A Kind of Network Intrusion Detection Algorithm Based on Quantum-behaved Particle Swarm Optimization

In order to overcomes the drawbacks of fuzzy clustering methods which are sensitive to the initial values and easily trapped into local minima in intrusion detection algorithm, a hybrid algorithm is proposed based on quantum-behaved particle swarm optimization and semi-supervised kernel fuzzy clustering algorithm. This algorithm can supervise and clustering a few labeled data to generate correct model, use this model to guide lots of unlabeled data to clustering, and enlarge the labeled data set. Those data still cannot be labeled, which are clustered by the kernel fuzzy methods based on quantum-behaved particle swarm optimization, and determine mark types. The simulation of KDD CUP 99 data set is implemented to evaluate the proposed algorithm. Comparing to other algorithms, the result shows the proposed algorithm can obtain the ideal error detection rate and false drop rate in the intrusion detection

Comprehensive analysis of the aldehyde dehydrogenase gene family in Phaseolus vulgaris L. and their response to saline–alkali stress

BackgroundAldehyde dehydrogenase (ALDH) scavenges toxic aldehyde molecules by catalyzing the oxidation of aldehydes to carboxylic acids. Although ALDH gene family members in various plants have been extensively studied and were found to regulate plant response to abiotic stress, reports on ALDH genes in the common bean (Phaseolus vulgaris L.) are limited. In this study, we aimed to investigate the effects of neutral (NS) and basic alkaline (AS) stresses on growth, physiological and biochemical indices, and ALDH activity, ALDH gene expression of common bean. In addition, We used bioinformatics techniques to analyze the physical and chemical properties, phylogenetic relationships, gene replication, collinearity, cis-acting elements, gene structure, motifs, and protein structural characteristics of PvALDH family members.ResultsWe found that both NS and AS stresses weakened the photosynthetic performance of the leaves, induced oxidative stress, inhibited common bean growth, and enhanced the antioxidative system to scavenge reactive oxygen species. Furthermore, we our findings revealed that ALDH in the common bean actively responds to NS or AS stress by inducing the expression of PvALDH genes. In addition, using the established classification criteria and phylogenetic analysis, 27 PvALDHs were identified in the common bean genome, belonging to 10 ALDH families. The primary expansion mode of PvALDH genes was segmental duplication. Cis-acting elemental analysis showed that PvALDHs were associated with abiotic stress and phytohormonal responses. Gene expression analysis revealed that the PvALDH gene expression was tissue-specific. For instance, PvALDH3F1 and PvALDH3H1 were highly expressed in flower buds and flowers, respectively, whereas PvALDH3H2 and PvALDH2B4 were highly expressed in green mature pods and young pods, respectively. PvALDH22A1 and PvALDH11A2 were highly expressed in leaves and young trifoliates, respectively; PvALDH18B2 and PvALDH18B3 were highly expressed in stems and nodules, respectively; and PvALDH2C2 and PvALDH2C3 were highly expressed in the roots. PvALDHs expression in the roots responded positively to NS–AS stress, and PvALDH2C3, PvALDH5F1, and PvALDH10A1 were significantly (P < 0.05) upregulated in the roots.ConclusionThese results indicate that AS stress causes higher levels of oxidative damage than NS stress, resulting in weaker photosynthetic performance and more significant inhibition of common bean growth. The influence of PvALDHs potentially modulates abiotic stress response, particularly in the context of saline–alkali stress. These findings establish a basis for future research into the potential roles of ALDHs in the common bean

The mediating effect of resilience on mental health literacy and positive coping style among Chinese empty nesters: A cross-sectional study

ObjectivesEmpty nesters in China have limited mental health literacy (MHL), which may lead to poorer health outcomes. Studies demonstrate that MHL is associated with both resilience and positive coping style. However, the potential mechanism of MHL, resilience and positive coping style remain unclear. Therefore, the study aims to investigate the possible mediating role of resilience in the relationship between MHL and positive coping style.MethodIn this cross-sectional study, a total of 363 empty nesters from Huzhou, China were surveyed in 2022. The Chinese version of Mental Health Literacy Scale (C-MHLS), the Chinese version of 10-item Connor-Davidson Resilience Scale (CD-RISC-10) and the Simplified Coping Style Questionnaire (SCSQ-19) were used to assess MHL, resilience, and positive coping style, respectively.ResultsPositive coping style was significantly correlated with MHL and resilience, and MHL was positively correlated with resilience (p < 0.01). MHL can significantly and positively predict the positive coping style, and resilience played a partial intermediary role between MHL and positive coping style, with the intermediary effect of 77.36%.ConclusionThis study indicates that MHL not only directly affected positive coping style, but also indirectly influences positive coping style by increasing the resilience of empty nesters. The results provide an empirical evidence for the development of intervention programs to improve positive coping style directly and indirectly. Consequently, community health servicers should take targeted measures which focus on MHL and resilience as breakthrough points to stimulate positive coping style of empty nesters, and ultimately achieve their overall well-being

Identification of Genome-Wide Variations among Three Elite Restorer Lines for Hybrid-Rice

Rice restorer lines play an important role in three-line hybrid rice production. Previous research based on molecular tagging has suggested that the restorer lines used widely today have narrow genetic backgrounds. However, patterns of genetic variation at a genome-wide scale in these restorer lines remain largely unknown. The present study performed re-sequencing and genome-wide variation analysis of three important representative restorer lines, namely, IR24, MH63, and SH527, using the Solexa sequencing technology. With the genomic sequence of the Indica cultivar 9311 as the reference, the following genetic features were identified: 267,383 single-nucleotide polymorphisms (SNPs), 52,847 insertion/deletion polymorphisms (InDels), and 3,286 structural variations (SVs) in the genome of IR24; 288,764 SNPs, 59,658 InDels, and 3,226 SVs in MH63; and 259,862 SNPs, 55,500 InDels, and 3,127 SVs in SH527. Variations between samples were also determined by comparative analysis of authentic collections of SNPs, InDels, and SVs, and were functionally annotated. Furthermore, variations in several important genes were also surveyed by alignment analysis in these lines. Our results suggest that genetic variations among these lines, although far lower than those reported in the landrace population, are greater than expected, indicating a complicated genetic basis for the phenotypic diversity of the restorer lines. Identification of genome-wide variation and pattern analysis among the restorer lines will facilitate future genetic studies and the molecular improvement of hybrid rice

Non-Intrusive Load Identification Based on Retrainable Siamese Network

Non-intrusive load monitoring (NILM) can identify each electrical load and its operating state in a household by using the voltage and current data measured at a single point on the bus, thereby behaving as a key technology for smart grid construction and effective energy consumption. The existing NILM methods mainly focus on the identification of pre-trained loads, which can achieve high identification accuracy and satisfying outcomes. However, unknown load identification is rarely involved among those methods and the scalability of NILM is still a crucial problem at the current stage. In light of this, we have proposed a non-intrusive load identification method based on a Siamese network, which can be retrained after the detection of an unknown load to increase the identification accuracy for unknown loads. The proposed Siamese network comprises a fixed convolutional neural network (CNN) and two retrainable back propagation (BP) networks. When an unknown load is detected, the low-dimensional features of its voltage–current (V-I) trajectory are extracted by using the fixed CNN model, and the BP networks are retrained online. The finetuning of BP network parameters through retraining can improve the representation ability of the network model; thus, a high accuracy of unknown load identification can be achieved by updating the Siamese network in real time. The public WHITED and PLAID datasets are used for the validation of the proposed method. Finally, the practicality and scalability of the method are demonstrated using a real-house environment test to prove the ability of online retraining on an embedded Linux system with STM32MP1 as the core

Cyclodextrin-modified polycarboxylate superplasticizers as dispersant agents for multiwalled carbon nanotubes

A new type poly(AA-co-beta-CD-A-co-TPEG) (PACD) copolymer was prepared by the copolymerization of a novel monovinyl beta-cyclodextrin monomer (beta-CD-A), acrylic acid, and isoprenyl oxy poly(ethylene glycol) (TPEG-2400). This copolymer could be used as dispersant for multiwalled carbon nanotubes (MWCNTs), which exhibit an excellent dispersion ability. This study mainly investigated the dispersing behavior of the PACD as well as the best ratio between these dispersants and MWCNTs. Transmission electron microscopy was employed to observe the morphology of the dispersed of MWCNTs. ultraviolet-visible-near infrared spectra were utilized to determine the dispersion of MWCNTs and the optimum concentration of PACD. It was found that the polycarboxylate superplasticizer decreased MWCNTs aggregative tendency in water but not as well as PACD. Moreover, the optimum mass ratio of the PACD to the MWCNTs is 5:1. In addition, the effect of PACD on the dispersion ability of MWCNTs was evaluated in cement samples. Our results indicated that MWCNTs could still disperse well with the help of PACD even with the presence of cement. (c) 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019, 136, 47311

Preparation of a Dmap-Catalysis Lignin Epoxide and the Study of Its High Mechanical-Strength Epoxy Resins with High-Biomass Content

The depletion of limited petroleum resources used for the fabrication of epoxy resins calls for the development of biomass-based epoxides as promising alternatives to petroleum-derived epoxides. However, it is challenging to obtain an epoxy resin with both high lignin content and excellent mechanical performance. Herein, a 4-dimethylaminopyridine (DMAP)-lignin epoxide with a certain epoxy value and a small molecular weight is obtained by the catalysis of DMAP for the macromolecular lignin. It was discovered that compared to the prepared composite resin of benzyltriethylammonium chloride (BTEAC)-lignin epoxide, there is a better low-temperature storage modulus for the DMAP-lignin epoxide resin and its composite resins with high-biomass contents, and higher tensile strength for its composite resins. In particular, the DMAP-lignin epoxide/ bisphenol A diglycidyl ether (BADGE) (DB) composite resin with DMAP-lignin epoxide replacement of 80 wt% BADGE, containing up to 58.0 wt% the lignin epoxide, exhibits the tensile strength of 76.3 ± 3.2 MPa. Its tensile strength is 110.2% of BTEAC-lignin epoxide/BADGE (BB) composite resins and is comparable to that of petroleum-based epoxy resins. There are good application prospects for the DB composite resin in the engineering plastics, functional composite, grouting, and other fields