Abstract: Hate speech detection on Twitter is critical for applications like controversial event extraction, building AI chatterbots, content recommendation, and sentiment analysis. We define this task as being able to classify a tweet as racist, sexist or neither. The complexity of the natural language constructs makes this task very challenging. We perform extensive experiments with multiple deep learning architectures to learn semantic word embeddings to handle this complexity. Our experiments on a benchmark dataset of 16K annotated tweets show that such deep learning methods outperform state-of-the-art char/word n-gram methods by ~18 F1 points.

Abstract: Importance In the United States, national associations of individual dietary factors with specific cardiometabolic diseases are not well established. Objective To estimate associations of intake of 10 specific dietary factors with mortality due to heart disease, stroke, and type 2 diabetes (cardiometabolic mortality) among US adults. Design, Setting, and Participants A comparative risk assessment model incorporated data and corresponding uncertainty on population demographics and dietary habits from National Health and Nutrition Examination Surveys (1999-2002: n = 8104; 2009-2012: n = 8516); estimated associations of diet and disease from meta-analyses of prospective studies and clinical trials with validity analyses to assess potential bias; and estimated disease-specific national mortality from the National Center for Health Statistics. Exposures Consumption of 10 foods/nutrients associated with cardiometabolic diseases: fruits, vegetables, nuts/seeds, whole grains, unprocessed red meats, processed meats, sugar-sweetened beverages (SSBs), polyunsaturated fats, seafood omega-3 fats, and sodium. Main Outcomes and Measures Estimated absolute and percentage mortality due to heart disease, stroke, and type 2 diabetes in 2012. Disease-specific and demographic-specific (age, sex, race, and education) mortality and trends between 2002 and 2012 were also evaluated. Results In 2012, 702 308 cardiometabolic deaths occurred in US adults, including 506 100 from heart disease (371 266 coronary heart disease, 35 019 hypertensive heart disease, and 99 815 other cardiovascular disease), 128 294 from stroke (16 125 ischemic, 32 591 hemorrhagic, and 79 578 other), and 67 914 from type 2 diabetes. Of these, an estimated 318 656 (95% uncertainty interval [UI], 306 064-329 755; 45.4%) cardiometabolic deaths per year were associated with suboptimal intakes—48.6% (95% UI, 46.2%-50.9%) of cardiometabolic deaths in men and 41.8% (95% UI, 39.3%-44.2%) in women; 64.2% (95% UI, 60.6%-67.9%) at younger ages (25-34 years) and 35.7% (95% UI, 33.1%-38.1%) at older ages (≥75 years); 53.1% (95% UI, 51.6%-54.8%) among blacks, 50.0% (95% UI, 48.2%-51.8%) among Hispanics, and 42.8% (95% UI, 40.9%-44.5%) among whites; and 46.8% (95% UI, 44.9%-48.7%) among lower-, 45.7% (95% UI, 44.2%-47.4%) among medium-, and 39.1% (95% UI, 37.2%-41.2%) among higher-educated individuals. The largest numbers of estimated diet-related cardiometabolic deaths were related to high sodium (66 508 deaths in 2012; 9.5% of all cardiometabolic deaths), low nuts/seeds (59 374; 8.5%), high processed meats (57 766; 8.2%), low seafood omega-3 fats (54 626; 7.8%), low vegetables (53 410; 7.6%), low fruits (52 547; 7.5%), and high SSBs (51 694; 7.4%). Between 2002 and 2012, population-adjusted US cardiometabolic deaths per year decreased by 26.5%. The greatest decline was associated with insufficient polyunsaturated fats (−20.8% relative change [95% UI, −18.5% to −22.8%]), nuts/seeds (−18.0% [95% UI, −14.6% to −21.0%]), and excess SSBs (−14.5% [95% UI, −12.0% to −16.9%]). The greatest increase was associated with unprocessed red meats (+14.4% [95% UI, 9.1%-19.5%]). Conclusions and Relevance Dietary factors were estimated to be associated with a substantial proportion of deaths from heart disease, stroke, and type 2 diabetes. These results should help identify priorities, guide public health planning, and inform strategies to alter dietary habits and improve health.

Abstract: OBJECTIVE: The aim of this study was to test the hypothesis that youths with obesity, when removed from structured school activities and confined to their homes during the coronavirus disease 2019 pandemic, will display unfavorable trends in lifestyle behaviors. METHODS: The sample included 41 children and adolescents with obesity participating in a longitudinal observational study located in Verona, Italy. Lifestyle information including diet, activity, and sleep behaviors was collected at baseline and 3 weeks into the national lockdown during which home confinement was mandatory. Changes in outcomes over the two study time points were evaluated for significance using paired t tests. RESULTS: There were no changes in reported vegetable intake; fruit intake increased (P = 0.055) during the lockdown. By contrast, potato chip, red meat, and sugary drink intakes increased significantly during the lockdown (P value range, 0.005 to < 0.001). Time spent in sports activities decreased by 2.30 (SD 4.60) h/wk (P = 0.003), and sleep time increased by 0.65 (SD 1.29) h/d (P = 0.003). Screen time increased by 4.85 (SD 2.40) h/d (P < 0.001). CONCLUSIONS: Recognizing these adverse collateral effects of the coronavirus disease 2019 pandemic lockdown is critical in avoiding depreciation of weight control efforts among youths afflicted with excess adiposity. Depending on duration, these untoward lockdown effects may have a lasting impact on a child's or adolescent's adult adiposity level.

Abstract: Measuring the morphological parameters of galaxies is a key requirement for studying their formation and evolution. Surveys such as the Sloan Digital Sky Survey have resulted in the availability of very large collections of images, which have permitted population-wide analyses of galaxy morphology. Morphological analysis has traditionally been carried out mostly via visual inspection by trained experts, which is time consuming and does not scale to large (≳104) numbers of images. Although attempts have been made to build automated classification systems, these have not been able to achieve the desired level of accuracy. The Galaxy Zoo project successfully applied a crowdsourcing strategy, inviting online users to classify images by answering a series of questions. Unfortunately, even this approach does not scale well enough to keep up with the increasing availability of galaxy images. We present a deep neural network model for galaxy morphology classification which exploits translational and rotational symmetry. It was developed in the context of the Galaxy Challenge, an international competition to build the best model for morphology classification based on annotated images from the Galaxy Zoo project. For images with high agreement among the Galaxy Zoo participants, our model is able to reproduce their consensus with near-perfect accuracy (>99 per cent) for most questions. Confident model predictions are highly accurate, which makes the model suitable for filtering large collections of images and forwarding challenging images to experts for manual annotation. This approach greatly reduces the experts’ workload without affecting accuracy. The application of these algorithms to larger sets of training data will be critical for analysing results from future surveys such as the Large Synoptic Survey Telescope.

Abstract: The boreal forest, one of the largest biomes on Earth, provides ecosystem services that benefit society at levels ranging from local to global. Currently, about two-thirds of the area covered by this biome is under some form of management, mostly for wood production. Services such as climate regulation are also provided by both the unmanaged and managed boreal forests. Although most of the boreal forests have retained the resilience to cope with current disturbances, projected environmental changes of unprecedented speed and amplitude pose a substantial threat to their health. Management options to reduce these threats are available and could be implemented, but economic incentives and a greater focus on the boreal biome in international fora are needed to support further adaptation and mitigation actions.

Abstract: We introduce the first end-to-end coreference resolution model and show that it significantly outperforms all previous work without using a syntactic parser or hand-engineered mention detector. The key idea is to directly consider all spans in a document as potential mentions and learn distributions over possible antecedents for each. The model computes span embeddings that combine context-dependent boundary representations with a head-finding attention mechanism. It is trained to maximize the marginal likelihood of gold antecedent spans from coreference clusters and is factored to enable aggressive pruning of potential mentions. Experiments demonstrate state-of-the-art performance, with a gain of 1.5 F1 on the OntoNotes benchmark and by 3.1 F1 using a 5-model ensemble, despite the fact that this is the first approach to be successfully trained with no external resources.

Abstract: Importance Children living in poverty generally perform poorly in school, with markedly lower standardized test scores and lower educational attainment. The longer children live in poverty, the greater their academic deficits. These patterns persist to adulthood, contributing to lifetime-reduced occupational attainment. Objective To determine whether atypical patterns of structural brain development mediate the relationship between household poverty and impaired academic performance. Design, Setting, and Participants Longitudinal cohort study analyzing 823 magnetic resonance imaging scans of 389 typically developing children and adolescents aged 4 to 22 years from the National Institutes of Health Magnetic Resonance Imaging Study of Normal Brain Development with complete sociodemographic and neuroimaging data. Data collection began in November 2001 and ended in August 2007. Participants were screened for a variety of factors suspected to adversely affect brain development, recruited at 6 data collection sites across the United States, assessed at baseline, and followed up at 24-month intervals for a total of 3 periods. Each study center used community-based sampling to reflect regional and overall US demographics of income, race, and ethnicity based on the US Department of Housing and Urban Development definitions of area income. One-quarter of sample households reported the total family income below 200% of the federal poverty level. Repeated observations were available for 301 participants. Exposure Household poverty measured by family income and adjusted for family size as a percentage of the federal poverty level. Main Outcomes and Measures Children’s scores on cognitive and academic achievement assessments and brain tissue, including gray matter of the total brain, frontal lobe, temporal lobe, and hippocampus. Results Poverty is tied to structural differences in several areas of the brain associated with school readiness skills, with the largest influence observed among children from the poorest households. Regional gray matter volumes of children below 1.5 times the federal poverty level were 3 to 4 percentage points below the developmental norm ( P P P Conclusions and Relevance The influence of poverty on children’s learning and achievement is mediated by structural brain development. To avoid long-term costs of impaired academic functioning, households below 150% of the federal poverty level should be targeted for additional resources aimed at remediating early childhood environments.

Abstract: We present a new major release of the OpenSubtitles collection of parallel corpora. The release is compiled from a large database of movie and TV subtitles and includes a total of 1689 bitexts spanning 2.6 billion sentences across 60 languages. The release also incorporates a number of enhancements in the preprocessing and alignment of the subtitles, such as the automatic correction of OCR errors and the use of meta-data to estimate the quality of each subtitle and score subtitle pairs.

Abstract: Ferroptosis is a novel type of cell death with distinct properties and recognizing functions involved in physical conditions or various diseases including cancers. The fast-growing studies of ferroptosis in cancer have boosted a perspective for its usage in cancer therapeutics. Here, we review the current findings of ferroptosis regulation and especially focus on the function of ncRNAs in mediating the process of cell ferroptotic death and on how ferroptosis was in relation to other regulated cell deaths. Aberrant ferroptosis in diverse cancer types and tissues were summarized, and we elaborated recent data about the novel actors of some “conventional” drugs or natural compounds as ferroptosis inducers in cancer. Finally, we deliberate future orientation for ferroptosis in cancer cells and current unsettled issues, which may forward the speed of clinical use of ferroptosis induction in cancer treatment.

Abstract: Ageing is a major risk factor for the development of many diseases, prominently including neurodegenerative disorders such as Alzheimer disease and Parkinson disease. A hallmark of many age-related diseases is the dysfunction in protein homeostasis (proteostasis), leading to the accumulation of protein aggregates. In healthy cells, a complex proteostasis network, comprising molecular chaperones and proteolytic machineries and their regulators, operates to ensure the maintenance of proteostasis. These factors coordinate protein synthesis with polypeptide folding, the conservation of protein conformation and protein degradation. However, sustaining proteome balance is a challenging task in the face of various external and endogenous stresses that accumulate during ageing. These stresses lead to the decline of proteostasis network capacity and proteome integrity. The resulting accumulation of misfolded and aggregated proteins affects, in particular, postmitotic cell types such as neurons, manifesting in disease. Recent analyses of proteome-wide changes that occur during ageing inform strategies to improve proteostasis. The possibilities of pharmacological augmentation of the capacity of proteostasis networks hold great promise for delaying the onset of age-related pathologies associated with proteome deterioration and for extending healthspan. Misfolded proteins have a high propensity to form potentially toxic aggregates. Cells employ a complex network of processes, involving chaperones and proteolytic machineries that ensure proper protein folding and remodel or degrade misfolded species and aggregates. This proteostasis network declines with age, which can be linked to human degenerative diseases.

Abstract: The Planck full mission cosmic microwave background(CMB) temperature and E-mode polarization maps are analysed to obtain constraints on primordial non-Gaussianity(NG). Using three classes of optimal bispectrum estimators - separable template-fitting (KSW), binned, and modal - we obtain consistent values for the local, equilateral, and orthogonal bispectrum amplitudes, quoting as our final result from temperature alone fNL^local=2.5+\-5.7, fNL^equil=-16+\-70 and fNL^ortho=-34+\-33(68%CL). Combining temperature and polarization data we obtain fNL^local=0.8+\-5.0, fNL^equil=-4+\-43 and fNL^ortho=-26+\-21 (68%CL). The results are based on cross-validation of these estimators on simulations, are stable across component separation techniques, pass an extensive suite of tests, and are consistent with Minkowski functionals based measurements. The effect of time-domain de-glitching systematics on the bispectrum is negligible. In spite of these test outcomes we conservatively label the results including polarization data as preliminary, owing to a known mismatch of the noise model in simulations and the data. Beyond fNL estimates, we present model-independent reconstructions of the CMB bispectrum and derive constraints on early universe scenarios that generate NG, including general single-field and axion inflation, initial state modifications, parity-violating tensor bispectra, and directionally dependent vector models. We also present a wide survey of scale-dependent oscillatory bispectra, and we look for isocurvature NG. Our constraint on the local primordial trispectrum amplitude is gNL^local=(-9.0+\-7.7)x10^4 (68%CL), and we perform an analysis of additional trispectrum shapes. The global picture is one of consistency with the premises of the LambdaCDM cosmology, namely that the structure we observe today was sourced by adiabatic, passive, Gaussian, and primordial seed perturbations.[abridged]

Abstract: We analyze the convergence rate of the alternating direction method of multipliers (ADMM) for minimizing the sum of two or more nonsmooth convex separable functions subject to linear constraints. Previous analysis of the ADMM typically assumes that the objective function is the sum of only two convex functions defined on two separable blocks of variables even though the algorithm works well in numerical experiments for three or more blocks. Moreover, there has been no rate of convergence analysis for the ADMM without strong convexity in the objective function. In this paper we establish the global R-linear convergence of the ADMM for minimizing the sum of any number of convex separable functions, assuming that a certain error bound condition holds true and the dual stepsize is sufficiently small. Such an error bound condition is satisfied for example when the feasible set is a compact polyhedron and the objective function consists of a smooth strictly convex function composed with a linear mapping, and a nonsmooth $$\ell _1$$l1 regularizer. This result implies the linear convergence of the ADMM for contemporary applications such as LASSO without assuming strong convexity of the objective function.

Abstract: We report the observation of a quantum anomalous Hall effect in twisted bilayer graphene showing Hall resistance quantized to within .1\% of the von Klitzing constant $h/e^2$ at zero magnetic field.The effect is driven by intrinsic strong correlations, which polarize the electron system into a single spin and valley resolved moire miniband with Chern number $C=1$. In contrast to extrinsic, magnetically doped systems, the measured transport energy gap $\Delta/k_B\approx 27$~K is larger than the Curie temperature for magnetic ordering $T_C\approx 9$~K, and Hall quantization persists to temperatures of several Kelvin. Remarkably, we find that electrical currents as small as 1~nA can be used to controllably switch the magnetic order between states of opposite polarization, forming an electrically rewritable magnetic memory.

Abstract: In the last year, new models and methods for pretraining and transfer learning have driven striking performance improvements across a range of language understanding tasks. The GLUE benchmark, introduced a little over one year ago, offers a single-number metric that summarizes progress on a diverse set of such tasks, but performance on the benchmark has recently surpassed the level of non-expert humans, suggesting limited headroom for further research. In this paper we present SuperGLUE, a new benchmark styled after GLUE with a new set of more difficult language understanding tasks, a software toolkit, and a public leaderboard. SuperGLUE is available at https://super.gluebenchmark.com.

Abstract: N6-methyladenosine (m6A) is an abundant internal RNA modification in both coding and non-coding RNAs that is catalysed by the METTL3-METTL14 methyltransferase complex. However, the specific role of these enzymes in cancer is still largely unknown. Here we define a pathway that is specific for METTL3 and is implicated in the maintenance of a leukaemic state. We identify METTL3 as an essential gene for growth of acute myeloid leukaemia cells in two distinct genetic screens. Downregulation of METTL3 results in cell cycle arrest, differentiation of leukaemic cells and failure to establish leukaemia in immunodeficient mice. We show that METTL3, independently of METTL14, associates with chromatin and localizes to the transcriptional start sites of active genes. The vast majority of these genes have the CAATT-box binding protein CEBPZ present at the transcriptional start site, and this is required for recruitment of METTL3 to chromatin. Promoter-bound METTL3 induces m6A modification within the coding region of the associated mRNA transcript, and enhances its translation by relieving ribosome stalling. We show that genes regulated by METTL3 in this way are necessary for acute myeloid leukaemia. Together, these data define METTL3 as a regulator of a chromatin-based pathway that is necessary for maintenance of the leukaemic state and identify this enzyme as a potential therapeutic target for acute myeloid leukaemia.

Abstract: Reversibility of hepatic fibrosis and cirrhosis following antiviral therapy for hepatitis B or C has advanced the prospect of developing antifibrotic therapies for patients with chronic liver diseases, especially non-alcoholic steatohepatitis. Mechanisms of fibrosis have focused on hepatic stellate cells, which become fibrogenic myofibroblasts during injury through ‘activation’, and are at the nexus of efforts to define novel drug targets. Recent studies have clarified pathways of stellate cell gene regulation and epigenetics, emerging pathways of fibrosis regression through the recruitment and amplification of fibrolytic macrophages, nuanced responses of discrete inflammatory cell subsets and the identification of the ‘ductular reaction’ as a marker of severe injury and repair. Based on our expanded knowledge of fibrosis pathogenesis, attention is now directed towards strategies for antifibrotic therapies and regulatory challenges for conducting clinical trials with these agents. New therapies are attempting to: 1) Control or cure the primary disease or reduce tissue injury; 2) Target receptor-ligand interactions and intracellular signaling; 3) Inhibit fibrogenesis; and 4) Promote resolution of fibrosis. Progress is urgently needed in validating non-invasive markers of fibrosis progression and regression that can supplant biopsy and shorten the duration of clinical trials. Both scientific and clinical challenges remain, however the past three decades of steady progress in understanding liver fibrosis have contributed to an emerging translational success story, with realistic hopes for antifibrotic therapies to treat patients with chronic liver disease in the near future.

Abstract: Many studies conducted during the last decade suggest the mental health benefits of green and blue spaces. We aimed to systematically review the available literature on the long-term mental health benefits of residential green and blue spaces by including studies that used standardized tools or objective measures of both the exposures and the outcomes of interest. We followed the PRISMA statement guidelines for reporting systematic reviews and meta-analysis. In total 28 studies were included in the systematic review. We found limited evidence for a causal relationship between surrounding greenness and mental health in adults, whereas the evidence was inadequate in children. The evidence was also inadequate for the other exposures evaluated (access to green spaces, quality of green spaces, and blue spaces) in both adults and children. The main limitation was the limited number of studies, together with the heterogeneity regarding exposure assessment. Given the increase in mental health problems and the current rapid urbanization worldwide, results of the present systematic review should be taken into account in future urban planning. However, further research is needed to provide more consistent evidence and more detailed information on the mechanisms and the characteristics of the green and blue spaces that promote better mental health. We provide recommendations for future studies in order to provide consistent and evidence-based recommendations for policy makers.

Abstract: The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) updates NASA's previous satellite era (1980 - onward) reanalysis system to include additional observations and improvements to the Goddard Earth Observing System, Version 5 (GEOS-5) Earth system model. As a major step towards a full Integrated Earth Systems Analysis (IESA), in addition to meteorological observations, MERRA-2 now includes assimilation of aerosol optical depth (AOD) from various ground- and space-based remote sensing platforms. Here, in the first of a pair of studies, we document the MERRA-2 aerosol assimilation, including a description of the prognostic model (GEOS-5 coupled to the GOCART aerosol module), aerosol emissions, and the quality control of ingested observations. We provide initial validation and evaluation of the analyzed AOD fields using independent observations from ground, aircraft, and shipborne instruments. We demonstrate the positive impact of the AOD assimilation on simulated aerosols by comparing MERRA-2 aerosol fields to an identical control simulation that does not include AOD assimilation. Having shown the AOD evaluation, we take a first look at aerosol-climate interactions by examining the shortwave, clear-sky aerosol direct radiative effect. In our companion paper, we evaluate and validate available MERRA-2 aerosol properties not directly impacted by the AOD assimilation (e.g. aerosol vertical distribution and absorption). Importantly, while highlighting the skill of the MERRA-2 aerosol assimilation products, both studies point out caveats that must be considered when using this new reanalysis product for future studies of aerosols and their interactions with weather and climate.

Abstract: We synthesized a two-dimensional (2D) crystalline covalent organic framework (sp2c-COF) that was designed to be fully π-conjugated and constructed from all sp2 carbons by C=C condensation reactions of tetrakis(4-formylphenyl)pyrene and 1,4-phenylenediacetonitrile. The C=C linkages topologically connect pyrene knots at regular intervals into a 2D lattice with π conjugations extended along both x and y directions and develop an eclipsed layer framework rather than the more conventionally obtained disordered structures. The sp2c-COF is a semiconductor with a discrete band gap of 1.9 electron volts and can be chemically oxidized to enhance conductivity by 12 orders of magnitude. The generated radicals are confined on the pyrene knots, enabling the formation of a paramagnetic carbon structure with high spin density. The sp2 carbon framework induces ferromagnetic phase transition to develop spin-spin coherence and align spins unidirectionally across the material.

Abstract: The pgopher program is a general purpose program for simulating and fitting molecular spectra, particularly the rotational structure. The current version can handle linear molecules, symmetric tops and asymmetric tops and many possible transitions, both allowed and forbidden, including multiphoton and Raman spectra in addition to the common electric dipole absorptions. Many different interactions can be included in the calculation, including those arising from electron and nuclear spin, and external electric and magnetic fields. Multiple states and interactions between them can also be accounted for, limited only by available memory. Fitting of experimental data can be to line positions (in many common formats), intensities or band contours and the parameters determined can be level populations as well as rotational constants. pgopher is provided with a powerful and flexible graphical user interface to simplify many of the tasks required in simulating, understanding and fitting molecular spectra, including Fortrat diagrams and energy level plots in addition to overlaying experimental and simulated spectra. The program is open source, and can be compiled with open source tools. This paper provides a formal description of the operation of version 9.1.

Abstract: We propose a practical method for L0 norm regularization for neural networks:pruning the network during training by encouraging weights to become exactly zero. Such regularization is interesting since (1) it can greatly speed up training and inference, and (2) it can improve generalization. AIC and BIC, well-known model selection criteria, are special cases of L0 regularization. However, since the L0 norm of weights is non-differentiable, we cannot incorporate it directly as a regularization term in the objective function. We propose a solution through the inclusion of a collection of non-negative stochastic gates, which collectively determine which weights to set to zero. We show that, somewhat surprisingly,for certain distributions over the gates, the expected L0 regularized objective is differentiable with respect to the distribution parameters. We further propose the hard concrete distribution for the gates, which is obtained by “stretching” a binary concrete distribution and then transforming its samples with a hard-sigmoid. The parameters of the distribution over the gates can then be jointly optimized with the original network parameters. As a result our method allows for straightforward and efficient learning of model structures with stochastic gradient descent and allows for conditional computation in a principled way. We perform various experiments to demonstrate the effectiveness of the resulting approach and regularizer.

Abstract: The mangrove forests of Southeast Asia are highly biodiverse and provide multiple ecosystem services upon which millions of people depend. Mangroves enhance fisheries and coastal protection, and store among the highest densities of carbon of any ecosystem globally. Mangrove forests have experienced extensive deforestation owing to global demand for commodities, and previous studies have identified the expansion of aquaculture as largely responsible. The proportional conversion of mangroves to different land use types has not been systematically quantified across Southeast Asia, however, particularly in recent years. In this study we apply a combined geographic information system and remote sensing method to quantify the key proximate drivers (i.e., replacement land uses) of mangrove deforestation in Southeast Asia between 2000 and 2012. Mangrove forests were lost at an average rate of 0.18% per year, which is lower than previously published estimates. In total, more than 100,000 ha of mangroves were removed during the study period, with aquaculture accounting for 30% of this total forest change. The rapid expansion of rice agriculture in Myanmar, and the sustained conversion of mangroves to oil palm plantations in Malaysia and Indonesia, are identified as additional increasing and under-recognized threats to mangrove ecosystems. Our study highlights frontiers of mangrove deforestation in the border states of Myanmar, on Borneo, and in Indonesian Papua. To implement policies that conserve mangrove forests across Southeast Asia, it is essential to consider the national and subnational variation in the land uses that follow deforestation.

Abstract: In the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. Deep learning has advanced rapidly since the early 2000s and now demonstrates state-of-the-art performance in various fields. Accordingly, application of deep learning in bioinformatics to gain insight from data has been emphasized in both academia and industry. Here, we review deep learning in bioinformatics, presenting examples of current research. To provide a useful and comprehensive perspective, we categorize research both by the bioinformatics domain (i.e., omics, biomedical imaging, biomedical signal processing) and deep learning architecture (i.e., deep neural networks, convolutional neural networks, recurrent neural networks, emergent architectures) and present brief descriptions of each study. Additionally, we discuss theoretical and practical issues of deep learning in bioinformatics and suggest future research directions. We believe that this review will provide valuable insights and serve as a starting point for researchers to apply deep learning approaches in their bioinformatics studies.

Abstract: This guideline from the U.S. Preventive Services Task Force addresses aspirin use for the prevention of cardiovascular disease and colorectal cancer. The recommendations apply to adults aged 40 yea...

Abstract: This article is focused on the importance and influence of Industry 4.0 and consequently the Internet-connected technologies for the creation of value added for organizations and society. The contribution of the article is mainly conceptual. With the development of the Internet, the Internet of things that is central to the new industrial revolution has led to “Industry 4.0.” The aim of this article is to synthesize the known theory and practices of Industry 4.0, and to investigate the changes that will result from Industry 4.0 and with the development of the Internet of things.

Abstract: All around the globe, humans have greatly altered the abiotic and biotic environment with ever-increasing speed. One defining feature of the Anthropocene epoch is the erosion of biogeographical barriers by human-mediated dispersal of species into new regions, where they can naturalize and cause ecological, economic and social damage. So far, no comprehensive analysis of the global accumulation and exchange of alien plant species between continents has been performed, primarily because of a lack of data. Here we bridge this knowledge gap by using a unique global database on the occurrences of naturalized alien plant species in 481 mainland and 362 island regions. In total, 13,168 plant species, corresponding to 3.9% of the extant global vascular flora, or approximately the size of the native European flora, have become naturalized somewhere on the globe as a result of human activity. North America has accumulated the largest number of naturalized species, whereas the Pacific Islands show the fastest increase in species numbers with respect to their land area. Continents in the Northern Hemisphere have been the major donors of naturalized alien species to all other continents. Our results quantify for the first time the extent of plant naturalizations worldwide, and illustrate the urgent need for globally integrated efforts to control, manage and understand the spread of alien species.