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Wind power forecasting is a critical technology for promoting the effective integration of wind energy. To enhance the accuracy of wind power predictions, this paper introduces a novel wind power prediction model that considers the evolving relationships of multi-scale variables and temporal dependencies. In this paper, a multi-scale frequency decomposition module is designed to split the raw data into high-frequency and low-frequency parts. Subsequently, features are extracted from the high-frequency information using a multi-scale temporal graph neural network combined with an adaptive graph learning module and from the low-frequency data using an improved bidirectional temporal network. Finally, the features are integrated through a cross-attention mechanism. To validate the effectiveness of the proposed model, extensive comprehensive experiments were conducted using a wind power dataset provided by the State Grid. The experimental results indicate that the MSE of the model proposed in this paper has decreased by an average of 7.1% compared to the state-of-the-art model and by 48.9% compared to the conventional model. Moreover, the improvement in model performance becomes more pronounced as the prediction horizon increases. [ABSTRACT FROM AUTHOR]

In this study, a ring light point cloud calibration technique based on collimated laser beams is developed, aiming to reduce errors caused by the position and attitude changes of traditional ring light measurement devices. This article details the generation mechanism of the ring beam and the principle of deep hole measurement. It introduces the collimated beam as a reference, building on traditional ring light measurement devices, to achieve the synchronous acquisition of the ring beam and collimated spot images by an industrial camera. The Steger algorithm is employed to accurately extract the coordinates of the point cloud contours of both the ring beam and the collimated spot. By analyzing the shape and position changes of the collimated spot contour, the spatial position and attitude of the measuring device are precisely determined. This technique is applied to the 3D reconstruction of the inner surface of deep holes, ensuring the accurate restoration of the spatial positional attitude of the ring beam by incorporating the spatial positional attitude parameters of the measuring device to precisely calibrate the cross-sectional point cloud coordinates. Experimental results with ring gauges and deep hole workpieces demonstrate that this technique effectively reduces the percentage of point cloud data outside the tolerance range, and improves the accuracy of the 3D reconstruction model by 6.287%, thereby verifying the accuracy and practicality of this technique. [ABSTRACT FROM AUTHOR]

Adenosine kinase (ADK) is a key enzyme widely distributed in plants, playing an important role in maintaining cellular energy homeostasis and regulating plant growth, development, and responses to environmental stresses. However, research on ADK genes in cotton (Gossypium hirsutum), an economically significant crop, has been limited. This study identified 92 ADK genes from four cotton species (G. arboreum, G. raimondii, G. hirsutum, and G. barbadense) using HMMER and Local BLASTP methods and classified them into six groups. Chromosomal localization revealed a random distribution of ADK genes in G. hirsutum, with 13 genes located on the At subgenome and 14 genes on the Dt subgenome. Gene structure analysis showed consistency in exon–intron organization within subgroups, while conserved motif analysis identified subgroup-specific motifs, indicating functional diversity. Synteny and collinearity mapping analysis revealed that the primary expansion mechanisms of the ADK gene family in cotton are polyploidy and segmental duplication. Cis-regulatory elements in GhADK promoters were classified into light response, hormone response, developmental regulation, and stress response. We also analyzed the expression patterns of GhADK genes under a low temperature (4 °C) and drought conditions. Most GhADK genes responded to cold stress with different expression patterns, indicating their roles in rapid response and long-term cold adaptation. Under drought stress, expression patterns varied, with some genes showing sustained high expression levels. The qRT-PCR validation of transcriptomic data confirmed the stress-induced expression patterns of selected GhADK genes. Functional analysis through the VIGS silencing of GhADK25 demonstrated its importance in cold and drought stress responses, with silencing resulting in poor growth under stress, highlighting its significance in stress tolerance. This study provides a basis for further understanding the evolutionary relationships and functions of the cotton ADK gene family. [ABSTRACT FROM AUTHOR]

Objective To assess the effect of caries management based on risk assessment in children and to provide the basis for the government to develop strategies to prevent and treat oral diseases. Methods From March 2018 to March 2019, 512 3-year-old children and 502 6-year-old children were selected by cluster sampling from kindergartens and primary schools, respectively, in the Minhang district of Shanghai, and oral examinations and questionnaires were carried out to assess baseline status. Then, the children were divided into 3 groups, including low-, middle- and high-risk groups, according to caries risk assessment. In each caries risk group, the children were randomly divided into an experimental group and a control group. The experimental groups were managed by risk assessment, and the control groups were provided basic oral public health services by the Shanghai government. The effect of caries prevention was evaluated 12 months later. Results Among the children with a high risk of caries, the incidence of caries was 51.22% in the 3-year-old control group, 34.17% in the experimental group, 51.27% in the 6-year-old control group and 33.15% in the experimental group, with statistical significance (P < 0.05). Among the children with a middle risk of caries, the incidence of caries was 38.71% in the 3-year-old control group and 7.32% in the experimental group, with statistical significance (P < 0.05). However, there was no significant difference in caries incidence between the control group and the experimental group for the children with low risk in the 3-year-old or 6-year-old groups and middle risk caries risk in the 6-year-old group. Both 3-year-old and 6-year-old children in the experimental group had a lower risk of caries than those in the observation group in 2019. Conclusion The caries prevention effect is remarkable in high-risk children, and caries management by risk assessment is probably recommended for children with high caries risk.

The interdependence between the scheduling method and the production efficiency of a micro-hole drilling production line for printed circuit boards (PCBs) holds significant importance, necessitating the optimization of such a production line's scheduling. Consequently, this research paper presents a scheduling optimization approach for the micro-hole drilling production line of a PCB, utilizing complex events as its foundation. Initially, a complex event model was constructed to establish correlations among extensive production line data. Subsequently, the typical complex events associated with the micro-hole drilling production line of a PCB were defined, thereby enabling the all-around monitoring of the operation state of such a production line. Furthermore, this study presents the establishment of a production scheduling model for PCB micro-hole drilling. With the goal of minimizing the maximum completion time, the catastrophe genetic algorithm was used to solve the initial scheduling scheme of the printed circuit board micro-hole drilling production line. The reliability and effectiveness of the catastrophe genetic algorithm in solving the hybrid-driven production scheduling problem of complex events were verified. Dynamic scheduling was performed when three complex events occurred in the production line: emergency order insertion, abnormal equipment operation, and tool failure. The scheduling optimization rate after identifying the emergency insertion event could reach 25.1%. The scheduling optimization rate of the production equipment operation event was related to the specific failure time of the equipment. The scheduling optimization rate after identifying the tool failure event could reach 25%. Rescheduling immediately after identifying the tool failure event could exert no effect on the initial scheduling process. It was proven that the identification and rescheduling of complex events can improve the production efficiency of a PCB micro-hole drilling production line. [ABSTRACT FROM AUTHOR]

Coronaviruses (CoVs) are a family of the largest RNA viruses that typically cause respiratory, enteric, and hepatic diseases in animals and humans, imposing great threats to the public safety and animal health. Porcine deltacoronavirus (PDCoV), a newly emerging enteropathogenic coronavirus, causes severe diarrhea in suckling piglets all over the world and poses potential risks of cross-species transmission. Here, we use PDCoV as a model of CoVs to illustrate the reciprocal regulation between CoVs infection and host antiviral responses. In this study, downregulation of DNA polymerase delta interacting protein 3 (POLDIP3) was confirmed in PDCoV infected IPEC-J2 cells by isobaric tags for relative and absolute quantification (iTRAQ) and Western blotting analysis. Overexpression of POLDIP3 inhibits PDCoV infection, whereas POLDIP3 knockout (POLDIP3-/-) by CRISPR-Cas9 editing significantly promotes PDCoV infection, indicating POLDIP3 as a novel antiviral regulator against PDCoV infection. Surprisingly, an antagonistic strategy was revealed that PDCoV encoded nonstructural protein 5 (nsp5) was responsible for POLDIP3 reduction via its 3C-like protease cleavage of POLDIP3 at the glutamine acid 176 (Q176), facilitating PDCoV infection due to the loss of antiviral effects of the cleaved fragments. Consistent with the obtained data in IPEC-J2 cell model in vitro, POLDIP3 reduction by cleavage was also corroborated in PDCoV infected-SPF piglets in vivo. Collectively, we unveiled a new antagonistic strategy evolved by PDCoV to counteract antiviral innate immunity by nsp5-mediated POLDIP3 cleavage, eventually ensuring productive virus replication. Importantly, we further demonstrated that nsp5s from PEDV and TGEV harbor the conserved function to cleave porcine POLDIP3 at the Q176 to despair POLDIP3-mediated antiviral effects. In addition, nsp5 from SARS-CoV-2 also cleaves human POLDIP3. Therefore, we speculate that coronaviruses employ similar POLDIP3 cleavage mechanisms mediated by nsp5 to antagonize the host antiviral responses to sustain efficient virus infection. Author summary: Coronavirus encodes the conserved 3C-like protease nsp5, which has been reported to antagonize interferon (IFN) responses by cleaving a variety of subtracts critical for interferon signaling pathways. In this study, POLDIP3 was screened with apparent downregulation post PDCoV infection and identified as a novel antiviral regulator against PDCoV infection. Notably, PDCoV employs its nsp5 to directly cleave POLDIP3 in favor of its replication. We revealed that nsp5 proteins from other coronaviruses, such as porcine epidemic diarrhea virus (PEDV), transmissible gastroenteritis virus (TGEV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also had the protease activity to cleave porcine and human POLDIP3. Thus, the findings will deepen our better understanding of pathogenic mechanisms of coronavirus infections and provide nsp5 as an appealing target for the therapeutic design against coronavirus infections. [ABSTRACT FROM AUTHOR]