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Abstract Linear discriminant analysis is a classical method for solving problems of dimensional reduction and pattern classification. Although it has been extensively developed, however, it still suffers from various common problems, such as the Small Sample Size (SSS) and the multimodal problem. Neighbourhood linear discriminant analysis (nLDA) was recently proposed to solve the problem of multimodal class caused by the contravention of independently and identically distributed samples. However, due to the existence of many small‐scale practical applications, nLDA still has to face the SSS problem, which leads to instability and poor generalisation caused by the singularity of the within‐neighbourhood scatter matrix. The authors exploit the eigenspectrum regularisation techniques to circumvent the singularity of the within‐neighbourhood scatter matrix of nLDA, which is called Eigenspectrum Regularisation Reverse Neighbourhood Discriminative Learning (ERRNDL). The algorithm of nLDA is reformulated as a framework by searching two projection matrices. Three eigenspectrum regularisation models are introduced to our framework to evaluate the performance. Experiments are conducted on the University of California, Irvine machine learning repository and six image classification datasets. The proposed ERRNDL‐based methods achieve considerable performance.

Micro/Nano plastics (MNPs) pollutants are widespread in the environment, raising significant concerns about their biosafety. Emerging studies indicate that the urinary system is a primary accumulation site for MNPs, leading to severe tissue and functional damage. This review aims to summarize recent research on the potential hazards that MNPs may pose to the urinary system, highlighting the mechanisms of toxicity and the current state of knowledge. Studies have shown that MNPs enter the human body through drinking water, the food chain, inhalation, and skin contact. They may penetrate the bloodstream via the digestive, respiratory, and skin systems, subsequently dispersing to various organs, including the urinary system. The potential accumulation of MNPs in the urinary system might induce cellular oxidative stress, inflammation, apoptosis, autophagy, the “intestine-kidney axis”, and other possible toxic mechanisms. These processes could disrupt kidney metabolic functions and promote tissue fibrosis, thereby potentially increasing the risk of urinary system diseases. Despite ongoing research, the understanding of MNPs’ impact on the urinary system remains limited. Therefore, this review provides a comprehensive overview of MNPs’ potential toxicity mechanisms in the urinary system, highlights key challenges, and outlines future research directions. It offers a theoretical basis for the development of effective protective measures and policies.

Abstract Backgrounds Personal growth initiative (PGI) is regarded as a meaningful concept with potential value at both the individual and organizational levels, but little is known about the factors that contribute to nurses’ PGI. This study aimed to explore how proactive personality and hospital work environment affect PGI of clinical nurses. Methods A cross-sectional study was conducted between September and October 2022 among 4414 nurses from 10 tertiary general hospitals in 10 cities in Sichuan, China, using a two-stage sampling method. Self-reported anonymous online questionnaires, such as sociodemographic information survey, personal growth initiative scale II, the 10-item proactive personality scale, and practice environment scale-nursing work index were used to collect data. Multiple hierarchical regression analyses were performed to examine research hypotheses. Results Among the control variables in this study, nurses’ self-perceptions of general health status and professional title positively predicted PGI (β = 0.462, 95%CI = 0.272–0.653; β = 1.078, 95%CI = 0.508–1.648). After adding control variables, both proactive personality (β = 1.143, 95%CI = 1.096–1.190) and work environment (β = 3.391, 95%CI = 2.904–3.879) positively predicted PGI. The work environment positively moderated the association between proactive personality and PGI (β = 0.108, 95%CI = 0.025–0.191). These predictors jointly explained 50.3% of the variance in PGI. Conclusions Nurses with a greater tendency to have a typical proactive personality have higher levels of personal growth initiative, and this positive effect will be better highlighted in a healthier work environment. Nursing managers should prioritize the employment of people with proactive personality traits, focus on the development and stimulation of proactive personality traits in nurses, and establish a supportive work environment to maximize the personal growth initiative of nurses.

Tomato yellow leaf curl virus (TYLCV) poses a significant threat to tomato production, leading to severe yield losses. The current control strategies primarily rely on the use of pesticides, which are often nonselective and costly. Therefore, there is an urgent need to identify more environmentally friendly alternatives. Dufulin, a novel compound that has been effective in controlling viral diseases in tobacco and rice, has not yet been tested against TYLCV. This study assessed the efficacy of dufulin in controlling TYLCV over a three-year span from 2021 to 2023 through field trials, by monitoring disease symptoms and viral titers. Additionally, this study assessed the expression levels of genes associated with systemic acquired resistance (SAR), specifically proteinase inhibitor II (PI II) and non-expressor of pathogenesis-related genes 1 (NPR1), using real-time qRT-PCR. The chlorophyll and nitrogen content in the leaves were also measured. Plants treated with dufulin showed reduced symptomatology and lower viral titers compared to the controls. Analysis of gene expression revealed that NPR1 was upregulated in the dufulin-treated plants, whereas PI II expression was consistently downregulated in the TYLCV-infected plants. Interestingly, PI II expression increased in the healthy plants following a seven-day post-treatment with dufulin. Moreover, the treated plants exhibited a higher chlorophyll content than the controls, though no significant differences in the nitrogen levels were observed between the dufulin-treated and water-treated plants. Overall, the application of dufulin significantly bolstered the plant’s defense response, effectively reducing TYLCV symptoms and enhancing resistance.

Background Hepatocellular carcinoma (HCC) is an aggressive malignancy with limited effective treatment options. Phenethyl isothiocyanate (PEITC) is a bioactive substance present primarily in the cruciferous vegetables. PEITC has exhibited anti-cancer properties in various cancers, including lung, bile duct, and prostate cancers. It has been demonstrated that PEITC can inhibit the proliferation, invasion, and metastasis of SK-Hep1 cells, while effectively inducing apoptosis and cell cycle arrest in HepG2 cells. However, knowledge of its anti-carcinogenic effects on Huh7.5.1 cells and its underlying mechanism remains elusive. In the present study, we aim to evaluate the anti-carcinogenic effects of PEITC on human HCC Huh7.5.1 cells. Methods MTT assay and colony formation assay was performed to investigate the anti-proliferative effects of PEITC against Huh7.5.1 cells. The pro-apoptosis effects of PEITC were determined by Annexin V-FITC/PI double staining assay by flow cytometry (FCM), mitochondrial transmembrane potential (MMP) measurement, and Caspase-3 activity detection. A DAPI staining and terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) assay was conducted to estimate the DNA damage in Huh7.5.1 cells induced by PEITC. Cell cycle progression was determined by FCM. Transwell invasion assay and wound healing migration assay were performed to investigate the impact of PEITC on the migration and invasion of Huh7.5.1 cells. In addition, transcriptome sequencing and gene set enrichment analysis (GSEA) were used to explore the potential molecular mechanisms of the inhibitory effects of PEITC on HCC. Quantitative real-time PCR (qRT-PCR) analysis was performed to verify the transcriptome data. Results MTT assay showed that treatment of Huh7.5.1 cells with PEITC resulted in a dose-dependent decrease in viability, and colony formation assay further confirmed its anti-proliferative effect. Furthermore, we found that PEITC could induce mitochondrial-related apoptotic responses, including a decrease of mitochondrial transmembrane potential, activation of Caspase-3 activity, and generation of intracellular reactive oxygen species. It was also observed that PEITC caused DNA damage and cell cycle arrest in the S-phase in Huh7.5.1 cells. In addition, the inhibitory effect of PEITC on the migration and invasion ability of Huh7.5.1 cells was assessed. Transcriptome sequencing analysis further suggested that PEITC could activate the typical MAPK, PI3K-Akt, and p53 signaling pathways, revealing the potential mechanism of PEITC in inhibiting the carcinogenic properties of Huh7.5.1 cells. Conclusion PEITC exhibits anti-carcinogenic activities against human HCC Huh7.5.1 cells by activating MAPK/PI3K-Akt/p53 signaling pathways. Our results suggest that PEITC may be useful for the anti-HCC treatment.

Based on the properties of the 2-tuples distribution matrix of the rotation symmetric orbits, all 7-variable 2-resilient rotation symmetric Boolean functions were constructed concretely.The results show that there are only 280 nonlinear 2-resilient rotation symmetric Boolean functions over F 2 7 .Furthermore, there are at least 280 nonlinear 2-resilient rotation symmetric Boolean functions over F 2 7k for any odd number k.

Hyperspectral image super-resolution (HSI-SR), which enhances the spatial resolution of hyperspectral image (HSI) by fusing a low spatial resolution HSI (LR-HSI) with a high spatial resolution multispectral image (HR-MSI), has gained increasing attention in recent years. In this article, we propose a sparsity regularization-based spatial-spectral tensor subspace representation (SR-SSTSR) approach for HSI-SR, which accurately depicts the spectral correlations and spatial self-similarities, as well as their distinctions. To fully leverage spectral correlations and spatial self-similarities, we employ the SSTSR scheme to approximate HR-HSI as three low-dimensional tensors: One spectral subspace, one spatial subspace, and one coefficient tensor. The SSTSR allows for different subspace dimensions in these subspaces, which can accurately depict the distinct low-rank characteristics in spatial and spectral modes. Since HR-MSI and LR-HSI individually contain the majority of the spatial and spectral information, the spectral and spatial subspaces are individually estimated from LR-HSI and HR-MSI via the Qatar Riyal decomposition-based tensor singular value decomposition. After identifying the subspaces, the coefficient tensor is estimated via sparsity regularization, which promotes a sparse representation of HR-HSI in both spectral and spatial subspaces, further leveraging spectral-spatial low-rank properties while effectively mitigating noise impacts from LR-HSI and HR-MSI. The coefficient optimization is solved by the proximal alternating minimization method. Experimental results from both simulated and real datasets confirm the superiority of the proposed method.

The investment-return model of power system plays an important part in the business model of power system. In previous studies, the financial pressure brought by the proportion of power project investment was neglected. An investment-return model based on asymmetric Nash bargaining was proposed in this paper, which could better reflect the game process of investment-return in the new power system. Firstly, the stakeholders of cooperative game were analyzed so as to establish the framework of cooperative game model. Secondly, combined with various characteristics of new power system, various influencing factors of the cooperative game was estimated. Thirdly, the expression and solution of Nash bargain were put forward. Finally, the availability of the model was verified by an example. The experiment showed that the investment-return model could reflect the process of investment-return of the new power system more completely.

Hepatocellular carcinoma (HCC) is one of the malignant tumors with high incidence and mortality rates in the world. Isothiocyanates (ITCs), bioactive substances present primarily in the plant order Brassicales, have been proved to be promising candidates for novel anti-HCC drugs with chemopreventive and anticancer activities. Iberverin, a predominant ITC isolated from the seeds of oxheart cabbage, has been discovered with anticancer property in lung cancer cells. However, the roles of iberverin in HCC remain elusive. In the present study, the effect and potential mechanisms of iberverin against human HCC were dissected. We demonstrated that low concentrations of iberverin inhibited cell proliferation, suppressed migration and induced mitochondrial-related apoptosis in vitro, and hampered tumorigenicity in vivo, with no obvious toxicity. Furthermore, we found that iberverin treatment induced DNA damage and G2/M phase arrest. Iberverin treatment also caused increased intracellular reactive oxygen species formation and glutathione depletion. Taken together, these results suggest that iberverin promotes mitochondrial-mediated apoptosis and induces DNA damage and G2/M cell cycle arrest in HCC by enhancing oxidative stress. Our findings provide better understanding of the anti-HCC mechanisms of ITCs and the potential for the natural product iberverin as a promising new anti-HCC biotherapeutic.

The Electric Bus Dynamic Wireless Charging (EB-DWC) system is a bus charging system that enables electric buses to receive power wirelessly from ground-based electromagnetic induction devices. In this system, how to optimally configure the charging infrastructures while considering the unpredictable nature of bus movement is a great challenge. This paper presents an optimization problem for an EB-DWC system in urban settings, addressing stochastic elements inherent in the vehicle speed, initial charging state, and dwell time at bus stops. We formulate a stochastic planning problem for the EB-DWC system by integrating these uncertainties and apply Monte Carlo sampling techniques to effectively solve this problem. The proposed method can improve the system’s robustness effectively.

Abstract Background Health promotion behaviors are key determinant of health and well-being, and also play an important role in promoting successful aging. This study investigated levels of engagement in health promotion behaviors among Chinese rural older adults, and explored effects of perceived health competence, health education activities experience and sociodemographic variables on health promotion behavior in this population. Methods A multicenter cross-sectional survey was performed. Participants were recruited by a multistage, stratified, cluster-sampling procedure from Nanbu County, Sichuan Province, China. All participants completed four paper questionnaires: sociodemographic characteristics and health care status survey, the Chinese version of the health promoting lifestyle profile-II (HPLP-II), perceived health competence scale and Lubben social network scale. Data were collected from July to August 2021. Stepwise multiple linear regression analysis was performed to analyze the effects of different factors on health promotion behaviors. Results A total of 425 rural older adults with an average age of 72.7 years were included in analysis. The overall average score of HPLP-II was 101.6. The stepwise multiple linear regression analysis results showed that those who had higher perceived health competence (β = 0.66, P

Bemisia tabaci (Gennadius) is an important invasive pest transmitting plant viruses that are maintained through a plant–insect–plant cycle. Tomato yellow leaf curl virus (TYLCV) can be transmitted in a persistent manner by B. tabaci, which causes great losses to global agricultural production. From an environmentally friendly, sustainable, and efficient point of view, in this study, we explored the function of d-limonene in reducing the acquisition and transmission of TYLCV by B. tabaci as a repellent volatile. D-limonene increased the duration of non-feeding waves and reduced the duration of phloem feeding in non-viruliferous and viruliferous whiteflies by the Electrical Penetration Graph technique (EPG). Additionally, after treatment with d-limonene, the acquisition and transmission rate of TYLCV was reduced. Furthermore, BtabOBP3 was determined as the molecular target for recognizing d-limonene by real-time quantitative PCR (RT-qPCR), fluorescence competitive binding assays, and molecular docking. These results confirmed that d-limonene is an important functional volatile which showed a potential contribution against viral infections with potential implications for developing effective TYLCV control strategies.

Due to technology and cost limitations, it is challenging to obtain high temporal and spatial resolution images from a single satellite spectrometer, which significantly limits the specific application of such remote sensing images in earth science. To solve the problem that the existing algorithms cannot effectively balance the spatial detail preservation and spectral change reconstruction, a pseudo-Siamese deep convolutional neural network (PDCNN) for spatiotemporal fusion is proposed in this article. The method proposes a pseudo-Siamese network framework model for fusion. This framework has two independent and equal feature extraction streams, but the weights are not shared. The two feature extraction streams process the image information at the previous and later moments and reconstruct the fine image of the corresponding time to fully extract the image information at different times. In the feature extraction stream, the multiscale mechanism and dilated convolution of flexible perception are designed, which can flexibly obtain feature image information and improve the model reconstruction accuracy. In addition, an attention mechanism is introduced to improve the weight of the crucial information for the remote sensing images. Adding a residual connection enhances the reuse of the initial feature information in shallow networks and reduces the loss of feature information in deep networks. Finally, the fine images obtained from the two feature extraction streams are weighted and fused to obtain the final predicted image. The subjective and objective results demonstrate that the PDCNN can effectively reconstruct the fusion image with higher quality.

This paper presents a method based on orthogonal arrays of constructing pure quaternary quantum error-correcting codes. As an application of the method, some infinite classes of quantum error-correcting codes with distances 2, 3, and 4 can be obtained. Moreover, the infinite class of quantum codes with distance 2 is optimal. The advantage of our method also lies in the fact that the quantum codes we obtain have less items for a basis quantum state than existing ones.

Hyperspectral image (HSI) super-resolution is a vital technique that generates high spatial-resolution HSI (HR-HSI) by integrating information from low spatial-resolution HSI with high spatial-resolution multispectral image (MSI). However, existing subspace representation-based methods face challenges, including adaptive subspace dimension determination, inadequate spectral correlation capture, and expensive computation. In this paper, we propose a novel factor group sparsity regularized subspace representation (FGSSR)-based method for HSI super-resolution that can simultaneously address these issues encountered in previous methods. Specifically, by incorporating the factor group sparsity regularization into the subspace representation model, we first propose an FGSSR model to capture the spectral correlation property of the HR-HSI. The key advantage of FGSSR lies in its equivalence to the Schatten-p norm and its adaptive determination of the accurate subspace dimension, enabling it to capture spectral correlation more effectively. To preserve the spatial self-similarity prior in the HR-HSI, the tensor nuclear norm regularization on the low-dimensional coefficients is also incorporated into the proposed FGSSR-based model. Finally, an effective proximal alternating minimization-based algorithm is developed to solve the FGSSR-based model. Experimental results on the simulated and real datasets demonstrate that the proposed FGSSR-based method outperforms several state-of-the-art fusion methods with significant improvements.

Abstract Background Although studies indicate that social support is related to emotional exhaustion, depression symptoms, and anxiety symptoms, the underlying mechanism between those variables remains unknown. Methods Based on a sample of 254 residents in standardized residency training programs, two mediation models were tested in which emotional exhaustion served as a mediator in the relationship between social support and anxiety symptoms/depression symptoms. We used the following self-reported questionnaires as instruments to collect data: zung self-rating depression scale, zung self-rating anxiety scale, social support rating scale, and emotional exhaustion scale. Results In the final study sample, the mean age of the residents was 25.92 years old (SD =1.88), and a total of 41.3% were male, and 58.7% were female. This current study suggested that social support was proven to be a relevant factor affecting anxiety symptoms and depression symptoms. Particularly, the results also indicated that emotional exhaustion partially mediated the impact of social support on anxiety symptoms and depression symptoms among Chinese residents in the standardized residency training program. Conclusions Our study signifies that enhancements in social support and reduction of emotional exhaustion can directly or indirectly affect anxiety symptoms and depression symptoms among Chinese residents in the standardized residency training program. These findings will offer insight for health-sector managers to develop programs aimed at social support and adopt individual-level interventions and organization-level interventions to reduce emotional exhaustion.

The premise and key of ensuring the safety and effectiveness of traditional Chinese medicine (TCM) is to construct appropriate quality evaluation system of TCM. This study aimed to establish a pre-column derivatization HPLC method for achieving the quality control of Polygonatum sibiricum by reacting synthesized 4-hydrazino-1,8-naphthalimide (HAN) with diverse monosaccharides from the hydrolytic product of P. sibiricum polysaccharides (PSPs), followed by HPLC separation. The HAN was synthesized based on a CuI-catalyzed cross-coupling reaction in water, and then employed as a novel chemosensor that reacts with reducing sugars. Good separation was achieved at a detection wavelength of 448 nm using an ZORBAX SB-C8 column under a gradient elution at a flow rate of 0.5 ml/min within 12 min. The monosaccharide compositions of PSP mainly include two hexoses [glucose (Glc), galactose (Gal)] and two hexuronic acids [glucuronic acid (GlcA) and galacturonic acid (GalA)], and the molar ratio of Glc, Gal, GlcA and GalA is 16.67:52.94:10.58:19.81. The verified HPLC method, possessing excellent precision and good accuracy, successfully achieved rapid qualitative and quantitative determination for PSP. Additionally, the HAN displayed fluorescence enhancement through “push–pull” mode, and fluorescence decreased through “pull–pull” mode after binding to monosaccharides, which is a potential for fluorescence determination of different monosaccharides.

This article presents a novel global gradient sparse and nonlocal low-rank tensor decomposition model with a hyper-Laplacian prior for hyperspectral image (HSI) superresolution to produce a high-resolution HSI (HR-HSI) by fusing a low-resolution HSI (LR-HSI) with an HR multispectral image (HR-MSI). Inspired by the investigated hyper-Laplacian distribution of the gradients of the difference images between the upsampled LR-HSI and latent HR-HSI, we formulate the relationship between these two datasets as a $\ell _{p}$ $(0 < p < 1)$-norm term to enforce spectral preservation. Then, the relationship between the HR-MSI and latent HR-HSI is built using a tensor-based fidelity term to recover the spatial details. To effectively capture the high spatio-spectral-nonlocal similarities of the latent HR-HSI, we design a novel nonlocal low-rank Tucker decomposition to model the 3-D regular tensors constructed from the grouped nonlocal similar HR-HSI cubes. The global spatial-spectral total variation regularization is then adopted to ensure the global spatial piecewise smoothness and spectral consistency of the reconstructed HR-HSI from nonlocal low-rank cubes. Finally, an alternating direction method of multipliers-based algorithm is designed to efficiently solve the optimization problem. Experiments on both the synthetic and real datasets collected by different sensors show the effectiveness of the proposed method, from visual and quantitative assessments.

Some properties of rotation symmetric orbits were proposed in n dimensional vector space over finite field of characteristic 2,a matrix on the distributions of number pairs such as 00,01 and 11 was defined,and a new characterization of 2-resilient rotation symmetric functions was introduced.Constructions of rotation symmetric 2-resilient Boolean functions with 4t-1 number of variables were presented by modifying the support of the linear rotation symmetric functions,such as f0(x)=x1+x2+…+xn,where n=4t-1.At last,an example was demonstrated to introduce the spirit of the proposed method to construct 2-resilient rotation symmetric functions with 4t-1 number of variables.

Abstract Background Plant viruses move through plasmodesmata (PD) to infect new cells. To overcome the PD barrier, plant viruses have developed specific protein(s) to guide their genomic RNAs or DNAs to path through the PD. Results In the present study, we analyzed the function of Pepper vein yellows virus P4 protein. Our bioinformatic analysis using five commonly used algorithms showed that the P4 protein contains an transmembrane domain, encompassing the amino acid residue 117–138. The subcellular localization of P4 protein was found to target PD and form small punctates near walls. The P4 deletion mutant or the substitution mutant constructed by overlap PCR lost their function to produce punctates near the walls inside the fluorescent loci. The P4-YFP fusion was found to move from cell to cell in infiltrated leaves, and P4 could complement Cucumber mosaic virus movement protein deficiency mutant to move between cells. Conclusion Taking together, we consider that the P4 protein is a movement protein of Pepper vein yellows virus.

A large amount of nano-/microparticles (MNPs) are released into water, not only causing severe water pollution, but also negatively affecting organisms. Therefore, it is crucial to evaluate MNP toxicity and mechanisms in water. There is a significant degree of similarity between the genes, the central nervous system, the liver, the kidney, and the intestines of zebrafish and the human body. It has been shown that zebrafish are exceptionally suitable for evaluating the toxicity and action mechanisms of MNPs in water on reproduction, the central nervous system, and metabolism. Providing ideas and methods for studying MNP toxicity, this article discusses the toxicity and mechanisms of MNPs from zebrafish.

Traditional Chinese medicine (TCM) safety and effectiveness can be ensured by establishing a suitable quality assessment system. This work aims to develop a pre-column derivatization HPLC method for Polygonatum cyrtonema Hua. quality control. In this study, 1-(4′-cyanophenyl)-3-methyl-5-pyrazolone (CPMP) was synthesized and reacted with monosaccharides derived from P. cyrtonema polysaccharides (PCPs), followed by HPLC separation. According to the Lambert–Beer law, CPMP has the highest molar extinction coefficient of all synthetic chemosensors. A satisfactory separation effect was obtained under a detection wavelength of 278 nm using a carbon-8 column and gradient elution over 14 min, with a flow rate of 1 mL per minute. Glucose (Glc), galactose (Gal), and mannose (Man) make up the majority of the monosaccharide components in PCPs, and their molar ratios are 1.73:0.58:1. The confirmed HPLC method has outstanding precision and accuracy, establishing a quality control method for PCPs. Additionally, the CPMP showed a visual improvement from colorless to orange after the detection of reducing sugars, allowing for further visual analysis.

Summary Although many biocontrol bacteria can be used to improve plant tolerance to stresses and to promote plant growth, the hostile environmental conditions on plant phyllosphere and the limited knowledge on bacterial colonization on plant phyllosphere minimized the beneficial effects produced by the biocontrol bacteria. Rhodopseudomonas palustris strain GJ‐22 is known as a phyllosphere biocontrol agent. In this paper, we described detailed processes of strain GJ‐22 colony establishment at various colonization stages. Four different types of bacterial colonies, Type 1, scattered single cells; Type 2, small cell clusters; Type 3, small cell aggregates; and Type 4, large cell aggregates, were observed in the course of bacterial colonization. We categorized bacterial colonization into four phases, which were, Phase I: bacterial colony exists as Type 1 and cell population reduced quickly; Phase II: Type 1 evolved into Type 2 and cell population remained steady; Phase III: Type 3 arose and replaced Type 2, and cell population expanded slowly; and Phase IV: Type 3 matured into Type 4 and cell population increased quickly. We have shown that the preferable location sites of bacterial aggregates on leaf phyllosphere are grooves between plant epidermal cells. Analyses of expressions of plant defence‐related genes showed that, starting from Phase III, bacterial cells in the Type 3 and Type 4 colonies produced unidentified signals to induce host defence against Tobacco mosaic virus infection. In addition, we determined the crucial role of aggregates formation of GJ‐22 cell on plant phyllosphere in terms of bacterial cell stress tolerance and ISR (induced systemic resistance) priming. To our knowledge, this is the first report focused on the colonization process of a phyllosphere biocontrol agent and gave a clear description on the morphological shift of bacterial colony on phyllosphere.

Abstract Development of a genetic tool for visualization of photosynthetic bacteria (PSB) is essential for understanding microbial function during their interaction with plant and microflora. In this study, Rhodopseudomonas palustris GJ-22-gfp harboring the vector pBBR1-pckAPT-gfp was constructed using an electroporation transformation method and was used for dynamic tracing of bacteria in plants. The results showed that strain GJ-22-gfp was stable and did not affect the biocontrol function, and the Confocal Laser Scanning Microscopy (CLSM) results indicated it could successfully colonised on the surface of leaf and root of tobacco and rice. In tobacco leaves, cells formed aggregates on the mesophyll epidermal cells. While in rice, no aggregate was found. Instead, the fluorescent cells colonise the longitudinal intercellular spaces between epidermal cells. In addition, the results of strain GJ-22 on the growth promotion and disease resistance of tobacco and rice indicated that the different colonization patterns might be related to the bacteria could induce systemic resistance in tobacco.

A neuropeptide precursor encoded by Bta06987 associates with AKH neuropeptide. In the AKH/RPCH family, these members have been demonstrated to participate in energy mobilization in many insects. In our research, the Bta06987 gene from Bemisia tabaci was cloned, and the amino acid sequence analysis was performed. During the starvation of B. tabaci, the mRNA level of Bta06987 showed a significant elevation. We investigated the functions of Bta06987 in B. tabaci using RNA interference (RNAi), and the adult females of B. tabaci after being fed with dsBta06987 showed a higher glycogen and triglyceride levels and lower trehalose content than the control. Furthermore, in the electrical penetration graph (EPG) experiment, B. tabaci showed changes in feeding behavior after feeding with dsBta06987, such as the reduction in parameters of E waveform percentage and total feeding time. Our findings might be helpful in developing strategies to control pest and plant virus transmission.

Tomato spotted wilt orthotospovirus (TSWV) causes serious crop losses worldwide and is transmitted by Frankliniella occidentalis (Pergande) (Thysanoptera: Thripidae). NSs protein is the silencing suppressor of TSWV and plays an important role in virus infection, cycling, and transmission process. In this research, we investigated the influences of NSs protein on the interaction of TSWV, plants, and F. occidentalis with the transgenic Arabidopsis thaliana. Compared with the wild-type Col-0 plant, F. occidentalis showed an increased number and induced feeding behavior on transgenic Arabidopsis thaliana expressing exogenous NSs. Further analysis showed that NSs reduced the expression of terpenoids synthesis-related genes and the content of monoterpene volatiles in Arabidopsis. These monoterpene volatiles played a repellent role in respect to F. occidentalis. In addition, the expression level of plant immune-related genes and the content of the plant resistance hormone jasmonic acid (JA) in transgenic Arabidopsis were reduced. The silencing suppressor of TSWV NSs alters the emission of plant volatiles and reduces the JA-regulated plant defenses, resulting in enhanced attractiveness of plants to F. occidentalis and may increase the transmission probability of TSWV.

It is difficult to extract both structural and functional information from the input grey magnetic resonance imaging (MRI) and pseudo-color positron emission tomography (PET) images using the same decomposition scheme in multi-scale transform fusion methods. To overcome this limitation, we propose two algorithms based on intrinsic image decomposition to decompose MRI and PET images into its two separate components in the spatial domain. Algorithm 1 could extract structural information while reducing the noise from the MRI image. Algorithm 2 is for averaging the color information from the PET image. As for the image fusion rule, the defined importance of image coefficients is used to combine the decomposed two-scale components to produce the final fused image, which could keep more spatial resolution with substitution strategies. It demonstrates that the proposed fusion methods could improve the values of mutual information by the metrics on the disease database. Furthermore, the proposed methods produce the competitive visual signal-to-noise ratio values on experiments for robustness database. In addition to the variance in metrics values, the non-parametric Friedman test and the post-hoc Bonferroni-Dunn test are used to analyze the significant difference between the proposed and the state-of-the-arts methods.

In this paper, we propose an efficient image fusion algorithm using multiple salient features with guided image filter to prevent the problem of low contrast detail. First, we employ the guided image filter to decompose the input images into a series of smoothed and detailed images at different scales. Second, the salient features are extracted from the decomposed smoothed images and detailed images using two different algorithms: the spectral residual (SR) algorithm for extracting mainframe information and the graph-based visual saliency (GBVS) model for extracting gradient saliency information to construct the fusion rules. In addition, generalized intensity-hue-saturation (GIHS) is adopted to combine the decomposition coefficients. Finally, the fused image is reconstructed by the fused smoothed and fused detailed images. The experimental results demonstrate that the proposed algorithm can achieve better performance than other fusion methods in the domains of MRI-PET and MRI-SPECT fusion.

Set-based image classification has become popular in recent years since it can provide a relatively large amount of within-set information that benefits classification. Grassmann Discriminant Analysis (GDA) models image sets as points (subspaces) on a Grassmann manifold and then explicitly maps them to a higher-dimensional Hilbert space, where Euclidean geometry applies, for Linear Discriminant Analysis (LDA). However, due to the noise disturbance and finite number of training samples in practice, the conventional problems of LDA, such as the singularity of the within-class scatter matrix and the instability of its inverse, also appear with GDA, which result in recognition performance deterioration. Inspired by eigenspectrum regularization techniques, we propose an eigenspectrum Regularized GDA (RGDA) method to alleviate the conventional problems of GDA in Grassmannian space. Moreover, we implement it with the graph embedded framework, three different eigenspectrum regularization models are incorporated into the proposed approach respectively. Extensive experimental results on set-based face recognition and object categorization tasks have confirmed the effectiveness of our approaches.

To solve LWE-based proxy re-encryption schemes cannot achieve fine-grained access and low efficiency problem,a ciphertext-policy attribute-based proxy re-encryption scheme was proposed.The scheme based on linear secret sharing scheme,RLWE and attribute encryption could shorten the key size,reduce the ciphertext space and improve the efficiency of encryption and decryption.At the same time,the linear secret sharing matrix was used as an access matrix to meet the requirements of authorized person fine-grained commissioning control and to resist the collusion between the agent and the authorized person.In addition,the proposed scheme is shown to be secure under the ring learning with errors assumption in the standard model.

Abstract Full length open reading frame of pyrethroid detoxification gene, Est3385, contains 963 nucleotides. This gene was identified and cloned based on the genome sequence of Rhodopseudomonas palustris PSB-S available at the GneBank. The predicted amino acid sequence of Est3385 shared moderate identities (30–46%) with the known homologous esterases. Phylogenetic analysis revealed that Est3385 was a member in the esterase family I. Recombinant Est3385 was heterologous expressed in E. coli, purified and characterized for its substrate specificity, kinetics and stability under various conditions. The optimal temperature and pH for Est3385 were 35 °C and 6.0, respectively. This enzyme could detoxify various pyrethroid pesticides and degrade the optimal substrate fenpropathrin with a Km and Vmax value of 0.734 ± 0.013 mmol·l−1 and 0.918 ± 0.025 U·µg−1, respectively. No cofactor was found to affect Est3385 activity but substantial reduction of enzymatic activity was observed when metal ions were applied. Taken together, a new pyrethroid degradation esterase was identified and characterized. Modification of Est3385 with protein engineering toolsets should enhance its potential for field application to reduce the pesticide residue from agroecosystems.

The value ranges of the number of output variables were determined respectively under the existence of multi-output rotation symmetric balanced functions and resilient functions with 2rinput variables.Based on the equivalence between the resilient functions and large sets of orthogonal arrays,some results on the construction and count of multi-output rotation symmetric balanced functions with 8 input variables were presented according to the different dimensions of output vectors,and construction and count of multi-output rotation symmetric 1-resilient functions with 8 input variables were also studied.Besides,constructions of multi-output rotation symmetric resilient functions are transformed into the problem of solving a system of equations.

Previous adaptive steganography algorithms were based on ordinal and full-embedding method.However,these algorithms might cause the concealment of secret information not good enough.Therefore,a random and non-fully embedding method was proposed to improve the concealment.The image system parameters could be obtained,so that the image full capacity was exactly greater than the length of information for non-full embedding.Moreover,these parameters made steganography more flexibility by reducing the modifications of image.Then,secret information embedding sequence was scrambled based on Arnold transform for the purpose that the steganalyst cannot detect out information orderly.Therefore,the secret information can be more concealed,which can improve the security of the algorithms.Experimental results show that the algorithm not only improves the concealment of steganography but also reduces stego distortion,and random non-full embedding operating can be applied to many other similar algorithms.

Sclerotinia sclerotiorum is a destructive ascomycete plant pathogen with worldwide distribution. Extensive research on different aspects of this pathogen’s capability to cause disease will help to uncover clues about new ways to safely control Sclerotinia diseases. The thioredoxin (Trx) system consists of Trx and thioredoxin reductase (TrxR), which play critical roles in maintenance of cellular redox homeostasis. In this study, we functionally characterized a gene encoding a TrxR (SsTrr1) in S. sclerotiorum. The amino acids of SsTrr1 exhibited high similarity with reported TrxRs in plant pathogens and targeted silencing of SsTrr1 lead to a decrease in TrxR activities of mycelium. SsTrr1 showed high expression levels during hyphae growth, and the levels decreased at the different stages of sclerotial development. SsTrr1 gene-silenced strains produced a smaller number of larger sclerotia on potato dextrose agar medium. The observations were consistent with the inhibitory effects on sclerotial development by the TrxR inhibitor, anrunofin. The expression of SsTrr1 showed a dramatic increase under the oxidative stress and the hyphal growth of gene-silenced strains showed more sensitivity to H2O2. SsTrr1 gene-silenced strains also showed impaired virulence in different hosts. Taken together, our results suggest that SsTrr1 encodes a TrxR that is of great important for oxidative stress tolerance, virulence, and sclerotial development of S. sclerotiorum.

Baesd on the property of the l-value support tables of the resilient rotation symmetric functions (RSF) with q number of variables, an equivalent characterization on the resilient RSF with q number of variables is derived. It is proved that construction of the resilient RSF with q number of variables are equivalent to solve an equation system. At last, the count of resilient RSF with q number of variables are represented by using all the solutions of the equation system. Key words: rotation symmetric functions; l-value support table; orthogonal arrays; resilient functions

The characteristic matrix of the resilient rotation symmetric Boolean functions(RSBF) with prime number va-riables were explored. Some properties about character ic matrix of them were given. A necessary and sufficient condi-tion on the construction of resilient RSBF with prime number variables was derived. So construction and count formula of all the resilient RSBF with prime number variables were determined by this way. At last, all the resilient RSBF with 3, 5 or 7 variables were given.

Sclerotinia sclerotiorum (Lib.) de Bary is a devastating fungal pathogen with worldwide distribution. S. sclerotiorum is a necrotrophic fungus that secretes many cell wall-degrading enzymes (CWDEs) that destroy plant’s cell-wall components. Functional analyses of the genes that encode CWEDs will help explain the mechanisms of growth and pathogenicity of S. sclerotiorum. Here, we isolated and characterized a gene SsXyl1 that encoded an endo-β-1, 4-xylanase in S. sclerotiorum. The SsXyl1 expression showed a slight increase during the development and germination stages of sclerotia and a dramatic increase during infection. The expression of SsXyl1 was induced by xylan. The SsXyl1 deletion strains produce aberrant sclerotia that could not germinate to form apothecia. The SsXyl1 deletion strains also lost virulence to the hosts. This study demonstrates the important roles of endo-β-1, 4-xylanase in the growth and virulence of S. sclerotiorum.

Acute lung injury (ALI) induced by intestinal ischemia/reperfusion (II/R) has high incidence and mortality, in which IL-1β was essential for the full development of ALI. However, the detailed regulating mechanism for this phenomenon remains to be unclear. The purpose of this study was to investigate whether inhibition of P38 MAPK could downregulate the expression of IL-1β to protect lung from acute injury in II/R rats. Here, we found that the level of pulmonary edema at 16 hours after operation (hpo) was obviously enhanced compared to that in 8hpo and sham groups. Immunofluorescent staining demonstrated that IL-1β and P38 MAPK were detected in lung tissues. And rats with II/R have the highest translation level for IL-1β and phosphorylation of P38 MAPK in lung tissues at 16hpo compared with 8hpo and sham groups. Moreover, administration of SB239063, an inhibitor of P38 α and β, could effectively downregulate the expressions of IL-1β and protects lung tissues from injury in II/R rats. Our findings indicate that the inhibition of P38 α and β may downregulate the expression of IL-1β to protect lung from acute injury in II/R, which could be used as a potential target for reducing ALI induced by II/R in the future clinical trial.