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Journal ArticleDOI
24 Apr 2015-Science
TL;DR: The current technologies for multilayer thin-film deposition using layer-by-layer assembly are reviewed, and the different properties and applications arising from the technologies are discussed.
Abstract: Multilayer thin films have garnered intense scientific interest due to their potential application in diverse fields such as catalysis, optics, energy, membranes, and biomedicine Here we review the current technologies for multilayer thin-film deposition using layer-by-layer assembly, and we discuss the different properties and applications arising from the technologies We highlight five distinct routes of assembly—immersive, spin, spray, electromagnetic, and fluidic assembly—each of which offers material and processing advantages for assembling layer-by-layer films Each technology encompasses numerous innovations for automating and improving layering, which is important for research and industrial applications Furthermore, we discuss how judicious choice of the assembly technology enables the engineering of thin films with tailor-made physicochemical properties, such as distinct-layer stratification, controlled roughness, and highly ordered packing

1,235 citations


Proceedings ArticleDOI
18 Jun 2018
TL;DR: The proposed Context Encoding Module significantly improves semantic segmentation results with only marginal extra computation cost over FCN, and can improve the feature representation of relatively shallow networks for the image classification on CIFAR-10 dataset.
Abstract: Recent work has made significant progress in improving spatial resolution for pixelwise labeling with Fully Convolutional Network (FCN) framework by employing Dilated/Atrous convolution, utilizing multi-scale features and refining boundaries. In this paper, we explore the impact of global contextual information in semantic segmentation by introducing the Context Encoding Module, which captures the semantic context of scenes and selectively highlights class-dependent featuremaps. The proposed Context Encoding Module significantly improves semantic segmentation results with only marginal extra computation cost over FCN. Our approach has achieved new state-of-the-art results 51.7% mIoU on PASCAL-Context, 85.9% mIoU on PASCAL VOC 2012. Our single model achieves a final score of 0.5567 on ADE20K test set, which surpasses the winning entry of COCO-Place Challenge 2017. In addition, we also explore how the Context Encoding Module can improve the feature representation of relatively shallow networks for the image classification on CIFAR-10 dataset. Our 14 layer network has achieved an error rate of 3.45%, which is comparable with state-of-the-art approaches with over 10A— more layers. The source code for the complete system are publicly available1.

1,235 citations


Journal ArticleDOI
08 Dec 2015-PLOS ONE
TL;DR: Estimates of the global prevalence and incidence of chlamydia, gonorrhoea, trichomoniasis, and syphilis in adult women and men remain high, with nearly one million new infections with curable STI each day.
Abstract: Background: Quantifying sexually transmitted infection (STI) prevalence and incidence is important for planning interventions and advocating for resources. The World Health Organization (WHO) periodically estimates global and regional prevalence and incidence of four curable STIs: chlamydia, gonorrhoea, trichomoniasis and syphilis.Methods and Findings: WHO's 2012 estimates were based upon literature reviews of prevalence data from 2005 through 2012 among general populations for genitourinary infection with chlamydia, gonorrhoea, and trichomoniasis, and nationally reported data on syphilis seroprevalence among antenatal care attendees. Data were standardized for laboratory test type, geography, age, and high risk subpopulations, and combined using a Bayesian meta-analytic approach. Regional incidence estimates were generated from prevalence estimates by adjusting for average duration of infection. In 2012, among women aged 15-49 years, the estimated global prevalence of chlamydia was 4.2%(95% uncertainty interval (UI): 3.7-4.7%), gonorrhoea 0.8%(0.6-1.0%), trichomoniasis 5.0%(4.0-6.4%), and syphilis 0.5%(0.4-0.6%); among men, estimated chlamydia prevalence was 2.7% (2.0-3.6%), gonorrhoea 0.6%(0.40.9%), trichomoniasis 0.6%(0.4-0.8%), and syphilis 0.48% (0.3-0.7%). These figures correspond to an estimated 131 million new cases of chlamydia (100-166 million), 78 million of gonorrhoea (53-110 million), 143 million of trichomoniasis (98-202 million), and 6 million of syphilis (4-8 million). Prevalence and incidence estimates varied by region and sex.Conclusions: Estimates of the global prevalence and incidence of chlamydia, gonorrhoea, trichomoniasis, and syphilis in adult women and men remain high, with nearly one million new infections with curable STI each day. The estimates highlight the urgent need for the public health community to ensure that well-recognized effective interventions for STI prevention, screening, diagnosis, and treatment are made more widely available. Improved estimation methods are needed to allow use of more varied data and generation of estimates at the national level.

1,235 citations


Journal ArticleDOI
TL;DR: This review paper begins at the definition of clustering, takes the basic elements involved in the clustering process, such as the distance or similarity measurement and evaluation indicators, into consideration, and analyzes the clustered algorithms from two perspectives, the traditional ones and the modern ones.
Abstract: Data analysis is used as a common method in modern science research, which is across communication science, computer science and biology science. Clustering, as the basic composition of data analysis, plays a significant role. On one hand, many tools for cluster analysis have been created, along with the information increase and subject intersection. On the other hand, each clustering algorithm has its own strengths and weaknesses, due to the complexity of information. In this review paper, we begin at the definition of clustering, take the basic elements involved in the clustering process, such as the distance or similarity measurement and evaluation indicators, into consideration, and analyze the clustering algorithms from two perspectives, the traditional ones and the modern ones. All the discussed clustering algorithms will be compared in detail and comprehensively shown in Appendix Table 22.

1,234 citations


Journal ArticleDOI
TL;DR: In this article, the authors reviewed recent progress in understanding of the excitonic properties in monolayer transition metal dichalcogenides (TMDs) and future challenges are laid out.
Abstract: Atomically thin materials such as graphene and monolayer transition metal dichalcogenides (TMDs) exhibit remarkable physical properties resulting from their reduced dimensionality and crystal symmetry. The family of semiconducting transition metal dichalcogenides is an especially promising platform for fundamental studies of two-dimensional (2D) systems, with potential applications in optoelectronics and valleytronics due to their direct band gap in the monolayer limit and highly efficient light-matter coupling. A crystal lattice with broken inversion symmetry combined with strong spin-orbit interactions leads to a unique combination of the spin and valley degrees of freedom. In addition, the 2D character of the monolayers and weak dielectric screening from the environment yield a significant enhancement of the Coulomb interaction. The resulting formation of bound electron-hole pairs, or excitons, dominates the optical and spin properties of the material. Here recent progress in understanding of the excitonic properties in monolayer TMDs is reviewed and future challenges are laid out. Discussed are the consequences of the strong direct and exchange Coulomb interaction, exciton light-matter coupling, and influence of finite carrier and electron-hole pair densities on the exciton properties in TMDs. Finally, the impact on valley polarization is described and the tuning of the energies and polarization observed in applied electric and magnetic fields is summarized.

1,234 citations


Journal ArticleDOI
26 Apr 2019-Science
TL;DR: A comparative analysis of electrocatalyst and carbon emissions assessment of CO2 products such as ethylene, ethanol, and carbon monoxide shows that electrocatalytic production has the potential to yield the greatest reduction in carbon emissions, provided that a steady supply of clean electricity is available.
Abstract: Electrocatalytic transformation of carbon dioxide (CO2) and water into chemical feedstocks offers the potential to reduce carbon emissions by shifting the chemical industry away from fossil fuel dependence. We provide a technoeconomic and carbon emission analysis of possible products, offering targets that would need to be met for economically compelling industrial implementation to be achieved. We also provide a comparison of the projected costs and CO2 emissions across electrocatalytic, biocatalytic, and fossil fuel-derived production of chemical feedstocks. We find that for electrosynthesis to become competitive with fossil fuel-derived feedstocks, electrical-to-chemical conversion efficiencies need to reach at least 60%, and renewable electricity prices need to fall below 4 cents per kilowatt-hour. We discuss the possibility of combining electro- and biocatalytic processes, using sequential upgrading of CO2 as a representative case. We describe the technical challenges and economic barriers to marketable electrosynthesized chemicals.

1,234 citations


Journal ArticleDOI
TL;DR: In this randomized trial, cryoballoon ablation was noninferior to radiofrequency ablation with respect to efficacy for the treatment of patients with drug-refractory paroxysmal atrial fibrillation, and there was no significant difference between the two methods with regard to overall safety.
Abstract: BackgroundCurrent guidelines recommend pulmonary-vein isolation by means of catheter ablation as treatment for drug-refractory paroxysmal atrial fibrillation. Radiofrequency ablation is the most common method, and cryoballoon ablation is the second most frequently used technology. MethodsWe conducted a multicenter, randomized trial to determine whether cryoballoon ablation was noninferior to radiofrequency ablation in symptomatic patients with drug-refractory paroxysmal atrial fibrillation. The primary efficacy end point in a time-to-event analysis was the first documented clinical failure (recurrence of atrial fibrillation, occurrence of atrial flutter or atrial tachycardia, use of antiarrhythmic drugs, or repeat ablation) following a 90-day period after the index ablation. The noninferiority margin was prespecified as a hazard ratio of 1.43. The primary safety end point was a composite of death, cerebrovascular events, or serious treatment-related adverse events. ResultsA total of 762 patients underwent...

1,234 citations


Journal ArticleDOI
TL;DR: In this paper, the authors proposed a max-min power control algorithm to ensure uniformly good service throughout the area of coverage in a cell-free massive MIMO system, where each user is served by a dedicated access point.
Abstract: A Cell-Free Massive MIMO (multiple-input multiple-output) system comprises a very large number of distributed access points (APs), which simultaneously serve a much smaller number of users over the same time/frequency resources based on directly measured channel characteristics. The APs and users have only one antenna each. The APs acquire channel state information through time-division duplex operation and the reception of uplink pilot signals transmitted by the users. The APs perform multiplexing/de-multiplexing through conjugate beamforming on the downlink and matched filtering on the uplink. Closed-form expressions for individual user uplink and downlink throughputs lead to max–min power control algorithms. Max–min power control ensures uniformly good service throughout the area of coverage. A pilot assignment algorithm helps to mitigate the effects of pilot contamination, but power control is far more important in that regard. Cell-Free Massive MIMO has considerably improved performance with respect to a conventional small-cell scheme, whereby each user is served by a dedicated AP, in terms of both 95%-likely per-user throughput and immunity to shadow fading spatial correlation. Under uncorrelated shadow fading conditions, the cell-free scheme provides nearly fivefold improvement in 95%-likely per-user throughput over the small-cell scheme, and tenfold improvement when shadow fading is correlated.

1,234 citations


Posted Content
TL;DR: The results show that deep networks can be trained using only 16-bit wide fixed-point number representation when using stochastic rounding, and incur little to no degradation in the classification accuracy.
Abstract: Training of large-scale deep neural networks is often constrained by the available computational resources. We study the effect of limited precision data representation and computation on neural network training. Within the context of low-precision fixed-point computations, we observe the rounding scheme to play a crucial role in determining the network's behavior during training. Our results show that deep networks can be trained using only 16-bit wide fixed-point number representation when using stochastic rounding, and incur little to no degradation in the classification accuracy. We also demonstrate an energy-efficient hardware accelerator that implements low-precision fixed-point arithmetic with stochastic rounding.

1,234 citations


Journal ArticleDOI
TL;DR: Electrochemical data strongly demonstrate that this nanoporous hybrid carbon material integrates the advantageous properties of the individual NC and GC, exhibiting a distinguished specific capacitance calculated from the galvanostatic charge-discharge curves at a current density of 2 A·g(-1).
Abstract: Core–shell structured ZIF-8@ZIF-67 crystals are well-designed and prepared through a seed-mediated growth method. After thermal treatment of ZIF-8@ZIF-67 crystals, we obtain selectively functionalized nanoporous hybrid carbon materials consisting of nitrogen-doped carbon (NC) as the cores and highly graphitic carbon (GC) as the shells. This is the first example of the integration of NC and GC in one particle at the nanometer level. Electrochemical data strongly demonstrate that this nanoporous hybrid carbon material integrates the advantageous properties of the individual NC and GC, exhibiting a distinguished specific capacitance (270 F·g–1) calculated from the galvanostatic charge–discharge curves at a current density of 2 A·g–1. Our study not only bridges diverse carbon-based materials with infinite metal–organic frameworks but also opens a new avenue for artificially designed nanoarchitectures with target functionalities.

1,233 citations


Proceedings ArticleDOI
06 Jun 2016
TL;DR: This work extensively evaluates Multimodal Compact Bilinear pooling (MCB) on the visual question answering and grounding tasks and consistently shows the benefit of MCB over ablations without MCB.
Abstract: Modeling textual or visual information with vector representations trained from large language or visual datasets has been successfully explored in recent years. However, tasks such as visual question answering require combining these vector representations with each other. Approaches to multimodal pooling include element-wise product or sum, as well as concatenation of the visual and textual representations. We hypothesize that these methods are not as expressive as an outer product of the visual and textual vectors. As the outer product is typically infeasible due to its high dimensionality, we instead propose utilizing Multimodal Compact Bilinear pooling (MCB) to efficiently and expressively combine multimodal features. We extensively evaluate MCB on the visual question answering and grounding tasks. We consistently show the benefit of MCB over ablations without MCB. For visual question answering, we present an architecture which uses MCB twice, once for predicting attention over spatial features and again to combine the attended representation with the question representation. This model outperforms the state-of-the-art on the Visual7W dataset and the VQA challenge.

Journal ArticleDOI
TL;DR: Among men with locally advanced or metastatic prostate cancer, ADT plus abiraterone and prednisolone was associated with significantly higher rates of overall and failure‐free survival than ADT alone.
Abstract: BackgroundAbiraterone acetate plus prednisolone improves survival in men with relapsed prostate cancer We assessed the effect of this combination in men starting long-term androgen-deprivation therapy (ADT), using a multigroup, multistage trial design MethodsWe randomly assigned patients in a 1:1 ratio to receive ADT alone or ADT plus abiraterone acetate (1000 mg daily) and prednisolone (5 mg daily) (combination therapy) Local radiotherapy was mandated for patients with node-negative, nonmetastatic disease and encouraged for those with positive nodes For patients with nonmetastatic disease with no radiotherapy planned and for patients with metastatic disease, treatment continued until radiologic, clinical, or prostate-specific antigen (PSA) progression; otherwise, treatment was to continue for 2 years or until any type of progression, whichever came first The primary outcome measure was overall survival The intermediate primary outcome was failure-free survival (treatment failure was defined as radi

Journal ArticleDOI
TL;DR: In patients with septic shock who were identified early and received intravenous antibiotics and adequate fluid resuscitation, hemodynamic management according to a strict EGDT protocol did not lead to an improvement in outcome.
Abstract: Background Early, goal-directed therapy (EGDT) is recommended in international guidelines for the resuscitation of patients presenting with early septic shock. However, adoption has been limited, and uncertainty about its effectiveness remains. Methods We conducted a pragmatic randomized trial with an integrated cost-effectiveness analysis in 56 hospitals in England. Patients were randomly assigned to receive either EGDT (a 6-hour resuscitation protocol) or usual care. The primary clinical outcome was all-cause mortality at 90 days. Results We enrolled 1260 patients, with 630 assigned to EGDT and 630 to usual care. By 90 days, 184 of 623 patients (29.5%) in the EGDT group and 181 of 620 patients (29.2%) in the usual-care group had died (relative risk in the EGDT group, 1.01; 95% confidence interval [CI], 0.85 to 1.20; P = 0.90), for an absolute risk reduction in the EGDT group of −0.3 percentage points (95% CI, −5.4 to 4.7). Increased treat ment intensity in the EGDT group was indicated by increased use of intravenous fluids, vasoactive drugs, and red-cell transfusions and reflected by significantly worse organ-failure scores, more days receiving advanced cardiovascular support, and longer stays in the intensive care unit. There were no significant differences in any other secondary outcomes, including health-related quality of life, or in rates of serious adverse events. On average, EGDT increased costs, and the probability that it was cost-effective was below 20%. Conclusions In patients with septic shock who were identified early and received intravenous antibiotics and adequate fluid resuscitation, hemodynamic management according to a strict EGDT protocol did not lead to an improvement in outcome. (Funded by the United Kingdom National Institute for Health Research Health Technology Assessment Programme; ProMISe Current Controlled Trials number, ISRCTN36307479.)

Journal ArticleDOI
29 Apr 2016-Science
TL;DR: The role of early-life education of the immune system during this “window of opportunity,” when disruption of optimal host-commensal interactions can lead to persistent and in some cases irreversible defects in the development and training of specific immune subsets is discussed.
Abstract: Microbial colonization of mucosal tissues during infancy plays an instrumental role in the development and education of the host mammalian immune system. These early-life events can have long-standing consequences: facilitating tolerance to environmental exposures or contributing to the development of disease in later life, including inflammatory bowel disease, allergy, and asthma. Recent studies have begun to define a critical period during early development in which disruption of optimal host-commensal interactions can lead to persistent and in some cases irreversible defects in the development and training of specific immune subsets. Here, we discuss the role of early-life education of the immune system during this “window of opportunity,” when microbial colonization has a potentially critical impact on human health and disease.

Journal ArticleDOI
TL;DR: The Difficult Airway Management Guidelines as discussed by the authors provide a strategy to manage unanticipated difficulty with tracheal intubation and rapid sequence induction, which emphasizes assessment, preparation, positioning, preoxygenation, maintenance of oxygenation, and minimizing trauma from airway interventions.
Abstract: Theseguidelines provide a strategy to manageunanticipated difficulty with tracheal intubation. Theyare foundedon published evidence. Where evidence is lacking, they have been directed by feedback from members of the Difficult Airway Society and based on expert opinion. These guidelines have been informed by advances in the understanding of crisis management; they emphasize the recognition and declaration of difficulty during airway management. A simplified, single algorithm now covers unanticipated difficulties in both routine intubation and rapid sequence induction. Planning for failed intubation should form part of the pre-induction briefing, particularly for urgent surgery. Emphasis is placed on assessment, preparation, positioning, preoxygenation, maintenance of oxygenation, and minimizing trauma from airway interventions. It is recommended that the number of airway interventions are limited, and blind techniques using a bougie or through supraglottic airway devices have been superseded by video- or fibre-optically guided intubation. If tracheal intubation fails, supraglottic airway devices are recommended to provide a route for oxygenation while reviewing how to proceed. Second-generation devices have advantages and are recommended. When both tracheal intubation and supraglottic airway device insertion have failed, waking the patient is the default option. If at this stage, face-mask oxygenation is impossible in the presence of muscle relaxation, cricothyroidotomy should follow immediately. Scalpel cricothyroidotomy is recommended as the preferred rescue technique and should be practised by all anaesthetists. The plans outlined are designed to be simple and easy to follow. They should be regularly rehearsed and made familiar to the whole theatre team.

Posted Content
TL;DR: A binary matrix multiplication GPU kernel is programmed with which it is possible to run the MNIST QNN 7 times faster than with an unoptimized GPU kernel, without suffering any loss in classification accuracy.
Abstract: We introduce a method to train Quantized Neural Networks (QNNs) --- neural networks with extremely low precision (e.g., 1-bit) weights and activations, at run-time. At train-time the quantized weights and activations are used for computing the parameter gradients. During the forward pass, QNNs drastically reduce memory size and accesses, and replace most arithmetic operations with bit-wise operations. As a result, power consumption is expected to be drastically reduced. We trained QNNs over the MNIST, CIFAR-10, SVHN and ImageNet datasets. The resulting QNNs achieve prediction accuracy comparable to their 32-bit counterparts. For example, our quantized version of AlexNet with 1-bit weights and 2-bit activations achieves $51\%$ top-1 accuracy. Moreover, we quantize the parameter gradients to 6-bits as well which enables gradients computation using only bit-wise operation. Quantized recurrent neural networks were tested over the Penn Treebank dataset, and achieved comparable accuracy as their 32-bit counterparts using only 4-bits. Last but not least, we programmed a binary matrix multiplication GPU kernel with which it is possible to run our MNIST QNN 7 times faster than with an unoptimized GPU kernel, without suffering any loss in classification accuracy. The QNN code is available online.

Journal ArticleDOI
07 Apr 2020-Chest
TL;DR: A multidisciplinary panel comprised principally of radiologists and pulmonologists from 10 countries with experience managing COVID-19 patients across a spectrum of healthcare environments evaluated the utility of imaging within three scenarios representing varying risk factors, community conditions, and resource constraints, resulting in five main and three additional recommendations intended to guide medical practitioners in the use of CXR and CT in the management of COIDs.

Journal ArticleDOI
TL;DR: Among patients receiving initial systemic treatment for HR-positive, HER2-negative advanced breast cancer, the duration of progression-free survival was significantly longer among those receiving ribociclib plus letrozole than among those received placebo plus let rozole, with a higher rate of myelosuppression in the ribocIClib group.
Abstract: BackgroundThe inhibition of cyclin-dependent kinases 4 and 6 (CDK4/6) could potentially overcome or delay resistance to endocrine therapy in advanced breast cancer that is positive for hormone receptor (HR) and negative for human epidermal growth factor receptor 2 (HER2). MethodsIn this randomized, placebo-controlled, phase 3 trial, we evaluated the efficacy and safety of the selective CDK4/6 inhibitor ribociclib combined with letrozole for first-line treatment in 668 postmenopausal women with HR-positive, HER2-negative recurrent or metastatic breast cancer who had not received previous systemic therapy for advanced disease. We randomly assigned the patients to receive either ribociclib (600 mg per day on a 3-weeks-on, 1-week-off schedule) plus letrozole (2.5 mg per day) or placebo plus letrozole. The primary end point was investigator-assessed progression-free survival. Secondary end points included overall survival, overall response rate, and safety. A preplanned interim analysis was performed on Januar...

Journal ArticleDOI
01 Sep 2020-BMJ
TL;DR: Pregnant and recently pregnant women are less likely to manifest covid-19 related symptoms of fever and myalgia than non-pregnant women of reproductive age, and high intensive care women without high risk of disease are potentially more likely to be risk factors for covid19 Pre-existing comorbidity.
Abstract: Objective To determine the clinical manifestations, risk factors, and maternal and perinatal outcomes in pregnant and recently pregnant women with suspected or confirmed coronavirus disease 2019 (covid-19). Design Living systematic review and meta-analysis. Data sources Medline, Embase, Cochrane database, WHO COVID-19 database, China National Knowledge Infrastructure (CNKI), and Wanfang databases from 1 December 2019 to 6 October 2020, along with preprint servers, social media, and reference lists. Study selection Cohort studies reporting the rates, clinical manifestations (symptoms, laboratory and radiological findings), risk factors, and maternal and perinatal outcomes in pregnant and recently pregnant women with suspected or confirmed covid-19. Data extraction At least two researchers independently extracted the data and assessed study quality. Random effects meta-analysis was performed, with estimates pooled as odds ratios and proportions with 95% confidence intervals. All analyses will be updated regularly. Results 192 studies were included. Overall, 10% (95% confidence interval 7% to 12%; 73 studies, 67 271 women) of pregnant and recently pregnant women attending or admitted to hospital for any reason were diagnosed as having suspected or confirmed covid-19. The most common clinical manifestations of covid-19 in pregnancy were fever (40%) and cough (41%). Compared with non-pregnant women of reproductive age, pregnant and recently pregnant women with covid-19 were less likely to have symptoms (odds ratio 0.28, 95% confidence interval 0.13 to 0.62; I2=42.9%) or report symptoms of fever (0.49, 0.38 to 0.63; I2=40.8%), dyspnoea (0.76, 0.67 to 0.85; I2=4.4%) and myalgia (0.53, 0.36 to 0.78; I2=59.4%). The odds of admission to an intensive care unit (odds ratio 2.13, 1.53 to 2.95; I2=71.2%), invasive ventilation (2.59, 2.28 to 2.94; I2=0%) and need for extra corporeal membrane oxygenation (2.02, 1.22 to 3.34; I2=0%) were higher in pregnant and recently pregnant than non-pregnant reproductive aged women. Overall, 339 pregnant women (0.02%, 59 studies, 41 664 women) with confirmed covid-19 died from any cause. Increased maternal age (odds ratio 1.83, 1.27 to 2.63; I2=43.4%), high body mass index (2.37, 1.83 to 3.07; I2=0%), any pre-existing maternal comorbidity (1.81, 1.49 to 2.20; I2=0%), chronic hypertension (2.0, 1.14 to 3.48; I2=0%), pre-existing diabetes (2.12, 1.62 to 2.78; I2=0%), and pre-eclampsia (4.21, 1.27 to 14.0; I2=0%) were associated with severe covid-19 in pregnancy. In pregnant women with covid-19, increased maternal age, high body mass index, non-white ethnicity, any pre-existing maternal comorbidity including chronic hypertension and diabetes, and pre-eclampsia were associated with serious complications such as admission to an intensive care unit, invasive ventilation and maternal death. Compared to pregnant women without covid-19, those with the disease had increased odds of maternal death (odds ratio 2.85, 1.08 to 7.52; I2=0%), of needing admission to the intensive care unit (18.58, 7.53 to 45.82; I2=0%), and of preterm birth (1.47, 1.14 to 1.91; I2=18.6%). The odds of admission to the neonatal intensive care unit (4.89, 1.87 to 12.81, I2=96.2%) were higher in babies born to mothers with covid-19 versus those without covid-19. Conclusion Pregnant and recently pregnant women with covid-19 attending or admitted to the hospitals for any reason are less likely to manifest symptoms such as fever, dyspnoea, and myalgia, and are more likely to be admitted to the intensive care unit or needing invasive ventilation than non-pregnant women of reproductive age. Pre-existing comorbidities, non-white ethnicity, chronic hypertension, pre-existing diabetes, high maternal age, and high body mass index are risk factors for severe covid-19 in pregnancy. Pregnant women with covid-19 versus without covid-19 are more likely to deliver preterm and could have an increased risk of maternal death and of being admitted to the intensive care unit. Their babies are more likely to be admitted to the neonatal unit. Systematic review registration PROSPERO CRD42020178076. Readers’ note This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This version is update 1 of the original article published on 1 September 2020 (BMJ 2020;370:m3320), and previous updates can be found as data supplements (https://www.bmj.com/content/370/bmj.m3320/related#datasupp). When citing this paper please consider adding the update number and date of access for clarity.

Journal ArticleDOI
TL;DR: BOLT-LMM is presented, which requires only a small number of O(MN) time iterations and increases power by modeling more realistic, non-infinitesimal genetic architectures via a Bayesian mixture prior on marker effect sizes.
Abstract: Linear mixed models are a powerful statistical tool for identifying genetic associations and avoiding confounding. However, existing methods are computationally intractable in large cohorts and may not optimize power. All existing methods require time cost O(MN(2)) (where N is the number of samples and M is the number of SNPs) and implicitly assume an infinitesimal genetic architecture in which effect sizes are normally distributed, which can limit power. Here we present a far more efficient mixed-model association method, BOLT-LMM, which requires only a small number of O(MN) time iterations and increases power by modeling more realistic, non-infinitesimal genetic architectures via a Bayesian mixture prior on marker effect sizes. We applied BOLT-LMM to 9 quantitative traits in 23,294 samples from the Women's Genome Health Study (WGHS) and observed significant increases in power, consistent with simulations. Theory and simulations show that the boost in power increases with cohort size, making BOLT-LMM appealing for genome-wide association studies in large cohorts.

Journal ArticleDOI
TL;DR: This study aimed to confirm the earlier findings with this extended follow-up and show the results for subgroup and biomarker analyses, and assesses endocrine therapy resistance by clinical parameters, quantitative hormone-receptor expression, and tumour PIK3CA mutational status in circulating DNA at baseline.
Abstract: Summary Background In the PALOMA-3 study, the combination of the CDK4 and CDK6 inhibitor palbociclib and fulvestrant was associated with significant improvements in progression-free survival compared with fulvestrant plus placebo in patients with metastatic breast cancer. Identification of patients most suitable for the addition of palbociclib to endocrine therapy after tumour recurrence is crucial for treatment optimisation in metastatic breast cancer. We aimed to confirm our earlier findings with this extended follow-up and show our results for subgroup and biomarker analyses. Methods In this multicentre, double-blind, randomised phase 3 study, women aged 18 years or older with hormone-receptor-positive, HER2-negative metastatic breast cancer that had progressed on previous endocrine therapy were stratified by sensitivity to previous hormonal therapy, menopausal status, and presence of visceral metastasis at 144 centres in 17 countries. Eligible patients—ie, any menopausal status, Eastern Cooperative Oncology Group performance status 0–1, measurable disease or bone disease only, and disease relapse or progression after previous endocrine therapy for advanced disease during treatment or within 12 months of completion of adjuvant therapy—were randomly assigned (2:1) via a centralised interactive web-based and voice-based randomisation system to receive oral palbociclib (125 mg daily for 3 weeks followed by a week off over 28-day cycles) plus 500 mg fulvestrant (intramuscular injection on days 1 and 15 of cycle 1; then on day 1 of subsequent 28-day cycles) or placebo plus fulvestrant. The primary endpoint was investigator-assessed progression-free survival. Analysis was by intention to treat. We also assessed endocrine therapy resistance by clinical parameters, quantitative hormone-receptor expression, and tumour PIK3CA mutational status in circulating DNA at baseline. This study is registered with ClinicalTrials.gov, NCT01942135. Findings Between Oct 7, 2013, and Aug 26, 2014, 521 patients were randomly assigned, 347 to fulvestrant plus palbociclib and 174 to fulvestrant plus placebo. Study enrolment is closed and overall survival follow-up is in progress. By March 16, 2015, 259 progression-free-survival events had occurred (145 in the fulvestrant plus palbociclib group and 114 in the fulvestrant plus placebo group); median follow-up was 8·9 months (IQR 8·7–9·2). Median progression-free survival was 9·5 months (95% CI 9·2–11·0) in the fulvestrant plus palbociclib group and 4·6 months (3·5–5·6) in the fulvestrant plus placebo group (hazard ratio 0·46, 95% CI 0·36–0·59, p PIK3CA mutation was detected in the plasma DNA of 129 (33%) of 395 patients for whom these data were available. Neither PIK3CA status nor hormone-receptor expression level significantly affected treatment response. Interpretation Fulvestrant plus palbociclib was associated with significant and consistent improvement in progression-free survival compared with fulvestrant plus placebo, irrespective of the degree of endocrine resistance, hormone-receptor expression level, and PIK3CA mutational status. The combination could be considered as a therapeutic option for patients with recurrent hormone-receptor-positive, HER2-negative metastatic breast cancer that has progressed on previous endocrine therapy. Funding Pfizer.

Journal ArticleDOI
11 Dec 2015-Hypoxia
TL;DR: Better understanding of the role of hypoxia in cancer progression will open new windows for the discovery of new therapeutics targeting hypoxic tumor cells and hypoxic microenvironment.
Abstract: Hypoxia is a non-physiological level of oxygen tension, a phenomenon common in a majority of malignant tumors. Tumor-hypoxia leads to advanced but dysfunctional vascularization and acquisition of epithelial-to-mesenchymal transition phenotype resulting in cell mobility and metastasis. Hypoxia alters cancer cell metabolism and contributes to therapy resistance by inducing cell quiescence. Hypoxia stimulates a complex cell signaling network in cancer cells, including the HIF, PI3K, MAPK, and NFĸB pathways, which interact with each other causing positive and negative feedback loops and enhancing or diminishing hypoxic effects. This review provides background knowledge on the role of tumor hypoxia and the role of the HIF cell signaling involved in tumor blood vessel formation, metastasis, and development of the resistance to therapy. Better understanding of the role of hypoxia in cancer progression will open new windows for the discovery of new therapeutics targeting hypoxic tumor cells and hypoxic microenvironment.

Journal ArticleDOI
TL;DR: SG is currently the most frequently performed procedure in the USA/Canada and in the Asia/Pacific regions, and second to RYGB in the Europe and Latin/South America regions.
Abstract: The first global survey of bariatric/metabolic surgery based on data from the nations or national groupings of the International Federation for the Surgery of Obesity and Metabolic Diseases (IFSO) was published in 1998, followed by reports in 2003, 2009, 2011, and 2012. In this survey, we report a global overview of worldwide bariatric surgery in 2013. A questionnaire evaluating the number and the type of bariatric procedure performed in 2013 was emailed to all members of bariatric societies belonging to IFSO. Trend analyses from 2003 to 2013 were also performed. There were 49/54 (90.7 %) responders; 37 of the 49 with national registries. The total number of bariatric procedures performed worldwide in 2013 was 468,609, 95.7 % carried out laparoscopically. The highest number (n = 154,276) was from the USA/Canada region. The most commonly performed procedure in the world was Roux-en-Y gastric bypass (RYGB), 45 %; followed by sleeve gastrectomy (SG), 37 %; and adjustable gastric banding (AGB), 10 %. Most significant were the rise in prevalence of SG from 0 to 37 % of the world total from 2003 to 2013, and the fall in AGB of 68 % from its peak in 2008 to 2013. SG is currently the most frequently performed procedure in the USA/Canada and in the Asia/Pacific regions, and second to RYGB in the Europe and Latin/South America regions. The accuracy of the IFSO-based world survey of procedures would be enhanced if each nation or national group would create a national registry.

Journal ArticleDOI
TL;DR: This work introduces EEGNet, a compact convolutional neural network for EEG-based BCIs, and introduces the use of depthwise and separable convolutions to construct an EEG-specific model which encapsulates well-known EEG feature extraction concepts for BCI.
Abstract: Objective Brain-computer interfaces (BCI) enable direct communication with a computer, using neural activity as the control signal. This neural signal is generally chosen from a variety of well-studied electroencephalogram (EEG) signals. For a given BCI paradigm, feature extractors and classifiers are tailored to the distinct characteristics of its expected EEG control signal, limiting its application to that specific signal. Convolutional neural networks (CNNs), which have been used in computer vision and speech recognition to perform automatic feature extraction and classification, have successfully been applied to EEG-based BCIs; however, they have mainly been applied to single BCI paradigms and thus it remains unclear how these architectures generalize to other paradigms. Here, we ask if we can design a single CNN architecture to accurately classify EEG signals from different BCI paradigms, while simultaneously being as compact as possible. Approach In this work we introduce EEGNet, a compact convolutional neural network for EEG-based BCIs. We introduce the use of depthwise and separable convolutions to construct an EEG-specific model which encapsulates well-known EEG feature extraction concepts for BCI. We compare EEGNet, both for within-subject and cross-subject classification, to current state-of-the-art approaches across four BCI paradigms: P300 visual-evoked potentials, error-related negativity responses (ERN), movement-related cortical potentials (MRCP), and sensory motor rhythms (SMR). Main results We show that EEGNet generalizes across paradigms better than, and achieves comparably high performance to, the reference algorithms when only limited training data is available across all tested paradigms. In addition, we demonstrate three different approaches to visualize the contents of a trained EEGNet model to enable interpretation of the learned features. Significance Our results suggest that EEGNet is robust enough to learn a wide variety of interpretable features over a range of BCI tasks. Our models can be found at: https://github.com/vlawhern/arl-eegmodels.

Book ChapterDOI
08 Oct 2016
TL;DR: This paper introduces new gating mechanism within LSTM to learn the reliability of the sequential input data and accordingly adjust its effect on updating the long-term context information stored in the memory cell, and proposes a more powerful tree-structure based traversal method.
Abstract: 3D action recognition – analysis of human actions based on 3D skeleton data – becomes popular recently due to its succinctness, robustness, and view-invariant representation. Recent attempts on this problem suggested to develop RNN-based learning methods to model the contextual dependency in the temporal domain. In this paper, we extend this idea to spatio-temporal domains to analyze the hidden sources of action-related information within the input data over both domains concurrently. Inspired by the graphical structure of the human skeleton, we further propose a more powerful tree-structure based traversal method. To handle the noise and occlusion in 3D skeleton data, we introduce new gating mechanism within LSTM to learn the reliability of the sequential input data and accordingly adjust its effect on updating the long-term context information stored in the memory cell. Our method achieves state-of-the-art performance on 4 challenging benchmark datasets for 3D human action analysis.

Journal ArticleDOI
TL;DR: In this paper, the authors comprehensively review and classify various step-up dc-dc converters based on their characteristics and voltage-boosting techniques, and discuss the advantages and disadvantages of these voltage boosting techniques and associated converters.
Abstract: DC–DC converters with voltage boost capability are widely used in a large number of power conversion applications, from fraction-of-volt to tens of thousands of volts at power levels from milliwatts to megawatts. The literature has reported on various voltage-boosting techniques, in which fundamental energy storing elements (inductors and capacitors) and/or transformers in conjunction with switch(es) and diode(s) are utilized in the circuit. These techniques include switched capacitor (charge pump), voltage multiplier, switched inductor/voltage lift, magnetic coupling, and multistage/-level, and each has its own merits and demerits depending on application, in terms of cost, complexity, power density, reliability, and efficiency. To meet the growing demand for such applications, new power converter topologies that use the above voltage-boosting techniques, as well as some active and passive components, are continuously being proposed. The permutations and combinations of the various voltage-boosting techniques with additional components in a circuit allow for numerous new topologies and configurations, which are often confusing and difficult to follow. Therefore, to present a clear picture on the general law and framework of the development of next-generation step-up dc–dc converters, this paper aims to comprehensively review and classify various step-up dc–dc converters based on their characteristics and voltage-boosting techniques. In addition, the advantages and disadvantages of these voltage-boosting techniques and associated converters are discussed in detail. Finally, broad applications of dc–dc converters are presented and summarized with comparative study of different voltage-boosting techniques.

Journal ArticleDOI
TL;DR: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality, so thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older.

Journal ArticleDOI
TL;DR: Efforts to reverse global trends in freshwater degradation now depend on bridging an immense gap between the aspirations of conservation biologists and the accelerating rate of species endangerment.
Abstract: In the 12 years since Dudgeon et al. (2006) reviewed major pressures on freshwater ecosystems, the biodiversity crisis in the world’s lakes, reservoirs, rivers, streams and wetlands has deepened. While lakes, reservoirs and rivers cover only 2.3% of the Earth’s surface, these ecosystems host at least 9.5% of the Earth’s described animal species. Furthermore, using the World Wide Fund for Nature’s Living Planet Index, freshwater population declines (83% between 1970 and 2014) continue to outpace contemporaneous declines in marine or terrestrial systems. The Anthropocene has brought multiple new and varied threats that disproportionately impact freshwater systems. We document 12 emerging threats to freshwater biodiversity that are either entirely new since 2006 or have since intensified: (i) changing climates; (ii) e-commerce and invasions; (iii) infectious diseases; (iv) harmful algal blooms; (v) expanding hydropower; (vi) emerging contaminants; (vii) engineered nanomaterials; (viii) microplastic pollution; (ix) light and noise; (x) freshwater salinisation; (xi) declining calcium; and (xii) cumulative stressors. Effects are evidenced for amphibians, fishes, invertebrates, microbes, plants, turtles and waterbirds, with potential for ecosystem-level changes through bottom-up and top-down processes. In our highly uncertain future, the net effects of these threats raise serious concerns for freshwater ecosystems. However, we also highlight opportunities for conservation gains as a result of novel management tools (e.g. environmental flows, environmental DNA) and specific conservation-oriented actions (e.g. dam removal, habitat protection policies,managed relocation of species) that have been met with varying levels of success.Moving forward, we advocate hybrid approaches that manage fresh waters as crucial ecosystems for human life support as well as essential hotspots of biodiversity and ecological function. Efforts to reverse global trends in freshwater degradation now depend on bridging an immense gap between the aspirations of conservation biologists and the accelerating rate of species endangerment.

Book ChapterDOI
08 Oct 2016
TL;DR: A multi-scale deep neural network for single-image dehazing by learning the mapping between hazy images and their corresponding transmission maps by combining a coarse-scale net which predicts a holistic transmission map based on the entire image, and a fine-scale network which refines results locally.
Abstract: The performance of existing image dehazing methods is limited by hand-designed features, such as the dark channel, color disparity and maximum contrast, with complex fusion schemes. In this paper, we propose a multi-scale deep neural network for single-image dehazing by learning the mapping between hazy images and their corresponding transmission maps. The proposed algorithm consists of a coarse-scale net which predicts a holistic transmission map based on the entire image, and a fine-scale net which refines results locally. To train the multi-scale deep network, we synthesize a dataset comprised of hazy images and corresponding transmission maps based on the NYU Depth dataset. Extensive experiments demonstrate that the proposed algorithm performs favorably against the state-of-the-art methods on both synthetic and real-world images in terms of quality and speed.

Proceedings ArticleDOI
27 May 2015
TL;DR: Spark SQL is a new module in Apache Spark that integrates relational processing with Spark's functional programming API, and includes a highly extensible optimizer, Catalyst, built using features of the Scala programming language.
Abstract: Spark SQL is a new module in Apache Spark that integrates relational processing with Spark's functional programming API. Built on our experience with Shark, Spark SQL lets Spark programmers leverage the benefits of relational processing (e.g. declarative queries and optimized storage), and lets SQL users call complex analytics libraries in Spark (e.g. machine learning). Compared to previous systems, Spark SQL makes two main additions. First, it offers much tighter integration between relational and procedural processing, through a declarative DataFrame API that integrates with procedural Spark code. Second, it includes a highly extensible optimizer, Catalyst, built using features of the Scala programming language, that makes it easy to add composable rules, control code generation, and define extension points. Using Catalyst, we have built a variety of features (e.g. schema inference for JSON, machine learning types, and query federation to external databases) tailored for the complex needs of modern data analysis. We see Spark SQL as an evolution of both SQL-on-Spark and of Spark itself, offering richer APIs and optimizations while keeping the benefits of the Spark programming model.