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In this work, we investigate how radio frequency heating of admixture of catalyst and RF susceptor can drive the propane dehydrogenation reaction, enabling distributed chemical manufacturing based on electric power rather than fossil fuel heating. 

Abstract This experimental study investigates fault detection and estimation in a continuous stirred‐tank reactor (CSTR) system under closed‐loop feedback control, including an analysis of different manipulative inputs for temperature regulation. A novel fault diagnosis approach is proposed, combining residual signal analysis andT²statistic for real‐time fault detection and size estimation. The closed‐loop system demonstrated robust setpoint tracking and fault tolerance across a range of fault magnitudes. Residual signals serve as direct estimators of fault size, critical for adaptive control, while theT²statistic enhances reliability by identifying deviations from normal behavior with fault‐confidence thresholds. As a step towards fault‐tolerant control, the proposed methodology lays the groundwork for advanced control strategies that can ensure safe and efficient operation of chemical reactor systems. 

Abstract This article presents an experimental application of fault detection, isolation, and estimation in a chemical reactor system, introducing a functional observer‐based approach without the need for linear approximation. The residual signal generators, functioning as disturbance‐decoupled functional observers, provide fault size estimates and enable fault isolation through multiple generators operating independently. The experimental study focuses on the 3‐Picoline oxidation process, deriving a discrete‐time model, and constructing specific residual generators for coolant inlet temperature and feed concentration faults. Fault diagnosis employs Fast Fourier Transform (FFT) filtering and Generalized Likelihood Ratio (GLR), facilitating on‐the‐fly detection during the experiment. The effectiveness of fault detection, disturbance decoupling, and estimation is experimentally validated. 

Understanding the genomic and environmental basis of cold adaptation is key to understand how plants survive and adapt to different environmental conditions across their natural range. Univariate and multivariate genome-wide association (GWAS) and genotype-environment association (GEA) analyses were used to test associations among genome-wide SNPs obtained from whole-genome resequencing, measures of growth, phenology, emergence, cold hardiness, and range-wide environmental variation in coastal Douglas-fir (Pseudotsuga menziesii). Results suggest a complex genomic architecture of cold adaptation, in which traits are either highly polygenic or controlled by both large and small effect genes. Newly discovered associations for cold adaptation in Douglas-fir included 130 genes involved in many important biological functions such as primary and secondary metabolism, growth and reproductive development, transcription regulation, stress and signaling, and DNA processes. These genes were related to growth, phenology and cold hardiness and strongly depend on variation in environmental variables such degree days below 0c, precipitation, elevation and distance from the coast. This study is a step forward in our understanding of the complex interconnection between environment and genomics and their role in cold-associated trait variation in boreal tree species, providing a baseline for the species’ predictions under climate change.