Experimental Study of Granular Clogging in Two-Dimensional Hopper

We experimentally investigate the clogging process of granular materials in a two-dimensional hopper, and present a self-consistent physical mechanism of clogging based on preformed dynamic chain structures in the flow. We found that these chain structures follow a specific modified restricted random walk, and clogging occurs when they are mechanically stable enough to withstand the flow fluctuations, resulting in the formation of an arch at the outlet. We introduce a simple model which can explain the clogging probability by incorporating an analytical expression for chain formation and its transition into an arch. Our results provide insight into the microscopic mechanism of clogging in hopper flow.Comment: 22 pages, 8 figure

Blood Eosinophils and Clinical Outcomes in Patients With Acute Exacerbation of Chronic Obstructive Pulmonary Disease: A Propensity Score Matching Analysis of Real-World Data in China

Background and Objective: Elevated eosinophils in chronic obstructive pulmonary disease (COPD) are recognized as a biomarker to guide inhaled corticosteroids use, but the value of blood eosinophils in hospitalized exacerbations of COPD remains controversial. This study aimed to evaluate the accuracy of eosinophils in predicting clinical outcomes in acute exacerbation of COPD (AECOPD).Methods: We analyzed data from the acute exacerbation of chronic obstructive pulmonary disease inpatient registry (ACURE) study, which is an ongoing nationwide multicenter, observational real-world study in patients admitted for AECOPD. Data collected between January 2018 and December 2019 in 163 centers were first reviewed. The eligible patients were divided into eosinophilic and non-eosinophilic groups, according to blood eosinophil with 2% of the total leukocyte count as the threshold. Propensity score (PS) matching was performed to adjust for confounders.Results: A total of 1,566 patients (median age: 69 years; 80.3% male) were included and 42.7% had an eosinophilic AECOPD. Eosinophil count <2% was associated with the development of respiratory failure and pneumonia. After PS matching, 650 pairs in overall patients, 468 pairs in patients with smoking history and 177 pairs in patients without smoking were selected, respectively. Only in patients with smoking history, the non-eosinophilic AECOPD was associated with longer median hospital stays (9 vs. 8 days, P = 0.034), higher dosage of corticosteroid use, higher economic burden of hospitalization, and poorer response to corticosteroid therapy compared to the eosinophilic AECOPD. No significant difference was found in patients without smoking. Eosinophil levels had no relationship with the change of COPD Assessment Test scores and readmissions or death after 30 days.Conclusion: Elevated eosinophils were associated with better short-term outcomes only in patients with a smoking history. Eosinophil levels cannot be confidently used as a predictor alone for estimating prognosis

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Determining Alloy Nucleation Core Origin and Grain Refinement Strategy Based on the Dependence Degree of Content Difference

What is nucleation core origin during alloy solidification, especially for equiaxed grains? Different dependence degrees of the magnitude or occurrence of element content variation could shed light on this long-standing issue in actual large ingots. Here, based on etched surface height and grayscale, element content distributions within the solid fraction in continuous casting billets and additive manufacturing samples are first obtained by only a two-dimensional surface. Then, combined with the phylogenetic trees, the rank correlation is applied to measure the dependence of content differences during initial solidification. Assessments of external dependence degrees are helpful to determine nucleation core origin and low internal dependence degree facilitates grain refinement. Moreover, in continuous casting, some nucleation cores in the central equiaxed grain zone are confirmed to originate from the edge-chilled zone and high equiaxed grain area ratio under a low superheat, which is attributed to the low ratio of temperature gradient to growth rate rather than remelting fewer cores originating from the chilled zone. In addition, the floating behavior of separated grains originating from the chilled zone can be affected by gravity force, but these grains should be more active when increasing the casting superheat that may weaken the influence of gravity to a certain extent

County Economy, Population, Construction Land, and Carbon Intensity in a Shrinkage Scenario

As the largest ecological background system and basic economic unit in China, counties are of great significance to China’s carbon emission reduction targets. This article conducts theoretical model construction and empirical test research from a contraction perspective, using population and built-up area change as variables and combining indicators of county scale structure in an attempt to find key scale structure elements and representative indicators that affect the carbon emission intensity of counties. By using data from 140 counties in Northeast China during the period of 2015–2020, an empirical study was conducted on population shrinkage clustering, county size structure, and carbon emission intensity. The results show that: (1) population shrinkage significantly increases the carbon intensity of counties, but the contribution of population shrinkage to carbon intensity is scale-heterogeneous, the contribution effect decreases with population size, and the effect on large counties is minimal; (2) population size and industrial structure are the main factors influencing carbon intensity in counties, both have a negative linear elasticity relationship, and GDP per capita is not included in the overall model and is only significant in large counties; (3) the relationship between total construction land and carbon intensity is an inverted U-shaped Kuznets curve, with a critical value of 30 km2, and the total construction land in most counties is below or close to the critical value

The Effect of Urban Shrinkage on Carbon Dioxide Emissions Efficiency in Northeast China

Climate change caused by CO2 emissions is a controversial topic in today’s society; improving CO2 emission efficiency (CEE) is an important way to reduce carbon emissions. While studies have often focused on areas with high carbon and large economies, the areas with persistent contraction have been neglected. These regions do not have high carbon emissions, but are facing a continuous decline in energy efficiency; therefore, it is of great relevance to explore the impact and mechanisms of CO2 emission efficiency in shrinking areas or shrinking cities. This paper uses a super-efficiency slacks-based measure (SBM) model to measure the CO2 emission efficiency and potential CO2 emission reduction (PCR) of 33 prefecture-level cities in northeast China from 2006 to 2019. For the first time, a Tobit model is used to analyze the factors influencing CEE, using the level of urban shrinkage as the core variable, with socio-economic indicators and urban construction indicators as control variables, while the mediating effect model is applied to identify the transmission mechanism of urban shrinkage. The results show that the CEE index of cities in northeast China is decreasing by 1.75% per annum. For every 1% increase in urban shrinkage, CEE decreased by approximately 2.1458%, with urban shrinkage, industrial structure, and expansion intensity index (EII) being the main factors influencing CEE. At the same time, urban shrinkage has a further dampening effect on CEE by reducing research and development expenditure (R&D) and urban compactness (COMP), with each 1% increase in urban shrinkage reducing R&D and COMP by approximately 0.534% and 1.233%, respectively. This can be improved by making full use of the available built-up space, increasing urban density, and promoting investment in research

CSE reduces OTUD4 triggering lung epithelial cell apoptosis via PAI-1 degradation

Abstract Ovarian tumor family deubiquitinase 4 (OTUD4), a member of the OTU deubiquitinating enzyme, is implicated to decrease in cancer to regulate cell apoptosis. However, the role of OTUD4 in cigarette smoke induced epithelial cell apoptosis and its mechanism have not been elucidated. In this study, we showed that OTUD4 protein reduced in CSE treated mice and airway epithelial cells. OTUD4 silence aggravated cell apoptosis and emphysematous change in the lung tissue of cigarette smoke extract (CSE) treated mice. Additionally, restoration of OTUD4 in the lung of mice alleviated CSE induced apoptosis and emphysematous morphology change. The effect of OTUD4 on cell apoptosis was also confirmed in vitro. Through protein profile screening, we identified that OTUD4 may interact with plasminogen activator inhibitor 1(PAI-1). We further confirmed that OTUD4 interacted with PAI-1 for de-ubiquitination and inhibiting CSE induced PAI-1 degradation. Furthermore, the protective role of OTUD4 in airway epithelial cells apoptosis was blocked by PAI-1 deactivation. Taken together, our data suggest that OTUD4 regulates cigarette smoke (CS)-triggered airway epithelial cell apoptosis via modulating PAI-1 degradation. Targeting OUTD4/PAI-1 signaling might potentially provide a therapeutic target against the lung cell apoptosis in cigarette smoke (CS)-induced emphysema

Characterization of a novel flavored yogurt enriched in γ-aminobutyric acid fermented by Levilactobacillus brevis CGMCC1.5954

ABSTRACT: This study developed and characterized a γ-aminobutyric acid (GABA)-enriched yogurt fermented by Levilactobacillus brevis CGMCC1.5954. The GABA content in the yogurt was 147.36 mg/100 mL, which was 317.06% higher than that of the control group. Furthermore, there was a significant improvement in the aroma, hardness, adhesion, cohesiveness, and gelatinousness of yogurt. The chromatography and metabolomics analyses further confirmed the high GABA content in yogurt and its nutritional value, and the metabolic pathway for GABA production by L. brevis 54 was identified. A total of 58 volatile flavor compounds were identified using headspace solid-phase microextraction-gas chromatography-mass spectrometry, of which 2-nonanone and 2-heptanone may be responsible for the high odor score of GABA-enriched yogurt. This study developed a nutritious and unique GABA-enriched flavored yogurt, summarized the metabolic pathway of GABA, and provided a flavor fingerprint that could guide the production of specifically flavored yogurts