Explore the vast range of titles available.

The gold standard for clinical assessment of Autism Spectrum Disorders (ASD) relies on assessing behavior via semi-structured play-based interviews and parent interviews. Although these methods show good sensitivity and specificity in diagnosing ASD cases, behavioral assessments alone may hinder the identification of asymptomatic at-risk group. Resting-state functional magnetic resonance imaging (rs-fMRI) could be an appropriate approach to produce objective neural markers to supplement behavioral assessments due to its non-invasive and task-free nature. Previous neuroimaging studies reported inconsistent resting-state abnormalities in ASD, which may be explained by small sample sizes and phenotypic heterogeneity in ASD subjects, and/or the use of different analytical methods across studies. The current study aims to investigate the local resting-state abnormalities of ASD regardless of subject age, IQ, gender, disease severity and methodological differences, using activation likelihood estimation (ALE). MEDLINE/PubMed databases were searched for whole-brain rs-fMRI studies on ASD published until Feb 2018. Eight experiments involving 424 subjects were included in the ALE meta-analysis. We demonstrate two ASD-related resting-state findings: local underconnectivity in the dorsal posterior cingulate cortex (PCC) and in the right medial paracentral lobule. This study contributes to uncovering a consistent pattern of resting-state local abnormalities that may serve as potential neurobiological markers for ASD.

Existing computational models for salient object detection primarily rely on hand-crafted features, which are only able to capture low-level contrast information. In this paper, we learn the hierarchical contrast features by formulating salient object detection as a binary labeling problem using deep learning techniques. A novel superpixelwise convolutional neural network approach, called SuperCNN, is proposed to learn the internal representations of saliency in an efficient manner. In contrast to the classical convolutional networks, SuperCNN has four main properties. First, the proposed method is able to learn the hierarchical contrast features, as it is fed by two meaningful superpixel sequences, which is much more effective for detecting salient regions than feeding raw image pixels. Second, as SuperCNN recovers the contextual information among superpixels, it enables large context to be involved in the analysis efficiently. Third, benefiting from the superpixelwise mechanism, the required number of predictions for a densely labeled map is hugely reduced. Fourth, saliency can be detected independent of region size by utilizing a multiscale network structure. Experiments show that SuperCNN can robustly detect salient objects and outperforms the state-of-the-art methods on three benchmark datasets.

Quantum coherence, present whenever a quantum system exists in a superposition of multiple classically distinct states, marks one of the fundamental departures from classical physics. Quantum coherence has recently been investigated rigorously within a resource-theoretic formalism. However, the finer-grained notion of multilevel coherence, which explicitly takes into account the number of superposed classical states, has remained relatively unexplored. A comprehensive analysis of multilevel coherence, which acts as the single-party analogue to multipartite entanglement, is essential for understanding natural quantum processes as well as for gauging the performance of quantum technologies. Here, we develop the theoretical and experimental groundwork for characterizing and quantifying multilevel coherence. We prove that nontrivial levels of purity are required for multilevel coherence, as there is a ball of states around the maximally mixed state that do not exhibit multilevel coherence in any basis. We provide a simple, necessary, and sufficient analytical criterion to verify the presence of multilevel coherence, which leads to a complete classification of multilevel coherence for three-level systems. We present the robustness of multilevel coherence, a bona fide quantifier, which we show to be numerically computable via semidefinite programming and experimentally accessible via multilevel coherence witnesses, which we introduce and characterize. We further verify and lower bound the robustness of multilevel coherence by performing a semi-device-independent phase discrimination task, which is implemented experimentally with four-level quantum probes in a photonic setup. Our results contribute to understanding the operational relevance of genuine multilevel coherence, also by demonstrating the key role it plays in enhanced phase discrimination—a primitive for quantum communication and metrology—and suggest new ways to reliably and effectively test the quantum behavior of physical systems.

The first measurement of the influence of the Stokes number on the distributions of particle concentration and velocity at the exit of a long pipe are reported, together with the subsequent influence on the downstream evolution of these distributions through a particle-laden jet in co-flow. The data were obtained by simultaneous particle image velocimetry (PIV) and planar nephelometry (PN), using four cameras to provide high resolution through the first 30 jet diameters and also correction for optical attenuation. These data provide much more detailed information than is available from previous measurements. From them, a new understanding is obtained of how the Stokes number influences the flow at the jet exit plane and how this influence propagates throughout the jet.

A growing body of research has employed information and communication technologies (ICTs) such as the Internet and mobile phones for disseminating physical activity (PA) interventions with young populations. Although several systematic reviews have documented the effects of ICT-based interventions on PA behavior, very few have focused on children and adolescents specifically. The present review aimed to systematically evaluate the efficacy and methodological quality of ICT-based PA interventions for children and adolescents based on evidence from randomized controlled trials. Electronic databases Medline, PsycInfo, CINAHL, and Web of Science were searched to retrieve English language articles published in international academic peer-reviewed journals from January 1, 1997, through December 31, 2009. Included were articles that provided descriptions of interventions designed to improve PA-related cognitive, psychosocial, and behavioral outcomes and that used randomized controlled trial design, included only children (6-12 years old) and adolescents (13-18 years old) in both intervention and control groups, and employed Internet, email, and/or short message services (SMS, also known as text messaging) as one or more major or assistive modes to deliver the intervention. In total, 9 studies were analyzed in the present review. All studies were published after 2000 and conducted in Western countries. Of the 9 studies, 7 demonstrated positive and significant within-group differences in at least one psychosocial or behavioral PA outcome. In all, 3 studies reported positive and significant between-group differences favoring the ICT group. When between-group differences were compared across studies, effect sizes were small in 6 studies and large in 3 studies. With respect to methodological quality, 7 of the 9 studies had good methodological quality. Failure to report allocation concealment, blinding to outcome assessment, and lack of long-term follow-up were the criteria met by the fewest studies. In addition, 5 studies measured the intervention exposure rate and only 1 study employed objective measures to record data. The present review provides evidence supporting the positive effects of ICTs in PA interventions for children and adolescents, especially when used with other delivery approaches (ie, face-to-face). Because ICT delivery approaches are often mixed with other approaches and these studies sometimes lack a comparable control group, additional research is needed to establish the true independent effects of ICT as an intervention delivery mode. Although two-thirds of the studies demonstrated satisfactory methodological quality, several quality criteria should be considered in future studies: clear descriptions of allocation concealment and blinding of outcome assessment, extension of intervention duration, and employment of objective measures in intervention exposure rate. Due to the small number of studies that met inclusion criteria and the lack of consistent evidence, researchers should be cautious when interpreting the findings of the present review.

The coronavirus disease 2019 (COVID-19) pandemic has resulted in millions of patients infected worldwide and indirectly affecting even more individuals through disruption of daily living. Long-term adverse outcomes have been reported with similar diseases from other coronaviruses, namely Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Emerging evidence suggests that COVID-19 adversely affects different systems in the human body. This review summarizes the current evidence on the short-term adverse health outcomes and assesses the risk of potential long-term adverse outcomes of COVID-19. Major adverse outcomes were found to affect different body systems: immune system (including but not limited to Guillain-Barré syndrome and paediatric inflammatory multisystem syndrome), respiratory system (lung fibrosis and pulmonary thromboembolism), cardiovascular system (cardiomyopathy and coagulopathy), neurological system (sensory dysfunction and stroke), as well as cutaneous and gastrointestinal manifestations, impaired hepatic and renal function. Mental health in patients with COVID-19 was also found to be adversely affected. The burden of caring for COVID-19 survivors is likely to be huge. Therefore, it is important for policy makers to develop comprehensive strategies in providing resources and capacity in the healthcare system. Future epidemiological studies are needed to further investigate the long-term impact on COVID-19 survivors.

Current technology using corn stover (CS) as feedstock, Ammonia Fiber Expansion (AFEX) as the pretreatment technology, and Saccharomyces cerevisiae 424A(LNH-ST) as the ethanologenic strain in Separate Hydrolysis and Fermentation was able to achieve 191.5 g EtOH/kg untreated CS, at an ethanol concentration of 40.0 g/L (5.1 vol/vol%) without washing of pretreated biomass, detoxification, or nutrient supplementation. Enzymatic hydrolysis at high solids loading was identified as the primary bottleneck affecting overall ethanol yield and titer. Degradation compounds in AFEX-pretreated biomass were shown to increase metabolic yield and specific ethanol production while decreasing the cell biomass generation. Nutrients inherently present in CS and those resulting from biomass processing are sufficient to support microbial growth during fermentation. This platform offers the potential to improve the economics of cellulosic ethanol production by reducing the costs associated with raw materials, process water, and capital equipment.

Acute upper gastrointestinal bleeding is a common medical emergency worldwide, a major cause of which are bleeding peptic ulcers. Endoscopic treatment and acid suppression with proton-pump inhibitors are cornerstones in the management of the disease, and both treatments have been shown to reduce mortality. The role of emergency surgery continues to diminish. In specialised centres, radiological intervention is increasingly used in patients with severe and recurrent bleeding who do not respond to endoscopic treatment. Despite these advances, mortality from the disorder has remained at around 10%. The disease often occurs in elderly patients with frequent comorbidities who use antiplatelet agents, non-steroidal anti-inflammatory drugs, and anticoagulants. The management of such patients, especially those at high cardiothrombotic risk who are on anticoagulants, is a challenge for clinicians. We summarise the published scientific literature about the management of patients with bleeding peptic ulcers, identify directions for future clinical research, and suggest how mortality can be reduced.

This systematic review and meta-analysis is to evaluate the risk of development of concomitant strabismus due to refractive errors. Eligible studies published from 1946 to April 1, 2016 were identified from MEDLINE and EMBASE that evaluated any kinds of refractive errors (myopia, hyperopia, astigmatism and anisometropia) as an independent factor for concomitant exotropia and concomitant esotropia. Totally 5065 published records were retrieved for screening, 157 of them eligible for detailed evaluation. Finally 7 population-based studies involving 23,541 study subjects met our criteria for meta-analysis. The combined OR showed that myopia was a risk factor for exotropia (OR: 5.23, P = 0.0001). We found hyperopia had a dose-related effect for esotropia (OR for a spherical equivalent [SE] of 2–3 diopters [D]: 10.16, P = 0.01; OR for an SE of 3-4D: 17.83, P < 0.0001; OR for an SE of 4-5D: 41.01, P < 0.0001; OR for an SE of ≥5D: 162.68, P < 0.0001). Sensitivity analysis indicated our results were robust. Results of this study confirmed myopia as a risk for concomitant exotropia and identified a dose-related effect for hyperopia as a risk of concomitant esotropia.