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This paper is concerned with the problem of controller design for switched systems under asynchronous switching with exogenous disturbances. The attention is focused on designing the feedback controller that guarantees the finite-time bounded and L∞ finite-time stability of the dynamic system. Firstly, when there exists asynchronous switching between the controller and the system, a sufficient condition for the existence of stabilizing switching law for the addressed switched system is derived. It is proved that the switched system is finite-time stabilizable under asynchronous switching satisfying the average dwell-time condition. Furthermore, the problem of L∞ control for switched systems under asynchronous switching is also investigated. Finally, a numerical example is given to illustrate the effectiveness of the proposed method

Robust H∞ switching rule design for Boost converters with uncertain parameters and disturbances

Pubished version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2013/120543 Open accessThis paper is concerned with the design problem of robust H∞ switching rule for Boost converters with uncertain parameters and disturbances. Firstly, the Boost converter is modeled as a switched affine linear system with uncertain parameters and disturbances. Then, using common Lyapunov function approach and linear matrix inequality (LMI) technique, a novel switching rule is proposed such that the H∞ model reference tracking performance is satisfied. Finally, a simulation result is provided to show the validity of the proposed method

Upregulation of SMAD4 inhibits thyroid cancer cell growth via MAPK/JNK pathway repression

Purpose: To investigate whether the effect of mothers against decapentaplegic homolog 4 (SMAD4) on thyroid cancer cell survival was via the MAPK/JNK pathway. Methods: Papillary thyroid cancer (TPC)-1 cells were cultured and transfected with SMAD4 overexpression plasmid or siRNA to achieve SMAD4 overexpression or knockdown, respectively. In TPC-1 cells, the mRNA and protein expression levels of SMAD4, mitogen-activated protein kinase (MAPK), and c-Jun N-terminal kinase (JNK) were quantified using reverse transcription-quantitative polymerase chain reaction and western blotting, respectively. Cell viability and apoptosis were measured using MTT assay and flow cytometry, respectively. MAPK and JNK inhibitors (U0126 and SP600125) were used for rescue experiments. The sensitivity of TPC-1 cells to chemotherapeutic drugs, cisplatin and doxorubicin, was also assessed. Results: A reduction in viability and an enhancement in apoptosis (p < 0.01) were found when SMAD4 was overexpressed in TPC-1 cells. Knockdown of SMAD4 elicited opposite results (p < 0.01). Overexpression of SMAD4 caused a decrease in the activation of MAPK and JNK, as evidenced by lower levels of phosphorylated MAPK and phosphorylated JNK (p < 0.05). Results from rescue experiments indicate that the increase in cell viability after SMAD4 knockdown was reversed by MAPK/JNK inhibitors (p < 0.05 and p < 0.01). Finally, overexpression of SMAD4 increased cytotoxic susceptibility of thyroid cancer cells to cisplatin/doxorubicin. Conclusion: These results indicate that SMAD4 inhibits thyroid cancer cell growth via inactivation of MAPK/JNK pathway. Overexpression of SMAD4 also increased thyroid cancer cell sensitivity to cisplatin/doxorubicin

The progress of research on the application of redox nanomaterials in disease therapy

Redox imbalance can trigger cell dysfunction and damage and plays a vital role in the origin and progression of many diseases. Maintaining the balance between oxidants and antioxidants in vivo is a complicated and arduous task, leading to ongoing research into the construction of redox nanomaterials. Nanodrug platforms with redox characteristics can not only reduce the adverse effects of oxidative stress on tissues by removing excess oxidants from the body but also have multienzyme-like activity, which can play a cytotoxic role in tumor tissues through the catalytic oxidation of their substrates to produce harmful reactive oxygen species such as hydroxyl radicals. In this review, various redox nanomaterials currently used in disease therapy are discussed, emphasizing the treatment methods and their applications in tumors and other human tissues. Finally, the limitations of the current clinical application of redox nanomaterials are considered

Personalized Federated Deep Reinforcement Learning-based Trajectory Optimization for Multi-UAV Assisted Edge Computing

In the era of 5G mobile communication, there has been a significant surge in research focused on unmanned aerial vehicles (UAVs) and mobile edge computing technology. UAVs can serve as intelligent servers in edge computing environments, optimizing their flight trajectories to maximize communication system throughput. Deep reinforcement learning (DRL)-based trajectory optimization algorithms may suffer from poor training performance due to intricate terrain features and inadequate training data. To overcome this limitation, some studies have proposed leveraging federated learning (FL) to mitigate the data isolation problem and expedite convergence. Nevertheless, the efficacy of global FL models can be negatively impacted by the high heterogeneity of local data, which could potentially impede the training process and even compromise the performance of local agents. This work proposes a novel solution to address these challenges, namely personalized federated deep reinforcement learning (PF-DRL), for multi-UAV trajectory optimization. PF-DRL aims to develop individualized models for each agent to address the data scarcity issue and mitigate the negative impact of data heterogeneity. Simulation results demonstrate that the proposed algorithm achieves superior training performance with faster convergence rates, and improves service quality compared to other DRL-based approaches

Clinical outcomes of S2 Alar-Iliac screw technique in the treatment of severe spinal sagittal imbalance: a retrospective 2-year follow-up study

Background: The treatment of adult spinal deformity (ASD) remains a significant challenge, especially in elderly patients. This study aimed to evaluate the outcomes of the S2AI screw technique in the treatment of severe spinal sagittal imbalance with a minimum 2-year follow-up.Methods: From January 2015 to December 2018, 23 patients with severe degenerative thoracolumbar kyphosis who underwent placement of S2AI screws for long segment fusion were retrospectively reviewed. Patients were divided into group A (no mechanical complications, 13 cases) and group B (with mechanical complications, 10 cases) according to the occurrence of mechanical complications at the last follow-up. Radiographic parameters were compared between groups preoperatively, 1 month postoperatively and at the last follow-up. Risk factors for mechanical complications were analyzed.Results: The incidence of mechanical complications was 43.5% and the revision rate was 17.4%. At 1 month postoperatively, sagittal correction was better in group A than in group B (p<0.05). The area under the curve for predicting mechanical complications of sacral slope (SS), lumbar lordosis (LL), PI (pelvic incidence)-LL at 1 month postoperatively were 0.762 (p=0.035), 0.896 (p=0.001) and 0.754 (p=0.041) respectively and the best cut-off values were 24.1°, 32.8°and 12.0°. The sagittal correction of both groups was partially lost at the last follow-up.Conclusions: A high incidence of mechanical complications was observed in long-segment corrective surgery with the S2AI screw technique for severe spinal sagittal imbalance. Inadequate sagittal correction is a risk factor for the development of mechanical complications.

Economic freedom, inclusive growth, and financial development : a heterogeneous panel analysis of developing countries

The effective and efficient management of financial systems and resources fosters a socioeconomic climate conducive to technological and innovative advancement, thereby fostering long-term economic growth. The study used panel data from 72 countries classified as less financially developed between 2009 and 2017 to examine the role of economic freedom and inclusive growth in financial development. For the long-run estimations, we utilised the linear dynamic panel GMM-IV estimator, panel corrected standard errors (PCSE) linear regression method, and contemporaneous correlation estimator, a generalised least squares method. Our analyses indicate that economic liberty, inclusive growth, and capital stock significantly contribute to financial development in a positive manner. Moreover, inclusive growth contributes positively to overall financial development by enhancing economic freedom. Regardless of exogenous and endogenous shocks, we found that the tax burden and investment freedom are negative drivers of financial development as measured by the overall financial development index. In contrast, protection of property rights, government spending, monetary freedom, and financial freedom are positive and significant drivers of economic growth