Abstract: In May 2019, the International Scientific Association for Probiotics and Prebiotics (ISAPP) convened a panel of nutritionists, physiologists and microbiologists to review the definition and scope of synbiotics. The panel updated the definition of a synbiotic to “a mixture comprising live microorganisms and substrate(s) selectively utilized by host microorganisms that confers a health benefit on the host”. The panel concluded that defining synbiotics as simply a mixture of probiotics and prebiotics could suppress the innovation of synbiotics that are designed to function cooperatively. Requiring that each component must meet the evidence and dose requirements for probiotics and prebiotics individually could also present an obstacle. Rather, the panel clarified that a complementary synbiotic, which has not been designed so that its component parts function cooperatively, must be composed of a probiotic plus a prebiotic, whereas a synergistic synbiotic does not need to be so. A synergistic synbiotic is a synbiotic for which the substrate is designed to be selectively utilized by the co-administered microorganisms. This Consensus Statement further explores the levels of evidence (existing and required), safety, effects upon targets and implications for stakeholders of the synbiotic concept. Gut microbiota can be manipulated to benefit host health, including the use of probiotics, prebiotics and synbiotics. This Consensus Statement outlines the definition and scope of the term ‘synbiotics’ as determined by an expert panel convened by the International Scientific Association for Probiotics and Prebiotics in May 2019.

Abstract: Learning vector representations (aka. embeddings) of users and items lies at the core of modern recommender systems. Ranging from early matrix factorization to recently emerged deep learning based methods, existing efforts typically obtain a user's (or an item's) embedding by mapping from pre-existing features that describe the user (or the item), such as ID and attributes. We argue that an inherent drawback of such methods is that, the collaborative signal, which is latent in user-item interactions, is not encoded in the embedding process. As such, the resultant embeddings may not be sufficient to capture the collaborative filtering effect. In this work, we propose to integrate the user-item interactions -- more specifically the bipartite graph structure -- into the embedding process. We develop a new recommendation framework Neural Graph Collaborative Filtering (NGCF), which exploits the user-item graph structure by propagating embeddings on it. This leads to the expressive modeling of high-order connectivity in user-item graph, effectively injecting the collaborative signal into the embedding process in an explicit manner. We conduct extensive experiments on three public benchmarks, demonstrating significant improvements over several state-of-the-art models like HOP-Rec and Collaborative Memory Network. Further analysis verifies the importance of embedding propagation for learning better user and item representations, justifying the rationality and effectiveness of NGCF. Codes are available at this https URL.

Abstract: Aims Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly evolved into a sweeping pandemic. Its major manifestation is in the respiratory tract, and the general extent of organ involvement and the microscopic changes in the lungs remain insufficiently characterised. Autopsies are essential to elucidate COVID-19-associated organ alterations. Methods and results This article reports the autopsy findings of 21 COVID-19 patients hospitalised at the University Hospital Basel and at the Cantonal Hospital Baselland, Switzerland. An in-corpore technique was performed to ensure optimal staff safety. The primary cause of death was respiratory failure with exudative diffuse alveolar damage and massive capillary congestion, often accompanied by microthrombi despite anticoagulation. Ten cases showed superimposed bronchopneumonia. Further findings included pulmonary embolism (n = 4), alveolar haemorrhage (n = 3), and vasculitis (n = 1). Pathologies in other organ systems were predominantly attributable to shock; three patients showed signs of generalised and five of pulmonary thrombotic microangiopathy. Six patients were diagnosed with senile cardiac amyloidosis upon autopsy. Most patients suffered from one or more comorbidities (hypertension, obesity, cardiovascular diseases, and diabetes mellitus). Additionally, there was an overall predominance of males and individuals with blood group A (81% and 65%, respectively). All relevant histological slides are linked as open-source scans in supplementary files. Conclusions This study provides an overview of postmortem findings in COVID-19 cases, implying that hypertensive, elderly, obese, male individuals with severe cardiovascular comorbidities as well as those with blood group A may have a lower threshold of tolerance for COVID-19. This provides a pathophysiological explanation for higher mortality rates among these patients.

Abstract: Electrochemical capacitors can store electrical energy harvested from intermittent sources and deliver energy quickly, but their energy density must be increased if they are to efficiently power flexible and wearable electronics, as well as larger equipment. This Review summarizes progress in the field of materials for electrochemical capacitors over the past decade as well as outlines key perspectives for future research. We describe electrical double-layer capacitors based on high-surface-area carbons, pseudocapacitive materials such as oxides and the two-dimensional inorganic compounds known as MXenes, and emerging microdevices for the Internet of Things. We show that new nanostructured electrode materials and matching electrolytes are required to maximize the amount of energy and speed of delivery, and different manufacturing methods will be needed to meet the requirements of the future generation of electronic devices. Scientifically justified metrics for testing, comparison and optimization of various kinds of electrochemical capacitors are provided and explained.

Abstract: BackgroundHydroxychloroquine and chloroquine have been proposed as treatments for coronavirus disease 2019 (Covid-19) on the basis of in vitro activity and data from uncontrolled studies and small, randomized trials.MethodsIn this randomized, controlled, open-label platform trial comparing a range of possible treatments with usual care in patients hospitalized with Covid-19, we randomly assigned 1561 patients to receive hydroxychloroquine and 3155 to receive usual care. The primary outcome was 28-day mortality.ResultsThe enrollment of patients in the hydroxychloroquine group was closed on June 5, 2020, after an interim analysis determined that there was a lack of efficacy. Death within 28 days occurred in 421 patients (27.0%) in the hydroxychloroquine group and in 790 (25.0%) in the usual-care group (rate ratio, 1.09; 95% confidence interval [CI], 0.97 to 1.23; P=0.15). Consistent results were seen in all prespecified subgroups of patients. The results suggest that patients in the hydroxychloroquine group were less likely to be discharged from the hospital alive within 28 days than those in the usual-care group (59.6% vs. 62.9%; rate ratio, 0.90; 95% CI, 0.83 to 0.98). Among the patients who were not undergoing mechanical ventilation at baseline, those in the hydroxychloroquine group had a higher frequency of invasive mechanical ventilation or death (30.7% vs. 26.9%; risk ratio, 1.14; 95% CI, 1.03 to 1.27). There was a small numerical excess of cardiac deaths (0.4 percentage points) but no difference in the incidence of new major cardiac arrhythmia among the patients who received hydroxychloroquine.ConclusionsAmong patients hospitalized with Covid-19, those who received hydroxychloroquine did not have a lower incidence of death at 28 days than those who received usual care. (Funded by UK Research and Innovation and National Institute for Health Research and others; RECOVERY ISRCTN number, ISRCTN50189673. opens in new tab; ClinicalTrials.gov number, NCT04381936. opens in new tab.)

Abstract: Contents: L.A. Shepard, Preface. J.L. Green, G. Camilli, P.B. Elmore, Introduction to the Handbook: What's Complementary About Complementary Methods. A. Skukauskaite, E. Grace, On Reading and Using the Volume: Notes to Students. Part I: Foundations. E. Bredo, Philosophies of Educational Research. G.J. Kelly, Epistemology and Educational Research. K.A. Strike, The Ethics of Educational Research. Part II: Introduction to Design & Analysis. C. Bazerman, Analyzing the Multidimensionality of Texts in Education. T. Barone, Arts-Based Educational Research. R.K. Yin, Case Study Methods. K.M. Borman, C. Clarke, B. Cotner, R. Lee, Cross-Case Analysis. A.C. Porter, Curriculum Assessment. K.H. Kim, P.M. Bentler, Data Modeling: Structural Equation Modeling. F. Erickson, Definition and Analysis of Data From Videotape: Some Research Procedures and Their Rationales. A.H. Schoenfeld, Design Experiments. H-Z. Ho, S.L. O'Farrell, S. Hong, S. You, Developmental Research: Theory, Method, Design, and Statistical Analysis. D. Bloome, C. Clark, Discourse-In-Use. H. Braun, Empirical Bayes. J.P. Shaffer, Estimation. K.M. Anderson-Levitt, Ethnography. J. Nespor, Finding Patters With Field Notes. R.J. Shavelson, N.M. Webb, Generalizability Theory. J.L. Rury, Historical Research in Education. A. Henry, Historical Studies: Groups/Institutions. M.E. Brenner, Interviewing in Educational Research. L. Crocker, Introduction to Measurement Theory. S. Embretson, X. Yang, Item Response Theory. D.M. Harrison, S.W. Raudenbush, Linear Regression and Hierarchical Linear Models. G.V. Glass, Meta-Analysis: The Quantitative Synthesis of Research Findings. C.A. Chinn, The Microgenetic Method: Current Work and Extensions to Classroom Research. M.L. Smith, Multiple Methodology in Education Research. F.M. Connelly, D.J. Clandinin, Narrative Inquiry. N.C. Burbules, B.R. Warnick, Philosophical Inquiry. M. Cochran-Smith, K. Donnell, Practitioner Inquiry: Blurring the Boundaries of Research and Practice. J.R. Levin, Probability and Hypothesis Testing. W.R. Shadish, J.K. Luellen, Quasi-Experimental Design. T.D. Cook, V. Sinha, Randomized Experiments in Educational Research. M. Eisenhart, Representing Qualitative Data. B. Thompson, Research Synthesis: Effect Sizes. H. Wainer, P.F. Velleman, Statistical Graphics: A Guidepost for Scientific Discovery. M. Berends, Survey Methods in Educational Research. J. Chromy, Survey Sampling. Part III: Programs of Research. C. Genishi, T. Glupczynski, Language and Literacy Research: Multiple Methods and Perspectives. L.M. McNeil, E.M. Coppola, Official and Unofficial Stories: Getting at the Impact of Policy on Educational Practice. M.E. Goertz, Policy Analysis: Studying Policy Implementation. S. Kushner, C. Adelman, Program Evaluation: A Democratic Practice. L.A. Rex, S.C. Steadman, M.K. Graciano, Researching the Complexity of Classroom Interaction. J.A. Banks, Researching Race, Culture, and Difference: Epistemological Challenges and Possibilities. J.G. Greeno, Theoretical and Practical Advances Through Research on Learning. S. Noffke, K. Zeichner, Programs of Research in Teacher Education.

Abstract: Importance While the outbreak of coronavirus disease 2019 (COVID-19) has resulted in more than 100 000 infected individuals in China and worldwide, there are few reports on the association of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with ocular abnormalities. Understanding ocular manifestations of patients with COVID-19 by ophthalmologists and others may facilitate the diagnosis and prevention of transmission of the disease. Objective To investigate ocular manifestations and viral prevalence in the conjunctiva of patients with COVID-19. Design, Setting, and Participants In this case series, patients with COVID-19 treated from February 9 to 15, 2020, at a hospital center in Hubei province, China, were retrospectively reviewed for ocular manifestations. During the period of treatment, the ocular signs and symptoms as well as results of blood tests and reverse transcriptase–polymerase chain reaction (RT-PCR) from nasopharyngeal and conjunctival swabs for SARS-CoV-2 were noted and analyzed. Main Outcomes and Measures Ocular signs and symptoms as well as results of blood tests and RT-PCR for SARS-CoV-2. Results Of the 38 included patients with clinically confirmed COVID-19, 25 (65.8%) were male, and the mean (SD) age was 65.8 (16.6) years. Among them, 28 patients (73.7%) had positive findings for COVID-19 on RT-PCR from nasopharyngeal swabs, and of these, 2 patients (5.2%) yielded positive findings for SARS-CoV-2 in their conjunctival as well as nasopharyngeal specimens. A total of 12 of 38 patients (31.6%; 95% CI, 17.5-48.7) had ocular manifestations consistent with conjunctivitis, including conjunctival hyperemia, chemosis, epiphora, or increased secretions. By univariate analysis, patients with ocular symptoms were more likely to have higher white blood cell and neutrophil counts and higher levels of procalcitonin, C-reactive protein, and lactate dehydrogenase than patients without ocular symptoms. In addition, 11 of 12 patients with ocular abnormalities (91.7%; 95% CI, 61.5-99.8) had positive results for SARS-CoV-2 on RT-PCR from nasopharyngeal swabs. Of these, 2 (16.7%) had positive results for SARS-CoV-2 on RT-PCR from both conjunctival and nasopharyngeal swabs. Conclusions and Relevance In this study, one-third of patients with COVID-19 had ocular abnormalities, which frequently occurred in patients with more severe COVID-19. Although there is a low prevalence of SARS-CoV-2 in tears, it is possible to transmit via the eyes.

Abstract: A q-form global symmetry is a global symmetry for which the charged operators are of space-time dimension q; e.g. Wilson lines, surface defects, etc., and the charged excitations have q spatial dimensions; e.g. strings, membranes, etc. Many of the properties of ordinary global symmetries (q = 0) apply here. They lead to Ward identities and hence to selection rules on amplitudes. Such global symmetries can be coupled to classical background fields and they can be gauged by summing over these classical fields. These generalized global symmetries can be spontaneously broken (either completely or to a sub-group). They can also have ’t Hooft anomalies, which prevent us from gauging them, but lead to ’t Hooft anomaly matching conditions. Such anomalies can also lead to anomaly inflow on various defects and exotic Symmetry Protected Topological phases. Our analysis of these symmetries gives a new unified perspective of many known phenomena and uncovers new results.

Abstract: Naturally derived cellulose nanocrystals (CNCs) and cellulose nanofibrils (CNFs) are emerging nanomaterials that display high strength, high surface area, and tunable surface chemistry, allowing for controlled interactions with polymers, nanoparticles, small molecules, and biological materials. Industrial production of nanocelluloses is increasing rapidly with several companies already producing on the tons-per-day scale, intensifying the quest for viable products across many sectors. While the hydrophilicity of the nanocellulose interface has posed a challenge to the use of CNCs and CNFs as reinforcing agents in conventional plastics, it is a significant benefit for creating reinforced or structured hydrogel composites (or, when dried, aerogels) exhibiting both mechanical reinforcement and a host of other desirable properties. In this context, this Review describes the quickly growing field of hydrogels and aerogels incorporating nanocelluloses; over 200 references are summarized in comprehensive tables ...

Abstract: Printing sensors and electronics over flexible substrates are an area of significant interest due to low-cost fabrication and possibility of obtaining multifunctional electronics over large areas. Over the years, a number of printing technologies have been developed to pattern a wide range of electronic materials on diverse substrates. As further expansion of printed technologies is expected in future for sensors and electronics, it is opportune to review the common features, the complementarities, and the challenges associated with various printing technologies. This paper presents a comprehensive review of various printing technologies, commonly used substrates and electronic materials. Various solution/dry printing and contact/noncontact printing technologies have been assessed on the basis of technological, materials, and process-related developments in the field. Critical challenges in various printing techniques and potential research directions have been highlighted. Possibilities of merging various printing methodologies have been explored to extend the lab developed standalone systems to high-speed roll-to-roll production lines for system level integration.

Abstract: Some energy services and industrial processes-such as long-distance freight transport, air travel, highly reliable electricity, and steel and cement manufacturing-are particularly difficult to provide without adding carbon dioxide (CO2) to the atmosphere. Rapidly growing demand for these services, combined with long lead times for technology development and long lifetimes of energy infrastructure, make decarbonization of these services both essential and urgent. We examine barriers and opportunities associated with these difficult-to-decarbonize services and processes, including possible technological solutions and research and development priorities. A range of existing technologies could meet future demands for these services and processes without net addition of CO2 to the atmosphere, but their use may depend on a combination of cost reductions via research and innovation, as well as coordinated deployment and integration of operations across currently discrete energy industries.

Abstract: Increasingly, colleges across the world are contending with rising rates of mental disorders, and in many cases, the demand for services on campus far exceeds the available resources. The present study reports initial results from the first stage of the WHO World Mental Health International College Student project, in which a series of surveys in 19 colleges across 8 countries (Australia, Belgium, Germany, Mexico, Northern Ireland, South Africa, Spain, United States) were carried out with the aim of estimating prevalence and basic sociodemographic correlates of common mental disorders among first-year college students. Web-based self-report questionnaires administered to incoming first-year students (45.5% pooled response rate) screened for six common lifetime and 12-month DSM-IV mental disorders: major depression, mania/hypomania, generalized anxiety disorder, panic disorder, alcohol use disorder, and substance use disorder. We focus on the 13,984 respondents who were full-time students: 35% of whom screened positive for at least one of the common lifetime disorders assessed and 31% screened positive for at least one 12-month disorder. Syndromes typically had onsets in early to middle adolescence and persisted into the year of the survey. Although relatively modest, the strongest correlates of screening positive were older age, female sex, unmarried-deceased parents, no religious affiliation, nonheterosexual identification and behavior, low secondary school ranking, and extrinsic motivation for college enrollment. The weakness of these associations means that the syndromes considered are widely distributed with respect to these variables in the student population. Although the extent to which cost-effective treatment would reduce these risks is unclear, the high level of need for mental health services implied by these results represents a major challenge to institutions of higher education and governments. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Abstract: Proliferation and activation of microglia in the brain, concentrated around amyloid plaques, is a prominent feature of Alzheimer’s disease (AD). Human genetics data point to a key role for microglia in the pathogenesis of AD. The majority of risk genes for AD are highly expressed (and many are selectively expressed) by microglia in the brain. There is mounting evidence that microglia protect against the incidence of AD, as impaired microglial activities and altered microglial responses to β-amyloid are associated with increased AD risk. On the other hand, there is also abundant evidence that activated microglia can be harmful to neurons. Microglia can mediate synapse loss by engulfment of synapses, likely via a complement-dependent mechanism; they can also exacerbate tau pathology and secrete inflammatory factors that can injure neurons directly or via activation of neurotoxic astrocytes. Gene expression profiles indicate multiple states of microglial activation in neurodegenerative disease settings, which might explain the disparate roles of microglia in the development and progression of AD pathology.

Abstract: We present a method that achieves state-of-the-art results for synthesizing novel views of complex scenes by optimizing an underlying continuous volumetric scene function using a sparse set of input views. Our algorithm represents a scene using a fully-connected (non-convolutional) deep network, whose input is a single continuous 5D coordinate (spatial location (x, y, z) and viewing direction \((\theta ,\phi )\)) and whose output is the volume density and view-dependent emitted radiance at that spatial location. We synthesize views by querying 5D coordinates along camera rays and use classic volume rendering techniques to project the output colors and densities into an image. Because volume rendering is naturally differentiable, the only input required to optimize our representation is a set of images with known camera poses. We describe how to effectively optimize neural radiance fields to render photorealistic novel views of scenes with complicated geometry and appearance, and demonstrate results that outperform prior work on neural rendering and view synthesis. View synthesis results are best viewed as videos, so we urge readers to view our supplementary video for convincing comparisons.

Abstract: Spontaneously occurring mutations accumulate in somatic cells throughout a person's lifetime. The majority of these mutations do not have a noticeable effect, but some can alter key cellular functions. Early somatic mutations can cause developmental disorders, whereas the progressive accumulation of mutations throughout life can lead to cancer and contribute to aging. Genome sequencing has revolutionized our understanding of somatic mutation in cancer, providing a detailed view of the mutational processes and genes that drive cancer. Yet, fundamental gaps remain in our knowledge of how normal cells evolve into cancer cells. We briefly summarize a number of the lessons learned over 5 years of cancer genome sequencing and discuss their implications for our understanding of cancer progression and aging.

Abstract: Image segmentation is a key topic in image processing and computer vision with applications such as scene understanding, medical image analysis, robotic perception, video surveillance, augmented reality, and image compression, among many others. Various algorithms for image segmentation have been developed in the literature. Recently, due to the success of deep learning models in a wide range of vision applications, there has been a substantial amount of works aimed at developing image segmentation approaches using deep learning models. In this survey, we provide a comprehensive review of the literature at the time of this writing, covering a broad spectrum of pioneering works for semantic and instance-level segmentation, including fully convolutional pixel-labeling networks, encoder-decoder architectures, multi-scale and pyramid based approaches, recurrent networks, visual attention models, and generative models in adversarial settings. We investigate the similarity, strengths and challenges of these deep learning models, examine the most widely used datasets, report performances, and discuss promising future research directions in this area.

Abstract: Standard accuracy metrics indicate that reading comprehension systems are making rapid progress, but the extent to which these systems truly understand language remains unclear. To reward systems with real language understanding abilities, we propose an adversarial evaluation scheme for the Stanford Question Answering Dataset (SQuAD). Our method tests whether systems can answer questions about paragraphs that contain adversarially inserted sentences, which are automatically generated to distract computer systems without changing the correct answer or misleading humans. In this adversarial setting, the accuracy of sixteen published models drops from an average of 75% F1 score to 36%; when the adversary is allowed to add ungrammatical sequences of words, average accuracy on four models decreases further to 7%. We hope our insights will motivate the development of new models that understand language more precisely.

Abstract: We present an effective implementation of the Prime Probe side-channel attack against the last-level cache. We measure the capacity of the covert channel the attack creates and demonstrate a cross-core, cross-VM attack on multiple versions of GnuPG. Our technique achieves a high attack resolution without relying on weaknesses in the OS or virtual machine monitor or on sharing memory between attacker and victim.

Abstract: The Canadian Network for Mood and Anxiety Treatments (CANMAT) previously published treatment guidelines for bipolar disorder in 2005, along with international commentaries and subsequent updates in 2007, 2009, and 2013. The last two updates were published in collaboration with the International Society for Bipolar Disorders (ISBD). These 2018 CANMAT and ISBD Bipolar Treatment Guidelines represent the significant advances in the field since the last full edition was published in 2005, including updates to diagnosis and management as well as new research into pharmacological and psychological treatments. These advances have been translated into clear and easy to use recommendations for first, second, and third- line treatments, with consideration given to levels of evidence for efficacy, clinical support based on experience, and consensus ratings of safety, tolerability, and treatment-emergent switch risk. New to these guidelines, hierarchical rankings were created for first and second- line treatments recommended for acute mania, acute depression, and maintenance treatment in bipolar I disorder. Created by considering the impact of each treatment across all phases of illness, this hierarchy will further assist clinicians in making evidence-based treatment decisions. Lithium, quetiapine, divalproex, asenapine, aripiprazole, paliperidone, risperidone, and cariprazine alone or in combination are recommended as first-line treatments for acute mania. First-line options for bipolar I depression include quetiapine, lurasidone plus lithium or divalproex, lithium, lamotrigine, lurasidone, or adjunctive lamotrigine. While medications that have been shown to be effective for the acute phase should generally be continued for the maintenance phase in bipolar I disorder, there are some exceptions (such as with antidepressants); and available data suggest that lithium, quetiapine, divalproex, lamotrigine, asenapine, and aripiprazole monotherapy or combination treatments should be considered first-line for those initiating or switching treatment during the maintenance phase. In addition to addressing issues in bipolar I disorder, these guidelines also provide an overview of, and recommendations for, clinical management of bipolar II disorder, as well as advice on specific populations, such as women at various stages of the reproductive cycle, children and adolescents, and older adults. There are also discussions on the impact of specific psychiatric and medical comorbidities such as substance use, anxiety, and metabolic disorders. Finally, an overview of issues related to safety and monitoring is provided. The CANMAT and ISBD groups hope that these guidelines become a valuable tool for practitioners across the globe.

Abstract: Focus group discussion is frequently used as a qualitative approach to gain an in-depth understanding of social issues. The method aims to obtain data from a purposely selected group of individuals rather than from a statistically representative sample of a broader population. Even though the application of this method in conservation research has been extensive, there are no critical assessment of the application of the technique. In addition, there are no readily available guidelines for conservation researchers. Here, we reviewed the applications of focus group discussion within biodiversity and conservation research between 1996 and April 2017. We begin with a brief explanation of the technique for first-time users. We then discuss in detail the empirical applications of this technique in conservation based on a structured literature review (using Scopus). The screening process resulted in 170 articles, the majority of which (67, n = 114,) were published between 2011 and 2017. Rarely was the method used as a stand-alone technique. The number of participants per focus group (where reported) ranged from 3 to 21 participants with a median of 10 participants. There were seven (median) focus group meetings per study. Focus group discussion sessions lasted for 90 (median) minutes. Four main themes emerged from the review: understanding of people's perspectives regarding conservation (32), followed by the assessment of conservation and livelihoods practices (21), examination of challenges and impacts of resource management interventions (19) and documenting the value of indigenous knowledge systems (16). Most of the studies were in Africa (n=76), followed by Asia (n=44), and Europe (n=30). We noted serious gaps in the reporting of the methodological details in the reviewed papers. More than half of the studies (n=101) did not report the sample size and group size (n=93), whereas 54 studies did not mention the number of focus group discussion sessions while reporting results. Rarely have the studies provided any information on the rationale for choosing the technique. We have provided guidelines to improve the standard of reporting and future application of the technique for conservation. © 2018 The Authors. Methods in Ecology and Evolution © 2018 British Ecological Society

Abstract: Species extinctions have defined the global biodiversity crisis, but extinction begins with loss in abundance of individuals that can result in compositional and functional changes of ecosystems. Using multiple and independent monitoring networks, we report population losses across much of the North American avifauna over 48 years, including once-common species and from most biomes. Integration of range-wide population trajectories and size estimates indicates a net loss approaching 3 billion birds, or 29% of 1970 abundance. A continent-wide weather radar network also reveals a similarly steep decline in biomass passage of migrating birds over a recent 10-year period. This loss of bird abundance signals an urgent need to address threats to avert future avifaunal collapse and associated loss of ecosystem integrity, function, and services.

Abstract: We apply recurrent neural networks (RNN) on a new domain, namely recommender systems. Real-life recommender systems often face the problem of having to base recommendations only on short session-based data (e.g. a small sportsware website) instead of long user histories (as in the case of Netflix). In this situation the frequently praised matrix factorization approaches are not accurate. This problem is usually overcome in practice by resorting to item-to-item recommendations, i.e. recommending similar items. We argue that by modeling the whole session, more accurate recommendations can be provided. We therefore propose an RNN-based approach for session-based recommendations. Our approach also considers practical aspects of the task and introduces several modifications to classic RNNs such as a ranking loss function that make it more viable for this specific problem. Experimental results on two data-sets show marked improvements over widely used approaches.

Abstract: We present Argoverse, a dataset designed to support autonomous vehicle perception tasks including 3D tracking and motion forecasting. Argoverse includes sensor data collected by a fleet of autonomous vehicles in Pittsburgh and Miami as well as 3D tracking annotations, 300k extracted interesting vehicle trajectories, and rich semantic maps. The sensor data consists of 360 degree images from 7 cameras with overlapping fields of view, forward-facing stereo imagery, 3D point clouds from long range LiDAR, and 6-DOF pose. Our 290km of mapped lanes contain rich geometric and semantic metadata which are not currently available in any public dataset. All data is released under a Creative Commons license at Argoverse.org. In baseline experiments, we use map information such as lane direction, driveable area, and ground height to improve the accuracy of 3D object tracking. We use 3D object tracking to mine for more than 300k interesting vehicle trajectories to create a trajectory forecasting benchmark. Motion forecasting experiments ranging in complexity from classical methods (k-NN) to LSTMs demonstrate that using detailed vector maps with lane-level information substantially reduces prediction error. Our tracking and forecasting experiments represent only a superficial exploration of the potential of rich maps in robotic perception. We hope that Argoverse will enable the research community to explore these problems in greater depth.

Abstract: Lithium-ion batteries are now reaching the energy density limits set by their electrode materials, requiring new paradigms for Li(+) and electron hosting in solid-state electrodes. Reversible oxygen redox in the solid state in particular has the potential to enable high energy density as it can deliver excess capacity beyond the theoretical transition-metal redox-capacity at a high voltage. Nevertheless, the structural and chemical origin of the process is not understood, preventing the rational design of better cathode materials. Here, we demonstrate how very specific local Li-excess environments around oxygen atoms necessarily lead to labile oxygen electrons that can be more easily extracted and participate in the practical capacity of cathodes. The identification of the local structural components that create oxygen redox sets a new direction for the design of high-energy-density cathode materials.