Multiperspective Light Field Reconstruction Method via Transfer Reinforcement Learning

Compared with traditional imaging, the light field contains more comprehensive image information and higher image quality. However, the available data for light field reconstruction are limited, and the repeated calculation of data seriously affects the accuracy and the real-time performance of multiperspective light field reconstruction. To solve the problems, this paper proposes a multiperspective light field reconstruction method based on transfer reinforcement learning. Firstly, the similarity measurement model is established. According to the similarity threshold of the source domain and the target domain, the reinforcement learning model or the feature transfer learning model is autonomously selected. Secondly, the reinforcement learning model is established. The model uses multiagent (i.e., multiperspective) Q-learning to learn the feature set that is most similar to the target domain and the source domain and feeds it back to the source domain. This model increases the capacity of the source-domain samples and improves the accuracy of light field reconstruction. Finally, the feature transfer learning model is established. The model uses PCA to obtain the maximum embedding space of source-domain and target-domain features and maps similar features to a new space for label data migration. This model solves the problems of multiperspective data redundancy and repeated calculations and improves the real-time performance of maneuvering target recognition. Extensive experiments on PASCAL VOC datasets demonstrate the effectiveness of the proposed algorithm against the existing algorithms

Adsorption of Coxsackievirus in Sediments: Influencing Factors, Kinetics, and Isotherm Modeling

Drinking groundwater contamination by pathogenic viruses represents a serious risk to worldwide public health, particularly for enteric viruses, which exhibit high prevalence and occurrence during outbreaks. Understanding how enteric viruses adsorb in groundwater is essential to protecting human health and ensuring the sustainable use of water resources. The adsorption properties of Coxsackievirus A16 (CA16), a common gastrointestinal virus that spreads through groundwater, were investigated in this work. A typical batch equilibrium approach was used to investigate CA16 adsorption and factors that influence it. In a laboratory recognized nationally as a biosafety level 2 facility, stringent research protocols were followed to guarantee compliance with experimental standards. The variables that were investigated included the size of the sediment particles, the starting concentration of the virus, temperature, pH level, and humic acid content. The findings showed that the CA16 virus was more strongly attracted to finer sediment particles and that its adsorption increased as the size of the sediment particle decreased. Furthermore, it was discovered that higher temperatures improved the CA16 virus’s ability to bind to sediment particles. The pH of the aqueous environment has a significant effect on the effectiveness of virus adsorption; higher effectiveness was seen in acidic environments. Furthermore, it was found that the presence of humic acid decreased the ability of clay to adsorb CA16, suggesting that humic acid has a detrimental influence on clay’s ability to adsorb viruses. The examination of kinetic models demonstrated that, in every scenario examined, the adsorption process of CA16 adhered to the pseudo-second-order kinetics model. Additionally, the Langmuir and Freundlich isotherm models were used to assess the equilibrium data that were collected in this investigation. The outcomes amply proved that the most accurate representation of the adsorption equilibrium was given by the Langmuir isotherm model. The study offered a solid scientific foundation for treating groundwater and creating plans to stop the spread of viruses

Correction: De novo assembly and analysis of the transcriptome of Rumex patientia L. during cold stress.

[This corrects the article DOI: 10.1371/journal.pone.0186470.]

De novo assembly and analysis of the transcriptome of Rumex patientia L. during cold stress.

Rumex patientia L. is consumed as a green vegetable in several parts of the world, and can withstand extremely low temperatures (-35°C). However, little or no available genomic data for this species has been reported to date. Here, we used Illumina Hiseq technology for transcriptome assembly in R. patientia under normal and cold conditions to evaluate how it responds to cold stress.After an in-depth RNA-Seq analysis, 115,589 unigenes were produced from the assembled transcripts. Based on similarity search analysis with seven databases, we obtained and annotated 60,157 assembled unigenes to at least one database. In total, 1,179 unigenes that were identified as differentially expressed genes (DEGs), including up-regulated (925) and down-regulated ones (254), were successfully assigned GO annotations and classified into three major metabolic pathways. Ribosome, carbon metabolism, oxidative phosphorylation and biosynthesis of amino acids were the most highly enriched pathways according to KEGG analysis. Overall, 66 up-regulated genes were identified as putatively involved in the response to cold stress, including members of MYB, AP2/ERF, CBF, Znf, bZIP, NAC and COR families.To our knowledge, this investigation was the first to provide a cold-responsive (COR) transcriptome assembly in R. patientia. A large number of potential COR genes were identified, suggesting that this species is suitable for cultivation in northern China. In summary, these data provide valuable information for future research and genomic studies in R. patientia

KEGG pathway classification of <i>R</i>. <i>patientia</i> unigenes.

<p>KEGG pathway classification of <i>R</i>. <i>patientia</i> unigenes.</p

Functional annotation of unigenes based on Gene Ontology (GO) classification.

<p>Functional annotation of unigenes based on Gene Ontology (GO) classification.</p

Statistics of transcriptome assemble and unigenes.

<p>Statistics of transcriptome assemble and unigenes.</p

The expression of <i>R</i>. <i>patientia</i> genes in response to chilling at different temperature for 0 to 8 h as determined by qRT-PCR.

<p>The expression of <i>R</i>. <i>patientia</i> genes in response to chilling at different temperature for 0 to 8 h as determined by qRT-PCR.</p

Sequencing output statistics of control and cold-treated <i>R</i>. <i>patientia</i>.

<p>Sequencing output statistics of control and cold-treated <i>R</i>. <i>patientia</i>.</p