Abstract: This paper is concerned with a leader-follower problem for a multi-agent system with a switching interconnection topology. Distributed observers are designed for the second-order follower-agents, under the common assumption that the velocity of the active leader cannot be measured in real time. Some dynamic neighbor-based rules, consisting of distributed controllers and observers for the autonomous agents, are developed to keep updating the information of the leader. With the help of an explicitly constructed common Lyapunov function (CLF), it is proved that each agent can follow the active leader. Moreover, the tracking error is estimated even in a noisy environment. Finally, a numerical example is given for illustration.

Abstract: A number of problems can be formulated as prediction on graph-structured data. In this work, we generalize the convolution operator from regular grids to arbitrary graphs while avoiding the spectral domain, which allows us to handle graphs of varying size and connectivity. To move beyond a simple diffusion, filter weights are conditioned on the specific edge labels in the neighborhood of a vertex. Together with the proper choice of graph coarsening, we explore constructing deep neural networks for graph classification. In particular, we demonstrate the generality of our formulation in point cloud classification, where we set the new state of the art, and on a graph classification dataset, where we outperform other deep learning approaches.

Abstract: 3 Building the tree 5 3.1 Splitting criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 3.2 Incorporating losses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.2.1 Generalized Gini index . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.2.2 Altered priors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.3 Example: Stage C prostate cancer (class method) . . . . . . . . . . . . . . 10 3.4 Variable importance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Abstract: The IllustrisTNG project is a new suite of cosmological magneto-hydrodynamical simulations of galaxy formation performed with the Arepo code and updated models for feedback physics. Here we introduce the first two simulations of the series, TNG100 and TNG300, and quantify the stellar mass content of about 4000 massive galaxy groups and clusters ($10^{13} \leq M_{\rm 200c}/M_{\rm sun} \leq 10^{15}$) at recent times ($z \leq 1$). The richest clusters have half of their total stellar mass bound to satellite galaxies, with the other half being associated with the central galaxy and the diffuse intra-cluster light. The exact ICL fraction depends sensitively on the definition of a central galaxy's mass and varies in our most massive clusters between 20 to 40% of the total stellar mass. Haloes of $5\times 10^{14}M_{\rm sun}$ and above have more diffuse stellar mass outside 100 kpc than within 100 kpc, with power-law slopes of the radial mass density distribution as shallow as the dark matter's ( $-3.5 < \alpha_{\rm 3D} < -3$). Total halo mass is a very good predictor of stellar mass, and vice versa: at $z=0$, the 3D stellar mass measured within 30 kpc scales as $\propto (M_{\rm 500c})^{0.49}$ with a $\sim 0.12$ dex scatter. This is possibly too steep in comparison to the available observational constraints, even though the abundance of TNG less massive galaxies ($< 10^{11}M_{\rm sun}$ in stars) is in good agreement with the measured galaxy stellar mass functions at recent epochs. The 3D sizes of massive galaxies fall too on a tight ($\sim$0.16 dex scatter) power-law relation with halo mass, with $r^{\rm stars}_{\rm 0.5} \propto (M_{\rm 500c})^{0.53}$. Even more fundamentally, halo mass alone is a good predictor for the whole stellar mass profiles beyond the inner few kpc, and we show how on average these can be precisely recovered given a single mass measurement of the galaxy or its halo.

Abstract: It may seem inevitable that highly entangled quantum states are susceptible to disturbance through interaction with a decohering environment. However, certain multiqubit entangled states are well protected from common forms of decoherence as the quantum information is hidden in inherently nonlocal degrees of freedom. This review shows that this robustness is enabled by specific measurements on subsets of qubits, implementing a quantum version of an error correction process. Beginning with the basics, the latest understanding of the relation between this form of error correction and the concept of two-dimensional topological order in many-body physics is reviewed.

Abstract: Bitcoin cryptocurrency demonstrated the utility of global consensus across thousands of nodes, changing the world of digital transactions forever. In the early days of Bitcoin, the performance of its probabilistic proof-of-work (PoW) based consensus fabric, also known as blockchain, was not a major issue. Bitcoin became a success story, despite its consensus latencies on the order of an hour and the theoretical peak throughput of only up to 7 transactions per second.

Abstract: Gene drive systems that enable super-Mendelian inheritance of a transgene have the potential to modify insect populations over a timeframe of a few years. We describe CRISPR-Cas9 endonuclease constructs that function as gene drive systems in Anopheles gambiae, the main vector for malaria. We identified three genes (AGAP005958, AGAP011377 and AGAP007280) that confer a recessive female-sterility phenotype upon disruption, and inserted into each locus CRISPR-Cas9 gene drive constructs designed to target and edit each gene. For each targeted locus we observed a strong gene drive at the molecular level, with transmission rates to progeny of 91.4 to 99.6%. Population modeling and cage experiments indicate that a CRISPR-Cas9 construct targeting one of these loci, AGAP007280, meets the minimum requirement for a gene drive targeting female reproduction in an insect population. These findings could expedite the development of gene drives to suppress mosquito populations to levels that do not support malaria transmission.

Abstract: Thousands of transiting exoplanets have been discovered, but spectral analysis of their atmospheres has so far been dominated by a small number of exoplanets and data spanning relatively narrow wavelength ranges (such as 1.1-1.7 micrometres). Recent studies show that some hot-Jupiter exoplanets have much weaker water absorption features in their near-infrared spectra than predicted. The low amplitude of water signatures could be explained by very low water abundances, which may be a sign that water was depleted in the protoplanetary disk at the planet's formation location, but it is unclear whether this level of depletion can actually occur. Alternatively, these weak signals could be the result of obscuration by clouds or hazes, as found in some optical spectra. Here we report results from a comparative study of ten hot Jupiters covering the wavelength range 0.3-5 micrometres, which allows us to resolve both the optical scattering and infrared molecular absorption spectroscopically. Our results reveal a diverse group of hot Jupiters that exhibit a continuum from clear to cloudy atmospheres. We find that the difference between the planetary radius measured at optical and infrared wavelengths is an effective metric for distinguishing different atmosphere types. The difference correlates with the spectral strength of water, so that strong water absorption lines are seen in clear-atmosphere planets and the weakest features are associated with clouds and hazes. This result strongly suggests that primordial water depletion during formation is unlikely and that clouds and hazes are the cause of weaker spectral signatures.

Abstract: A typical prokaryote population sequencing study can now consist of hundreds or thousands of isolates. Interrogating these datasets can provide detailed insights into the genetic structure of of prokaryotic genomes. We introduce Roary, a tool that rapidly builds large-scale pan genomes, identifying the core and dispensable accessory genes. Roary makes construction of the pan genome of thousands of prokaryote samples possible on a standard desktop without compromising on the accuracy of results. Using a single CPU Roary can produce a pan genome consisting of 1000 isolates in 4.5 hours using 13 GB of RAM, with further speedups possible using multiple processors.

Abstract: Production of hydrogen by water splitting is an appealing solution for sustainable energy storage. Development of bifunctional catalysts that are active for both the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER) is a key factor in enhancing electrochemical water splitting activity and simplifying the overall system design. Here, recent developments in HER–OER bifunctional catalysts are reviewed. Several main types of bifunctional water splitting catalysts such as cobalt-, nickel- and iron-based materials are discussed in detail. Particular attention is paid to their synthesis, bifunctional catalytic activity and stability, and strategies for activity enhancement. The current challenges faced are also concluded and future perspectives towards bifunctional water splitting electrocatalysts are proposed.

Abstract: Weyl points can be thought of as magnetic monopoles in momentum space that always appear in pairs. Magnetoresistance measurements indicate the existence of the long-anticipated chiral anomaly in Weyl semimetal TaAs single crystals.

Abstract: The economic downturn caused by the current COVID-19 outbreak has substantial implications for gender equality, both during the downturn and the subsequent recovery. Compared to “regular” recessions, which affect men’s employment more severely than women’s employment, the employment drop related to social distancing measures has a large impact on sectors with high female employment shares. In addition, closures of schools and daycare centers have massively increased child care needs, which has a particularly large impact on working mothers. The effects of the crisis on working mothers are likely to be persistent, due to high returns to experience in the labor market. Beyond the immediate crisis, there are opposing forces which may ultimately promote gender equality in the labor market. First, businesses are rapidly adopting flexible work arrangements, which are likely to persist. Second, there are also many fathers who now have to take primary responsibility for child care, which may erode social norms that currently lead to a lopsided distribution of the division of labor in house work and child care.

Abstract: We train a recurrent neural network language model using a distributed, on-device learning framework called federated learning for the purpose of next-word prediction in a virtual keyboard for smartphones. Server-based training using stochastic gradient descent is compared with training on client devices using the Federated Averaging algorithm. The federated algorithm, which enables training on a higher-quality dataset for this use case, is shown to achieve better prediction recall. This work demonstrates the feasibility and benefit of training language models on client devices without exporting sensitive user data to servers. The federated learning environment gives users greater control over the use of their data and simplifies the task of incorporating privacy by default with distributed training and aggregation across a population of client devices.

Abstract: Rational design and facile preparation of non-noble trifunctional electrocatalysts with high performance, low cost and strong durability for the oxygen reduction reaction (ORR), oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) are highly demanded, but remain as a big challenge. Herein, we report a spontaneous gas-foaming method to prepare nitrogen doped ultrathin carbon nanosheets (NCNs) by simply pyrolysing a mixture of citric acid and NH4Cl. Under the optimized pyrolysis temperature (carbonized at 1000 °C) and mass ratio of precursors (1 : 1), the synthesized NCN-1000-5 sample possesses an ultrathin sheet structure, an ultrahigh specific surface area (1793 m2 g−1), and rich edge defects, and exhibits low overpotential and robust stability for the ORR, OER and HER. By means of density functional theory (DFT) computations, we revealed that the intrinsic active sites for the ORR, OER and HER are the carbon atoms located at the armchair edge and adjacent to the graphitic N dopants. When practically used as a catalyst in rechargeable Zn–air batteries, a high energy density (806 W h kg−1), a low charge/discharge voltage gap (0.77 V) and an ultralong cycle life (over 330 h) were obtained at 10 mA cm−2 for NCN-1000-5. This work not only presents a versatile strategy to develop advanced carbon materials with ultrahigh specific surface area and abundant edge defects, but also provides useful guidance for designing and developing multifunctional metal-free catalysts for various energy-related electrocatalytic reactions.

Abstract: Extracellular vesicles (EVs), such as exosomes and microvesicles, are released by different cell types and participate in physiological and pathophysiological processes. EVs mediate intercellular communication as cell-derived extracellular signalling organelles that transmit specific information from their cell of origin to their target cells. As a result of these properties, EVs of defined cell types may serve as novel tools for various therapeutic approaches, including (a) anti-tumour therapy, (b) pathogen vaccination, (c) immune-modulatory and regenerative therapies and (d) drug delivery. The translation of EVs into clinical therapies requires the categorization of EV-based therapeutics in compliance with existing regulatory frameworks. As the classification defines subsequent requirements for manufacturing, quality control and clinical investigation, it is of major importance to define whether EVs are considered the active drug components or primarily serve as drug delivery vehicles. For an effective and particularly safe translation of EV-based therapies into clinical practice, a high level of cooperation between researchers, clinicians and competent authorities is essential. In this position statement, basic and clinical scientists, as members of the International Society for Extracellular Vesicles (ISEV) and of the European Cooperation in Science and Technology (COST) program of the European Union, namely European Network on Microvesicles and Exosomes in Health and Disease (ME-HaD), summarize recent developments and the current knowledge of EV-based therapies. Aspects of safety and regulatory requirements that must be considered for pharmaceutical manufacturing and clinical application are highlighted. Production and quality control processes are discussed. Strategies to promote the therapeutic application of EVs in future clinical studies are addressed.

Abstract: One of the most promising suggested applications of quantum computing is solving classically intractable chemistry problems. This may help to answer unresolved questions about phenomena such as high temperature superconductivity, solid-state physics, transition metal catalysis, and certain biochemical reactions. In turn, this increased understanding may help us to refine, and perhaps even one day design, new compounds of scientific and industrial importance. However, building a sufficiently large quantum computer will be a difficult scientific challenge. As a result, developments that enable these problems to be tackled with fewer quantum resources should be considered important. Driven by this potential utility, quantum computational chemistry is rapidly emerging as an interdisciplinary field requiring knowledge of both quantum computing and computational chemistry. This review provides a comprehensive introduction to both computational chemistry and quantum computing, bridging the current knowledge gap. Major developments in this area are reviewed, with a particular focus on near-term quantum computation. Illustrations of key methods are provided, explicitly demonstrating how to map chemical problems onto a quantum computer, and how to solve them. The review concludes with an outlook on this nascent field.

Abstract: In value-based reinforcement learning methods such as deep Q-learning, function approximation errors are known to lead to overestimated value estimates and suboptimal policies. We show that this problem persists in an actor-critic setting and propose novel mechanisms to minimize its effects on both the actor and the critic. Our algorithm builds on Double Q-learning, by taking the minimum value between a pair of critics to limit overestimation. We draw the connection between target networks and overestimation bias, and suggest delaying policy updates to reduce per-update error and further improve performance. We evaluate our method on the suite of OpenAI gym tasks, outperforming the state of the art in every environment tested.

Abstract: Summary Background Cancer is a major cause of death in children worldwide, and the recorded incidence tends to increase with time. Internationally comparable data on childhood cancer incidence in the past two decades are scarce. This study aimed to provide internationally comparable local data on the incidence of childhood cancer to promote research of causes and implementation of childhood cancer control. Methods This population-based registry study, devised by the International Agency for Research on Cancer in collaboration with the International Association of Cancer Registries, collected data on all malignancies and non-malignant neoplasms of the CNS diagnosed before age 20 years in populations covered by high-quality cancer registries with complete data for 2001–10. Incidence rates per million person-years for the 0–14 years and 0–19 years age groups were age-adjusted using the world standard population to provide age-standardised incidence rates (WSRs), using the age-specific incidence rates (ASR) for individual age groups (0–4 years, 5–9 years, 10–14 years, and 15–19 years). All rates were reported for 19 geographical areas or ethnicities by sex, age group, and cancer type. The regional WSRs for children aged 0–14 years were compared with comparable data obtained in the 1980s. Findings Of 532 invited cancer registries, 153 registries from 62 countries, departments, and territories met quality standards, and contributed data for the entire decade of 2001–10. 385 509 incident cases in children aged 0–19 years occurring in 2·64 billion person-years were included. The overall WSR was 140·6 per million person-years in children aged 0–14 years (based on 284 649 cases), and the most common cancers were leukaemia (WSR 46·4), followed by CNS tumours (WSR 28·2), and lymphomas (WSR 15·2). In children aged 15–19 years (based on 100 860 cases), the ASR was 185·3 per million person-years, the most common being lymphomas (ASR 41·8) and the group of epithelial tumours and melanoma (ASR 39·5). Incidence varied considerably between and within the described regions, and by cancer type, sex, age, and racial and ethnic group. Since the 1980s, the global WSR of registered cancers in children aged 0–14 years has increased from 124·0 (95% CI 123·3–124·7) to 140·6 (140·1–141·1) per million person-years. Interpretation This unique global source of childhood cancer incidence will be used for aetiological research and to inform public health policy, potentially contributing towards attaining several targets of the Sustainable Development Goals. The observed geographical, racial and ethnic, age, sex, and temporal variations require constant monitoring and research. Funding International Agency for Research on Cancer and the Union for International Cancer Control.

Abstract: Solution-processed planar perovskite devices are highly desirable in a wide variety of optoelectronic applications; however, they are prone to hysteresis and current instabilities. Here we report the first perovskite-PCBM hybrid solid with significantly reduced hysteresis and recombination loss achieved in a single step. This new material displays an efficient electrically coupled microstructure: PCBM is homogeneously distributed throughout the film at perovskite grain boundaries. The PCBM passivates the key PbI3(-) antisite defects during the perovskite self-assembly, as revealed by theory and experiment. Photoluminescence transient spectroscopy proves that the PCBM phase promotes electron extraction. We showcase this mixed material in planar solar cells that feature low hysteresis and enhanced photovoltage. Using conductive AFM studies, we reveal the memristive properties of perovskite films. We close by positing that PCBM, by tying up both halide-rich antisites and unincorporated halides, reduces electric field-induced anion migration that may give rise to hysteresis and unstable diode behaviour.

Abstract: Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Abstract: Per-pixel ground-truth depth data is challenging to acquire at scale. To overcome this limitation, self-supervised learning has emerged as a promising alternative for training models to perform monocular depth estimation. In this paper, we propose a set of improvements, which together result in both quantitatively and qualitatively improved depth maps compared to competing self-supervised methods. Research on self-supervised monocular training usually explores increasingly complex architectures, loss functions, and image formation models, all of which have recently helped to close the gap with fully-supervised methods. We show that a surprisingly simple model, and associated design choices, lead to superior predictions. In particular, we propose (i) a minimum reprojection loss, designed to robustly handle occlusions, (ii) a full-resolution multi-scale sampling method that reduces visual artifacts, and (iii) an auto-masking loss to ignore training pixels that violate camera motion assumptions. We demonstrate the effectiveness of each component in isolation, and show high quality, state-of-the-art results on the KITTI benchmark.

Abstract: Weyl semimetals are predicted to exhibit a host of unusual transport properties. NbP, a system predicted to share characteristics of both normal and Weyl semimetals, is now shown to have a very large, non-saturating magnetoresistance. Recent experiments have revealed spectacular transport properties in semimetals, such as the large, non-saturating magnetoresistance exhibited by WTe2 (ref. 1). Topological semimetals with massless relativistic electrons have also been predicted2 as three-dimensional analogues of graphene3. These systems are known as Weyl semimetals, and are predicted to have a range of exotic transport properties and surface states4,5,6,7, distinct from those of topological insulators8,9. Here we examine the magneto-transport properties of NbP, a material the band structure of which has been predicted to combine the hallmarks of a Weyl semimetal10,11 with those of a normal semimetal. We observe an extremely large magnetoresistance of 850,000% at 1.85 K (250% at room temperature) in a magnetic field of up to 9 T, without any signs of saturation, and an ultrahigh carrier mobility of 5 × 106 cm2 V−1 s−1 that accompanied by strong Shubnikov–de Haas (SdH) oscillations. NbP therefore presents a unique example of a material combining topological and conventional electronic phases, with intriguing physical properties resulting from their interplay.

Abstract: The formation of soap bubbles from thin films is accompanied by topological transitions. Here we show how a magnetic topological structure, a skyrmion bubble, can be generated in a solid-state system in a similar manner. Using an inhomogeneous in-plane current in a system with broken inversion symmetry, we experimentally “blow” magnetic skyrmion bubbles from a geometrical constriction. The presence of a spatially divergent spin-orbit torque gives rise to instabilities of the magnetic domain structures that are reminiscent of Rayleigh-Plateau instabilities in fluid flows. We determine a phase diagram for skyrmion formation and reveal the efficient manipulation of these dynamically created skyrmions, including depinning and motion. The demonstrated current-driven transformation from stripe domains to magnetic skyrmion bubbles could lead to progress in skyrmion-based spintronics.

Abstract: By reaching near-atomic resolution for a wide range of specimens, single-particle cryo-EM structure determination is transforming structural biology. However, the necessary calculations come at large computational costs, which has introduced a bottleneck that is currently limiting throughput and the development of new methods. Here, we present an implementation of the RELION image processing software that uses graphics processors (GPUs) to address the most computationally intensive steps of its cryo-EM structure determination workflow. Both image classification and high-resolution refinement have been accelerated more than an order-of-magnitude, and template-based particle selection has been accelerated well over two orders-of-magnitude on desktop hardware. Memory requirements on GPUs have been reduced to fit widely available hardware, and we show that the use of single precision arithmetic does not adversely affect results. This enables high-resolution cryo-EM structure determination in a matter of days on a single workstation.

Abstract: Importance Lack of current and comprehensive trend data derived from a uniform, reliable, and valid source on alcohol use, high-risk drinking, andDSM-IValcohol use disorder (AUD) represents a major gap in public health information. Objective To present nationally representative data on changes in the prevalences of 12-month alcohol use, 12-month high-risk drinking, 12-monthDSM-IVAUD, 12-monthDSM-IVAUD among 12-month alcohol users, and 12-monthDSM-IVAUD among 12-month high-risk drinkers between 2001-2002 and 2012-2013. Design, Setting, and Participants The study data were derived from face-to-face interviews conducted in 2 nationally representative surveys of US adults: the National Epidemiologic Survey on Alcohol and Related Conditions, with data collected from April 2001 to June 2002, and the National Epidemiologic Survey on Alcohol and Related Conditions III, with data collected from April 2012 to June 2013. Data were analyzed in November and December 2016. Main Outcomes and Measures Twelve-month alcohol use, high-risk drinking, andDSM-IVAUD. Results The study sample included 43 093 participants in the National Epidemiologic Survey on Alcohol and Related Conditions and 36 309 participants in the National Epidemiologic Survey on Alcohol and Related Conditions III. Between 2001-2002 and 2012-2013, 12-month alcohol use, high-risk drinking, andDSM-IVAUD increased by 11.2%, 29.9%, and 49.4%, respectively, with alcohol use increasing from 65.4% (95% CI, 64.3%-66.6%) to 72.7% (95% CI, 71.4%-73.9%), high-risk drinking increasing from 9.7% (95% CI, 9.3%-10.2%) to 12.6% (95% CI, 12.0%-13.2%), andDSM-IVAUD increasing from 8.5% (95% CI, 8.0%-8.9%) to 12.7% (95% CI, 12.1%-13.3%). With few exceptions, increases in alcohol use, high-risk drinking, andDSM-IVAUD between 2001-2002 and 2012-2013 were also statistically significant across sociodemographic subgroups. Increases in all of these outcomes were greatest among women, older adults, racial/ethnic minorities, and individuals with lower educational level and family income. Increases were also seen for the total sample and most sociodemographic subgroups for the prevalences of 12-monthDSM-IVAUD among 12-month alcohol users from 12.9% (95% CI, 12.3%-17.5%) to 17.5% (95% CI, 16.7%-18.3%) and 12-monthDSM-IVAUD among 12-month high-risk drinkers from 46.5% (95% CI, 44.3%-48.7%) to 54.5% (95% CI, 52.7%-56.4%). Conclusions and Relevance Increases in alcohol use, high-risk drinking, andDSM-IVAUD in the US population and among subgroups, especially women, older adults, racial/ethnic minorities, and the socioeconomically disadvantaged, constitute a public health crisis. Taken together, these findings portend increases in many chronic comorbidities in which alcohol use has a substantial role.