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In this paper, we address the state/fault estimation and observer-based control issues for switched systems with sensor faults. The main objective is to estimate sensor faults and compensate for their effects on the system state estimation, and then stabilize the switched system by the estimated state feedback. Applying the mode-dependent average dwell time (MDADT) concept and the Lyapunov stability theory, a new separation principle is developed, which allows formalizing the observer-based controller design in the form of linear matrix inequalities (LMI) instead of bilinear ones. Finally, a highly manoeuvrable aircraft technology (HiMAT) example, a DC-DC boost converter example, and a numerical example are investigated to show the practicability and efficiency of the obtained results.
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http://dx.doi.org/10.1016/j.isatra.2020.12.005 | DOI Listing |
ACS Synth Biol
September 2025
School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85281, United States.
Cellular resource limitations create unintended interactions among synthetic gene circuit modules, compromising circuit modularity. This challenge is particularly pronounced in circuits with positive feedback, where uneven resource allocation can lead to Winner-Takes-All (WTA) behavior, favoring one module at the expense of others. In this study, we experimentally implemented a Negatively Competitive Regulatory (NCR) controller using CRISPR interference (CRISPRi) and evaluated its effectiveness in mitigating WTA behavior in two gene circuits: dual self-activation and cascading bistable switch.
View Article and Find Full Text PDFmBio
September 2025
Department of Microbiology, Oregon State University, Corvallis, Oregon, USA.
Quorum sensing (QS) is a widespread signaling mechanism in bacteria that coordinates collective behaviors according to population density. A foundational assumption in this field is that QS functions as a gene expression switch that synchronizes responses at the population level. While some studies indeed report homogeneous on/off transitions, others report heterogeneity at the cellular level, challenging the canonical view.
View Article and Find Full Text PDFJ Mater Chem B
September 2025
Department of Chemistry, Indian Institute of Technology Ropar, Rupnagar, Punjab 140001, India.
The unregulated use and improper disposal of active pharmaceutical ingredients (APIs), particularly phenylbutazone (PBZ), are contaminating water resources and posing serious risks to the food chain. PBZ is a nonsteroidal anti-inflammatory drug (NSAID) commonly used for treating pain and fever in animals, and its persistence in the environment due to inadequate waste management has become a cause of concern. To address this, we report the fabrication of benzimidazole-based self-assembled nanomicelles (R2 NMs) for selective detection and removal of PBZ.
View Article and Find Full Text PDFAdv Mater
September 2025
Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electronic and Information Engineering, Hebei University, Baoding, 071002, China.
Neuromorphic Visual Devices hold considerable promise for integration into neuromorphic vision systems that combine sensing, memory, and computing. This potential arises from their synergistic benefits in optical signal detection and neuro-inspired computational processes. However, current devices face challenges such as insufficient light/dark resistance ratios, mismatched transient photo-response, and volatile retention characteristics, limiting their adaptability to complex artificial vision systems.
View Article and Find Full Text PDFPatterns (N Y)
July 2025
Department of Methodology and Statistics, Faculty of Social and Behavioral Sciences, Utrecht University, Utrecht, the Netherlands.
ASReview LAB v.2 introduces an advancement in AI-assisted systematic reviewing by enabling collaborative screening with multiple experts ("a crowd of oracles") using a shared AI model. The platform supports multiple AI agents within the same project, allowing users to switch between fast general-purpose models and domain-specific, semantic, or multilingual transformer models.
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