Abstract: Since the outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, China, it has rapidly spread across many other countries. While the majority of patients were considered mild, critically ill pat...

Abstract: As the proverbial creatures of habit, people tend to repeat the same behaviors in recurring contexts. This review characterizes habits in terms of their cognitive, motivational, and neurobiological properties. In so doing, we identify three ways that habits interface with deliberate goal pursuit: First, habits form as people pursue goals by repeating the same responses in a given context. Second, as outlined in computational models, habits and deliberate goal pursuit guide actions synergistically, although habits are the efficient, default mode of response. Third, people tend to infer from the frequency of habit performance that the behavior must have been intended. We conclude by applying insights from habit research to understand stress and addiction as well as the design of effective interventions to change health and consumer behaviors.

Abstract: Scaling laws underpin unifying theories of biodiversity and are among the most predictively powerful relationships in biology. However, scaling laws developed for plants and animals often go untested or fail to hold for microorganisms. As a result, it is unclear whether scaling laws of biodiversity will span evolutionarily distant domains of life that encompass all modes of metabolism and scales of abundance. Using a global-scale compilation of ∼35,000 sites and ∼5.6⋅106 species, including the largest ever inventory of high-throughput molecular data and one of the largest compilations of plant and animal community data, we show similar rates of scaling in commonness and rarity across microorganisms and macroscopic plants and animals. We document a universal dominance scaling law that holds across 30 orders of magnitude, an unprecedented expanse that predicts the abundance of dominant ocean bacteria. In combining this scaling law with the lognormal model of biodiversity, we predict that Earth is home to upward of 1 trillion (1012) microbial species. Microbial biodiversity seems greater than ever anticipated yet predictable from the smallest to the largest microbiome.

Abstract: Engineering the electromagnetic environment of a nanometre-scale light emitter by use of a photonic cavity can significantly enhance its spontaneous emission rate, through cavity quantum electrodynamics in the Purcell regime. This effect can greatly reduce the lasing threshold of the emitter, providing a low-threshold laser system with small footprint, low power consumption and ultrafast modulation. An ultralow-threshold nanoscale laser has been successfully developed by embedding quantum dots into a photonic crystal cavity (PCC). However, several challenges impede the practical application of this architecture, including the random positions and compositional fluctuations of the dots, extreme difficulty in current injection, and lack of compatibility with electronic circuits. Here we report a new lasing strategy: an atomically thin crystalline semiconductor--that is, a tungsten diselenide monolayer--is non-destructively and deterministically introduced as a gain medium at the surface of a pre-fabricated PCC. A continuous-wave nanolaser operating in the visible regime is thereby achieved with an optical pumping threshold as low as 27 nanowatts at 130 kelvin, similar to the value achieved in quantum-dot PCC lasers. The key to the lasing action lies in the monolayer nature of the gain medium, which confines direct-gap excitons to within one nanometre of the PCC surface. The surface-gain geometry gives unprecedented accessibility and hence the ability to tailor gain properties via external controls such as electrostatic gating and current injection, enabling electrically pumped operation. Our scheme is scalable and compatible with integrated photonics for on-chip optical communication technologies.

Abstract: Optogenetics has revolutionized the experimental interrogation of neural circuits and holds promise for the treatment of neurological disorders It is limited, however, because visible light cannot penetrate deep inside brain tissue Upconversion nanoparticles (UCNPs) absorb tissue-penetrating near-infrared (NIR) light and emit wavelength-specific visible light Here, we demonstrate that molecularly tailored UCNPs can serve as optogenetic actuators of transcranial NIR light to stimulate deep brain neurons Transcranial NIR UCNP-mediated optogenetics evoked dopamine release from genetically tagged neurons in the ventral tegmental area, induced brain oscillations through activation of inhibitory neurons in the medial septum, silenced seizure by inhibition of hippocampal excitatory cells, and triggered memory recall UCNP technology will enable less-invasive optical neuronal activity manipulation with the potential for remote therapy

Abstract: We develop the topological band theory for systems described by non-Hermitian Hamiltonians, whose energy spectra are generally complex. After generalizing the notion of gapped band structures to the non-Hermitian case, we classify ``gapped'' bands in one and two dimensions by explicitly finding their topological invariants. We find nontrivial generalizations of the Chern number in two dimensions, and a new classification in one dimension, whose topology is determined by the energy dispersion rather than the energy eigenstates. We then study the bulk-edge correspondence and the topological phase transition in two dimensions. Different from the Hermitian case, the transition generically involves an extended intermediate phase with complex-energy band degeneracies at isolated ``exceptional points'' in momentum space. We also systematically classify all types of band degeneracies.

Abstract: A coronavirus (HCoV-19) has caused the novel coronavirus disease (COVID-19) outbreak in Wuhan, China. Preventing and reversing the cytokine storm may be the key to save the patients with severe COVID-19 pneumonia. Mesenchymal stem cells (MSCs) have been shown to possess a comprehensive powerful immunomodulatory function. This study aims to investigate whether MSC transplantation improves the outcome of 7 enrolled patients with COVID-19 pneumonia in Beijing YouAn Hospital, China, from Jan 23, 2020 to Feb 16, 2020. The clinical outcomes, as well as changes of inflammatory and immune function levels and adverse effects of 7 enrolled patients were assessed for 14 days after MSC injection. MSCs could cure or significantly improve the functional outcomes of seven patients without observed adverse effects. The pulmonary function and symptoms of these seven patients were significantly improved in 2 days after MSC transplantation. Among them, two common and one severe patient were recovered and discharged in 10 days after treatment. After treatment, the peripheral lymphocytes were increased, the C-reactive protein decreased, and the overactivated cytokine-secreting immune cells CXCR3+CD4+ T cells, CXCR3+CD8+ T cells, and CXCR3+ NK cells disappeared in 3-6 days. In addition, a group of CD14+CD11c+CD11bmid regulatory DC cell population dramatically increased. Meanwhile, the level of TNF-α was significantly decreased, while IL-10 increased in MSC treatment group compared to the placebo control group. Furthermore, the gene expression profile showed MSCs were ACE2- and TMPRSS2- which indicated MSCs are free from COVID-19 infection. Thus, the intravenous transplantation of MSCs was safe and effective for treatment in patients with COVID-19 pneumonia, especially for the patients in critically severe condition.

Abstract: Background Current approaches to predict cardiovascular risk fail to identify many people who would benefit from preventive treatment, while others receive unnecessary intervention. Machine-learning offers opportunity to improve accuracy by exploiting complex interactions between risk factors. We assessed whether machine-learning can improve cardiovascular risk prediction. Methods Prospective cohort study using routine clinical data of 378,256 patients from UK family practices, free from cardiovascular disease at outset. Four machine-learning algorithms (random forest, logistic regression, gradient boosting machines, neural networks) were compared to an established algorithm (American College of Cardiology guidelines) to predict first cardiovascular event over 10-years. Predictive accuracy was assessed by area under the ‘receiver operating curve’ (AUC); and sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) to predict 7.5% cardiovascular risk (threshold for initiating statins). Findings 24,970 incident cardiovascular events (6.6%) occurred. Compared to the established risk prediction algorithm (AUC 0.728, 95% CI 0.723–0.735), machine-learning algorithms improved prediction: random forest +1.7% (AUC 0.745, 95% CI 0.739–0.750), logistic regression +3.2% (AUC 0.760, 95% CI 0.755–0.766), gradient boosting +3.3% (AUC 0.761, 95% CI 0.755–0.766), neural networks +3.6% (AUC 0.764, 95% CI 0.759–0.769). The 78 highest achieving (neural networks) algorithm predicted 4,998/7,404 cases (sensitivity 79 67.5%, PPV 18.4%) and 53,458/75,585 non-cases (specificity 70.7%, NPV 95.7%), correctly predicting 355 (+7.6%) more patients who developed cardiovascular disease compared to the established algorithm. Conclusions Machine-learning significantly improves accuracy of cardiovascular risk prediction, increasing the number of patients identified who could benefit from preventive treatment, while avoiding unnecessary treatment of others.

Abstract: The alliance continues to be one of the most investigated variables related to success in psychotherapy irrespective of theoretical orientation. We define and illustrate the alliance (also conceptualized as therapeutic alliance, helping alliance, or working alliance) and then present a meta-analysis of 295 independent studies that covered more than 30,000 patients (published between 1978 and 2017) for face-to-face and Internet-based psychotherapy. The relation of the alliance and treatment outcome was investigated using a three-level meta-analysis with random-effects restricted maximum-likelihood estimators. The overall alliance-outcome association for face-to-face psychotherapy was r = .278 (95% confidence intervals [.256, .299], p < .0001; equivalent of d = .579). There was heterogeneity among the effect sizes, and 2% of the 295 effect sizes indicated negative correlations. The correlation for Internet-based psychotherapy was approximately the same (viz., r = .275, k = 23). These results confirm the robustness of the positive relation between the alliance and outcome. This relation remains consistent across assessor perspectives, alliance and outcome measures, treatment approaches, patient characteristics, and countries. The article concludes with causality considerations, research limitations, diversity considerations, and therapeutic practices. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Abstract: Recent work pre-training Transformers with self-supervised objectives on large text corpora has shown great success when fine-tuned on downstream NLP tasks including text summarization. However, pre-training objectives tailored for abstractive text summarization have not been explored. Furthermore there is a lack of systematic evaluation across diverse domains. In this work, we propose pre-training large Transformer-based encoder-decoder models on massive text corpora with a new self-supervised objective. In PEGASUS, important sentences are removed/masked from an input document and are generated together as one output sequence from the remaining sentences, similar to an extractive summary. We evaluated our best PEGASUS model on 12 downstream summarization tasks spanning news, science, stories, instructions, emails, patents, and legislative bills. Experiments demonstrate it achieves state-of-the-art performance on all 12 downstream datasets measured by ROUGE scores. Our model also shows surprising performance on low-resource summarization, surpassing previous state-of-the-art results on 6 datasets with only 1000 examples. Finally we validated our results using human evaluation and show that our model summaries achieve human performance on multiple datasets.

Abstract: Over the last decade, there has been an increasing focus on service across socioeconomic sectors coupled with transformational developments in information and communication technologies (ICTs). Together these developments are engendering dramatic new opportunities for service innovation, the study of which is both timely and important. Fully understanding these opportunities challenges us to question conventional approaches that construe service as a distinctive form of socioeconomic exchange (i.e., as services) and to reconsider what service means and thus how service innovation may develop. The aim of this special issue, therefore, is to bring together some of the latest scholarship from the Marketing and Information Systems disciplines to advance theoretical developments on service innovation in a digital age.

Abstract: Saliva Specimens to Detect SARS-CoV-2 Infection In this letter, the investigators report that saliva specimens and nasopharyngeal swab specimens had similar sensitivity in the detection of SARS-CoV...

Abstract: The TOR (target of rapamycin) kinase limits longevity by poorly understood mechanisms. Rapamycin suppresses the mammalian TORC1 complex, which regulates translation, and extends lifespan in diverse species, including mice. We show that rapamycin selectively blunts the pro-inflammatory phenotype of senescent cells. Cellular senescence suppresses cancer by preventing cell proliferation. However, as senescent cells accumulate with age, the senescence-associated secretory phenotype (SASP) can disrupt tissues and contribute to age-related pathologies, including cancer. MTOR inhibition suppressed the secretion of inflammatory cytokines by senescent cells. Rapamycin reduced IL6 and other cytokine mRNA levels, but selectively suppressed translation of the membrane-bound cytokine IL1A. Reduced IL1A diminished NF-κB transcriptional activity, which controls much of the SASP; exogenous IL1A restored IL6 secretion to rapamycin-treated cells. Importantly, rapamycin suppressed the ability of senescent fibroblasts to stimulate prostate tumour growth in mice. Thus, rapamycin might ameliorate age-related pathologies, including late-life cancer, by suppressing senescence-associated inflammation.

Abstract: Fullerenes have formed an integral part of high performance organic solar cells over the last 20 years, however their inherent limitations in terms of synthetic flexibility, cost and stability have acted as a motivation to develop replacements; the so-called non-fullerene electron acceptors. A rapid evolution of such materials has taken place over the last few years, yielding a number of promising candidates that can exceed the device performance of fullerenes and provide opportunities to improve upon the stability and processability of organic solar cells. In this review we explore the structure–property relationships of a library of non-fullerene acceptors, highlighting the important chemical modifications that have led to progress in the field and provide an outlook for future innovations in electron acceptors for use in organic photovoltaics.

Abstract: So far, roughly 40 quasars with redshifts greater than z = 6 have been discovered(1-8) Each quasar contains a black hole with a mass of about one billion solar masses (10(9) M-circle dot)(2,6,7,9-13) The existence of such black holes when the Universe was less than one billion years old presents substantial challenges to theories of the formation and growth of black holes and the coevolution of black holes and galaxies(14) Here we report the discovery of an ultraluminous quasar, SDSS J01001302+2802258, at redshift z = 630 It has an optical and near-infrared luminosity a few times greater than those of previously known z > 6 quasars On the basis of the deep absorption trough(15) on the blue side of the Lyman-alpha emission line in the spectrum, we estimate the proper size of the ionized proximity zone associated with the quasar to be about 26 million light years, larger than found with other z > 61 quasars with lower luminosities(16) We estimate (on the basis of a near-infrared spectrum) that the black hole has a mass of similar to 12 x 10(10) M-circle dot, which is consistent with the 13 x 10(10) M-circle dot derived by assuming an Eddington-limited accretion rate

Abstract: 3D printing has the potential to significantly change the field of microfluidics. The ability to fabricate a complete microfluidic device in a single step from a computer model has obvious attractions, but it is the ability to create truly three dimensional structures that will provide new microfluidic capability that is challenging, if not impossible to make with existing approaches. This critical review covers the current state of 3D printing for microfluidics, focusing on the four most frequently used printing approaches: inkjet (i3DP), stereolithography (SLA), two photon polymerisation (2PP) and extrusion printing (focusing on fused deposition modeling). It discusses current achievements and limitations, and opportunities for advancement to reach 3D printing's full potential.

Abstract: This paper explores the impacts that autonomous (also called self-driving, driverless or robotic) vehicles are likely to have on travel demands and transportation planning. It discusses autonomous vehicle benefits and costs, predicts their likely development and implementation based on experience with previous vehicle technologies, and explores how they will affect planning decisions such as optimal road, parking and public transit supply. The analysis indicates that some benefits, such as independent mobility for affluent non-drivers, may begin in the 2020s or 2030s, but most impacts, including reduced traffic and parking congestion (and therefore road and parking facility supply requirements), independent mobility for low-income people (and therefore reduced need to subsidize transit), increased safety, energy conservation and pollution reductions, will only be significant when autonomous vehicles become common and affordable, probably in the 2040s to 2060s, and some benefits may require prohibiting human-driven vehicles on certain roadways, which could take longer.

Abstract: We introduce the adversarially learned inference (ALI) model, which jointly learns a generation network and an inference network using an adversarial process. The generation network maps samples from stochastic latent variables to the data space while the inference network maps training examples in data space to the space of latent variables. An adversarial game is cast between these two networks and a discriminative network is trained to distinguish between joint latent/data-space samples from the generative network and joint samples from the inference network. We illustrate the ability of the model to learn mutually coherent inference and generation networks through the inspections of model samples and reconstructions and confirm the usefulness of the learned representations by obtaining a performance competitive with state-of-the-art on the semi-supervised SVHN and CIFAR10 tasks.

Abstract: Genomic copy number variants (CNVs) have been strongly implicated in the etiology of schizophrenia (SCZ). However, apart from a small number of risk variants, elucidation of the CNV contribution to risk has been difficult due to the rarity of risk alleles, all occurring in less than 1% of cases. We sought to address this obstacle through a collaborative effort in which we applied a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. We observed a global enrichment of CNV burden in cases (OR=1.11, P=5.7e-15), which persisted after excluding loci implicated in previous studies (OR=1.07, P=1.7e-6). CNV burden is also enriched for genes associated with synaptic function (OR = 1.68, P = 2.8e-11) and neurobehavioral phenotypes in mouse (OR = 1.18, P= 7.3e-5). We identified genome-wide significant support for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. We find support at a suggestive level for nine additional candidate susceptibility and protective loci, which consist predominantly of CNVs mediated by non-allelic homologous recombination (NAHR).

Abstract: The final results of the search for the lepton flavour violating decay $$\mathrm {\mu }^+ \rightarrow \mathrm {e}^+ \mathrm {\gamma }$$ based on the full dataset collected by the MEG experiment at the Paul Scherrer Institut in the period 2009–2013 and totalling $$7.5\times 10^{14}$$ stopped muons on target are presented. No significant excess of events is observed in the dataset with respect to the expected background and a new upper limit on the branching ratio of this decay of $$ \mathcal{B} (\mu ^+ \rightarrow \mathrm{e}^+ \gamma ) < 4.2 \times 10^{-13}$$ (90 % confidence level) is established, which represents the most stringent limit on the existence of this decay to date.

Abstract: . Extreme haze episodes repeatedly shrouded Beijing during the winter of 2012–2013, causing major environmental and health problems. To better understand these extreme events, we performed a model-assisted analysis of the hourly observation data of PM2.5 and its major chemical compositions. The synthetic analysis shows that (1) the severe winter haze was driven by stable synoptic meteorological conditions over northeastern China, and not by an abrupt increase in anthropogenic emissions. (2) Secondary species, including organics, sulfate, nitrate, and ammonium, were the major constituents of PM2.5 during this period. (3) Due to the dimming effect of high loading of aerosol particles, gaseous oxidant concentrations decreased significantly, suggesting a reduced production of secondary aerosols through gas-phase reactions. Surprisingly, the observational data reveals an enhanced production rate of secondary aerosols, suggesting an important contribution from other formation pathways, most likely heterogeneous reactions. These reactions appeared to be more efficient in producing secondary inorganics aerosols than organic aerosols resulting in a strongly elevated fraction of inorganics during heavily polluted periods. (4) Moreover, we found that high aerosol concentration was a regional phenomenon. The accumulation process of aerosol particles occurred successively from cities southeast of Beijing. The apparent sharp increase in PM2.5 concentration of up to several hundred μg m−3 per hour recorded in Beijing represented rapid recovery from an interruption to the continuous pollution accumulation over the region, rather than purely local chemical production. This suggests that regional transport of pollutants played an important role during these severe pollution events.

Abstract: Recently, along with the rapid development of mobile communication technology, edge computing theory and techniques have been attracting more and more attention from global researchers and engineers, which can significantly bridge the capacity of cloud and requirement of devices by the network edges, and thus can accelerate content delivery and improve the quality of mobile services. In order to bring more intelligence to edge systems, compared to traditional optimization methodology, and driven by the current deep learning techniques, we propose to integrate the Deep Reinforcement Learning techniques and Federated Learning framework with mobile edge systems, for optimizing mobile edge computing, caching and communication. And thus, we design the "In-Edge AI" framework in order to intelligently utilize the collaboration among devices and edge nodes to exchange the learning parameters for a better training and inference of the models, and thus to carry out dynamic system-level optimization and application-level enhancement while reducing the unnecessary system communication load. "In-Edge AI" is evaluated and proved to have near-optimal performance but relatively low overhead of learning, while the system is cognitive and adaptive to mobile communication systems. Finally, we discuss several related challenges and opportunities for unveili

Abstract: In this review, the clinical features of Parkinson's disease, both motor and non-motor, are described in the context of the progression of the disease. Also briefly discussed are the major treatment strategies and their complications. Parkinson's disease is a slowly progressing neurodegenerative disorder, causing impaired motor function with slow movements, tremor and gait and balance disturbances. A variety of non-motor symptoms are common in Parkinson's disease. They include disturbed autonomic function with orthostatic hypotension, constipation and urinary disturbances, a variety of sleep disorders and a spectrum of neuropsychiatric symptoms. This article describes the different clinical symptoms that may occur and the clinical course of the disease. This article is part of a special issue on Parkinson disease.

Abstract: The family of 2D materials grows day by day, drastically expanding the scope of possible phenomena to be explored in two dimensions, as well as the possible van der Waals heterostructures that one can create. Such 2D materials currently cover a vast range of properties. Until recently, this family has been missing one crucial member - 2D magnets. The situation has changed over the last two years with the introduction of a variety of atomically-thin magnetic crystals. Here we will discuss the difference between magnetic states in 2D materials and in bulk crystals and present an overview of the 2D magnets that have been explored recently. We will focus, in particular, on the case of the two most studied systems - semiconducting CrI$_3$ and metallic Fe$_3$GeTe$_2$ - and illustrate the physical phenomena that have been observed. Special attention will be given to the range of novel van der Waals heterostructures that became possible with the appearance of 2D magnets, offering new perspectives in this rapidly expanding field.

Abstract: Importance Exposure to nicotine in electronic cigarettes (e-cigarettes) is becoming increasingly common among adolescents who report never having smoked combustible tobacco. Objective To evaluate whether e-cigarette use among 14-year-old adolescents who have never tried combustible tobacco is associated with risk of initiating use of 3 combustible tobacco products (ie, cigarettes, cigars, and hookah). Design, Setting, and Participants Longitudinal repeated assessment of a school-based cohort at baseline (fall 2013, 9th grade, mean age = 14.1 years) and at a 6-month follow-up (spring 2014, 9th grade) and a 12-month follow-up (fall 2014, 10th grade). Ten public high schools in Los Angeles, California, were recruited through convenience sampling. Participants were students who reported never using combustible tobacco at baseline and completed follow-up assessments at 6 or 12 months (N = 2530). At each time point, students completed self-report surveys during in-classroom data collections. Exposure Student self-report of whether he or she ever used e-cigarettes (yes or no) at baseline. Main Outcomes and Measures Six- and 12-month follow-up reports on use of any of the following tobacco products within the prior 6 months: (1) any combustible tobacco product (yes or no); (2) combustible cigarettes (yes or no), (3) cigars (yes or no); (4) hookah (yes or no); and (5) number of combustible tobacco products (range: 0-3). Results Past 6-month use of any combustible tobacco product was more frequent in baseline e-cigarette ever users (n = 222) than never users (n = 2308) at the 6-month follow-up (30.7% vs 8.1%, respectively; difference between groups in prevalence rates, 22.7% [95% CI, 16.4%-28.9%]) and at the 12-month follow-up (25.2% vs 9.3%, respectively; difference between groups, 15.9% [95% CI, 10.0%-21.8%]). Baseline e-cigarette use was associated with greater likelihood of use of any combustible tobacco product averaged across the 2 follow-up periods in the unadjusted analyses (odds ratio [OR], 4.27 [95% CI, 3.19-5.71]) and in the analyses adjusted for sociodemographic, environmental, and intrapersonal risk factors for smoking (OR, 2.73 [95% CI, 2.00-3.73]). Product-specific analyses showed that baseline e-cigarette use was positively associated with combustible cigarette (OR, 2.65 [95% CI, 1.73-4.05]), cigar (OR, 4.85 [95% CI, 3.38-6.96]), and hookah (OR, 3.25 [95% CI, 2.29-4.62]) use and with the number of different combustible products used (OR, 4.26 [95% CI, 3.16-5.74]) averaged across the 2 follow-up periods. Conclusions and Relevance Among high school students in Los Angeles, those who had ever used e-cigarettes at baseline compared with nonusers were more likely to report initiation of combustible tobacco use over the next year. Further research is needed to understand whether this association may be causal.