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Accurate photovoltaic （PV） output power forecasting plays a crucial role in ensuring the secure and stable operation of distribution networks. In light of this， the paper proposes a short-term PV power forecasting method using cosine similarity and a hybrid TSO （tuna swarm optimization） and BP （back propagation） neural network. Firstly， the cosine similarity algorithm is utilized to identify historical data with strong resemblance to the forecast day as training samples. Subsequently， the TSO algorithm is employed to search for optimal initial weights and thresholds for the BP neural network. The TSO-BP model is then trained for short-term PV power forecasting. Finally， the TSO-BP model is applied to predict PV output power under both stable and fluctuating weather conditions. Simulation results indicate that， the proposed method， compared to traditional forecasting methods， achieves higher accuracy in predictions for both steady and fluctuating weather scenarios.

Objectives: COVID-19 viral pneumonia can result in increased arterial stiffness, along with cardiac and systemic inflammatory responses. This study aimed to investigate the association between arterial stiffness, inflammation severity, and all-cause mortality in patients with COVID-19. Methods: In this study, anthropometric data, pneumonia infection severity, and blood tests were analyzed. Arterial stiffness was assessed using the non-invasive assessment indices, including arterial velocity pulse index (AVI) and central arterial pulse pressure (CAPP). Infection volumes and percentages for the whole lungs, most lobes, and most segments were extracted from CT images using artificial intelligence-based quantitative analysis software. The relationship between arterial stiffness, central hemodynamics, and all-cause mortality was investigated. Results: In multivariable Cox regression analysis, high CAPP was significantly associated with all-cause mortality (hazard ratio: 0.263, 95% CI, 0.073–0.945, p = 0.041). Whole lung infection percentages were independently associated with high CAPP, with an area under the curve (AUC) of 0.662 and a specificity of 89.09%. Conclusions: High CAPP, but not high AVI, demonstrated independent prognostic value for all-cause mortality in patients due to COVID-19 pneumonia infection. Evaluating this parameter could help in risk assessment and improve diagnostic and therapeutic strategies in viral pneumonia infections. [ABSTRACT FROM AUTHOR]

To explore the influence of raw materials from different cultivars on the quality of Sichuan dark tea, the raw materials of 4 tea cultivars were used in this study. The main chemicals and aroma components were analyzed by sensory evaluation, chemical analysis and gas chromato graphy-mass spectrometry (GC-MS) . The main components of Sichuan dark teas made from different tea cultivars were significantly different. The contents of water extract, tea polyphenols, catechins and caffeine of Sichuan dark teas from 'Zijuan' were the highest, which were 49.45%, 18.54%, 4.77%, and 4.21%, respectively, followed by Sichuan dark tea processed with 'Huangjinya' cultivar, all of them were significantly (P<0.05) higher than the Sichuan dark tea processed with 'Fuding Dabai' and 'Baiye 1'. The contents of L-asparagine, L-theanine, aspartic acid and glutamic acid were the highest of Sichuan dark teas from 'Huangjinya', which were 115.78, 279.86, 154.47, 70.76 mg/100 g, respectively, significantly (P<0.05) higher than Sichuan dark tea processed with other cultivars. Aroma analysis showed that main aroma components were alcohols, aldehydes, ketones, hydrocarbons and esters, accounting for more than 80% of the total aroma. The similarity rate of aroma between 'Fuding Dabai' and 'Baiye 1' was 0.98, and that of 'Huangjinya' and 'Zijuan' was 0.99. The Sichuan dark tea processed with the 'Baiye 1' had floral fragrance, and the Sichuan dark tea processed with the 'Zijuan' had ''stale flavor''. Sensory quality analysis showed that the comprehensive qualities of Sichuan dark teas from 'Fuding Dabai','Baiye 1' and 'Huangjinya' were the better, with a score of more than 82, while the Sichuan dark tea from 'Zijuan' had the lowest score. The Sichuan dark tea processed with 'Huangjinya' materials was rich in substances and had good comprehensive quality. The Sichuan dark tea processed with 'Baiye 1' material had floral fragrance, which could be used as a variety for processing advanced special Sichuan dark tea. The Sichuan dark tea processed with 'Zijuan' materials had high content of water extracts and tea polyphenols, with ''stale flavor''. It was suitable for blending and processing with other cultivars of low polyphenol content, and could be used as a blending variety for dark tea products with ''stale flavor''. [ABSTRACT FROM AUTHOR]

Spider mite infestation has a severe impact on tea growth and quality. In this study, we conducted a deep exploration of the functions and regulations of the CsPIP5K gene family using chromosomal localization and collinearity analysis. Additionally, we carefully examined the cis elements within these genes. To fully understand the metabolic response of CsPIP5K under spider mite infection, we integrated previously published metabolomic and transcriptomic data. Our analysis revealed that multiple CsPIP5K genes are associated with phospholipid metabolism, with CsPIP5K06 showing the strongest correlation. Therefore, we employed qPCR and subcellular localization techniques to determine the expression pattern of this gene and its functional location within the cell. Overall, this study not only comprehensively elucidated the characteristics, structure, and evolution of the CsPIP5K gene family but also identified several candidate CsPIP5K genes related to phospholipid biosynthesis and associated with spider mites based on previously published data. This research makes a significant contribution to enhancing the resistance of tea to spider mite and maintaining optimal tea quality. [ABSTRACT FROM AUTHOR]

Purpose: Predicting highly cited papers can enable an evaluation of the potential of papers and the early detection and determination of academic achievement value. However, most highly cited paper prediction studies consider early citation information, so predicting highly cited papers by publication is challenging. Therefore, the authors propose a method for predicting early highly cited papers based on their own features. Design/methodology/approach: This research analyzed academic papers published in the Journal of the Association for Computing Machinery (ACM) from 2000 to 2013. Five types of features were extracted: paper features, journal features, author features, reference features and semantic features. Subsequently, the authors applied a deep neural network (DNN), support vector machine (SVM), decision tree (DT) and logistic regression (LGR), and they predicted highly cited papers 1–3 years after publication. Findings: Experimental results showed that early highly cited academic papers are predictable when they are first published. The authors' prediction models showed considerable performance. This study further confirmed that the features of references and authors play an important role in predicting early highly cited papers. In addition, the proportion of high-quality journal references has a more significant impact on prediction. Originality/value: Based on the available information at the time of publication, this study proposed an effective early highly cited paper prediction model. This study facilitates the early discovery and realization of the value of scientific and technological achievements. [ABSTRACT FROM AUTHOR]

The full enzymatic activity of the cullin-RING ubiquitin ligases (CRLs) requires a ubiquitin-like protein (that is, Nedd8) modification. By deamidating Gln40 of Nedd8 to glutamate (Q40E), the bacterial cycle-inhibiting factor (Cif) family is able to inhibit CRL E3 activities, thereby interfering with cellular functions. Despite extensive structural studies on CRLs, the molecular mechanism by which Nedd8 Gln40 deamidation affects CRL functions remains unclear. We apply a new quantitative cross-linking mass spectrometry approach to characterize three different types of full-length human Cul1-Rbx1 complexes and uncover major Nedd8-induced structural rearrangements of the CRL1 catalytic core. More importantly, we find that those changes are not induced by Nedd8(Q40E) conjugation, indicating that the subtle change of a single Nedd8 amino acid is sufficient to revert the structure of the CRL catalytic core back to its unmodified form. Our results provide new insights into how neddylation regulates the conformation and activity of CRLs.

Due to the strong nonlinear interaction between the flow field and blades, the prediction of turbine energy acquisition capacity is still quite complex, the traditional methods take too long time to evaluate. In this article, the digital twin model + CFD simulation + monitor data are used for turbine energy efficiency assessment. A self-designed vertical wave flow turbine (VWFT) is taken as the research object, the prediction takes into account the coupling of the VWFT for motion and blade rotation, which is in good agreement with the monitor data at sea. The simulations show that the torque, thrust force and lateral force flow rate data can be loaded from the database into the digital model. If those data are not in the database, the interpolation method is used along with deep learning of recurrent neural network to obtain the energy harvesting parameters, all the error is no more than 10%. [ABSTRACT FROM AUTHOR]

The target of rapamycin (TOR) plays a central role in eukaryotic cell growth control. With prevalent hyperactivation of the mammalian TOR (mTOR) pathway in human cancers, strategies to enhance TOR pathway inhibition are needed. We used a yeast-based screen to identify small-molecule enhancers of rapamycin (SMERs) and discovered an inhibitor (SMER3) of the Skp1-Cullin-F-box (SCF)(Met30) ubiquitin ligase, a member of the SCF E3-ligase family, which regulates diverse cellular processes including transcription, cell-cycle control and immune response. We show here that SMER3 inhibits SCF(Met30) in vivo and in vitro, but not the closely related SCF(Cdc4). Furthermore, we demonstrate that SMER3 diminishes binding of the F-box subunit Met30 to the SCF core complex in vivo and show evidence for SMER3 directly binding to Met30. Our results show that there is no fundamental barrier to obtaining specific inhibitors to modulate function of individual SCF complexes.