, and both are therefore expected to be stable when observed in future EHT campaigns. Overall, the observed image is consistent with expectations for the shadow of a spinning Kerr black hole as predicted by general relativity. If the black hole spin and M87's large scale jet are aligned, then the black hole spin vector is pointed away from Earth. Models in our library of non-spinning black holes are inconsistent with the observations as they do not produce sufficiently powerful jets. At the same time, in those models that produce a sufficiently powerful jet, the latter is powered by extraction of black hole spin energy through mechanisms akin to the Blandford-Znajek process. We briefly consider alternatives to a black hole for the central compact object. Analysis of existing EHT polarization data and data taken simultaneously at other wavelengths will soon enable new tests of the GRMHD models, as will future EHT campaigns at 230 and 345 GHz.

First M87 Event Horizon Telescope Results. II. Array and Instrumentation

Abstract: The Event Horizon Telescope (EHT) is a very long baseline interferometry (VLBI) array that comprises millimeter- and submillimeter-wavelength telescopes separated by distances comparable to the diameter of the Earth. At a nominal operating wavelength of ~1.3 mm, EHT angular resolution (λ/D) is ~25 μas, which is sufficient to resolve nearby supermassive black hole candidates on spatial and temporal scales that correspond to their event horizons. With this capability, the EHT scientific goals are to probe general relativistic effects in the strong-field regime and to study accretion and relativistic jet formation near the black hole boundary. In this Letter we describe the system design of the EHT, detail the technology and instrumentation that enable observations, and provide measures of its performance. Meeting the EHT science objectives has required several key developments that have facilitated the robust extension of the VLBI technique to EHT observing wavelengths and the production of instrumentation that can be deployed on a heterogeneous array of existing telescopes and facilities. To meet sensitivity requirements, high-bandwidth digital systems were developed that process data at rates of 64 gigabit s^(−1), exceeding those of currently operating cm-wavelength VLBI arrays by more than an order of magnitude. Associated improvements include the development of phasing systems at array facilities, new receiver installation at several sites, and the deployment of hydrogen maser frequency standards to ensure coherent data capture across the array. These efforts led to the coordination and execution of the first Global EHT observations in 2017 April, and to event-horizon-scale imaging of the supermassive black hole candidate in M87.

Automotive Li-Ion Batteries: Current Status and Future Perspectives

Abstract: Lithium-ion batteries (LIBs) are currently the most suitable energy storage device for powering electric vehicles (EVs) owing to their attractive properties including high energy efficiency, lack of memory effect, long cycle life, high energy density and high power density. These advantages allow them to be smaller and lighter than other conventional rechargeable batteries such as lead–acid batteries, nickel–cadmium batteries (Ni–Cd) and nickel–metal hydride batteries (Ni–MH). Modern EVs, however, still suffer from performance barriers (range, charging rate, lifetime, etc.) and technological barriers (high cost, safety, reliability, etc.), limiting their widespread adoption. Given these facts, this review sets the extensive market penetration of LIB-powered EVs as an ultimate objective and then discusses recent advances and challenges of electric automobiles, mainly focusing on critical element resources, present and future EV markets, and the cost and performance of LIBs. Finally, novel battery chemistries and technologies including high-energy electrode materials and all-solid-state batteries are also evaluated for their potential capabilities in next-generation long-range EVs.

First M87 Event Horizon Telescope Results. III. Data Processing and Calibration

Abstract: We present the calibration and reduction of Event Horizon Telescope (EHT) 1.3 mm radio wavelength observations of the supermassive black hole candidate at the center of the radio galaxy M87 and the quasar 3C 279, taken during the 2017 April 5–11 observing campaign. These global very long baseline interferometric observations include for the first time the highly sensitive Atacama Large Millimeter/submillimeter Array (ALMA); reaching an angular resolution of 25 μas, with characteristic sensitivity limits of ~1 mJy on baselines to ALMA and ~10 mJy on other baselines. The observations present challenges for existing data processing tools, arising from the rapid atmospheric phase fluctuations, wide recording bandwidth, and highly heterogeneous array. In response, we developed three independent pipelines for phase calibration and fringe detection, each tailored to the specific needs of the EHT. The final data products include calibrated total intensity amplitude and phase information. They are validated through a series of quality assurance tests that show consistency across pipelines and set limits on baseline systematic errors of 2% in amplitude and 1° in phase. The M87 data reveal the presence of two nulls in correlated flux density at ~3.4 and ~8.3 Gλ and temporal evolution in closure quantities, indicating intrinsic variability of compact structure on a timescale of days, or several light-crossing times for a few billion solar-mass black hole. These measurements provide the first opportunity to image horizon-scale structure in M87.

Space/Aerial-Assisted Computing Offloading for IoT Applications: A Learning-Based Approach

Abstract: Internet of Things (IoT) computing offloading is a challenging issue, especially in remote areas where common edge/cloud infrastructure is unavailable. In this paper, we present a space-air-ground integrated network (SAGIN) edge/cloud computing architecture for offloading the computation-intensive applications considering remote energy and computation constraints, where flying unmanned aerial vehicles (UAVs) provide near-user edge computing and satellites provide access to the cloud computing. First, for UAV edge servers, we propose a joint resource allocation and task scheduling approach to efficiently allocate the computing resources to virtual machines (VMs) and schedule the offloaded tasks. Second, we investigate the computing offloading problem in SAGIN and propose a learning-based approach to learn the optimal offloading policy from the dynamic SAGIN environments. Specifically, we formulate the offloading decision making as a Markov decision process where the system state considers the network dynamics. To cope with the system dynamics and complexity, we propose a deep reinforcement learning-based computing offloading approach to learn the optimal offloading policy on-the-fly, where we adopt the policy gradient method to handle the large action space and actor-critic method to accelerate the learning process. Simulation results show that the proposed edge VM allocation and task scheduling approach can achieve near-optimal performance with very low complexity and the proposed learning-based computing offloading algorithm not only converges fast but also achieves a lower total cost compared with other offloading approaches.

Long cycle life and dendrite-free lithium morphology in anode-free lithium pouch cells enabled by a dual-salt liquid electrolyte

Abstract: Cells with lithium-metal anodes are viewed as the most viable future technology, with higher energy density than existing lithium-ion batteries. Many researchers believe that for lithium-metal cells, the typical liquid electrolyte used in lithium-ion batteries must be replaced with a solid-state electrolyte to maintain the flat, dendrite-free lithium morphologies necessary for long-term stable cycling. Here, we show that anode-free lithium-metal pouch cells with a dual-salt LiDFOB/LiBF4 liquid electrolyte have 80% capacity remaining after 90 charge–discharge cycles, which is the longest life demonstrated to date for cells with zero excess lithium. The liquid electrolyte enables smooth dendrite-free lithium morphology comprised of densely packed columns even after 50 charge–discharge cycles. NMR measurements reveal that the electrolyte salts responsible for the excellent lithium morphology are slowly consumed during cycling. Extensive efforts have recently been geared towards developing all-solid-state batteries largely because of their potential to enable high-energy-density Li anodes. Here, the authors report a high-performance lithium pouch cell with no excess lithium, enabled by just a dual-salt liquid electrolyte.

Atomic and electronic reconstruction at the van der Waals interface in twisted bilayer graphene

Abstract: Control of the interlayer twist angle in two-dimensional van der Waals (vdW) heterostructures enables one to engineer a quasiperiodic moire superlattice of tunable length scale1–8. In twisted bilayer graphene, the simple moire superlattice band description suggests that the electronic bandwidth can be tuned to be comparable to the vdW interlayer interaction at a ‘magic angle’9, exhibiting strongly correlated behaviour. However, the vdW interlayer interaction can also cause significant structural reconstruction at the interface by favouring interlayer commensurability, which competes with the intralayer lattice distortion10–16. Here we report atomic-scale reconstruction in twisted bilayer graphene and its effect on the electronic structure. We find a gradual transition from an incommensurate moire structure to an array of commensurate domains with soliton boundaries as we decrease the twist angle across the characteristic crossover angle, θc ≈ 1°. In the solitonic regime (θ < θc) where the atomic and electronic reconstruction become significant, a simple moire band description breaks down and the secondary Dirac bands appear. On applying a transverse electric field, we observe electronic transport along the network of one-dimensional topological channels that surround the alternating triangular gapped domains. Atomic and electronic reconstruction at the vdW interface provide a new pathway to engineer the system with continuous tunability. An investigation of the structural and transport properties of bilayer graphene as a function of the twist angle between the layers reveals atomic-scale reconstruction for twist angles smaller than a critical value.

Earthquake-Induced Chains of Geologic Hazards: Patterns, Mechanisms, and Impacts

Abstract: Large earthquakes initiate chains of surface processes that last much longer than the brief moments of strong shaking. Most moderate‐ and large‐magnitude earthquakes trigger landslides, ranging from small failures in the soil cover to massive, devastating rock avalanches. Some landslides dam rivers and impound lakes, which can collapse days to centuries later, and flood mountain valleys for hundreds of kilometers downstream. Landslide deposits on slopes can remobilize during heavy rainfall and evolve into debris flows. Cracks and fractures can form and widen on mountain crests and flanks, promoting increased frequency of landslides that lasts for decades. More gradual impacts involve the flushing of excess debris downstream by rivers, which can generate bank erosion and floodplain accretion as well as channel avulsions that affect flooding frequency, settlements, ecosystems, and infrastructure. Ultimately, earthquake sequences and their geomorphic consequences alter mountain landscapes over both human and geologic time scales. Two recent events have attracted intense research into earthquake‐induced landslides and their consequences: the magnitude M 7.6 Chi‐Chi, Taiwan earthquake of 1999, and the M 7.9 Wenchuan, China earthquake of 2008. Using data and insights from these and several other earthquakes, we analyze how such events initiate processes that change mountain landscapes, highlight research gaps, and suggest pathways toward a more complete understanding of the seismic effects on the Earth's surface.

Study of energy storage systems and environmental challenges of batteries

Abstract: As more renewable energy is developed, energy storage is increasingly important and attractive, especially grid-scale electrical energy storage; hence, finding and implementing cost-effective and sustainable energy storage and conversion systems is vital. Batteries of various types and sizes are considered one of the most suitable approaches to store energy and extensive research exists for different technologies and applications of batteries; however, environmental impacts of large-scale battery use remain a major challenge that requires further study. In this paper, batteries from various aspects including design features, advantages, disadvantages, and environmental impacts are assessed. This review reaffirms that batteries are efficient, convenient, reliable and easy-to-use energy storage systems (ESSs). It also confirms that battery shelf life and use life are limited; a large amount and wide range of raw materials, including metals and non-metals, are used to produce batteries; and, the battery industry can generate considerable amounts of environmental pollutants (e.g., hazardous waste, greenhouse gas emissions and toxic gases) during different processes such as mining, manufacturing, use, transportation, collection, storage, treatment, disposal and recycling. Battery use at a large scale or grid-scale (>50 MW), which is widely anticipated, will have significant social and environmental impacts; hence, it must be compared carefully with alternatives in terms of sustainability, while focusing on research to quantify externalities and reduce risk. Alternatives such as pumped hydro and compressed air energy storage must be encouraged because of their low environmental impact compared to different types of batteries.

Meta-omics analysis of elite athletes identifies a performance-enhancing microbe that functions via lactate metabolism.

Abstract: The human gut microbiome is linked to many states of human health and disease1. The metabolic repertoire of the gut microbiome is vast, but the health implications of these bacterial pathways are poorly understood. In this study, we identify a link between members of the genus Veillonella and exercise performance. We observed an increase in Veillonella relative abundance in marathon runners postmarathon and isolated a strain of Veillonella atypica from stool samples. Inoculation of this strain into mice significantly increased exhaustive treadmill run time. Veillonella utilize lactate as their sole carbon source, which prompted us to perform a shotgun metagenomic analysis in a cohort of elite athletes, finding that every gene in a major pathway metabolizing lactate to propionate is at higher relative abundance postexercise. Using 13C3-labeled lactate in mice, we demonstrate that serum lactate crosses the epithelial barrier into the lumen of the gut. We also show that intrarectal instillation of propionate is sufficient to reproduce the increased treadmill run time performance observed with V. atypica gavage. Taken together, these studies reveal that V. atypica improves run time via its metabolic conversion of exercise-induced lactate into propionate, thereby identifying a natural, microbiome-encoded enzymatic process that enhances athletic performance.

Presence and Cybersickness in Virtual Reality Are Negatively Related: A Review

Abstract: In order to take advantage of the potential offered by the medium of virtual reality (VR), it will be essential to develop an understanding of how to maximize the desirable experience of "presence" in a virtual space ("being there"), and how to minimize the undesirable feeling of "cybersickness" (a constellation of discomfort symptoms experienced in VR). Although there have been frequent reports of a possible link between the observer's sense of presence and the experience of bodily discomfort in VR, the amount of literature that discusses the nature of the relationship is limited. Recent research has underlined the possibility that these variables have shared causes, and that both factors may be manipulated with a single approach. This review paper summarizes the concepts of presence and cybersickness and highlights the strengths and gaps in our understanding about their relationship. We review studies that have measured the association between presence and cybersickness, and conclude that the balance of evidence favors a negative relationship between the two factors which is driven principally by sensory integration processes. We also discuss how system immersiveness might play a role in modulating both presence and cybersickness. However, we identify a serious absence of high-powered studies that aim to reveal the nature of this relationship. Based on this evidence we propose recommendations for future studies investigating presence, cybersickness, and other related factors.

Learning-Based Computation Offloading for IoT Devices With Energy Harvesting

Abstract: Internet of Things (IoT) devices can apply mobile edge computing (MEC) and energy harvesting (EH) to provide high-level experiences for computational intensive applications and concurrently to prolong the lifetime of the battery. In this paper, we propose a reinforcement learning (RL) based offloading scheme for an IoT device with EH to select the edge device and the offloading rate according to the current battery level, the previous radio transmission rate to each edge device, and the predicted amount of the harvested energy. This scheme enables the IoT device to optimize the offloading policy without knowledge of the MEC model, the energy consumption model, and the computation latency model. Further, we present a deep RL-based offloading scheme to further accelerate the learning speed. Their performance bounds in terms of the energy consumption, computation latency, and utility are provided for three typical offloading scenarios and verified via simulations for an IoT device that uses wireless power transfer for energy harvesting. Simulation results show that the proposed RL-based offloading scheme reduces the energy consumption, computation latency, and task drop rate, and thus increases the utility of the IoT device in the dynamic MEC in comparison with the benchmark offloading schemes.

Gated-SCNN: Gated Shape CNNs for Semantic Segmentation

Abstract: Current state-of-the-art methods for image segmentation form a dense image representation where the color, shape and texture information are all processed together inside a deep CNN. This however may not be ideal as they contain very different type of information relevant for recognition. Here, we propose a new two-stream CNN architecture for semantic segmentation that explicitly wires shape information as a separate processing branch, i.e. shape stream, that processes information in parallel to the classical stream. Key to this architecture is a new type of gates that connect the intermediate layers of the two streams. Specifically, we use the higher-level activations in the classical stream to gate the lower-level activations in the shape stream, effectively removing noise and helping the shape stream to only focus on processing the relevant boundary-related information. This enables us to use a very shallow architecture for the shape stream that operates on the image-level resolution. Our experiments show that this leads to a highly effective architecture that produces sharper predictions around object boundaries and significantly boosts performance on thinner and smaller objects. Our method achieves state-of-the-art performance on the Cityscapes benchmark, in terms of both mask (mIoU) and boundary (F-score) quality, improving by 2% and 4% over strong baselines.

Bridging the academic and industrial metrics for next-generation practical batteries.

Abstract: Batteries have shaped much of our modern world. This success is the result of intense collaboration between academia and industry over the past several decades, culminating with the advent of and improvements in rechargeable lithium-ion batteries. As applications become more demanding, there is the risk that stunted growth in the performance of commercial batteries will slow the adoption of important technologies such as electric vehicles. Yet the scientific literature includes many reports describing material designs with allegedly superior performance. A considerable gap needs to be filled if we wish these laboratory-based achievements to reach commercialization. In this Perspective, we discuss some of the most relevant testing parameters that are often overlooked in academic literature but are critical for practical applicability outside the laboratory. We explain metrics such as anode energy density, voltage hysteresis, mass of non-active cell components and anode/cathode mass ratio, and we make recommendations for future reporting. We hope that this Perspective, together with other similar guiding principles that have recently started to emerge, will aid the transition from lab-scale research to next-generation practical batteries. This Perspective discussed the best practices for reporting lab-scale performance metrics in battery papers.

Recent Progress in Electrically Rechargeable Zinc–Air Batteries

Abstract: Over the past decade, the surging interest for higher-energy-density, cheaper, and safer battery technology has spurred tremendous research efforts in the development of improved rechargeable zinc-air batteries. Current zinc-air batteries suffer from poor energy efficiency and cycle life, owing mainly to the poor rechargeability of zinc and air electrodes. To achieve high utilization and cyclability in the zinc anode, construction of conductive porous framework through elegant optimization strategies and adaptation of alternate active material are employed. Equally, there is a need to design new and improved bifunctional oxygen catalysts with high activity and stability to increase battery energy efficiency and lifetime. Efforts to engineer catalyst materials to increase the reactivity and/or number of bifunctional active sites are effective for improving air electrode performance. Here, recent key advances in material development for rechargeable zinc-air batteries are described. By improving fundamental understanding of materials properties relevant to the rechargeable zinc and air electrodes, zinc-air batteries will be able to make a significant impact on the future energy storage for electric vehicle application. To conclude, a brief discussion on noteworthy concepts of advanced electrode and electrolyte systems that are beyond the current state-of-the-art zinc-air battery chemistry, is presented.

End-to-End Open-Domain Question Answering with BERTserini

Abstract: We demonstrate an end-to-end question answering system that integrates BERT with the open-source Anserini information retrieval toolkit. In contrast to most question answering and reading comprehension models today, which operate over small amounts of input text, our system integrates best practices from IR with a BERT-based reader to identify answers from a large corpus of Wikipedia articles in an end-to-end fashion. We report large improvements over previous results on a standard benchmark test collection, showing that fine-tuning pretrained BERT with SQuAD is sufficient to achieve high accuracy in identifying answer spans.

Circular RNA in cardiovascular disease

Abstract: Circular RNA (circRNA) are endogenous transcripts that display differential expression across species, developmental stages, and pathologies. Their lack of free ends confers increased stability when compared with linear transcripts, making them ideal candidates for future diagnostic biomarkers and therapeutic interventions. Increasing evidence has implicated circRNA in the pathogenesis of multiple cardiovascular diseases. In this paper, we summarize current understanding of circRNA biogenesis, properties, expression profiles, detection methods, functions, and their implication in cardiac pathologies including/ischemia reperfusion injury, myocardial infarction, cardiac senescence, cardiac fibrosis, cardiomyopathy, cardiac hypertrophy and heart failure, atherosclerosis, coronary artery disease, and aneurysm.

Simple BERT Models for Relation Extraction and Semantic Role Labeling.

Abstract: We present simple BERT-based models for relation extraction and semantic role labeling. In recent years, state-of-the-art performance has been achieved using neural models by incorporating lexical and syntactic features such as part-of-speech tags and dependency trees. In this paper, extensive experiments on datasets for these two tasks show that without using any external features, a simple BERT-based model can achieve state-of-the-art performance. To our knowledge, we are the first to successfully apply BERT in this manner. Our models provide strong baselines for future research.