181 research outputs found
A Tent L\'evy Flying Sparrow Search Algorithm for Feature Selection: A COVID-19 Case Study
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
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
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
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
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
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
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
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Cognitive Benefits of Activity Engagement among 12,093 Adults Aged over 65 Years.
OBJECTIVE: The present study includes two aims: (1) to understand patterns of activity engagement among older Chinese adults; (2) to further investigate associations between activity engagement and cognitive abilities in this population. METHODS: Latent class analysis was applied to answer the aforementioned research questions across different age ranges while controlling for confounding variables (age, health, socioeconomic status (SES), and living alone). Specifically, five latent classes (non-active, working-active, comprehensive-active, physical-active, and less-active) were identified. Furthermore, associations between the classes of activity engagement and cognition were examined separately in three age groups: less than 80 years (young-old group), 80-99.5 years (old-old group) and more than 100 years (oldest-old group) of age. RESULTS: Compared with Non-active older individuals, the other classes with a higher probability of engagement in various activities generally showed higher cognitive abilities (including general cognition, orientation, calculation, recall, and language), but not all patterns of active engagement in daily life were positively associated with better cognitive status across different age ranges. In particular, differences in the individuals' cognitive abilities across the four active latent classes were especially obvious in the old-old group as follows: the Comprehensive-active class had higher general cognitive and recall abilities than the other three active classes and higher calculation and language abilities than the Working-active class. In addition, significant sex differences were observed in activity patterns, cognition, and their associations in the young-old and old-old groups. Culture-specific programs should be customized to subgroups of different ages and genders by providing different training or activity modules based on their related dimensions of cognitive decline
Disparities and risks of sexually transmissible infections among men who have sex with men in China: a meta-analysis and data synthesis.
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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