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Background: Hylurgus ligniperda, a major international forestry quarantine pest, was recently found to have invaded and posed a serious threat to the Pinus forests of the Jiaodong Peninsula in China. Continuous monitoring and vigilance of the early population is imperative, and rapid molecular detection technology is urgently needed. We focused on developing a single-gene-based species-specific PCR (SS-PCR) method. Results: We sequenced and assembled the mitochondrial genome of H. ligniperda to identify suitable target genes. We identified three closely related species for detecting the specificity of SS-PCR through phylogenetic analysis based on 13 protein-coding genes (PCGs). Subsequently, we analyzed the evolution of 13 PCGs and selected four mitochondrial genes to represent slow-evolving gene (COI) and faster-evolving genes (e.g. ND2, ND4, and ND5), respectively. We developed four species-specific primers targeting COI, ND2, ND4, and ND5 to rapidly identify H. ligniperda. The results showed that the four species-specific primers exhibited excellent specificity and sensitivity in the PCR assays, with consistent performance across a broader range of species. This method demonstrates the ability to identify beetles promptly, even during their larval stage. The entire detection process can be completed within 2–3 h. Conclusions: This method is suitable for large-scale species detection in laboratory settings. Moreover, the selection of target genes in the SS-PCR method is not affected by the evolutionary rate. SS-PCR can be widely implemented at port and forestry workstations, significantly enhancing early management strategies and quarantine measures against H. ligniperda. This approach will help prevent the spread of the pest and effectively preserve the resources of Chinese pine forests. [ABSTRACT FROM AUTHOR]

Insect infestations cause substantial changes in the leaves they attack, but the effects of insect infestation on photosynthesis and gene expression in the whole infestation period are rarely reported. In this study, the effects of poplar aphid (Chaitophorus populialbae Boyer de Fonscoloube) on photosynthetic rate and gene expression of Populus alba var. pyramidalis were studied, from 2 to 36 days after low-density aphid inoculation (DAI). The results revealed a dynamic change of photosynthesis in poplar after aphid infestation: compensatory increased at 8 DAI, was inhibited at 17 DAI, but repaired after 21 DAI. Aphid infestation promoted the expression of the majority of differentially expressed genes (DEGs) at 4, 6, 8, and 21 DAI. The DEGs were enriched into a plant–pathogen interaction, plant hormone signal transduction, and MAPK signaling pathway, suggesting a significant but transient resistance to disease or other stresses. Photosynthesis-related DEGs were downregulated at 8 DAI, which might result in photosynthetic inhibition at 17 DAI. The expression of flavonoid biosynthesis-related DEGs dynamic changed from all downregulated at 2 DAI to almost all upregulated at 21 DAI, suggesting a persistent resistance to insect infestation. This study reveals dynamic changes in photosynthesis, resistance to pathogens, and insects in poplar leaves after aphid infestation. [ABSTRACT FROM AUTHOR]

In complex and heterogeneous geoenvironments, landslides exhibit varying features in different environments, and data in landslide inventories are imbalanced. Existing data-driven landslide susceptibility evaluation (LSE) methods overlook environmental heterogeneity and cannot reliably predict regions with few samples. Alternatively, global random negative sampling strategies may produce imbalanced positive and negative samples in some environments, contributing to inaccurate predictions. This article proposes a graph neural network (GNN) constrained by environmental consistency (GNN-EC) to overcome these problems. The GNN-EC consists of graphs with nodes, and edges. A graph represents the environmental relationships in the study area. Nodes are geographic units delineated from terrain polygon approximation. Edges capture the relationships between node-pairs. Additionally, the weights of edges reflect the similarity between two node environments. A GNN aggregates node information in the graph for LSE. Our experiment showed that the proposed method outperformed the common machine learning methods: increasing prediction accuracy by approximately 7, 5–6 and 3–4% compared to the artificial neural network (ANN), the support vector machine (SVM) and the random forest (RF), respectively. Moreover, our method can maintain high prediction accuracy, even with a small training set. [ABSTRACT FROM AUTHOR]

In the current technological world, artificially intelligent deep learning techniques are adapted in many fields. This advanced technology is also used in the field of education. In this study, people will conduct research on the optimization of ideological and political education strategies in colleges and universities based on deep learning. Deep learning is often a machine learning technique that uses artificial neural networks that allow a machine to imitate human behaviour. Ideological and political education deals with the social studies implied by the political scenario. Ideological and political education aims to teach the younger generation social, economic, and political awareness. In our proposed system, people will deploy the deep learning algorithm named brute force algorithm to optimize ideological and political education in colleges and universities. The teaching optimization is performed by automating the training of the deep learning model. The results were compared with the existing K-means algorithm, and it is observed that the proposed system has achieved a higher accuracy of 99.12% in optimizing the educational strategies. [ABSTRACT FROM AUTHOR]

Agrilus mali Matsumura is a wood-boring beetle that aggressively attacks species of the genus Malus, that has recently caused serious damage to the wild apple tree M. sieversii (Lebed.) in the western Tianshan Mountains in Xinjiang. It was first detected there in the early 1990s and spread rapidly, being thus considered a regional invasive pest. To explore the possible outbreak mechanism of the local population and characterize the genetic differentiation of A. mali across different regions of China, we used three mitochondrial genes (COI , COII , and CytB) to investigate the genetic diversity and genetic structure of 17 A. mali populations containing 205 individuals collected from five Chinese provinces. Among them, nine populations were from the western Tianshan Mountains. Ultimately, of the 136 pairwise F st comparisons, 99 showed high genetic differentiation among overall populations, and Tianshan populations exhibited significant differentiation with most of the non-Tianshan populations. Furthermore, A. mali populations represented relatively abundant haplotypes (54 haplotypes). Nine populations from the Tianshan Mountains showed 32 haplotypes (26 of which were unique), displaying relatively high genetic diversity. Additionally, the Mantel test revealed population genetic differentiation among either overall populations or the Tianshan Mountains populations, likely caused by geographical isolation. Phylogenic relationships showed that all populations clustered into three clades, and Tianshan Mountains populations, including CY, occupied one of the three clades. These results suggest that A. mali in the western Tianshan region has possibly been present in the area for a long period, and may not have been introduced recently. Highly frequent gene flows within Tianshan populations are possibly caused by human activities and may enhance the adaptability of A. mali along the western Tianshan Mountains, leading to periodic outbreaks. These findings enhance our understanding of jewel beetle population genetics and provide valuable information for pest management. [ABSTRACT FROM AUTHOR]

Malus sieversii, a valuable crop in Xinjiang, China, is an important natural resource for researching the genetic diversity and phylogenetic evolution of the genus Malus worldwide. Samples from 152 M. sieversii individuals with different symptom grades of deadwood were collected from Gongliu and Xinyuan and analysed with 21 pairs of simple sequence repeat (SSR) primers, revealing molecular genetic characteristics and phylogeny of different groups and individuals. The samples showed high genetic diversity at the species level (Na = 10.76, Ne = 4.37, H = 0.73, I = 1.65, Ho = 0.71, and He = 0.73). Variation was mainly found within groups with lower genetic differentiation (Fst = 0.092) and higher gene flow (Nm = 2.67). A total of 226 alleles were obtained, of which 25 exclusive alleles were from samples with < 40% deadwood rate, and 23 exclusive alleles were from samples with > 40% deadwood rate. Specific bands relating to individuals with deadwood rate < 10% (10 exclusive alleles) or > 60% (7 exclusive alleles) were amplified with 11 pairs of SSR primers. The number of exclusive alleles from M. sieversii plants collected in Gongliu was 52 and from those collected in Xinyuan was 24. Using unweighted pair-group method with arithmetic cluster analysis, the groups with different symptom grades from different sampling sites were shown to be clearly differentiated and formed several discrete subclades. Significantly, the six groups from Gongliu were further classified into two subclusters: Gongliu 1, including three groups with < 40% deadwood rate, and Gongliu 2, including three groups with > 40% deadwood rate. [ABSTRACT FROM AUTHOR]

This paper introduces a ripple-based adaptive on-time controlled buck converter with pseudo triangular ramp compensation. Ripple-based control has its advantages over traditional PWM control of fast response and simple structure without frequency compensation network. Constant on-time (COT) control is one of the conventional ripple-based control methods, which needs large output capacitance with large ESR to guarantee the system stability, yet leading to large output ripple. In order to strengthen system stability with small output ripple and fast transient response, a novel pseudo triangular ramp compensation is proposed. Also COT control has its drawback of switching frequency variation. Therefore an adaptive on-time generator is adopted to fix switching frequency, in which VO/N2RS and Vin/N2RS are used as current sources to eliminate the effect of input/output voltage. A voltage outer loop is also adopted to improve DC precision. The power MOSFETs are integrated inside the chip. The proposed converter was implemented in 0.18 μm 5 V CMOS process. Experimental results show that the output ripple is around 20 mV. The switching frequency can be fixed at 2.5 MHz with only 1% variation. Also with 330 nH off-chip power inductor, this converter can output up to 6 A load current. Measured peak efficiency is 85%. [ABSTRACT FROM AUTHOR]

Wild apple forests in the Tian Shan Mountains in north‐western China have been adversely affected by an unknown disease in recent years. Symptoms attributed to this disease that affects wild apple trees include xylem browning and dieback which are suggestive of infection by Fusarium species. Therefore, the research team conducted the first survey for Fusarium in the afflicted wild apple forests. Twig samples with symptoms of xylem browning and dieback were collected in the Xinyuan, Gongliu, Yining and Huocheng Counties of Xinjiang Uighur Autonomous Region in China. Based on phylogenetic analyses and morphological observation, sixty strains of Fusarium accounted for 48% of the total number of fungi isolated from samples were subsequently classified into six species including twenty‐four F. avenaceum, seventeen F. solani, ten F. tricinctum, five F. proliferatum, two F. sporotrichioides and two unfamiliar Fusarium sp. 1. The five previously known species of Fusarium were then tested for pathogenicity to leaves and twigs in vitro. The results indicated that all of the species, except for F. tricinctum, can cause obvious lesions on the leaves of host plants and on the twigs of Fuji and wild apple. This is the first report of Fusarium species pathogenicity in Xinjiang wild apple forests, confirming a new host for these pathogens in this study. [ABSTRACT FROM AUTHOR]