Particle-Filter-Based Fault Diagnosis for the Startup Process of an Open-Cycle Liquid-Propellant Rocket Engine.

This study introduces a fault diagnosis algorithm based on particle filtering for open-cycle liquid-propellant rocket engines (LPREs). The algorithm serves as a model-based method for the startup process, accounting for more than 30% of engine failures. Similar to the previous fault detection and diagnosis (FDD) algorithm for the startup process, the algorithm in this study is composed of a nonlinear filter to generate residuals, a residual analysis, and a multiple-model (MM) approach to detect and diagnose faults from the residuals. In contrast to the previous study, this study makes use of the modified cumulative sum (CUSUM) algorithm, widely used in change-detection monitoring, and a particle filter (PF), which is theoretically the most accurate nonlinear filter. The algorithm is confirmed numerically using the CUSUM and MM methods. Subsequently, the FDD algorithm is compared with an algorithm from a previous study using a Monte Carlo simulation. Through a comparative analysis of algorithmic performance, this study demonstrates that the current PF-based FDD algorithm outperforms the algorithm based on other nonlinear filters.

Assessing the role of cold front passage and synoptic patterns on air pollution in the Korean Peninsula.

Various numerical experiments using WRF (Weather Research & Forecasting Model) and CMAQ (Community Multiscale Air Quality Modeling System) were performed to analyze the phenomenon of rapidly high concentration PM2.5 after the passage of a cold front in an area with limited local emissions. The episode period was from January 14 to 23, 2018, and analysis was conducted by dividing it into two stages according to the characteristics of changes in PM2.5 concentrations during the period. Through the analysis of observational data during the episode period, we confirmed meteorological impacts (decrease in temperature, increase in wind speed and relative humidity) and an increase in air pollution (PM10 and PM2.5) attributed to the passage of a cold front. Using CMAQ's IPR (Integrated Process Rate) analysis, the contribution of the horizontal advection process was observed in transporting PM2.5 to Gangneung at higher altitudes, and the PM2.5 concentrations at the surface increased because the vertical advection process was influenced by the terrain. Notably, in Stage 2 (64 µg·m-3), a higher contribution of the vertical advection process compared to Stage 1 (35 µg·m-3) was observed, which is attributed to the differences in synoptic patterns following the passage of the cold front. During Stage 2, following the cold front, atmospheric stability (dominance of high-pressure system) led to air subsidence and the presence of a temperature inversion layer, creating favorable meteorological conditions for the accumulation of air pollutants. This study offers the mechanisms of air pollution over the Korean Peninsula under non-stationary meteorological conditions, particularly in relation to the passage of the cold front (low-pressure system). Notably, the influence of a cold front can vary according to the synoptic patterns that develop following its passage.

Neuronal differentiation drives the antitumor activity of mitogen-activated protein kinase kinase (MEK) inhibition in glioblastoma.

Background: Epidermal growth factor receptor (EGFR) amplification is found in nearly 40%-50% of glioblastoma cases. Several EGFR inhibitors have been tested in glioblastoma but have failed to demonstrate long-term therapeutic benefit, presumably because of acquired resistance. Targeting EGFR downstream signaling with mitogen-activated protein kinase kinase 1 and 2 (MEK1/2) inhibitors would be a more effective approach to glioblastoma treatment. We tested the therapeutic potential of MEK1/2 inhibitors in glioblastoma using 3D cultures of glioma stem-like cells (GSCs) and mouse models of glioblastoma. Methods: Several MEK inhibitors were screened in an unbiased high-throughput platform using GSCs. Cell death was evaluated using flow cytometry and Western blotting (WB) analysis. RNA-seq, real-time quantitative polymerase chain reaction, immunofluorescence, and WB analysis were used to identify and validate neuronal differentiation. Results: Unbiased screening of multiple MEK inhibitors in GSCs showed antiproliferative and apoptotic cell death in sensitive cell lines. An RNA-seq analysis of cells treated with trametinib, a potent MEK inhibitor, revealed upregulation of neurogenesis and neuronal differentiation genes, such as achaete-scute homolog 1 (ASCL1), delta-like 3 (DLL3), and neurogenic differentiation 4 (NeuroD4). We validated the neuronal differentiation phenotypes in vitro and in vivo using selected differentiation markers (ß-III-tubulin, ASCL1, DLL3, and NeuroD4). Oral treatment with trametinib in an orthotopic GSC xenograft model significantly improved animal survival, with 25%-30% of mice being long-term survivors. Conclusions: Our findings demonstrated that MEK1/2 inhibition promotes neuronal differentiation in glioblastoma, a potential additional mechanism of action of MEK1/2 inhibitors. Thus, MEK inhibitors could be efficacious in glioblastoma patients with activated EGFR/MAPK signaling.