Abstract: The distribution of elements in galaxies provides a wealth of information about their production sites and their subsequent mixing into the interstellar medium. Here we investigate the distribution of elements within stars in the IllustrisTNG simulations. In particular, we analyze the abundance ratios of magnesium and europium in Milky Way-like galaxies from the TNG100 simulation (stellar masses ${\log} (M_\star / {\rm M}_\odot) \sim 9.7 - 11.2$). As abundances of magnesium and europium for individual stars in the Milky Way are observed across a variety of spatial locations and metallicities, comparison with the stellar abundances in our more than $850$ Milky Way-like galaxies provides stringent constraints on our chemical evolutionary methods. To this end we use the magnesium to iron ratio as a proxy for the effects of our SNII and SNIa metal return prescription, and a means to compare our simulated abundances to a wide variety of galactic observations. The europium to iron ratio tracks the rare ejecta from neutron star -- neutron star mergers, the assumed primary site of europium production in our models, which in turn is a sensitive probe of the effects of metal diffusion within the gas in our simulations. We find that europium abundances in Milky Way-like galaxies show no correlation with assembly history, present day galactic properties, and average galactic stellar population age. In general, we reproduce the europium to iron spread at low metallicities observed in the Milky Way, with the level of enhancement being sensitive to gas properties during redshifts $z \approx 2-4$. We show that while the overall normalization of [Eu/Fe] is susceptible to resolution and post-processing assumptions, the relatively large spread of [Eu/Fe] at low [Fe/H] when compared to that at high [Fe/H] is very robust.

Abstract: Unprecedented bioaccumulation and biomagnification of heavy metals (HMs) in the environment have become a dilemma for all living organisms including plants. HMs at toxic levels have the capability to interact with several vital cellular biomolecules such as nuclear proteins and DNA, leading to excessive augmentation of reactive oxygen species (ROS). This would inflict serious morphological, metabolic, and physiological anomalies in plants ranging from chlorosis of shoot to lipid peroxidation and protein degradation. In response, plants are equipped with a repertoire of mechanisms to counteract heavy metal (HM) toxicity. The key elements of these are chelating metals by forming phytochelatins (PCs) or metallothioneins (MTs) metal complex at the intra- and intercellular level, which is followed by the removal of HM ions from sensitive sites or vacuolar sequestration of ligand-metal complex. Nonenzymatically synthesized compounds such as proline (Pro) are able to strengthen metal-detoxification capacity of intracellular antioxidant enzymes. Another important additive component of plant defense system is symbiotic association with arbuscular mycorrhizal (AM) fungi. AM can effectively immobilize HMs and reduce their uptake by host plants via binding metal ions to hyphal cell wall and excreting several extracellular biomolecules. Additionally, AM fungi can enhance activities of antioxidant defense machinery of plants.

Abstract: Psychologists must be able to test both for the presence of an effect and for the absence of an effect. In addition to testing against zero, researchers can use the two one-sided tests (TOST) proce...

Abstract: Cascade is a classic yet powerful architecture that has boosted performance on various tasks. However, how to introduce cascade to instance segmentation remains an open question. A simple combination of Cascade R-CNN and Mask R-CNN only brings limited gain. In exploring a more effective approach, we find that the key to a successful instance segmentation cascade is to fully leverage the reciprocal relationship between detection and segmentation. In this work, we propose a new framework, Hybrid Task Cascade (HTC), which differs in two important aspects: (1) instead of performing cascaded refinement on these two tasks separately, it interweaves them for a joint multi-stage processing; (2) it adopts a fully convolutional branch to provide spatial context, which can help distinguishing hard foreground from cluttered background. Overall, this framework can learn more discriminative features progressively while integrating complementary features together in each stage. Without bells and whistles, a single HTC obtains 38.4% and 1.5% improvement over a strong Cascade Mask R-CNN baseline on MSCOCO dataset. Moreover, our overall system achieves 48.6 mask AP on the test-challenge split, ranking 1st in the COCO 2018 Challenge Object Detection Task. Code is available at https://github.com/open-mmlab/mmdetection.

Abstract: Summary Background There is no standard of care for adjuvant therapy for patients with hepatocellular carcinoma. This trial was designed to assess the efficacy and safety of sorafenib versus placebo as adjuvant therapy in patients with hepatocellular carcinoma after surgical resection or local ablation. Methods We undertook this phase 3, double-blind, placebo-controlled study of patients with hepatocellular carcinoma with a complete radiological response after surgical resection (n=900) or local ablation (n=214) in 202 sites (hospitals and research centres) in 28 countries. Patients were randomly assigned (1:1) to receive 400 mg oral sorafenib or placebo twice a day, for a maximum of 4 years, according to a block randomisation scheme (block size of four) using an interactive voice-response system. Patients were stratified by curative treatment, geography, Child-Pugh status, and recurrence risk. The primary outcome was recurrence-free survival assessed after database cut-off on Nov 29, 2013. We analysed efficacy in the intention-to-treat population and safety in randomly assigned patients receiving at least one study dose. The final analysis is reported. This study is registered with ClinicalTrials.gov, number NCT00692770. Findings We screened 1602 patients between Aug 15, 2008, and Nov 17, 2010, and randomly assigned 1114 patients. Of 556 patients in the sorafenib group, 553 (>99%) received the study treatment and 471 (85%) terminated treatment. Of 558 patients in the placebo group, 554 (99%) received the study treatment and 447 (80%) terminated treatment. Median duration of treatment and mean daily dose were 12·5 months (IQR 2·6–35·8) and 577 mg per day (SD 212·8) for sorafenib, compared with 22·2 months (8·1–38·8) and 778·0 mg per day (79·8) for placebo. Dose modification was reported for 497 (89%) of 559 patients in the sorafenib group and 206 (38%) of 548 patients in the placebo group. At final analysis, 464 recurrence-free survival events had occurred (270 in the placebo group and 194 in the sorafenib group). Median follow-up for recurrence-free survival was 8·5 months (IQR 2·9–19·5) in the sorafenib group and 8·4 months (2·9–19·8) in the placebo group. We noted no difference in median recurrence-free survival between the two groups (33·3 months in the sorafenib group vs 33·7 months in the placebo group; hazard ratio [HR] 0·940; 95% CI 0·780–1·134; one-sided p=0·26). The most common grade 3 or 4 adverse events were hand-foot skin reaction (154 [28%] of 559 patients in the sorafenib group vs four [ vs five [ Interpretation Our data indicate that sorafenib is not an effective intervention in the adjuvant setting for hepatocellular carcinoma following resection or ablation. Funding Bayer HealthCare Pharmaceuticals and Onyx Pharmaceuticals.

Abstract: BackgroundMaternal anxiety negatively influences child outcomes. Reliable estimates have not been established because of varying published prevalence rates.AimsTo establish summary estimates for the prevalence of maternal anxiety in the antenatal and postnatal periods.MethodWe searched multiple databases including MEDLINE, Embase, and PsycINFO to identify studies published up to January 2016 with data on the prevalence of antenatal or postnatal anxiety. Data were extracted from published reports and any missing information was requested from investigators. Estimates were pooled using random-effects meta-analyses.ResultsWe reviewed 23 468 abstracts, retrieved 783 articles and included 102 studies incorporating 221 974 women from 34 countries. The prevalence for self-reported anxiety symptoms was 18.2% (95% CI 13.6-22.8) in the first trimester, 19.1% (95% CI 15.9-22.4) in the second trimester and 24.6% (95% CI 21.2-28.0) in the third trimester. The overall prevalence for a clinical diagnosis of any anxiety disorder was 15.2% (95% CI 9.0-21.4) and 4.1% (95% CI 1.9-6.2) for a generalised anxiety disorder. Postnatally, the prevalence for anxiety symptoms overall at 1-24 weeks was 15.0% (95% CI 13.7-16.4). The prevalence for any anxiety disorder over the same period was 9.9% (95% CI 6.1-13.8), and 5.7% (95% CI 2.3-9.2) for a generalised anxiety disorder. Rates were higher in low- to middle-income countries.ConclusionsResults suggest perinatal anxiety is highly prevalent and merits clinical attention. Research is warranted to develop evidence-based interventions.

Abstract: A pyramid has expressed the idea of hierarchy of medical evidence for so long, that not all evidence is the same. Systematic reviews and meta-analyses have been placed at the top of this pyramid for several good reasons. However, there are several counterarguments to this placement. We suggest another way of looking at the evidence-based medicine pyramid and explain how systematic reviews and meta-analyses are tools for consuming evidence—that is, appraising, synthesising and applying evidence.

Abstract: Visual attention has been successfully applied in structural prediction tasks such as visual captioning and question answering. Existing visual attention models are generally spatial, i.e., the attention is modeled as spatial probabilities that re-weight the last conv-layer feature map of a CNN encoding an input image. However, we argue that such spatial attention does not necessarily conform to the attention mechanism --- a dynamic feature extractor that combines contextual fixations over time, as CNN features are naturally spatial, channel-wise and multi-layer. In this paper, we introduce a novel convolutional neural network dubbed SCA-CNN that incorporates Spatial and Channel-wise Attentions in a CNN. In the task of image captioning, SCA-CNN dynamically modulates the sentence generation context in multi-layer feature maps, encoding where (i.e., attentive spatial locations at multiple layers) and what (i.e., attentive channels) the visual attention is. We evaluate the proposed SCA-CNN architecture on three benchmark image captioning datasets: Flickr8K, Flickr30K, and MSCOCO. It is consistently observed that SCA-CNN significantly outperforms state-of-the-art visual attention-based image captioning methods.

Abstract: BACKGROUND: Considerable research has documented that exposure to traumatic events has negative effects on physical and mental health. Much less research has examined the predictors of traumatic event exposure. Increased understanding of risk factors for exposure to traumatic events could be of considerable value in targeting preventive interventions and anticipating service needs. METHOD: General population surveys in 24 countries with a combined sample of 68 894 adult respondents across six continents assessed exposure to 29 traumatic event types. Differences in prevalence were examined with cross-tabulations. Exploratory factor analysis was conducted to determine whether traumatic event types clustered into interpretable factors. Survival analysis was carried out to examine associations of sociodemographic characteristics and prior traumatic events with subsequent exposure. RESULTS: Over 70% of respondents reported a traumatic event; 30.5% were exposed to four or more. Five types - witnessing death or serious injury, the unexpected death of a loved one, being mugged, being in a life-threatening automobile accident, and experiencing a life-threatening illness or injury - accounted for over half of all exposures. Exposure varied by country, sociodemographics and history of prior traumatic events. Being married was the most consistent protective factor. Exposure to interpersonal violence had the strongest associations with subsequent traumatic events. CONCLUSIONS: Given the near ubiquity of exposure, limited resources may best be dedicated to those that are more likely to be further exposed such as victims of interpersonal violence. Identifying mechanisms that account for the associations of prior interpersonal violence with subsequent trauma is critical to develop interventions to prevent revictimization. Language: en

Abstract: A European League Against Rheumatism (EULAR) task force was established to define points to consider on use of antirheumatic drugs before pregnancy, and during pregnancy and lactation. Based on a systematic literature review and pregnancy exposure data from several registries, statements on the compatibility of antirheumatic drugs during pregnancy and lactation were developed. The level of agreement among experts in regard to statements and propositions of use in clinical practice was established by Delphi voting. The task force defined 4 overarching principles and 11 points to consider for use of antirheumatic drugs during pregnancy and lactation. Compatibility with pregnancy and lactation was found for antimalarials, sulfasalazine, azathioprine, ciclosporin, tacrolimus, colchicine, intravenous immunoglobulin and glucocorticoids. Methotrexate, mycophenolate mofetil and cyclophosphamide require discontinuation before conception due to proven teratogenicity. Insufficient documentation in regard to fetal safety implies the discontinuation of leflunomide, tofacitinib as well as abatacept, rituximab, belimumab, tocilizumab, ustekinumab and anakinra before a planned pregnancy. Among biologics tumour necrosis factor inhibitors are best studied and appear reasonably safe with first and second trimester use. Restrictions in use apply for the few proven teratogenic drugs and the large proportion of medications for which insufficient safety data for the fetus/child are available. Effective drug treatment of active inflammatory rheumatic disease is possible with reasonable safety for the fetus/child during pregnancy and lactation. The dissemination of the data to health professionals and patients as well as their implementation into clinical practice may help to improve the management of pregnant and lactating patients with rheumatic disease.

Abstract: Cytoscape is one of the most successful network biology analysis and visualization tools, but because of its interactive nature, its role in creating reproducible, scalable, and novel workflows has been limited. We describe Cytoscape Automation (CA), which marries Cytoscape to highly productive workflow systems, for example, Python/R in Jupyter/RStudio. We expose over 270 Cytoscape core functions and 34 Cytoscape apps as REST-callable functions with standardized JSON interfaces backed by Swagger documentation. Independent projects to create and publish Python/R native CA interface libraries have reached an advanced stage, and a number of automation workflows are already published.

Abstract: This paper considers the argument for obesity as a chronic relapsing disease process. Obesity is viewed from an epidemiological model, with an agent affecting the host and producing disease. Food is the primary agent, particularly foods that are high in energy density such as fat, or in sugar-sweetened beverages. An abundance of food, low physical activity and several other environmental factors interact with the genetic susceptibility of the host to produce positive energy balance. The majority of this excess energy is stored as fat in enlarged, and often more numerous fat cells, but some lipid may infiltrate other organs such as the liver (ectopic fat). The enlarged fat cells and ectopic fat produce and secrete a variety of metabolic, hormonal and inflammatory products that produce damage in organs such as the arteries, heart, liver, muscle and pancreas. The magnitude of the obesity and its adverse effects in individuals may relate to the virulence or toxicity of the environment and its interaction with the host. Thus, obesity fits the epidemiological model of a disease process except that the toxic or pathological agent is food rather than a microbe. Reversing obesity will prevent most of its detrimental effects.

Abstract: The explosive growth in video streaming gives rise to challenges on performing video understanding at high accuracy and low computation cost. Conventional 2D CNNs are computationally cheap but cannot capture temporal relationships; 3D CNN based methods can achieve good performance but are computationally intensive, making it expensive to deploy. In this paper, we propose a generic and effective Temporal Shift Module (TSM) that enjoys both high efficiency and high performance. Specifically, it can achieve the performance of 3D CNN but maintain 2D CNN's complexity. TSM shifts part of the channels along the temporal dimension; thus facilitate information exchanged among neighboring frames. It can be inserted into 2D CNNs to achieve temporal modeling at zero computation and zero parameters. We also extended TSM to online setting, which enables real-time low-latency online video recognition and video object detection. TSM is accurate and efficient: it ranks the first place on the Something-Something leaderboard upon publication; on Jetson Nano and Galaxy Note8, it achieves a low latency of 13ms and 35ms for online video recognition. The code is available at: this https URL.

Abstract: The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10(-33); 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.

Abstract: BACKGROUND: The robustness of F-test to non-normality has been studied from the 1930s through to the present day. However, this extensive body of research has yielded contradictory results, there being evidence both for and against its robustness. This study provides a systematic examination of F-test robustness to violations of normality in terms of Type I error, considering a wide variety of distributions commonly found in the health and social sciences. METHOD: We conducted a Monte Carlo simulation study involving a design with three groups and several known and unknown distributions. The manipulated variables were: Equal and unequal group sample sizes; group sample size and total sample size; coefficient of sample size variation; shape of the distribution and equal or unequal shapes of the group distributions; and pairing of group size with the degree of contamination in the distribution. RESULTS: The results showed that in terms of Type I error the F-test was robust in 100% of the cases studied, independently of the manipulated conditions. // Antecedentes: las consecuencias de la violacion de la normalidad sobre la robustez del estadistico F han sido estudiadas desde 1930 y siguen siendo de interes en la actualidad. Sin embargo, aunque la investigacion ha sido extensa, los resultados son contradictorios, encontrandose evidencia a favor y en contra de su robustez. El presente estudio presenta un analisis sistematico de la robustez del estadistico F en terminos de error de Tipo I ante violaciones de la normalidad, considerando una amplia variedad de distribuciones frecuentemente encontradas en ciencias sociales y de la salud. METODO: se ha realizado un estudio de simulacion Monte Carlo considerando un diseno de tres grupos y diferentes distribuciones conocidas y no conocidas. Las variables manipuladas han sido: igualdad o desigualdad del tamano de los grupos, tamano muestral total y de los grupos; coeficiente de variacion del tamano muestral; forma de la distribucion e igualdad o desigualdad de la forma en los grupos; y emparejamiento entre el tamano muestral con el grado de contaminacion en la distribucion. RESULTADOS: los resultados muestran que el estadistico F es robusto en terminos de error de Tipo I en el 100% de los casos estudiados, independientemente de las condiciones manipuladas.

Abstract: For dengue viruses 1 to 4 (DENV1-4), a specific range of antibody titer has been shown to enhance viral replication in vitro and severe disease in animal models. Although suspected, such antibody-dependent enhancement of severe disease has not been shown to occur in humans. Using multiple statistical approaches to study a long-term pediatric cohort in Nicaragua, we show that risk of severe dengue disease is highest within a narrow range of preexisting anti-DENV antibody titers. By contrast, we observe protection from all symptomatic dengue disease at high antibody titers. Thus, immune correlates of severe dengue must be evaluated separately from correlates of protection against symptomatic disease. These results have implications for studies of dengue pathogenesis and for vaccine development, because enhancement, not just lack of protection, is of concern.

Abstract: In this note we analyze the temporal dynamics of the coronavirus disease 2019 outbreak in China, Italy and France in the time window 22 / 01 − 15 / 03 / 2020 . A first analysis of simple day-lag maps points to some universality in the epidemic spreading, suggesting that simple mean-field models can be meaningfully used to gather a quantitative picture of the epidemic spreading, and notably the height and time of the peak of confirmed infected individuals. The analysis of the same data within a simple susceptible-infected-recovered-deaths model indicates that the kinetic parameter that describes the rate of recovery seems to be the same, irrespective of the country, while the infection and death rates appear to be more variable. The model places the peak in Italy around March 21st 2020, with a peak number of infected individuals of about 26000 (not including recovered and dead) and a number of deaths at the end of the epidemics of about 18,000. Since the confirmed cases are believed to be between 10 and 20% of the real number of individuals who eventually get infected, the apparent mortality rate of COVID-19 falls between 4% and 8% in Italy, while it appears substantially lower, between 1% and 3% in China. Based on our calculations, we estimate that 2500 ventilation units should represent a fair figure for the peak requirement to be considered by health authorities in Italy for their strategic planning. Finally, a simulation of the effects of drastic containment measures on the outbreak in Italy indicates that a reduction of the infection rate indeed causes a quench of the epidemic peak. However, it is also seen that the infection rate needs to be cut down drastically and quickly to observe an appreciable decrease of the epidemic peak and mortality rate. This appears only possible through a concerted and disciplined, albeit painful, effort of the population as a whole.

Abstract: Adiponectin is the most abundant peptide secreted by adipocytes, whose reduction plays a central role in obesity-related diseases, including insulin resistance/type 2 diabetes and cardiovascular disease. In addition to adipocytes, other cell types, such as skeletal and cardiac myocytes and endothelial cells, can also produce this adipocytokine. Adiponectin effects are mediated by adiponectin receptors, which occur as two isoforms (AdipoR1 and AdipoR2). Adiponectin has direct actions in liver, skeletal muscle, and the vasculature.Adiponectin exists in the circulation as varying molecular weight forms, produced by multimerization. Several endoplasmic reticulum ER-associated proteins, including ER oxidoreductase 1-α (Ero1-α), ER resident protein 44 (ERp44), disulfide-bond A oxidoreductase-like protein (DsbA-L), and glucose-regulated protein 94 (GPR94), have recently been found to be involved in the assembly and secretion of higher-order adiponectin complexes. Recent data indicate that the high-molecular weight (HMW) complexes have the predominant action in metabolic tissues. Studies have shown that adiponectin administration in humans and rodents has insulin-sensitizing, anti-atherogenic, and anti-inflammatory effects, and, in certain settings, also decreases body weight. Therefore, adiponectin replacement therapy in humans may suggest potential versatile therapeutic targets in the treatment of obesity, insulin resistance/type 2 diabetes, and atherosclerosis. The current knowledge on regulation and function of adiponectin in obesity, insulin resistance, and cardiovascular disease is summarized in this review.

Abstract: Neural summarization produces outputs that are fluent and readable, but which can be poor at content selection, for instance often copying full sentences from the source document This work explores the use of data-efficient content selectors to over-determine phrases in a source document that should be part of the summary We use this selector as a bottom-up attention step to constrain the model to likely phrases We show that this approach improves the ability to compress text, while still generating fluent summaries This two-step process is both simpler and higher performing than other end-to-end content selection models, leading to significant improvements on ROUGE for both the CNN-DM and NYT corpus Furthermore, the content selector can be trained with as little as 1,000 sentences making it easy to transfer a trained summarizer to a new domain

Abstract: Humans gather information through conversations involving a series of interconnected questions and answers. For machines to assist in information gathering, it is therefore essential to enable them to answer conversational questions. We introduce CoQA, a novel dataset for building Conversational Question Answering systems. Our dataset contains 127k questions with answers, obtained from 8k conversations about text passages from seven diverse domains. The questions are conversational, and the answers are free-form text with their corresponding evidence highlighted in the passage. We analyze CoQA in depth and show that conversational questions have challenging phenomena not present in existing reading comprehension datasets, e.g., coreference and pragmatic reasoning. We evaluate strong dialogue and reading comprehension models on CoQA. The best system obtains an F1 score of 65.4%, which is 23.4 points behind human performance (88.8%), indicating there is ample room for improvement. We present CoQA as a challenge to the community at https://stanfordnlp.github.io/coqa

Abstract: More than 90% of common variants associated with complex traits do not affect proteins directly, but instead the circuits that control gene expression. This has increased the urgency of understanding the regulatory genome as a key component for translating genetic results into mechanistic insights and ultimately therapeutics. To address this challenge, we developed HaploReg (http://compbio.mit.edu/HaploReg) to aid the functional dissection of genome-wide association study (GWAS) results, the prediction of putative causal variants in haplotype blocks, the prediction of likely cell types of action, and the prediction of candidate target genes by systematic mining of comparative, epigenomic and regulatory annotations. Since first launching the website in 2011, we have greatly expanded HaploReg, increasing the number of chromatin state maps to 127 reference epigenomes from ENCODE 2012 and Roadmap Epigenomics, incorporating regulator binding data, expanding regulatory motif disruption annotations, and integrating expression quantitative trait locus (eQTL) variants and their tissue-specific target genes from GTEx, Geuvadis, and other recent studies. We present these updates as HaploReg v4, and illustrate a use case of HaploReg for attention deficit hyperactivity disorder (ADHD)-associated SNPs with putative brain regulatory mechanisms.

Abstract: The Journal of Physiology and Experimental Physiology have always used UK legislation as the basis of their policy on ethical standards in experiments on non-human animals. However, for international journals with authors, editors and referees from outside the UK the policy can lack transparency and is sometimes cumbersome, requiring the intervention of a Senior Ethics Reviewer or advice from external experts familiar with UK legislation. The journals have therefore decided to set out detailed guidelines for how authors should report experimental procedures that involve animals. As well as helping authors, this new clarity will facilitate the review process and decision making where there are questions regarding animal ethics.

Abstract: Three-dimensional topological (crystalline) insulators are materials with an insulating bulk but conducting surface states that are topologically protected by time-reversal (or spatial) symmetries. We extend the notion of three-dimensional topological insulators to systems that host no gapless surface states but exhibit topologically protected gapless hinge states. Their topological character is protected by spatiotemporal symmetries of which we present two cases: (i) Chiral higher-order topological insulators protected by the combination of time-reversal and a fourfold rotation symmetry. Their hinge states are chiral modes, and the bulk topology is Z 2 -classified. (ii) Helical higher-order topological insulators protected by time-reversal and mirror symmetries. Their hinge states come in Kramers pairs, and the bulk topology is Z -classified. We provide the topological invariants for both cases. Furthermore, we show that SnTe as well as surface-modified Bi2TeI, BiSe, and BiTe are helical higher-order topological insulators and propose a realistic experimental setup to detect the hinge states.

Abstract: Key physiological functions of the liver, including glucose and lipid metabolism, become disturbed in the setting of non-alcoholic fatty liver disease (NAFLD) and may be associated with a systemic inflammatory 'milieu' initiated in part by liver-secreted cytokines and molecules. Consequently, the pathophysiological effects of NAFLD extend beyond the liver with a large body of clinical evidence demonstrating NAFLD to be independently associated with both prevalent and incident cardiovascular disease (CVD), chronic kidney disease (CKD) and type 2 diabetes mellitus (T2DM). The magnitude of risk of developing these extrahepatic diseases parallels the underlying severity of NAFLD, such that patients with non-alcoholic steatohepatitis (NASH) appear to be at greater risk of incident CVD, CKD and T2DM than those with simple steatosis. Other modifiers of risk may include genetic variants (eg, patatin-like phospholipase domain-containing 3 and trans-membrane 6 superfamily member 2 polymorphisms), visceral adipose tissue accumulation, dietary intake and the gut microbiome. Emerging data also suggest that NAFLD may be a risk factor for colonic neoplasia and reduced bone mineral density, especially among men. Importantly, improvement/resolution of NAFLD is associated with a reduced incidence of T2DM and improved kidney function, adding weight to causality and suggesting liver focused treatments may reduce risk of extrahepatic complications. Awareness of these associations is important for the clinicians such that CVD risk factor management, screening for T2DM and CKD are part of the routine management of patients with NAFLD.

Abstract: Deep neural networks have achieved impressive experimental results in image classification, but can surprisingly be unstable with respect to adversarial perturbations, that is, minimal changes to the input image that cause the network to misclassify it With potential applications including perception modules and end-to-end controllers for self-driving cars, this raises concerns about their safety We develop a novel automated verification framework for feed-forward multi-layer neural networks based on Satisfiability Modulo Theory (SMT) We focus on safety of image classification decisions with respect to image manipulations, such as scratches or changes to camera angle or lighting conditions that would result in the same class being assigned by a human, and define safety for an individual decision in terms of invariance of the classification within a small neighbourhood of the original image We enable exhaustive search of the region by employing discretisation, and propagate the analysis layer by layer Our method works directly with the network code and, in contrast to existing methods, can guarantee that adversarial examples, if they exist, are found for the given region and family of manipulations If found, adversarial examples can be shown to human testers and/or used to fine-tune the network We implement the techniques using Z3 and evaluate them on state-of-the-art networks, including regularised and deep learning networks We also compare against existing techniques to search for adversarial examples and estimate network robustness

Abstract: The central challenge of the 21st century is to develop economic, social, and governance systems capable of ending poverty and achieving sustainable levels of population and consumption while securing the life-support systems underpinning current and future human well-being. Essential to meeting this challenge is the incorporation of natural capital and the ecosystem services it provides into decision-making. We explore progress and crucial gaps at this frontier, reflecting upon the 10 y since the Millennium Ecosystem Assessment. We focus on three key dimensions of progress and ongoing challenges: raising awareness of the interdependence of ecosystems and human well-being, advancing the fundamental interdisciplinary science of ecosystem services, and implementing this science in decisions to restore natural capital and use it sustainably. Awareness of human dependence on nature is at an all-time high, the science of ecosystem services is rapidly advancing, and talk of natural capital is now common from governments to corporate boardrooms. However, successful implementation is still in early stages. We explore why ecosystem service information has yet to fundamentally change decision-making and suggest a path forward that emphasizes: (i) developing solid evidence linking decisions to impacts on natural capital and ecosystem services, and then to human well-being; (ii) working closely with leaders in government, business, and civil society to develop the knowledge, tools, and practices necessary to integrate natural capital and ecosystem services into everyday decision-making; and (iii) reforming institutions to change policy and practices to better align private short-term goals with societal long-term goals.

Abstract: Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive desktop software suite of interoperable COBRA methods. It has found widespread application in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. This protocol is an update to the COBRA Toolbox v.1.0 and v.2.0. Version 3.0 includes new methods for quality-controlled reconstruction, modeling, topological analysis, strain and experimental design, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimization solvers for multi-scale, multi-cellular, and reaction kinetic modeling, respectively. This protocol provides an overview of all these new features and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios. The COBRA Toolbox v.3.0 provides an unparalleled depth of COBRA methods.