Resolving natural organic matter and nanoplastics in binary or ternary systems via UV-Vis analysis.

Nanoplastics (NPs) and natural organic matter (NOM) are ubiquitous and usually present simultaneously in the environment. Both NPs and NOM can be adsorbed to minerals such as iron-(hydr)oxides, with such interactions being important for controlling their fate in the environment. However, the quantification of NPs and NOM in mixtures remains challenging even under controlled conditions in laboratory studies. In this research, a UV-Vis method was established to quantify concentrations of NOM, such as humic acid (HA) and fulvic acid (FA), and polystyrene NPs (PSNPs) in mixtures. In addition, both original NOM samples and those recovered following adsorptive fractionation using an iron oxide (goethite, α-FeOOH) were mixed separately with PSNPs and their concentrations were further calculated via the developed UV-Vis method. The UV-Vis method performed well (recovery of 100 ± 16 %) with original NOM and PSNPs system at detection limits of 20.8 and 7.4 mgC L-1, respectively. Particularly, for original FA and PSNPs systems with carboxylic groups (PSNPs-COOH, 200 nm), a similar recovery rate could be obtained at detection limits of only 2.5 and 1.9 mgC L-1, respectively. For fractionated NOM and PSNPs systems, detection limits (31.2 mgC L-1 and 27.5 mgC L-1, respectively) are increased to reach the same accuracy. Furthermore, the UV-Vis method can be used to estimate the proportion of HA that is adsorbed to PSNPs. The relative errors are < 13.7 % when the mass ratios of PSNPs and HA was between 1.6:1 and 8:1 and HA concentration was higher than 4.6 mgC L-1. This method developed can be applied to future laboratory research to investigate the interaction between NOM, NPs, and minerals.

HHI-AttentionNet: An Enhanced Human-Human Interaction Recognition Method Based on a Lightweight Deep Learning Model with Attention Network from CSI.

Nowadays WiFi based human activity recognition (WiFi-HAR) has gained much attraction in an indoor environment due to its various benefits, including privacy and security, device free sensing, and cost-effectiveness. Recognition of human-human interactions (HHIs) using channel state information (CSI) signals is still challenging. Although some deep learning (DL) based architectures have been proposed in this regard, most of them suffer from limited recognition accuracy and are unable to support low computation resource devices due to having a large number of model parameters. To address these issues, we propose a dynamic method using a lightweight DL model (HHI-AttentionNet) to automatically recognize HHIs, which significantly reduces the parameters with increased recognition accuracy. In addition, we present an Antenna-Frame-Subcarrier Attention Mechanism (AFSAM) in our model that enhances the representational capability to recognize HHIs correctly. As a result, the HHI-AttentionNet model focuses on the most significant features, ignoring the irrelevant features, and reduces the impact of the complexity on the CSI signal. We evaluated the performance of the proposed HHI-AttentionNet model on a publicly available CSI-based HHI dataset collected from 40 individual pairs of subjects who performed 13 different HHIs. Its performance is also compared with other existing methods. These proved that the HHI-AttentionNet is the best model providing an average accuracy, F1 score, Cohen's Kappa, and Matthews correlation coefficient of 95.47%, 95.45%, 0.951%, and 0.950%, respectively, for recognition of 13 HHIs. It outperforms the best existing model's accuracy by more than 4%.

Anti-inflammatory effects of hydroxycinnamic acid derivatives.

NF-kappaB family of transcription factors are involved in numerous cellular processes, including differentiation, proliferation, and inflammation. It was reported that hydroxycinnamic acid derivatives (HADs) are inhibitors of NF-kappaB activation. Rice bran oil contains a lot of phytosteryl ferulates, one of HADs. We have investigated effects of phytosteryl ferulates on NF-kappaB activation in macrophage. Cycloartenyl ferulate (CAF), one of phytosteryl ferulates, significantly reduced lipopolysaccharide (LPS)-induced NO production and mRNA expression of inducible NO synthase and cyclooxygenese-2 but upregulated SOD activity. Electrophoresis mobility shift assay revealed that CAF inhibited DNA-binding of NF-kappaB. CAF and phytosteryl ferulates probably have potentially anti-inflammatory properties.