170 research outputs found

    A Tent L\'evy Flying Sparrow Search Algorithm for Feature Selection: A COVID-19 Case Study

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    The "Curse of Dimensionality" induced by the rapid development of information science, might have a negative impact when dealing with big datasets. In this paper, we propose a variant of the sparrow search algorithm (SSA), called Tent L\'evy flying sparrow search algorithm (TFSSA), and use it to select the best subset of features in the packing pattern for classification purposes. SSA is a recently proposed algorithm that has not been systematically applied to feature selection problems. After verification by the CEC2020 benchmark function, TFSSA is used to select the best feature combination to maximize classification accuracy and minimize the number of selected features. The proposed TFSSA is compared with nine algorithms in the literature. Nine evaluation metrics are used to properly evaluate and compare the performance of these algorithms on twenty-one datasets from the UCI repository. Furthermore, the approach is applied to the coronavirus disease (COVID-19) dataset, yielding the best average classification accuracy and the average number of feature selections, respectively, of 93.47% and 2.1. Experimental results confirm the advantages of the proposed algorithm in improving classification accuracy and reducing the number of selected features compared to other wrapper-based algorithms

    Effects of postharvest techniques on nutritional quality of cherry tomatoes

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    Cherry tomatoes play an important part in the human diet as they have a high content of nutritional component, including ascorbic acid, carotenoids and total phenolics. This study aimed to investigate how postharvest techniques, temperature, light irradiation and Modified atmosphere packaging (MAP) affected nutritional quality of cherry tomatoes, and to identify the strategies to preserve their quality. Three temperatures (5, 15, 20Β°C) were examined to evaluate the effect of temperature on cherry tomatoes. A storage temperature of 15Β°C was found to inhibit weight loss and the decrease of lycopene, s-carotene and lutein content when compared with 20Β°C, whereas a low temperature (5Β°C) caused chilling injuries, such as pour colour development, and inhibited the increase of lycopene and s-carotene content compared with 15 and 20Β°C. The effect of postharvest red/far-red (ratio 0.89) and blue light irradiation on fruit quality was also investigated. The results showed that red/far-red light inhibited weight loss, inducing colour changing from green to red, and increased the content of lycopene, b-carotene, and total phenolics compared to darkness. In contrast, blue light induced weight loss, and had little effect on colour change and the content of ascorbic acid, lycopene and total phenolics compared to darkness. The influence of the combination of red/far-red light and modified atmosphere packaging on fruit quality was also examined. The results showed that the combined treatment effectively extended shelf-life of cherry tomatoes by delaying ripening as indicated by the delayed increase of respiration and colour change from green to red, reduced weight loss, and increased the content of lycopene and s-carotene. The role and mechanism of red/far-red light in the regulation of carotenoid biosynthesis were explored. Results showed that gene Phytoene synthase (PSY), Zeta carotene (ZDS) and Chloroplast lycopene beta cyclase (LCY-b) and were overexpressed in fruits treated with red/far-red light during storage compared to the darkness. Moreover, red/far-red light induced expression of 1-aminocyclopropane-1- carboxylate synthase 2 (ACS2) during the first 25 days of storage, Ripening inhibitor (RIN) during the first 28 days and Elongated hypocotyl 5 (HY5) during the whole period of storage. This provided a hypothetical model of red/far-red light in the regulation of carotenoid biosynthesis

    A Reinforcement Learning-assisted Genetic Programming Algorithm for Team Formation Problem Considering Person-Job Matching

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    An efficient team is essential for the company to successfully complete new projects. To solve the team formation problem considering person-job matching (TFP-PJM), a 0-1 integer programming model is constructed, which considers both person-job matching and team members' willingness to communicate on team efficiency, with the person-job matching score calculated using intuitionistic fuzzy numbers. Then, a reinforcement learning-assisted genetic programming algorithm (RL-GP) is proposed to enhance the quality of solutions. The RL-GP adopts the ensemble population strategies. Before the population evolution at each generation, the agent selects one from four population search modes according to the information obtained, thus realizing a sound balance of exploration and exploitation. In addition, surrogate models are used in the algorithm to evaluate the formation plans generated by individuals, which speeds up the algorithm learning process. Afterward, a series of comparison experiments are conducted to verify the overall performance of RL-GP and the effectiveness of the improved strategies within the algorithm. The hyper-heuristic rules obtained through efficient learning can be utilized as decision-making aids when forming project teams. This study reveals the advantages of reinforcement learning methods, ensemble strategies, and the surrogate model applied to the GP framework. The diversity and intelligent selection of search patterns along with fast adaptation evaluation, are distinct features that enable RL-GP to be deployed in real-world enterprise environments.Comment: 16 page

    Ensemble Reinforcement Learning: A Survey

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    Reinforcement Learning (RL) has emerged as a highly effective technique for addressing various scientific and applied problems. Despite its success, certain complex tasks remain challenging to be addressed solely with a single model and algorithm. In response, ensemble reinforcement learning (ERL), a promising approach that combines the benefits of both RL and ensemble learning (EL), has gained widespread popularity. ERL leverages multiple models or training algorithms to comprehensively explore the problem space and possesses strong generalization capabilities. In this study, we present a comprehensive survey on ERL to provide readers with an overview of recent advances and challenges in the field. First, we introduce the background and motivation for ERL. Second, we analyze in detail the strategies that have been successfully applied in ERL, including model averaging, model selection, and model combination. Subsequently, we summarize the datasets and analyze algorithms used in relevant studies. Finally, we outline several open questions and discuss future research directions of ERL. By providing a guide for future scientific research and engineering applications, this survey contributes to the advancement of ERL.Comment: 42 page

    Characteristics and formation mechanism of intestinal bacteria particles emitted from aerated wastewater treatment tanks

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    Aeration tanks in municipal wastewater treatment plants (WWTPs) are regarded as sources of bioaerosols, often containing particles and microbes. In this study, intestinal bacteria were investigated from biochemical reaction tanks (BRTs) of six municipal WWTPs. It was observed that 86β€―CFU/m3 of intestinal bacteria (in average) occurred in the BRTs installed surface aerator, which was higher than those adopted submerged aeration (67β€―CFU/m3 in average). 62.72% of fine particles were observed in the BRTs supplied oxygen by submerged aerator, while 75.73% of coarse particles emitted during surface aeration. Pseudomonas sp., Serratia sp. and Acinetobacter sp. were identified as pathogenic bacteria presented in the intestinal bacteria population and most of them existed initially in water or sludge, particularly in water surface. The emission level and particle size distribution were significantly correlated with aeration mode adopted by the WWTPs. The bioaerosols particles emitted from surface aeration process was higher than that from submerged aeration process. Meanwhile, the BRTs with submerged aerators released more fine particles, which can get into the alveoli and represented the potential challenge to human health. Canonical correspondence analysis results exhibited that population of intestinal bacteria had a positive correlation with aeration rate and water quality. As the intestinal bacteria in the bioaerosols emitted from the WWTPs may pose a potential risk to onsite operators, aeration tanks in WWTPs should be paid more attention as a source of intestinal bacterial emissions

    Reinforcement Learning-assisted Evolutionary Algorithm: A Survey and Research Opportunities

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    Evolutionary algorithms (EA), a class of stochastic search methods based on the principles of natural evolution, have received widespread acclaim for their exceptional performance in various real-world optimization problems. While researchers worldwide have proposed a wide variety of EAs, certain limitations remain, such as slow convergence speed and poor generalization capabilities. Consequently, numerous scholars actively explore improvements to algorithmic structures, operators, search patterns, etc., to enhance their optimization performance. Reinforcement learning (RL) integrated as a component in the EA framework has demonstrated superior performance in recent years. This paper presents a comprehensive survey on integrating reinforcement learning into the evolutionary algorithm, referred to as reinforcement learning-assisted evolutionary algorithm (RL-EA). We begin with the conceptual outlines of reinforcement learning and the evolutionary algorithm. We then provide a taxonomy of RL-EA. Subsequently, we discuss the RL-EA integration method, the RL-assisted strategy adopted by RL-EA, and its applications according to the existing literature. The RL-assisted procedure is divided according to the implemented functions including solution generation, learnable objective function, algorithm/operator/sub-population selection, parameter adaptation, and other strategies. Finally, we analyze potential directions for future research. This survey serves as a rich resource for researchers interested in RL-EA as it overviews the current state-of-the-art and highlights the associated challenges. By leveraging this survey, readers can swiftly gain insights into RL-EA to develop efficient algorithms, thereby fostering further advancements in this emerging field.Comment: 26 pages, 16 figure

    A Genome-Wide Analysis of StTGA Genes Reveals the Critical Role in Enhanced Bacterial Wilt Tolerance in Potato During Ralstonia solanacearum Infection

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    TGA is one of the members of TGACG sequence-specific binding protein family, which plays a crucial role in the regulated course of hormone synthesis as a stress-responsive transcription factor (TF). Little is known, however, about its implication in response to bacterial wilt disease in potato (Solanum tuberosum) caused by Ralstonia solanacearum. Here, we performed an in silico identification and analysis of the members of the TGA family based on the whole genome data of potato. In total, 42 StTGAs were predicted to be distributed on four chromosomes in potato genome. Phylogenetic analysis showed that the proteins of StTGAs could be divided into six sub-families. We found that many of these genes have more than one exon according to the conserved motif and gene structure analysis. The heat map inferred that StTGAs are generally expressed in different tissues which are at different stages of development. Genomic collinear analysis showed that there are homologous relationships among potato, tomato, pepper, Arabidopsis, and tobacco TGA genes. Cis-element in silico analysis predicted that there may be many cis-acting elements related to abiotic and biotic stress upstream of StTGA promoter including plant hormone response elements. A representative member StTGA39 was selected to investigate the potential function of the StTGA genes for further analysis. Quantitative real-time polymerase chain reaction (qRT-PCR) assays indicated that the expression of the StTGAs was significantly induced by R. solanacearum infection and upregulated by exogenous salicylic acid (SA), abscisic acid (ABA), gibberellin 3 (GA3), and methyl jasmonate (MeJA). The results of yeast one-hybrid (Y1H) assay showed that StTGA39 regulates S. tuberosum BRI1-associated receptor kinase 1 (StBAK1) expression. Thus, our study provides a theoretical basis for further research of the molecular mechanism of the StTGA gene of potato tolerance to bacterial wilt

    Disparities and risks of sexually transmissible infections among men who have sex with men in China: a meta-analysis and data synthesis.

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    BACKGROUND: Sexually transmitted infections (STIs), including Hepatitis B and C virus, are emerging public health risks in China, especially among men who have sex with men (MSM). This study aims to assess the magnitude and risks of STIs among Chinese MSM. METHODS: Chinese and English peer-reviewed articles were searched in five electronic databases from January 2000 to February 2013. Pooled prevalence estimates for each STI infection were calculated using meta-analysis. Infection risks of STIs in MSM, HIV-positive MSM and male sex workers (MSW) were obtained. This review followed the PRISMA guidelines and was registered in PROSPERO. RESULTS: Eighty-eight articles (11 in English and 77 in Chinese) investigating 35,203 MSM in 28 provinces were included in this review. The prevalence levels of STIs among MSM were 6.3% (95% CI: 3.5-11.0%) for chlamydia, 1.5% (0.7-2.9%) for genital wart, 1.9% (1.3-2.7%) for gonorrhoea, 8.9% (7.8-10.2%) for hepatitis B (HBV), 1.2% (1.0-1.6%) for hepatitis C (HCV), 66.3% (57.4-74.1%) for human papillomavirus (HPV), 10.6% (6.2-17.6%) for herpes simplex virus (HSV-2) and 4.3% (3.2-5.8%) for Ureaplasma urealyticum. HIV-positive MSM have consistently higher odds of all these infections than the broader MSM population. As a subgroup of MSM, MSW were 2.5 (1.4-4.7), 5.7 (2.7-12.3), and 2.2 (1.4-3.7) times more likely to be infected with chlamydia, gonorrhoea and HCV than the broader MSM population, respectively. CONCLUSION: Prevalence levels of STIs among MSW were significantly higher than the broader MSM population. Co-infection of HIV and STIs were prevalent among Chinese MSM. Integration of HIV and STIs healthcare and surveillance systems is essential in providing effective HIV/STIs preventive measures and treatments. TRIAL REGISTRATION: PROSPERO NO: CRD42013003721
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