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This paper focuses on the decentralized finite-time prescribed performance control problem for a class of large-scale nonlinear interconnected systems with input dead zone using an adaptive fuzzy approach. Specifically, fuzzy logic systems are utilized to approximate unknown nonlinear system functions and a finite-time prescribed performance control scheme is designed by taking advantage of both the adaptive technique and backstepping scheme. By introducing two smooth functions and utilizing the command filter backstepping design, the ‘explosion of complexity’ problem inherent in the conventional backstepping control is overcome, while the associated problems due to unknown interconnections are solved. The proposed control scheme guarantees that all signals within the closed-loop controlled system are bounded and the output tracking error falls within a small range predefined by the prescribed performance within a finite time. Two simulation examples are given to verify the high effectiveness of the presented control approach.

As the operational status of aircraft engines evolves, their fault modes also undergo changes. In response to the operational degradation trend of aircraft engines, this paper proposes an aircraft engine fault diagnosis model based on 1DCNN-BiLSTM with CBAM. The model can be directly applied to raw monitoring data without the need for additional algorithms to extract fault degradation features. It fully leverages the advantages of 1DCNN in extracting local features along the spatial dimension and incorporates CBAM, a channel and spatial attention mechanism. CBAM could assign higher weights to features relevant to fault categories and make the model pay more attention to them. Subsequently, it utilizes BiLSTM to handle nonlinear time feature sequences and bidirectional contextual feature information. Finally, experimental validation is conducted on the publicly available CMAPSS dataset from NASA, categorizing fault modes into three types: faultless, HPC fault (the single fault), and HPC&Fan fault (the mixed fault). Comparative analysis with other models reveals that the proposed model has a higher classification accuracy, which is of practical significance in improving the reliability of aircraft engine operations and for Remaining Useful Life (RUL) prediction.

The rapid increase in household leverage in China has led to potential financial risks and threatened socio-economic stability. In mitigating household debt risks, the effectiveness of monetary policy regulation varies significantly with differences in household financial literacy. Based on micro-level household financial data from China, this paper delves into the impact of monetary policy on household leverage and its underlying mechanisms and analyzes the role of financial literacy in the transmission of monetary policy. The findings reveal that expansionary monetary policy helps reduce household leverage, while contractionary monetary policy leads to an increase. Monetary policy affects household leverage through the “income effect,”“wealth effect” and “substitution effect.” Notably, low financial literacy amplifies the impact of contractionary monetary policy on leverage, whereas high financial literacy mitigates this effect. This paper suggests strengthening financial regulation and risk warning systems, optimizing the design of monetary policy transmission, promoting multi-tiered financial product supply, and deepening the promotion of financial literacy education to achieve an effective balance between “stable growth” and “risk prevention.”

Fuel substrate switching between carbohydrates and fat is essential for maintaining metabolic homeostasis. During aerobic exercise, the predominant energy source gradually shifts from carbohydrates to fat. While it is well known that exercise mobilizes fat storage from adipose tissues, it remains largely obscure how circulating lipids are distributed tissue-specifically according to distinct energy requirements. Here, we demonstrate that aerobic exercise is linked to nutrient availability to regulate tissue-specific activities of lipoprotein lipase (LPL), the key enzyme catabolizing circulating triglyceride (TG) for tissue uptake, through the differential actions of angiopoietin-like (ANGPTL) proteins. Exercise reduced the tissue binding of ANGPTL3 protein, increasing LPL activity and TG uptake in the heart and skeletal muscle in the postprandial state specifically. Mechanistically, exercise suppressed insulin secretion, attenuating hepatic Angptl8 transcription through the PI3K/mTOR/CEBPα pathway, which is imperative for the tissue binding of its partner ANGPTL3. Constitutive expression of ANGPTL8 hampered lipid utilization and resulted in cardiac dysfunction in response to exercise. Conversely, exercise promoted the expression of ANGPTL4 in white adipose tissues, overriding the regulatory actions of ANGPTL8/ANGPTL3 in suppressing adipose LPL activity, thereby diverting circulating TG away from storage. Collectively, our findings show an overlooked bifurcated ANGPTL-LPL network that orchestrates fuel switching in response to aerobic exercise.

In this article, the problem of fuzzy adaptive fixed-time control is addressed for nonstrict-feedback nonlinear systems with input saturation and dead zone. The universal approximation properties of fuzzy logic systems are employed to model the unknown nonlinear functions. A command filter-based fixed-time adaptive fuzzy control strategy is presented based on the backstepping framework and fixed-time control theory. The command filter technique is presented to address the “computational explosion” problem inherent in the backstepping scheme, and an error compensation mechanism is adopted to reduce the errors arising from command filters. Meanwhile, the non-smooth input saturation and dead zone nonlinearities are approximated using a non-affine smooth function, and they are transformed into an affine form based on the mean-value theorem. The fixed-time convergence of the tracking error and the boundedness of the closed-loop signals are proved using the fixed-time stability theory. Finally, simulation was performed to demonstrate the effectiveness of the presented method.

In this article, the problem of adaptive fuzzy finite-time command filtered control is considered for a class of nonstrict-feedback nonlinear systems. The explosion of complexity problem is dealt with by employing the command filter approach. In order to design a finite-time control scheme, a finite-time semi-global practical stability criterion is first presented. Based on this criterion, by applying the command filter technology and backstepping technique, adaptive fuzzy finite-time tracking control scheme is developed with the help of fuzzy logic systems approximation. Under the presented adaptive control scheme, all the closed-loop variables are semi-global practical finite-time stable and the tracking error goes into an adjustable neighborhood around the origin in a finite time. Finally, simulations are utilized to verify the effectiveness of designed control scheme.

This research focuses on the issue of adaptive fuzzy fault-tolerant position tracking for permanent magnet synchronous motors (PMSMs) subject to finite-time prescribed performance. An improved finite-time prescribed performance control strategy, in which unknown nonlinear functions can be tackled via fuzzy logic systems (FLSs), is presented via incorporating the approach of prescribed performance control with the technique of command filter. In addition, the command filtered method is utilized to conquer the ‘explosion of complexity’ emerged in the classic backstepping method and the error compensation mechanism is adopted to diminish the error generated by filtering process. Further, the impact of actuator failures is dealt with based on fault-tolerant control. It is proven that the designed controllers not only assure the semi-global boundedness of all the controlled system signals, but also make the output tracking error is preserved in a specified prescribed performance within a finite-time interval. Finally, simulation results are supplied to display the significance and potential of the proposed control technique.

This research focuses on the issue of adaptive fuzzy fault-tolerant position tracking for permanent magnet synchronous motors (PMSMs) subject to finite-time prescribed performance. An improved finite-time prescribed performance control strategy, in which unknown nonlinear functions can be tackled via fuzzy logic systems (FLSs), is presented via incorporating the approach of prescribed performance control with the technique of command filter. In addition, the command filtered method is utilized to conquer the ‘explosion of complexity’ emerged in the classic backstepping method and the error compensation mechanism is adopted to diminish the error generated by filtering process. Further, the impact of actuator failures is dealt with based on fault-tolerant control. It is proven that the designed controllers not only assure the semi-global boundedness of all the controlled system signals, but also make the output tracking error is preserved in a specified prescribed performance within a finite-time interval. Finally, simulation results are supplied to display the significance and potential of the proposed control technique.

The focus of this research study investigated the impact of agroecosystem on the ecological footprint in Pakistan, using the time series data over the period from 1990 to 2019. The econometric methods of time series were employed to investigate the long-term association between an agroecosystem and ecological footprint. After performing the stationarity tests Johansen approach was employed. Results of the Johansen method imply that long-term co-integration exists between the exogenous and endogenous variables. Moreover, the ARDL model was performed and long-run results were validated by the bound testing approach. The elasticity of the short-run form of the ARDL model reveals that agricultural land, employment, energy consumption, fertilizer use, and biomass burned dry matter in agriculture have a positive relationship with the agroecosystem. In contrast in the log-run form of ARDL agricultural land, employment, energy consumption, fertilizer use in agriculture and temperature have a positive impact on ecological footprint. Results of the impulse response function revealed that employment and fertilizer use in agriculture have positive while energy consumption and livestock in number have a negative influence on the ecological footprint. Thus, rigorous practices of agriculture for higher production put extra pressure on the agroecosystem. As a result, the stability of the agroecosystem deteriorates and reduces. To minimize the ecological ecosystem, modern technology is required to reduce carbon emission, enhance greener production and improve the biocapacity of the land in the country. This study would help the researcher, planner, policymaker and academicians to provide a proper guideline and vision to provide sustainable food and environment. RESUMO: O foco deste estudo é investigar o impacto do agroecossistema na pegada ecológica no Paquistão, usando os dados de séries temporais no período de 1990 a 2019. Os métodos econométricos de séries temporais foram empregados para investigar a associação de longo prazo entre um agroecossistema e a pegada ecológica. Após a realização dos testes de estacionaridade, a abordagem de Johansen foi empregada. Os resultados do método de Johansen implicam que existe cointegração de longo prazo entre as variáveis exógenas e endógenas. Além disso, o modelo ARDL foi realizado e os resultados de longo prazo foram validados pela abordagem de teste vinculado. A elasticidade da forma de curto prazo do modelo ARDL revela que terras agrícolas, emprego, consumo de energia, uso de fertilizantes e biomassa queimada na agricultura têm uma relação positiva com o agroecossistema. Em contraste, na forma log-run das terras agrícolas ARDL, o emprego, o consumo de energia, o uso de fertilizantes na agricultura e a temperatura têm um impacto positivo na pegada ecológica. Os resultados da função impulso resposta revelam que o emprego e o uso de fertilizantes na agricultura são positivos enquanto o consumo de energia e a pecuária em número têm uma influência negativa na pegada ecológica. Assim, práticas rigorosas de agricultura para maior produção colocam uma pressão extra sobre o agroecossistema. Como resultado, a estabilidade do agroecossistema se deteriora e reduz. Para minimizar o ecossistema ecológico, é necessária tecnologia moderna para reduzir a emissão de carbono, aumentar a produção mais verde e melhorar a biocapacidade da terra no país. Este estudo ajudaria o pesquisador, planejador, formulador de políticas e acadêmicos a ter uma orientação e visão adequadas para fornecer alimentos e meio ambiente sustentáveis.

Alzheimer’s disease (AD) is the most common progressive neurodegenerative disease. The accumulation of amyloid-beta (Aβ) plaques is a distinctive pathological feature of AD patients. The aims of this study were to evaluate the therapeutic effect of chicoric acid (CA) on AD models and to explore its underlying mechanisms. APPswe/Ind SH-SY5Y cells and 5xFAD mice were treated with CA. Soluble Aβ1–42 and Aβ plaque levels were analyzed by ELISA and immunohistochemistry, respectively. Transcriptome sequencing was used to compare the changes in hippocampal gene expression profiles among the 5xFAD mouse groups. The specific gene expression levels were quantified by qRT-PCR and Western blot analysis. It was found that CA treatment reduced the Aβ1–42 levels in the APPswe/Ind cells and 5xFAD mice. It also reduced the Aβ plaque levels as well as the APP and BACE1 levels. Transcriptome analysis showed that CA affected the synaptic-plasticity-related genes in the 5xFAD mice. The levels of L1CAM, PSD-95 and synaptophysin were increased in the APPswe/Ind SH-SY5Y cells and 5xFAD mice treated with CA, which could be inhibited by administering siRNA-L1CAM to the CA-treated APPswe/Ind SH-SY5Y cells. In summary, CA reduced Aβ levels and increased the expression levels of synaptic-function-related markers via L1CAM in AD models.