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Objective: To evaluate the effect of Lactobacillus plantarum CCFM8661 on reducing lead in the human body and its effect on human health. Methods: In total, 60 volunteers suffering from foodborne heavy metal exposure were recruited and divided into two groups, with one orally receiving L. plantarum CCFM8661 powder and the other orally receiving a placebo. The protective effect of L. plantarum CCFM8661 on lead-exposed populations was evaluated comprehensively by analyzing the volunteers’ blood lead levels, blood cells, blood biochemical indexes, serum calcium and iron levels before and after interventions. Results: L. plantarum CCFM8661 intervention effectively reduced the blood lead level in the lead-exposed population, and down-regulated total bilirubin, urea and total serum protein while having no significant effect on blood cells, blood calcium or iron levels. Conclusion: L. plantarum CCFM8661 could protect lead-exposed subjects by effectively reducing lead levels and, thereby, has the potential to be further developed into a biological agent for the bioreduction of heavy metals.

The fatigue performance of the asphalt mixture was the main focus of this study, with five typical factors—phase angle, cumulative dissipated energy, failure strain, failure stiffness modulus, and strain rate—identified as potential design indexes. The effect of asphalt content on the parameters under different gradation and stress ratios was tested. It was observed that the selected parameters exhibited varying levels of sensitivity and relevance to the fatigue behavior of asphalt mixtures under cyclic loads. By comparison, the strain rate proved sensitive to the asphalt content and independent of the other parameters, namely aggregate gradations and stress ratio, thus establishing the strain rate as a critical design index based on fatigue performance. On this basis, a design method based on the fatigue performance for the asphalt mixtures is herein proposed. It was confirmed that the asphalt mixture formulated using the proposed method exhibited enhanced fatigue endurance compared to those designed using the conventional method. [ABSTRACT FROM AUTHOR]

From fairy tales, war stories, Gothic novels to domestic novels and children novels, Louisa May Alcott's genre transformations are closely related to the developments and demands of the American literary market in the 19th century, which reflects her sensitivity, flexibility and versatility as a writer. Faced with the needs from the market and readers, Alcott actively adjusts her writings, and thus becomes a successful professional writer. Instead of blindly catering to readers and the market, Alcott "games" with them through the whole career. In her transformation work Little Women, Alcott effectively makes use of the readers' horizons of expectations to develop and innovate the novel, so that it holds its unique and lasting literary values in addition to mere commercial values. In a male-dominated literary market, Alcott's genre choices are also the products of a compromise. Compared with their male counterparts of the same period, female writers suffer from more restrictions and constraints in writing. How to realize individual values and fight for equal rights are vital issues for female writers represented by Alcott. An analysis of Alcott's writings from the perspective of literary market also provides effective references for interpreting women's gender dilemma and ideal demands in this period. [ABSTRACT FROM AUTHOR]

Social distancing is an important non-pharmaceutical intervention tool (NPIs) to prevent the spread of COVID-19. However, it also created negative impacts of economic activities. Understanding the emotions and public opinions about social distancing are important for the future policy making of COVID-19 mitigation and the assessment of public health impacts. This study collected 77,627 number of Twitter messages (tweets) between February 1, 2020 and April 30, 2020 from five English-speaking countries (United States, the United Kingdom, India, Canada, and Australia) using the social distancing keywords. We adopted a multi-module hybrid convolutional neural network model sentiment analysis on social distancing related tweets with 85.95% accuracy. This paper conducts a sentiment analysis of tweets from the public on social distancing measures in five countries. Our findings show similar sentiments in tweets from these five countries, which is more positives than negatives about social distancing measures in the public. Additionally, when the daily number of new cases changes, public sentiment fluctuates with it. We believe that social distancing is effective in preventing the spread of coronavirus. [ABSTRACT FROM AUTHOR]