Showing papers by "Australian National University published in 2021"
University of Southern California1, French Institute for Research in Computer Science and Automation2, University of Oulu3, Princeton University4, University of Warwick5, Georgia Institute of Technology6, Rutgers University7, University of Virginia8, University of Washington9, Carnegie Mellon University10, École Polytechnique Fédérale de Lausanne11, University of Pittsburgh12, University of Wisconsin-Madison13, University of California, San Diego14, University of Illinois at Urbana–Champaign15, Nanyang Technological University16, Australian National University17, Stanford University18, IT University of Copenhagen19, Massachusetts Institute of Technology20, University of California, Berkeley21, Cornell University22, Emory University23, Hong Kong University of Science and Technology24
TL;DR: In this article, the authors describe the state-of-the-art in the field of federated learning from the perspective of distributed optimization, cryptography, security, differential privacy, fairness, compressed sensing, systems, information theory, and statistics.
Abstract: The term Federated Learning was coined as recently as 2016 to describe a machine learning setting where multiple entities collaborate in solving a machine learning problem, under the coordination of a central server or service provider. Each client’s raw data is stored locally and not exchanged or transferred; instead, focused updates intended for immediate aggregation are used to achieve the learning objective. Since then, the topic has gathered much interest across many different disciplines and the realization that solving many of these interdisciplinary problems likely requires not just machine learning but techniques from distributed optimization, cryptography, security, differential privacy, fairness, compressed sensing, systems, information theory, statistics, and more. This monograph has contributions from leading experts across the disciplines, who describe the latest state-of-the art from their perspective. These contributions have been carefully curated into a comprehensive treatment that enables the reader to understand the work that has been done and get pointers to where effort is required to solve many of the problems before Federated Learning can become a reality in practical systems. Researchers working in the area of distributed systems will find this monograph an enlightening read that may inspire them to work on the many challenging issues that are outlined. This monograph will get the reader up to speed quickly and easily on what is likely to become an increasingly important topic: Federated Learning.
2,144 citations
TL;DR: A comprehensive review of deep learning-based image segmentation can be found in this article, where the authors investigate the relationships, strengths, and challenges of these DL-based models, examine the widely used datasets, compare performances, and discuss promising research directions.
Abstract: Image segmentation is a key task in computer vision and image processing with important applications such as scene understanding, medical image analysis, robotic perception, video surveillance, augmented reality, and image compression, among others, and numerous segmentation algorithms are found in the literature. Against this backdrop, the broad success of Deep Learning (DL) has prompted the development of new image segmentation approaches leveraging DL models. We provide a comprehensive review of this recent literature, covering the spectrum of pioneering efforts in semantic and instance segmentation, including convolutional pixel-labeling networks, encoder-decoder architectures, multiscale and pyramid-based approaches, recurrent networks, visual attention models, and generative models in adversarial settings. We investigate the relationships, strengths, and challenges of these DL-based segmentation models, examine the widely used datasets, compare performances, and discuss promising research directions.
827 citations
University of Oxford1, Australian National University2, Harvard University3, University of Bristol4, University of Manchester5, London School of Economics and Political Science6, University of London7, University of Cambridge8, Tufts University9, Imperial College London10, Medical Research Council11
TL;DR: The results indicate that, by using effective interventions, some countries could control the epidemic while avoiding stay-at-home orders, and this model accounts for uncertainty in key epidemiological parameters, such as the average delay from infection to death.
Abstract: Governments are attempting to control the COVID-19 pandemic with nonpharmaceutical interventions (NPIs). However, the effectiveness of different NPIs at reducing transmission is poorly understood. We gathered chronological data on the implementation of NPIs for several European, and other, countries between January and the end of May 2020. We estimate the effectiveness of NPIs, ranging from limiting gathering sizes, business closures, and closure of educational institutions to stay-at-home orders. To do so, we used a Bayesian hierarchical model that links NPI implementation dates to national case and death counts and supported the results with extensive empirical validation. Closing all educational institutions, limiting gatherings to 10 people or less, and closing face-to-face businesses each reduced transmission considerably. The additional effect of stay-at-home orders was comparatively small.
674 citations
TL;DR: In this article, the population of 47 compact binary mergers detected with a false-alarm rate of 0.614 were dynamically assembled, and the authors found that the BBH rate likely increases with redshift, but not faster than the star formation rate.
Abstract: We report on the population of 47 compact binary mergers detected with a false-alarm rate of 0.01 are dynamically assembled. Third, we estimate merger rates, finding RBBH = 23.9-+8.614.3 Gpc-3 yr-1 for BBHs and RBNS = 320-+240490 Gpc-3 yr-1 for binary neutron stars. We find that the BBH rate likely increases with redshift (85% credibility) but not faster than the star formation rate (86% credibility). Additionally, we examine recent exceptional events in the context of our population models, finding that the asymmetric masses of GW190412 and the high component masses of GW190521 are consistent with our models, but the low secondary mass of GW190814 makes it an outlier.
468 citations
Centre for Mental Health1, Swansea University2, University of Sydney3, University of Manchester4, Griffith University5, University College Cork6, Stellenbosch University7, Sao Paulo State University8, University of Zagreb9, University of Rochester Medical Center10, University of Udine11, National Taiwan University12, Innsbruck Medical University13, Yale University14, Johns Hopkins University15, Australian National University16, Brigham and Women's Hospital17, University of Auckland18, Hobart Corporation19, Columbia University Medical Center20, University of Oxford21, National Institute for Health Research22, Aga Khan University23, Katholieke Universiteit Leuven24, University of Bristol25, University of Peradeniya26, World Health Organization27, Karolinska Institutet28, First Pavlov State Medical University of St. Peterburg29, Medical University of Vienna30, University of Nottingham31, University of Glasgow32, University of Edinburgh33, Shanghai Jiao Tong University34, Columbia University35, University of Ulm36, University of Oslo37, Goethe University Frankfurt38, Saint Petersburg State University39, Sunnybrook Health Sciences Centre40, University of Toronto41, Waseda University42, Rajarata University of Sri Lanka43, Tel Aviv University44, University Hospitals Bristol NHS Foundation Trust45
TL;DR: In this article, the early effect of the COVID-19 pandemic on suicide rates around the world was assessed using real-time suicide data from countries or areas within countries through a systematic internet search and recourse to our networks and the published literature.
413 citations
TL;DR: In this article, the authors reported the observation of gravitational waves from two compact binary coalescences in LIGO's and Virgo's third observing run with properties consistent with neutron star-black hole (NSBH) binaries.
Abstract: We report the observation of gravitational waves from two compact binary coalescences in LIGO’s and Virgo’s third observing run with properties consistent with neutron star–black hole (NSBH) binaries. The two events are named GW200105_162426 and GW200115_042309, abbreviated as GW200105 and GW200115; the first was observed by LIGO Livingston and Virgo and the second by all three LIGO–Virgo detectors. The source of GW200105 has component masses 8.9−1.5+1.2 and 1.9−0.2+0.3M⊙ , whereas the source of GW200115 has component masses 5.7−2.1+1.8 and 1.5−0.3+0.7M⊙ (all measurements quoted at the 90% credible level). The probability that the secondary’s mass is below the maximal mass of a neutron star is 89%–96% and 87%–98%, respectively, for GW200105 and GW200115, with the ranges arising from different astrophysical assumptions. The source luminosity distances are 280−110+110 and 300−100+150Mpc , respectively. The magnitude of the primary spin of GW200105 is less than 0.23 at the 90% credible level, and its orientation is unconstrained. For GW200115, the primary spin has a negative spin projection onto the orbital angular momentum at 88% probability. We are unable to constrain the spin or tidal deformation of the secondary component for either event. We infer an NSBH merger rate density of 45−33+75Gpc−3yr−1 when assuming that GW200105 and GW200115 are representative of the NSBH population or 130−69+112Gpc−3yr−1 under the assumption of a broader distribution of component masses.
374 citations
Evgeny Epifanovsky, Andrew T.B. Gilbert1, Andrew T.B. Gilbert2, Xintian Feng3 +235 more•Institutions (54)
TL;DR: The Q-Chem quantum chemistry program package as discussed by the authors provides a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, and methods for computing vibronic spectra, the nuclear-electronic orbital method, and several different energy decomposition analysis techniques.
Abstract: This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange-correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear-electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an "open teamware" model and an increasingly modular design.
360 citations
TL;DR: In this article, the authors reviewed COVID-19 responses in 28 countries using a new health systems resilience framework, and synthesize four salient elements that underlie highly effective national responses and offer recommendations toward strengthening health system resilience globally.
Abstract: Health systems resilience is key to learning lessons from country responses to crises such as coronavirus disease 2019 (COVID-19). In this perspective, we review COVID-19 responses in 28 countries using a new health systems resilience framework. Through a combination of literature review, national government submissions and interviews with experts, we conducted a comparative analysis of national responses. We report on domains addressing governance and financing, health workforce, medical products and technologies, public health functions, health service delivery and community engagement to prevent and mitigate the spread of COVID-19. We then synthesize four salient elements that underlie highly effective national responses and offer recommendations toward strengthening health systems resilience globally.
336 citations
TL;DR: The data recorded by these instruments during their first and second observing runs are described, including the gravitational-wave strain arrays, released as time series sampled at 16384 Hz.
320 citations
University of Edinburgh1, Ruhr University Bochum2, Swinburne University of Technology3, University College London4, Leiden University5, Max Planck Society6, Stanford University7, Polish Academy of Sciences8, Kapteyn Astronomical Institute9, Spanish National Research Council10, University of Bonn11, Astronomical Observatory of Capodimonte12, University of Oxford13, Princeton University14, Australian National University15, Chinese Academy of Sciences16, Korea Astronomy and Space Science Institute17, Shanghai Astronomical Observatory18
TL;DR: In this paper, a joint cosmological analysis of weak gravitational lensing observations from the Kilo-Degree Survey (KiDS-1000), with Baryon Oscillation Spectroscopic Survey (BOSS) and galaxy-galaxy lensing was presented.
Abstract: We present a joint cosmological analysis of weak gravitational lensing observations from the Kilo-Degree Survey (KiDS-1000), with
redshift-space galaxy clustering observations from the Baryon Oscillation Spectroscopic Survey (BOSS) and galaxy-galaxy lensing
observations from the overlap between KiDS-1000, BOSS, and the spectroscopic 2-degree Field Lensing Survey (2dFLenS). This
combination of large-scale structure probes breaks the degeneracies between cosmological parameters for individual observables,
resulting in a constraint on the structure growth parameter S 8 = σ8
√
Ωm/0.3 = 0.766+0.020
−0.014, which has the same overall precision as
that reported by the full-sky cosmic microwave background observations from Planck. The recovered S 8 amplitude is low, however,
by 8.3 ± 2.6% relative to Planck. This result builds from a series of KiDS-1000 analyses where we validate our methodology with
variable depth mock galaxy surveys, our lensing calibration with image simulations and null-tests, and our optical-to-near-infrared
redshift calibration with multi-band mock catalogues and a spectroscopic-photometric clustering analysis. The systematic uncertainties identified by these analyses are folded through as nuisance parameters in our cosmological analysis. Inspecting the offset between
the marginalised posterior distributions, we find that the S 8-difference with Planck is driven by a tension in the matter fluctuation
amplitude parameter, σ8. We quantify the level of agreement between the cosmic microwave background and our large-scale structure
constraints using a series of different metrics, finding differences with a significance ranging between ∼ 3σ, when considering the
offset in S 8, and ∼2σ, when considering the full multi-dimensional parameter space.
305 citations
Harvard University1, VU University Amsterdam2, University of Bern3, University of Oxford4, Public Health Research Institute5, University of Wuppertal6, Kyoto University7, University of Amsterdam8, University of New South Wales9, University of Melbourne10, City University London11, University of Gothenburg12, Free University of Berlin13, University of Texas at Austin14, Carlos III Health Institute15, James I University16, Ohio State University17, Northwestern University18, University of Erlangen-Nuremberg19, University of Bristol20, University Hospitals Bristol NHS Foundation Trust21, Trinity College, Dublin22, University of York23, Karolinska Institutet24, Peking Union Medical College25, Linköping University26, University of Regina27, University of Sydney28, McLean Hospital29, University of Lübeck30, University of Zaragoza31, Imperial College London32, University of Nottingham33, University of Hamburg34, Oregon Research Institute35, Australian National University36, Hofstra University37, The Ohio State University Wexner Medical Center38, Stockholm University39, Hull York Medical School40, Tilburg University41, Linnaeus University42
TL;DR: In this article, the authors conducted a systematic review and IPD network meta-analysis and estimated relative treatment effect sizes across different patient characteristics through IPD-network meta-regression, and found that both guided and unguided iCBT were associated with more effectiveness as measured by PHQ-9 scores than control treatments over the short term and the long term.
Abstract: Importance Personalized treatment choices would increase the effectiveness of internet-based cognitive behavioral therapy (iCBT) for depression to the extent that patients differ in interventions that better suit them. Objective To provide personalized estimates of short-term and long-term relative efficacy of guided and unguided iCBT for depression using patient-level information. Data Sources We searched PubMed, Embase, PsycInfo, and Cochrane Library to identify randomized clinical trials (RCTs) published up to January 1, 2019. Study Selection Eligible RCTs were those comparing guided or unguided iCBT against each other or against any control intervention in individuals with depression. Available individual patient data (IPD) was collected from all eligible studies. Depression symptom severity was assessed after treatment, 6 months, and 12 months after randomization. Data Extraction and Synthesis We conducted a systematic review and IPD network meta-analysis and estimated relative treatment effect sizes across different patient characteristics through IPD network meta-regression. Main Outcomes and Measures Patient Health Questionnaire–9 (PHQ-9) scores. Results Of 42 eligible RCTs, 39 studies comprising 9751 participants with depression contributed IPD to the IPD network meta-analysis, of which 8107 IPD were synthesized. Overall, both guided and unguided iCBT were associated with more effectiveness as measured by PHQ-9 scores than control treatments over the short term and the long term. Guided iCBT was associated with more effectiveness than unguided iCBT (mean difference [MD] in posttreatment PHQ-9 scores, −0.8; 95% CI, −1.4 to −0.2), but we found no evidence of a difference at 6 or 12 months following randomization. Baseline depression was found to be the most important modifier of the relative association for efficacy of guided vs unguided iCBT. Differences between unguided and guided iCBT in people with baseline symptoms of subthreshold depression (PHQ-9 scores 5-9) were small, while guided iCBT was associated with overall better outcomes in patients with baseline PHQ-9 greater than 9. Conclusions and Relevance In this network meta-analysis with IPD, guided iCBT was associated with more effectiveness than unguided iCBT for individuals with depression, benefits were more substantial in individuals with moderate to severe depression. Unguided iCBT was associated with similar effectiveness among individuals with symptoms of mild/subthreshold depression. Personalized treatment selection is entirely possible and necessary to ensure the best allocation of treatment resources for depression.
01 Jun 2021
TL;DR: In this article, the authors explore seven plausible scenarios of COVID-19 and the macroeconomic outcomes using a global hybrid DSGE/CGE general equilibrium model and demonstrate that even a contained outbreak could significantly impact the global economy in the short run.
Abstract: COVID-19 has disrupted the Chinese economy and is spreading globally. The evolution of the disease and its economic impacts are highly uncertain, making formulation of appropriate macroeconomic policy responses challenging. This paper explores seven plausible scenarios of COVID-19 and the macroeconomic outcomes using a global hybrid DSGE/CGE general equilibrium model. The results demonstrate that even a contained outbreak could significantly impact the global economy in the short run. Economic costs could be significantly avoided with greater investment in public health systems in all economies, particularly in economies where health care systems are less developed and population density is high.
TL;DR: In this article, the authors showed that the cell-surface NINJ1 protein, which contains two transmembrane regions, has an essential role in the induction of PMR.
Abstract: Plasma membrane rupture (PMR) is the final cataclysmic event in lytic cell death. PMR releases intracellular molecules known as damage-associated molecular patterns (DAMPs) that propagate the inflammatory response1-3. The underlying mechanism of PMR, however, is unknown. Here we show that the cell-surface NINJ1 protein4-8, which contains two transmembrane regions, has an essential role in the induction of PMR. A forward-genetic screen of randomly mutagenized mice linked NINJ1 to PMR. Ninj1-/- macrophages exhibited impaired PMR in response to diverse inducers of pyroptotic, necrotic and apoptotic cell death, and were unable to release numerous intracellular proteins including HMGB1 (a known DAMP) and LDH (a standard measure of PMR). Ninj1-/- macrophages died, but with a distinctive and persistent ballooned morphology, attributable to defective disintegration of bubble-like herniations. Ninj1-/- mice were more susceptible than wild-type mice to infection with Citrobacter rodentium, which suggests a role for PMR in anti-bacterial host defence. Mechanistically, NINJ1 used an evolutionarily conserved extracellular domain for oligomerization and subsequent PMR. The discovery of NINJ1 as a mediator of PMR overturns the long-held idea that cell death-related PMR is a passive event.
Australian National University1, Max Planck Society2, University of Sydney3, University of Ljubljana4, Uppsala University5, Stockholm University6, University of New South Wales7, Monash University8, Macquarie University9, Aarhus University10, Leibniz Institute for Astrophysics Potsdam11, University of Southern Queensland12, International Space Science Institute13, Lund University14, University of Western Australia15, Kapteyn Astronomical Institute16, University of Hertfordshire17, Swinburne University of Technology18, Johns Hopkins University19, Columbia University20, York University21
TL;DR: In this paper, the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1093/mnras/stab1242
Abstract: © 2021 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1093/mnras/stab1242
Oak Ridge National Laboratory1, University of New South Wales2, Ludwig Maximilian University of Munich3, University of Arizona4, Stanford University5, Scripps Institution of Oceanography6, Smithsonian Environmental Research Center7, University of Sydney8, Max Planck Society9, Smithsonian Conservation Biology Institute10, Smithsonian Tropical Research Institute11, Seconda Università degli Studi di Napoli12, University of Leeds13, Swiss Federal Institute for Forest, Snow and Landscape Research14, Aix-Marseille University15, University of California, Santa Barbara16, Commonwealth Scientific and Industrial Research Organisation17, Université Paris-Saclay18, Australian National University19, National University of Singapore20, ETH Zurich21, California Institute of Technology22, Imperial College London23, Northern Arizona University24, Oeschger Centre for Climate Change Research25, Lawrence Berkeley National Laboratory26, University of California, Berkeley27, University of Basel28, Auckland University of Technology29, Indiana University30, University of Oxford31, Spanish National Research Council32, Umeå University33, University of Exeter34, Lawrence Livermore National Laboratory35, University of California, Irvine36, United States Geological Survey37, State University of New York College of Environmental Science and Forestry38, Rutgers University39, Wageningen University and Research Centre40
TL;DR: A range of evidence supports a positive terrestrial carbon sink in response to iCO2, albeit with uncertain magnitude and strong suggestion of a role for additional agents of global change.
Abstract: Atmospheric carbon dioxide concentration ([CO2 ]) is increasing, which increases leaf-scale photosynthesis and intrinsic water-use efficiency. These direct responses have the potential to increase plant growth, vegetation biomass, and soil organic matter; transferring carbon from the atmosphere into terrestrial ecosystems (a carbon sink). A substantial global terrestrial carbon sink would slow the rate of [CO2 ] increase and thus climate change. However, ecosystem CO2 responses are complex or confounded by concurrent changes in multiple agents of global change and evidence for a [CO2 ]-driven terrestrial carbon sink can appear contradictory. Here we synthesize theory and broad, multidisciplinary evidence for the effects of increasing [CO2 ] (iCO2 ) on the global terrestrial carbon sink. Evidence suggests a substantial increase in global photosynthesis since pre-industrial times. Established theory, supported by experiments, indicates that iCO2 is likely responsible for about half of the increase. Global carbon budgeting, atmospheric data, and forest inventories indicate a historical carbon sink, and these apparent iCO2 responses are high in comparison to experiments and predictions from theory. Plant mortality and soil carbon iCO2 responses are highly uncertain. In conclusion, a range of evidence supports a positive terrestrial carbon sink in response to iCO2 , albeit with uncertain magnitude and strong suggestion of a role for additional agents of global change.
TL;DR: A nanopatterned electron transport layer is introduced that overcomes this trade-off by modifying the spatial distribution of the passivation layer to form nanoscale localized charge transport pathways through an otherwise passivated interface, thereby providing both effective passivation and excellent charge extraction.
Abstract: Polymer passivation layers can improve the open-circuit voltage of perovskite solar cells when inserted at the perovskite-charge transport layer interfaces. Unfortunately, many such layers are poor conductors, leading to a trade-off between passivation quality (voltage) and series resistance (fill factor, FF). Here, we introduce a nanopatterned electron transport layer that overcomes this trade-off by modifying the spatial distribution of the passivation layer to form nanoscale localized charge transport pathways through an otherwise passivated interface, thereby providing both effective passivation and excellent charge extraction. By combining the nanopatterned electron transport layer with a dopant-free hole transport layer, we achieved a certified power conversion efficiency of 21.6% for a 1-square-centimeter cell with FF of 0.839, and demonstrate an encapsulated cell that retains ~91.7% of its initial efficiency after 1000 hours of damp heat exposure.
TL;DR: The emergence of virulence during the evolution of E. coli is explored, with a focus on the main ExPEC, InPEC and hybrid clones, to argue for an optimization of strain fitness through epistatic interactions between the virulence determinants and the remaining genome.
Abstract: Escherichia coli is a commensal of the vertebrate gut that is increasingly involved in various intestinal and extra-intestinal infections as an opportunistic pathogen. Numerous pathotypes that represent groups of strains with specific pathogenic characteristics have been described based on heterogeneous and complex criteria. The democratization of whole-genome sequencing has led to an accumulation of genomic data that render possible a population phylogenomic approach to the emergence of virulence. Few lineages are responsible for the pathologies compared with the diversity of commensal strains. These lineages emerged multiple times during E. coli evolution, mainly by acquiring virulence genes located on mobile elements, but in a specific chromosomal phylogenetic background. This repeated emergence of stable and cosmopolitan lineages argues for an optimization of strain fitness through epistatic interactions between the virulence determinants and the remaining genome.
TL;DR: In this paper, a representative longitudinal online survey of over 3000 adults from Australia that examines the demographic, attitudinal, political and social attitudes and COVID-19 health behavior correlates of vaccine hesitance and resistance to a COVID19 vaccine was conducted.
Abstract: BACKGROUND: High levels of vaccination coverage in populations will be required even with vaccines that have high levels of effectiveness to prevent and stop outbreaks of coronavirus. The World Health Organisation has suggested that governments take a proactive response to vaccine hesitancy 'hotspots' based on social and behavioural insights. METHODS: Representative longitudinal online survey of over 3000 adults from Australia that examines the demographic, attitudinal, political and social attitudes and COVID-19 health behavior correlates of vaccine hesitance and resistance to a COVID-19 vaccine. RESULTS: Overall, 59% would definitely get the vaccine, 29% had low levels of hesitancy, 7% had high levels of hesitancy and 6% were resistant. Females, those living in disadvantaged areas, those who reported that risks of COVID-19 was overstated, those who had more populist views and higher levels of religiosity were more likely to be hesitant or resistant while those who had higher levels of household income, those who had higher levels of social distancing, who downloaded the COVID-Safe App, who had more confidence in their state or territory government or confidence in their hospitals, or were more supportive of migration were more likely to intend to get vaccinated. CONCLUSIONS: Our findings suggest that vaccine hesitancy, which accounts for a significant proportion of the population can be addressed by public health messaging but for a significant minority of the population with strongly held beliefs, alternative policy measures may well be needed to achieve sufficient vaccination coverage to end the pandemic.
TL;DR: In this paper, the authors summarize the recent experimental and computational research progress in the modification of MnO2 single species by morphology control, structure construction, facet engineering, and element doping.
Abstract: Manganese dioxide (MnO2 ) is a promising photo-thermo-electric-responsive semiconductor material for environmental applications, owing to its various favorable properties. However, the unsatisfactory environmental purification efficiency of this material has limited its further applications. Fortunately, in the last few years, significant efforts have been undertaken for improving the environmental purification efficiency of this material and understanding its underlying mechanism. Here, the aim is to summarize the recent experimental and computational research progress in the modification of MnO2 single species by morphology control, structure construction, facet engineering, and element doping. Moreover, the design and fabrication of MnO2 -based composites via the construction of homojunctions and MnO2 /semiconductor/conductor binary/ternary heterojunctions is discussed. Their applications in environmental purification systems, either as an adsorbent material for removing heavy metals, dyes, and microwave (MW) pollution, or as a thermal catalyst, photocatalyst, and electrocatalyst for the degradation of pollutants (water and gas, organic and inorganic) are also highlighted. Finally, the research gaps are summarized and a perspective on the challenges and the direction of future research in nanostructured MnO2 -based materials in the field of environmental applications is presented. Therefore, basic guidance for rational design and fabrication of high-efficiency MnO2 -based materials for comprehensive environmental applications is provided.
TL;DR: The factors that lie behind the historical cost reductions of solar PV are reviewed and innovations in the pipeline are identified that could contribute to maintaining a high learning rate, which will be crucial to remain in a decarbonization path compatible with the Paris Agreement.
TL;DR: In this article, it was shown that carbon-containing defects in hexagonal boron nitride (hBN) are carbon-related and that only carbon implantation creates single photon emitters in the visible spectral range.
Abstract: Single-photon emitters (SPEs) in hexagonal boron nitride (hBN) have garnered increasing attention over the last few years due to their superior optical properties. However, despite the vast range of experimental results and theoretical calculations, the defect structure responsible for the observed emission has remained elusive. Here, by controlling the incorporation of impurities into hBN via various bottom-up synthesis methods and directly through ion implantation, we provide direct evidence that the visible SPEs are carbon related. Room-temperature optically detected magnetic resonance is demonstrated on ensembles of these defects. We perform ion-implantation experiments and confirm that only carbon implantation creates SPEs in the visible spectral range. Computational analysis of the simplest 12 carbon-containing defect species suggest the negatively charged $${\rm{V}}_{\rm{B}}{\rm{C}}_{\rm{N}}^ -$$
defect as a viable candidate and predict that out-of-plane deformations make the defect environmentally sensitive. Our results resolve a long-standing debate about the origin of single emitters at the visible range in hBN and will be key to the deterministic engineering of these defects for quantum photonic devices. Comparison of hexagonal boron nitride samples grown with different techniques and with varying carbon-doping content provides evidence that the defects emitting single photons in the visible range are carbon related.
TL;DR: It is found that the frequency of greenspace use and the existence of green window views from within the home was associated with increased levels of self‐esteem, life satisfaction, and subjective happiness and decreased levels of depression, anxiety, and loneliness, suggesting that urban nature has great potential to be used as a nature‐based solution for improved public health.
Abstract: The COVID-19 pandemic and its global response have resulted in unprecedented and rapid changes to most people's day-to-day lives. To slow the spread of the virus, governments have implemented the practice of physical distancing ("social distancing"), which includes isolation within the home with limited time spent outdoors. During this extraordinary time, nature around the home may play a key role in mitigating against adverse mental health outcomes due to the pandemic and the measures taken to address it. To assess whether this is the case, we conducted an online questionnaire survey (n = 3,000) in Tokyo, Japan, to quantify the association between five mental health outcomes (depression, life satisfaction, subjective happiness, self-esteem, and loneliness) and two measures of nature experiences (frequency of greenspace use and green view through windows from home). Accounting for sociodemographic and lifestyle variables, we found that the frequency of greenspace use and the existence of green window views from within the home was associated with increased levels of self-esteem, life satisfaction, and subjective happiness and decreased levels of depression, anxiety, and loneliness. Our findings suggest that a regular dose of nature can contribute to the improvement of a wide range of mental health outcomes. With the recent escalation in the prevalence of mental health disorders, and the possible negative impacts of the COVID-19 pandemic on public mental health, our findings have major implications for policy, suggesting that urban nature has great potential to be used as a "nature-based solution" for improved public health.
University of New England (Australia)1, New South Wales Department of Primary Industries2, Cooperative Research Centre3, University of Western Australia4, Australian National University5, Spanish National Research Council6, Agricultural Research Organization, Volcani Center7, Colorado State University8, Kazan Federal University9, University of Göttingen10, Zhejiang University11, Korea University12, University of Edinburgh13, University of Queensland14, Cornell University15
TL;DR: In this paper, the authors synthesized 20 years of research to explain the interrelated processes that determine soil and plant responses to biochar and found that biochar can catalyze biotic and abiotic reactions, particularly in the rhizosphere, that increase nutrient supply and uptake by plants.
Abstract: We synthesized 20 years of research to explain the interrelated processes that determine soil and plant responses to biochar. The properties of biochar and its effects within agricultural ecosystems largely depend on feedstock and pyrolysis conditions. We describe three stages of reactions of biochar in soil: dissolution (1–3 weeks); reactive surface development (1–6 months); and aging (beyond 6 months). As biochar ages, it is incorporated into soil aggregates, protecting the biochar carbon and promoting the stabilization of rhizodeposits and microbial products. Biochar carbon persists in soil for hundreds to thousands of years. By increasing pH, porosity, and water availability, biochars can create favorable conditions for root development and microbial functions. Biochars can catalyze biotic and abiotic reactions, particularly in the rhizosphere, that increase nutrient supply and uptake by plants, reduce phytotoxins, stimulate plant development, and increase resilience to disease and environmental stressors. Meta-analyses found that, on average, biochars increase P availability by a factor of 4.6; decrease plant tissue concentration of heavy metals by 17%–39%; build soil organic carbon through negative priming by 3.8% (range −21% to +20%); and reduce non-CO2 greenhouse gas emissions from soil by 12%–50%. Meta-analyses show average crop yield increases of 10%–42% with biochar addition, with greatest increases in low-nutrient P-sorbing acidic soils (common in the tropics), and in sandy soils in drylands due to increase in nutrient retention and water holding capacity. Studies report a wide range of plant responses to biochars due to the diversity of biochars and contexts in which biochars have been applied. Crop yields increase strongly if site-specific soil constraints and nutrient and water limitations are mitigated by appropriate biochar formulations. Biochars can be tailored to address site constraints through feedstock selection, by modifying pyrolysis conditions, through pre- or post-production treatments, or co-application with organic or mineral fertilizers. We demonstrate how, when used wisely, biochar mitigates climate change and supports food security and the circular economy.
TL;DR: In this paper, the authors examined the gender earnings gap among rideshare drivers in the U.S. and found that women's relatively high opportunity cost of non-paid-work time and gender-based differences in preferences and constraints can sustain a gender pay gap.
Abstract: The growth of the “gig” economy generates worker flexibility that, some have speculated, will favour women. We explore this by examining labour supply choices and earnings among more than a million rideshare drivers on Uber in the U.S. We document a roughly 7% gender earnings gap amongst drivers. We show that this gap can be entirely attributed to three factors: experience on the platform (learning-by-doing), preferences and constraints over where to work (driven largely by where drivers live and, to a lesser extent, safety), and preferences for driving speed. We do not find that men and women are differentially affected by a taste for specific hours, a return to within-week work intensity, or customer discrimination. Our results suggest that, in a “gig” economy setting with no gender discrimination and highly flexible labour markets, women’s relatively high opportunity cost of non-paid-work time and gender-based differences in preferences and constraints can sustain a gender pay gap.
TL;DR: In this article, a tree-based data structure encoding the inferred evolutionary history of the SARS-CoV-2 virus was proposed to enable real-time genomic contact tracing, which greatly improves the speed of phylogenetic placement of new samples and data visualization.
Abstract: As the SARS-CoV-2 virus spreads through human populations, the unprecedented accumulation of viral genome sequences is ushering in a new era of 'genomic contact tracing'-that is, using viral genomes to trace local transmission dynamics. However, because the viral phylogeny is already so large-and will undoubtedly grow many fold-placing new sequences onto the tree has emerged as a barrier to real-time genomic contact tracing. Here, we resolve this challenge by building an efficient tree-based data structure encoding the inferred evolutionary history of the virus. We demonstrate that our approach greatly improves the speed of phylogenetic placement of new samples and data visualization, making it possible to complete the placements under the constraints of real-time contact tracing. Thus, our method addresses an important need for maintaining a fully updated reference phylogeny. We make these tools available to the research community through the University of California Santa Cruz SARS-CoV-2 Genome Browser to enable rapid cross-referencing of information in new virus sequences with an ever-expanding array of molecular and structural biology data. The methods described here will empower research and genomic contact tracing for SARS-CoV-2 specifically for laboratories worldwide.
TL;DR: In this article, the first and second observing runs of the Advanced LIGO and Virgo detector network were used to obtain the first standard-siren measurement of the Hubble constant (H 0).
Abstract: This paper presents the gravitational-wave measurement of the Hubble constant (H 0) using the detections from the first and second observing runs of the Advanced LIGO and Virgo detector network. The presence of the transient electromagnetic counterpart of the binary neutron star GW170817 led to the first standard-siren measurement of H 0. Here we additionally use binary black hole detections in conjunction with galaxy catalogs and report a joint measurement. Our updated measurement is H 0 = km s−1 Mpc−1 (68.3% of the highest density posterior interval with a flat-in-log prior) which is an improvement by a factor of 1.04 (about 4%) over the GW170817-only value of km s−1 Mpc−1. A significant additional contribution currently comes from GW170814, a loud and well-localized detection from a part of the sky thoroughly covered by the Dark Energy Survey. With numerous detections anticipated over the upcoming years, an exhaustive understanding of other systematic effects are also going to become increasingly important. These results establish the path to cosmology using gravitational-wave observations with and without transient electromagnetic counterparts.
Peking University1, Chinese Academy of Sciences2, Colorado State University3, Beijing Normal University4, École Normale Supérieure5, Lanzhou University6, University of Southampton7, Harvard University8, Lawrence Berkeley National Laboratory9, University of California, Berkeley10, Commonwealth Scientific and Industrial Research Organisation11, Australian Research Council12, International Institute for Applied Systems Analysis13, Tsinghua University14, Australian National University15
TL;DR: In this paper, the authors synthesize observational and modelling evidence to demonstrate emerging differences in dryland aridity dependent on the specific metric considered and place these climate-induced aridity changes in the context of exacerbated water scarcity driven by rapidly increasing anthropogenic needs for freshwater to support population growth and economic development.
Abstract: Drylands are an essential component of the Earth System and are among the most vulnerable to climate change. In this Review, we synthesize observational and modelling evidence to demonstrate emerging differences in dryland aridity dependent on the specific metric considered. Although warming heightens vapour pressure deficit and, thus, atmospheric demand for water in both the observations and the projections, these changes do not wholly propagate to exacerbate soil moisture and runoff deficits. Moreover, counter-intuitively, many arid ecosystems have exhibited significant greening and enhanced vegetation productivity since the 1980s. Such divergence between atmospheric and ecohydrological aridity changes can primarily be related to moisture limitations by dry soils and plant physiological regulations of evapotranspiration under elevated CO2. The latter process ameliorates water stress on plant growth and decelerates warming-enhanced water losses from soils, while simultaneously warming and drying the near-surface air. We place these climate-induced aridity changes in the context of exacerbated water scarcity driven by rapidly increasing anthropogenic needs for freshwater to support population growth and economic development. Under future warming, dryland ecosystems might respond non-linearly, caused by, for example, complex ecosystem–hydrology–human interactions and increased mortality risks from drought and heat stress, which is a foremost priority for future research. Estimates of global dryland changes are often conflicting. This Review discusses and quantifies observed and projected aridity changes, revealing divergent responses between atmospheric and ecohydrological metrics that can be explained by plant physiological responses to elevated CO2.
University of Cape Town1, University of Miami2, Australian Antarctic Division3, University of Washington4, Australian National University5, Victoria University of Wellington6, RAND Corporation7, University of Zurich8, Griffith University9, Joint Global Change Research Institute10, Environmental Change Institute11, University of KwaZulu-Natal12, University of Bristol13, ETH Zurich14, Goldman Sachs15, University of Twente16, Columbia University17, École Normale Supérieure18
TL;DR: In this article, the authors present a framework for three categories of increasingly complex climate change risk that focus on interactions among the multiple drivers of risk, as well as among multiple risks.
Abstract: Real-world experience underscores the complexity of interactions among multiple drivers of climate change risk and of how multiple risks compound or cascade. However, a holistic framework for assessing such complex climate change risks has not yet been achieved. Clarity is needed regarding the interactions that generate risk, including the role of adaptation and mitigation responses. In this perspective, we present a framework for three categories of increasingly complex climate change risk that focus on interactions among the multiple drivers of risk, as well as among multiple risks. A significant innovation is recognizing that risks can arise both from potential impacts due to climate change and from responses to climate change. This approach encourages thinking that traverses sectoral and regional boundaries and links physical and socio-economic drivers of risk. Advancing climate change risk assessment in these ways is essential for more informed decision making that reduces negative climate change impacts. © 2021 The Authors
Stockholm University1, Royal Swedish Academy of Sciences2, Potsdam Institute for Climate Impact Research3, University of Waterloo4, Harvard University5, Wageningen University and Research Centre6, University of Wisconsin-Madison7, University of Alaska Fairbanks8, Yale University9, Princeton University10, Stanford University11, University of Cambridge12, Oregon State University13, Australian National University14, Commonwealth Scientific and Industrial Research Organisation15
TL;DR: A systemic overview of the current situation where people and nature are dynamically intertwined and embedded in the biosphere, placing shocks and extreme events as part of this dynamic is provided in this paper.
Abstract: The COVID-19 pandemic has exposed an interconnected and tightly coupled globalized world in rapid change. This article sets the scientific stage for understanding and responding to such change for global sustainability and resilient societies. We provide a systemic overview of the current situation where people and nature are dynamically intertwined and embedded in the biosphere, placing shocks and extreme events as part of this dynamic; humanity has become the major force in shaping the future of the Earth system as a whole; and the scale and pace of the human dimension have caused climate change, rapid loss of biodiversity, growing inequalities, and loss of resilience to deal with uncertainty and surprise. Taken together, human actions are challenging the biosphere foundation for a prosperous development of civilizations. The Anthropocene reality—of rising system-wide turbulence—calls for transformative change towards sustainable futures. Emerging technologies, social innovations, broader shifts in cultural repertoires, as well as a diverse portfolio of active stewardship of human actions in support of a resilient biosphere are highlighted as essential parts of such transformations.
University of New South Wales1, Garvan Institute of Medical Research2, University of Western Australia3, Imperial College London4, Australian National University5, University of Sydney6, Centenary Institute7, Medical University of Vienna8, University of Queensland9, Commonwealth Scientific and Industrial Research Organisation10, University of Bristol11
TL;DR: This article showed that osteomorphs are transcriptionally distinct from osteoclasts and macrophages and express a number of non-canonical osteoclast genes that are associated with structural and functional bone phenotypes when deleted in mice.