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As the focus of space exploration has recently shifted from national efforts to private enterprises, interest in the space industry has increased. With the rising number of satellite launches, the risk of collisions between satellites and between satellites and space debris has grown, which can lead not only to property damage but also casualties caused by the debris. To address this issue, various machine learning and deep learning-based methods have been researched to improve the accuracy of satellite orbit prediction and mitigate these risks. However, most studies have applied basic machine learning models to orbit prediction without considering the model size and execution time, even though satellite operations require lightweight models that offer both a strong prediction performance and rapid execution. In this study, we propose a time series forecasting framework, the Lightweight Transformer Encoder (LTE), for satellite orbit prediction. The LTE is a prediction model that modifies the encoder structure of the Transformer model to enhance the accuracy of satellite orbit prediction and reduce the computational resources used. To evaluate its performance, we conducted experiments using about 4.8 million data points collected every minute from January 2016 to December 2018 by the KOMPSAT-3, KOMPSAT-3A, and KOMPSAT-5 satellites, which are part of the Korea Multi-Purpose Satellite (KOMPSAT) series operated by the Korea Aerospace Research Institute (KARI). We compare the performance of our model against various baseline models in terms of prediction error, execution time, and the number of parameters used. Our LTE model demonstrates significant improvements: it reduces the orbit prediction error by 50.61% in the KOMPSAT-3 dataset, 42.40% in the KOMPSAT-3A dataset, and 30.00% in the KOMPSAT-5 dataset compared to the next-best-performing model. Additionally, in the KOMPSAT-3 dataset, it decreases the execution time by 36.86% (from 1731 to 1093 s) and lowers the number of parameters by 2.33% compared to the next-best-performing model. [ABSTRACT FROM AUTHOR]

This study aims to investigate left- and right-side merging sections on urban underground roads based on virtual reality driving simulator experiments. The behaviors investigated were changed by acceleration lane in the merging section, including 100, 120, and 140 m, considering current design guidelines. Typically, lane changing behavior was studied based on experiments using speed and lateral placement on driving. The behavior of more speed reduction in merging sections occurred in left-side merging than in right-side merging sections. In the left-side merging sections, speed reduction and acceleration rate decreased with the length of the acceleration lane. In the cases with relatively long acceleration lanes, lane changing locations for left-side merging sections were more sensitive than those of right-side merging sections. Some results from the driving simulator experiments show that road geometric design based on left-side merging sections might have more risk situations due to driver expectation and behaviors. This article provides technical knowledge to be applied to the acceleration lanes of left-side merging sections that extend 1.4 times longer than the usual road designs. [ABSTRACT FROM AUTHOR]

Allergic asthma is a type 2 immune-response-mediated chronic respiratory disease. Mast cell activation influences the pathogenesis and exacerbation of allergic asthma. Therefore, the development of mast cell-targeting pharmacotherapy is important for managing allergic airway inflammation. We investigated the efficacy of hispidulin (HPD), natural flavone, in a mast-cell-mediated ovalbumin (OVA)-induced allergic airway inflammation model. HPD alleviated symptoms of allergic asthma and decreased the levels of immunoglobulin (Ig) E, type 2 inflammation, immune cell infiltration, and mast cell activation in the lung. Furthermore, in vivo analysis confirmed the efficacy of HPD through the evaluation of IgE-mediated allergic responses in a mast cell line. HPD treatment inhibited mast cell degranulation through inhibition of the FcεR1 signaling pathway and suppressed the expression of inflammatory cytokines (TNF-α, IL-4, IL-6, and IL-13) through suppression of the NF-κB signaling pathway. The antioxidant effects of HPD in activated mast cells were identified through modulation of antioxidant enzymes and the Nrf2/HO-1 signaling pathway. In conclusion, HPD may be a potential therapeutic candidate for allergic airway inflammation of asthma and acts by suppressing mast cell activation and oxidative stress. [ABSTRACT FROM AUTHOR]

Cisplatin is a widely used anti-cancer drug for treating solid tumors, but it is associated with severe side effects, including nephrotoxicity. Various studies have suggested that the nephrotoxicity of cisplatin could be overcome; nonetheless, an effective adjuvant drug has not yet been established. Oleanolic acid acetate (OAA), a triterpenoid isolated from Vigna angularis, is commonly used to treat inflammatory and allergic diseases. This study aimed to investigate the protective effects of OAA against cisplatin-induced apoptosis and necroptosis using TCMK-1 cells and a mouse model. In cisplatin-treated TCMK-1 cells, OAA treatment significantly reduced Bax and cleaved-caspase3 expression, whereas it increased Bcl-2 expression. Moreover, in a cisplatin-induced kidney injury mouse model, OAA treatment alleviated weight loss in the body and major organs and also relieved cisplatin-induced nephrotoxicity symptoms. RNA sequencing analysis of kidney tissues identified lipocalin-2 as the most upregulated gene by cisplatin. Additionally, necroptosis-related genes such as receptor-interacting protein kinase (RIPK) and mixed lineage kinase domain-like (MLKL) were identified. In an in vitro study, the phosphorylation of RIPKs and MLKL was reduced by OAA pretreatment in both cisplatin-treated cells and cells boosted via co-treatment with z-VAD-FMK. In conclusion, OAA could protect the kidney from cisplatin-induced nephrotoxicity and may serve as an anti-cancer adjuvant. [ABSTRACT FROM AUTHOR]

Inflammatory bowel disease (IBD), a chronic disorder affecting the colon and rectum, involves the overproduction of pro-inflammatory cytokines causing damage to tight junctions (TJ) in the intestinal epithelial cells and chronic inflammation. The current mainstay of treatment, sulfasalazine, often causes adverse effects, thereby necessitating the exploration of alternative herbal medicines with fewer side effects. Portulaca oleracea L. (P. oleracea), a traditional medicinal herb, contains feruloyl amide compounds. We synthesized new compounds by conjugating ferulic acid (FA) with (±)-octopamine. Our study focused on novel FA derivatives that demonstrate protective effects against the intestinal epithelial barrier and inflammatory responses. In lipopolysaccharide-induced cells, C1 and C1a inhibited the production of inflammatory mediators. In Caco-2 cells, these compounds maintained the TJ protein expression, thereby demonstrating their protective effects on the epithelial barrier. In a mouse model of dextran sulfate sodium-induced IBD, a treatment with these compounds ameliorated features including a body weight reduction, colon shortening, an increased disease activity index, and histopathological changes. Furthermore, C1a demonstrated greater efficacy than C1 at the same concentration. These findings suggest that the novel FA derivative (C1a) effectively alleviates clinical signs and inflammatory mediators in IBD, making these compounds potential candidates as natural medicines for the treatment of IBD. [ABSTRACT FROM AUTHOR]

Using Chebyshev's sum inequality, we generalize E[X2] ≥ E2[X] into a moment inequality with a general combination of moments that compares E[Xr+s] and E[Xr]E[Xs]. We also provide its economic application. [ABSTRACT FROM AUTHOR]

We propose an empirical method to analyze data from first-price procurements where bidders are asymmetric in their risk-aversion (CRRA) coefficients and distributions of private costs. Our Bayesian approach evaluates the likelihood by solving type-symmetric equilibria using the boundary-value method and integrates out unobserved heterogeneity through data augmentation. We study a new dataset from Russian government procurements focusing on the category of printing papers. We find that there is no unobserved heterogeneity (presumably because the job is routine), but bidders are highly asymmetric in their cost and risk-aversion. Our counterfactual study shows that choosing a type-specific cost-minimizing reserve price marginally reduces the procurement cost; however, inviting one more bidder substantially reduces the cost, by at least 5.5%. Furthermore, incorrectly imposing risk-neutrality would severely mislead inference and policy recommendations, but the bias from imposing homogeneity in risk-aversion is small. [ABSTRACT FROM AUTHOR]