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In this paper, a hybrid load frequency control (LFC) scheme is proposed for multi-area interconnected power systems to decouple the intricate double control objectives, by dividing all subareas into the responsible areas and the free areas. The LFC in the responsible area has the function of regulating both the local frequency and the tie-line power, while the control objective of the LFC in the free area is thus simplified to regulate the local frequency only. Then, addressing the complex network coupling and uncertain dynamics, an integrated LFC controller is proposed for the free areas, which consists of two parts, namely, the coupling attenuation baseline controller and the disturbance compensation controller. The coupling attenuation baseline controller satisfying the predefined bounded L2-Gain condition is derived based on the solution to a multi-player zero-sum differential game. Additionally, a novel generalized integral observer is designed to estimate the system's integrated disturbance, and the corresponding disturbance compensation controller is derived. After that, the ultimately uniformly bounded (UUB) stability of the integrated LFC controller combining baseline controller and disturbance compensation controller is proven rigorously. Finally, the performance superiority of the proposed hybrid LFC scheme is validated by the simulations in challenging operating modes.

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BACKGROUND: Short sleep can lead to an increase in inflammation and regular exercise has been shown to have a mitigation effect. However, the association between physical exercise (PE) and inflammation in the short sleep population is an unknown and intriguing issue. METHODS: NHANES dataset spanning the years 2007 to 2018 were analyzed. To investigate the relationship mentioned above, we carried out multivariate linear regression models controlling for sociodemographic and lifestyles factors. The systemic immune inflammation index (SII) served as a reflection of inflammatory potential, calculated as the product of platelet count, neutrophil count, and divided by the lymphocyte count. Self-reported questionnaires were used to collect sleep and exercise information. RESULTS: A total of 14,664 participants were included for final analysis. Across the three models, PE showed significant negative associations with SII as a continuous variable [Crude Model, ß (95% CI): -1.261(-1.600, -0.922), p < 0.001; Model 1, ß (95% CI): -1.005(-1.344, -0.666), p < 0.001; Model 2, ß (95% CI): -0.470(-0.827, -0.112), p = 0.011]. The consistent nature of the findings persisted when investigating physical exercise (PE) as a categorized variable. By two-piecewise linear regression model, we calculated a saturation effect of PE with the inflection point as 2400 MET-minutes/week. CONCLUSION: This study suggested that performing no more than 2400 MET-minutes/week of PE was associated with lower SII levels in the short sleep population, while more PE might not bring additional benefits.

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Correlations of fluctuations are essential to understanding many-body systems and key information for advancing quantum technologies. To fully describe the dynamics of a physical system, all time-ordered correlations (TOCs), i.e., the dynamics-complete set of correlations are needed. The current measurement techniques can only access a limited set of TOCs, and there has been no systematic and feasible solution for extracting the dynamic-complete set of correlations hitherto. Here we propose a platform-universal protocol to selectively detect arbitrary types of TOCs via quantum channels. In our method, the quantum channels are synthesized with various controls, and engineer the evolution of a sensor-target system along a specific path that corresponds to a desired correlation. Using nuclear magnetic resonance, we experimentally demonstrate this protocol by detecting a specific type of fourth-order TOC that has never been accessed previously. We also show that the knowledge of the TOCs can be used to significantly improve the precision of quantum optimal control. Our method provides a new toolbox for characterizing the quantum many-body states and quantum noise, and hence for advancing the fields of quantum sensing and quantum computing.

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Strawberry root rot caused by Fusarium solani is one of the main diseases of strawberries and significantly impacts the yield and quality of strawberry fruit. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional chemical fungicides. To obtain antagonistic bacteria with a high biocontrol effect on strawberry root rot, over 72 rhizosphere bacteria were isolated from the strawberry rhizosphere soil and screened for their antifungal activity against F. solani by dual culture assay. Among them, strains CMS5 and CMR12 showed the strongest inhibitory activity against F. solani (inhibition rate 57.78% and 65.93%, respectively) and exhibited broad-spectrum antifungal activity. According to the phylogenetic tree based on 16S rDNA and gyrB genes, CMS5 and CMR12 were identified as Bacillus amyloliquefaciens. Lipopeptide genes involved in surfactin, iturin, and fengycin biosynthesis were detected in the DNA genomes of CMS5 and CMR12 by PCR amplification. The genes related to the three major lipopeptide metabolites existed in the DNA genome of strains CMS5 and CMR12, and the lipopeptides could inhibit the mycelial growth of F. solani and resulted in distorted hyphae. The inhibitory rates of lipopeptides of CMS5 and CMR12 on the spore germination of F. solani were 61.00% and 42.67%, respectively. The plant-growth-promoting (PGP) traits in vitro screening showed that CMS5 and CMR12 have the ability to fix nitrogen and secreted indoleacetic acid (IAA). In the potting test, the control efficiency of CMS5, CMR12 and CMS5+CMR12 against strawberry root rot were 65.3%, 67.94% and 88.00%, respectively. Furthermore, CMS5 and CMR12 enhanced the resistance of strawberry to F. solani by increasing the activities of defense enzymes MDA, CAT and SOD. Moreover, CMS5 and CMR12 significantly promoted the growth of strawberry seedlings such as root length, seedling length and seedling fresh weight. This study revealed that B. amyloliquefaciens CMS5 and CMR12 have high potential to be used as biocontrol agents to control strawberry root rot.

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The main topic of this research is the relationship between dietary intake of live microbe-containing (LMC) foods, recreational physical activity (RPA), and the systemic immune-inflammation index (SII). This study presented a cohort of 26,254 individuals in the National Health and Nutrition Examination Survey (NHANES), representing an estimated weighted population of 193,637,615 in the United States. Weighted multivariable linear regression models were used in consideration of the multi-stage sampling design. Results: The study found that medium-LMC foods were negatively associated with the SII [ß (95% CI): -4.807 (-7.752, -1.862), p = 0.002], indicating that their intake was correlated with lower levels of the SII. However, no significant associations were found with low- or high-LMC foods. The study also explored the relationship between RPA and the SII, finding that more time spent in RPA was negatively associated with the SII [ß (95% CI): -0.022 (-0.034, -0.011), p < 0.001]. A mediation analysis was conducted to investigate the role of RPA in the relationship between medium-LMC food intake and the SII. The analysis revealed that RPA had a notable indirect effect, contributing to 6.7% of the overall change in the SII. Overall, this study suggests that medium-LMC food intake and RPA may have beneficial effects on systemic immune inflammation.

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Objective: This study evaluated the efficacy and safety of the gemcitabine and oxaliplatin intrathoracic perfusion chemotherapy (IPCGOR) regimen combined with interleukin-2 (IL-2) for advanced non-small cell lung cancer (NSCLC). Methods: We conducted a retrospective analysis of 460 advanced NSCLC patients from the Yunnan Province Early Cancer Diagnosis and Treatment Project (June 2020-October 2022), assessing the IPCGOR and IL-2 combination. Outcomes were measured based on RECIST 1.1 criteria, focusing on objective response rate (ORR), disease control rate (DCR), median progression-free survival (mPFS), median overall survival (MOS), and treatment safety. Results: The treatment demonstrated an ORR of 67.4%, a DCR of 97.4%, an mPFS of 8.5 months, and an MOS of 12.5 months. 14 patients underwent successful surgery post-treatment. Common adverse reactions were manageable, with no treatment-related deaths reported. Conclusion: The IPCGOR combined with IL-2 regimen shows promising efficacy and a tolerable safety profile for advanced NSCLC. These findings suggest its potential as a reference for treating advanced NSCLC. However, the study's retrospective nature and single-center design pose limitations. Future research should focus on prospective studies, randomized controlled trials, and long-term outcome assessments, particularly in diverse patient subgroups, to further validate and refine the clinical application of this regimen.

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Sleep is a modifiable behavior that can be targeted in interventions aimed at promoting healthy aging. This study aims to (i) identify the sleep duration trend in US adults; (ii) investigate the relationship between sleep duration and phenotypic age; and (iii) explore the role of exercise in this relationship. Phenotypic age as a novel index was calculated according to biomarkers collected from US adults based on the National Health and Nutrition Examination Survey (NHANES). Sleep information was self-reported by participants and discerned through individual interviews. The principal analytical method employed was weighted multivariable linear regression modeling, which accommodated for the complex multi-stage sampling design. The potential non-linear relationship was explored using a restricted cubic spline (RCS) model. Furthermore, subgroup analyses evaluated the potential effects of sociodemographic and lifestyle factors on the primary study outcomes. A total of 13,569 participants were finally included in, thereby resulting in a weighted population of 78,880,615. An examination of the temporal trends in sleep duration revealed a declining proportion of individuals with insufficient and markedly deficient sleep time since the 2015-2016 cycle. Taken normal sleep group as a reference, participants with extreme short sleep [ß (95% CI) 0.582 (0.018, 1.146), p = 0.044] and long sleep [ß (95% CI) 0.694 (0.186, 1.203), p = 0.010] were both positively associated with phenotypic age using the fully adjusted model. According to the dose-response relationship between sleep duration and phenotypic age, long sleep duration can benefit from regular exercise activity, whereas short sleep duration with more exercise tended to have higher phenotypic age. There is an inverted U-shaped relationship between short and long sleep durations and phenotypic age. This study represents an important step forward in our understanding of the complex relationship between sleep and healthy aging. By shedding light on this topic and providing practical exercise recommendations for promoting healthy sleep habits, researchers can help individuals live longer, healthier, and more fulfilling lives.

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In response to the need for multiple complete bearing degradation datasets in traditional deep learning networks to predict the impact on individual bearings, a novel deep learning-based rolling bearing remaining life prediction method is proposed in the absence of fully degraded bearng data. This method involves processing the raw vibration data through Channel-wise Attention Encoder (CAE) from the Encoder-Channel Attention (ECA), extracting features related to mutual correlation and relevance, selecting the desired characteristics, and incorporating the selected features into the constructed Autoformer-based time prediction model to forecast the degradation trend of bearings' remaining time. The feature extraction method proposed in this approach outperforms CAE and multilayer perceptual-Attention Encoder in terms of feature extraction capabilities, resulting in reductions of 0.0059 and 0.0402 in mean square error, respectively. Additionally, the indirect prediction approach for the degradation trend of the target bearing demonstrates higher accuracy compared to Informer and Transformer models, with mean square error reductions of 0.3352 and 0.1174, respectively. This suggests that the combined deep learning model proposed in this paper for predicting rolling bearing life may be a more effective life prediction method deserving further research and application.

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Traditional industries and industrialization have led to widespread environmental pollution and ecosystem degradation in major river basins globally. Strategies centered on ecological restoration and ecological economy are emerging as essential tools for effective environmental governance. This study aims to investigate how a multifaceted framework for land ecological consolidation, with various developmental goals, can effectively support ecological restoration and sustainability. Through quantitative analysis and in-depth interviews, we investigated the case of Yangtze riverside chemical industrial park in Changzhou. This park pursues ecological and economic sustainability through chemical industry transformation, ecological restoration and protection, ecological management, and ecological industry development. The results show that this practice established a multi-objective action framework rooted in urban renewal, land consolidation, ecological restoration, industrial transformation, and rural revitalization. Through multiplanning integration, integrated implementation and full-cycle profit distribution, the aim of ecological protection has been initially achieved, offering a crucial guarantee for sustainable development. A total of 96.47 ha ecological space expanded, which can generate ecological product worth CNY 7.283 billion, alongside a net economic benefit of CNY 978 million over three decades. The top-down ecological responsibilities, coupled with local developmental demands, have stimulated collaborations within a bottom-up endogenous network comprising government, enterprises, and residents.

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Abnormal cellular apoptosis plays a pivotal role in the pathogenesis of Multiple Myeloma (MM). Over the years, BCL-2, a crucial anti-apoptotic protein, has garnered significant attention in MM therapeutic research. Venetoclax (VTC), a small-molecule targeted agent, effectively inhibits BCL-2, promoting the programmed death of cancerous cells. While VTC has been employed to treat various hematological malignancies, its particular efficacy in MM has showcased its potential for broader clinical applications. In this review, we delve into the intricacies of how VTC modulates apoptosis in MM cells by targeting BCL-2 and the overarching influence of the BCL-2 protein family in MM apoptosis regulation. Our findings highlight the nuanced interplay between VTC, BCL-2, and MM, offering insights that may pave the way for optimizing therapeutic strategies. Through this comprehensive analysis, we aim to lay a solid groundwork for future explorations into VTC's clinical applications and the profound effects of BCL-2 on cellular apoptosis.