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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]

System logs, serving as a pivotal data source for performance monitoring and anomaly detection, play an indispensable role in assuring service stability and reliability. Despite this, the majority of existing log-based anomaly detection methodologies predominantly depend on the sequence or quantity attributes of logs, utilizing solely a single Recurrent Neural Network (RNN) and its variant sequence models for detection. These approaches have not thoroughly exploited the semantic information embedded in logs, exhibit limited adaptability to novel logs, and a single model struggles to fully unearth the potential features within the log sequence. Addressing these challenges, this article proposes a hybrid architecture based on a multiscale convolutional neural network, efficient channel attention and mogrifier gated recurrent unit networks (LogCEM), which amalgamates multiple neural network technologies. Capitalizing on the superior performance of robustly optimized BERT approach (RoBERTa) in the realm of natural language processing, we employ RoBERTa to extract the original word vectors from each word in the log template. In conjunction with the enhanced Smooth Inverse Frequency (SIF) algorithm, we generate more precise log sentence vectors, thereby achieving an in-depth representation of log semantics. Subsequently, these log vector sequences are fed into a hybrid neural network, which fuses 1D Multi-Scale Convolutional Neural Network (MSCNN), Efficient Channel Attention Mechanism (ECA), and Mogrifier Gated Recurrent Unit (GRU). This amalgamation enables the model to concurrently capture the local and global dependencies of the log sequence and autonomously learn the significance of different log sequences, thereby markedly enhancing the efficacy of log anomaly detection. To validate the effectiveness of the LogCEM model, we conducted evaluations on two authoritative open-source datasets. The experimental results demonstrate that LogCEM not only exhibits excellent accuracy and robustness, but also outperforms the current mainstream log anomaly detection methods. [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]

Objectives: We aimed to establish a diagnostic model of endometriosis (EM) based on disulfidptosis‐related genes (DRGs). Materials and Methods: The mRNA expression data of EM were downloaded from the gene expression omnibus database and subjected to differential analysis, and co‐expression analysis was performed based on 10 disulfidptosis genes to acquire DRGs. The differentially expressed DRGs were subjected to biofunctional analysis. Lasso analysis and support vector machine‐recursive feature elimination (SVM‐RFE) analysis were employed to extract the intersection of feature genes as biomarkers, and the diagnostic values of biomarkers for EM were evaluated based on receiver operating characteristic curves. The correlations between biomarkers and the immune microenvironment were assessed by Pearson analysis of biomarkers and immune cell infiltration levels. Results: Transforming growth factor β stimulated protein clone 22 domain family member 4 (TSC22D4), and F‐box/SPRY domain‐containing protein 1 (FBXO45) worked as the diagnostic classifiers in EM, with an obvious decrease in FBXO45 expression and an evident increase in TSC22D4 expression. The areas under the curves of FBXO45 and TSC22D4 were 0.752 and 0.706, respectively, and the area of FBXO45 combined with TSC22D4 reached 0.865, suggesting that TSC22D4 and FBXO45 had high predictive values. The diagnostic markers were closely correlated with immune cell infiltration. Conclusion: The diagnostic markers constructed based on disulfidptosis are good predictors for EM, which have close correlations with EM. [ABSTRACT FROM AUTHOR]

The ability of plasmonic optical tweezers based on metal nanostructure to stably trap and dynamically manipulate nanoscale objects at low laser power has been widely used in the fields of nanotechnology and life sciences. In particular, their plasmonic nanocavity structure can improve the local field intensity and trap depth by confining electromagnetic fields to subwavelength volumes. In this paper, the R6G dye molecules with 10−6 M were successfully trapped by using the Ag@Polydimethylsiloxane nanocavity array structure, and a R6G micro-ring was formed under the combined action of plasmonic optical force and thermophoresis. Subsequently, the theoretical investigation revealed that the trapping performance can be flexibly adjusted by changing the structural parameters of the conical nanocavity unit, and it can provide a stable potential well for polystyrene particles of RNP = 14 nm when the cavity depth is 140 nm. In addition, it is found that multiple trapping sites can be activated simultaneously in the laser irradiation area by investigating the trapping properties of the hexagonal conical nanocavity array structure. This multi-site stable trapping platform makes it possible to analyze multiple target particles contemporaneously. [ABSTRACT FROM AUTHOR]

Swine acute diarrhea syndrome coronavirus (SADS-CoV), an emerging Alpha-coronavirus, brings huge economic loss in swine industry. Interferons (IFNs) participate in a frontline antiviral defense mechanism triggering the activation of numerous downstream antiviral genes. Here, we demonstrated that TRIM25 overexpression significantly inhibited SADS-CoV replication, whereas TRIM25 deficiency markedly increased viral yield. We found that SADS-CoV N protein suppressed interferon-beta (IFN-β) production induced by Sendai virus (SeV) or poly(I:C). Moreover, we determined that SADS-CoV N protein interacted with RIG-I N-terminal two caspase activation and recruitment domains (2CARDs) and TRIM25 coiled-coil dimerization (CCD) domain. The interaction of SADS-CoV N protein with RIG-I and TRIM25 caused TRIM25 multimerization inhibition, the RIG-I-TRIM25 interaction disruption, and consequent the IRF3 and TBK1 phosphorylation impediment. Overexpression of SADS-CoV N protein facilitated the replication of VSV-GFP by suppressing IFN-β production. Our results demonstrate that SADS-CoV N suppresses the host IFN response, thus highlighting the significant involvement of TRIM25 in regulating antiviral immune defenses. [ABSTRACT FROM AUTHOR]

Objective: This study investigates the serial multiple mediation of job stress and perceived behavioral control (PBC) in the relationship between social support and oral health behavior (OHB). Materials and Methods: This cross‐sectional study was conducted in Minhang District, Shanghai, China, between July and November 2021. 559 Employees from 10 community health centers were recruited. A five‐part survey was used to collect data on demographic characteristics, social support, job stress, PBC and OHB. Descriptive statistics, independent‐sample t‐test, Pearson's correlation analysis, ordinary least‐squares regression and the bootstrap method were used to analyze data. Results: Social support was found to impact OHB through three significant mediation pathways: the pathway through job stress (point estimate = 0.033; 95%BC CI [0.004, 0.089]), the pathway through PBC (point estimate = 0.283; 95%BC CI [0.174, 0.416]), and the serial multiple mediating pathway through first job stress and then PBC (point estimate = 0.006; 95%BC CI [0.001, 0.019]). Conclusion: This study indicates that job stress and PBC play a serial multiple‐mediator role in the relationship between social support and OHB. To ensure the effectiveness of social support intervention on OHB, workplace managers and employees should strengthen the motivators that could promote the reduction of job stress and the improvement of PBC. [ABSTRACT FROM AUTHOR]

Endometriosis (EMS) is a chronic inflammatory disorder of high incidence that causes serious reproductive consequences. High estrogen production is a consistently observed endocrine feature of EMS. The present study aims to probe the molecular mechanism of G protein-coupled estrogen receptor 1 (GPER) in the invasion and migration of ectopic endometrial stromal cells (Ect-ESCs) and provides a new rationale for EMS treatment. Eutopic and ectopic endometrial tissues were collected from 41 EMS patients, and primary ESCs were separated. GPER, miR-16-5p, and miR-103a-3p levels in cells and tissues were determined by qRT-PCR or Western blot assay. Cell viability, proliferation, invasion, and migration were evaluated by CCK-8, colony formation, and Transwell assays. The upstream miRNAs of GPER were predicted by databases, and dual-luciferase assay was performed to validate the binding of miR-16-5p and miR-103a-3p to GPER 3'UTR. GPER was highly expressed in EMS tissues and Ect-ESCs. Inhibition of GPER mitigated the proliferation, invasion, and migration of Ect-ESCs. GPER was regulated by miR-16-5p and miR-103a-3p. Overexpression of miR-16-5p and miR-103a-3p negatively regulated GPER expression and inhibited the invasion and migration of Ect-ESC. In conclusion, GPER promoted the invasion and migration of Ect-ESCs, which can be reversed by upstream miR-16-5p and miR-103a-3p. [ABSTRACT FROM AUTHOR]

Gestures have long been recognized as an interaction technique that can provide a more natural, creative, and intuitive way to communicate with computers. However, some existing difficulties include the high probability that the same type of movement done at different speeds will be recognized as a different category of movement; cluttered, occluded, and low-resolution backgrounds; and the near-impossibility of fusing different types of features. To this end, we propose a novel framework for integrating different scales of RGB and motion skeletons to obtain higher recognition accuracy using multiple features. Specifically, we provide a network architecture that combines a three-dimensional convolutional neural network (3DCNN) and post-fusion to better embed different features. Also, we combine RGB and motion skeleton information at different scales to mitigate speed and background issues. Experiments on several gesture recognition public datasets show desirable results, validating the superiority of the proposed gesture recognition method. Finally, we do a human-computer interaction experiment to prove its practicality. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Cholesterol 25-Hydroxylase Suppresses Swine Acute Diarrhea Syndrome Coronavirus Infection by Blocking Spike Protein-Mediated Membrane Fusion" published in the journal Viruses. The correction addresses a mistake in Figure 1E of the original publication, which was taken from a previously published master's degree article. The corrected figure has been provided, and the authors state that the scientific conclusions remain unaffected. The original publication has been updated accordingly. [Extracted from the article]

Background: Cervical cancer (CC) is one of the major types of gynecological cancer, with a high global incidence and mortality rate. Methyltransferase-like 3 (METTL3), a key constituent of methyltransferase, plays a crucial role in various biological processes. Still, only a rare report has been made on its involvement in the progression of CC. Therefore, this study aims to investigate the impact of METTL3 in CC and its molecular mechanisms., Methods: Gene expression datasets about CC were obtained from the Gene Expression Omnibus (GEO) database, and the expression of METTL3 and Myc was analyzed. Cell viability was detected after METTL3 knockdown in HeLa and SiHa cells, followed by cell counting Kit-8 (CCK-8) assays. The relative expression of METTL3 and Myc was detected via real-time quantitative PCR (qPCR) assays, and the protein expression was determined using Western blot. Meanwhile, cell invasion and migration capabilities were assessed utilizing transwell assays, and cell proliferation was detected using the EdU experiment. Furthermore, RNA methylation immunoprecipitation-qPCR detection was performed to determine the expression of Myc after N 6 -methyladenosine (m 6 A) modification., Results: Analysis of the GEO database indicated elevated expression of METTL3 and Myc in CC tissues. Patients with high METTL3 expression had shorter disease-free survival, and patients with high Myc expression had shorter overall survival. Following the knockdown of METTL3 , there was a significant reduction in the viability, proliferation, invasion, and migration abilities of HeLa and SiHa cells. Besides, the expression of METTL3 and Myc mRNAs and proteins was greatly reduced. The level of m 6 A Myc decreased significantly after METTL3 knockdown., Conclusions: METTL3 plays an important role in regulating cervical cancer cells. METTL3 promotes CC development through m 6 A modification to regulate the expression of the oncogene Myc .

Porcine epidemic diarrhea virus (PEDV) is associated with severe enteritis, which contributes to high mortality in piglets. The aim of this study was to describe molecular mechanisms associated with proinflammatory cytokine(s) production during PEDV infection. We showed that infection of porcine intestine epithelial cell clone J2 (IPEC-J2) with PEDV induces a gradual increase in interleukin 8 (IL-8) production at different time points, as well as infection of Vero E6 with PEDV. The secretion of IL-8 in these two cell lines infected with PEDV is related to the activation of NF-κB. Furthermore, the cells expressing PEDV M or E protein can induce the upregulation of IL-8. These findings suggest that the IL-8 production can be the initiator of inflammatory response by the host cells upon PEDV infection., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Wu, Wang, Wang, Li, Yan, Shi, Shi, Chen, Guo and Feng.)

Current research on the effects of glyceryl trinitrate (GTN) on the lowering of elevated blood pressure (BP) among patients with acute intracerebral hemorrhage (AIH) has not been highly emphasized. The aim of this meta-analysis is to examine the effects of GTN in patients with acute stroke. The lowering of BP was the primary outcome measure in patients treated with GTN compared to no-GTN treatment. A meta-analysis was performed to evaluate the efficacy of GTN in lowering BPs and analyze the outcomes of GTN treatment. Appropriate articles were searched using PubMed, Taylor & Francis Online, Cochrane, Scopus, ScienceDirect, Wiley Online Library, and Springer, with the use of appropriate keywords as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Out of 13 articles eligible for this study, 7 studies qualified for the meta-analysis by meeting the inclusion criteria. The PRISMA guidelines and the recommendations of Cochrane Collaboration were followed when conducting this meta-analysis. After subgroup analysis, differences between patients treated with GTN and without GTN were analyzed. The lowering of BP resulted in improved functional outcomes in patients treated with GTN. This meta-analysis showed differences between the 2 groups, with a risk ratio (RR) of 1.01 (95% confidence interval (95% CI): 0.92-10.07, p = 0.30, I2 = 18%). There was a significant improvement in outcome measures in patients treated with GTN by lowering elevated BP after acute stroke.