EEG-DG: A Multi-Source Domain Generalization Framework for Motor Imagery EEG Classification.

Motor imagery EEG classification plays a crucial role in non-invasive Brain-Computer Interface (BCI) research. However, the performance of classification is affected by the non-stationarity and individual variations of EEG signals. Simply pooling EEG data with different statistical distributions to train a classification model can severely degrade the generalization performance. To address this issue, the existing methods primarily focus on domain adaptation, which requires access to the test data during training. This is unrealistic and impractical in many EEG application scenarios. In this paper, we propose a novel multi-source domain generalization framework called EEG-DG, which leverages multiple source domains with different statistical distributions to build generalizable models on unseen target EEG data. We optimize both the marginal and conditional distributions to ensure the stability of the joint distribution across source domains and extend it to a multi-source domain generalization framework to achieve domain-invariant feature representation, thereby alleviating calibration efforts. Systematic experiments conducted on a simulative dataset, BCI competition IV 2a, 2b, and OpenBMI datasets, demonstrate the superiority and competitive performance of our proposed framework over other state-of-the-art methods. Specifically, EEG-DG achieves average classification accuracies of 81.79% and 87.12% on datasets IV-2a and IV-2b, respectively, and 78.37% and 76.94% for inter-session and inter-subject evaluations on dataset OpenBMI, which even outperforms some domain adaptation methods. Our code is available at https://github.com/zxchit2022/EEG-DG for evaluation.

A deep domain adaptation framework with correlation alignment for EEG-based motor imagery classification.

It is impractical to collect sufficient and well-labeled EEG data in Brain-computer interface because of the time-consuming data acquisition and costly annotation. Conventional classification methods reusing EEG data from different subjects and time periods (across domains) significantly decrease the classification accuracy of motor imagery. In this paper, we propose a deep domain adaptation framework with correlation alignment (DDAF-CORAL) to solve the problem of distribution divergence for motor imagery classification across domains. Specifically, a two-stage framework is adopted to extract deep features for raw EEG data. The distribution divergence caused by subjected-related and time-related variations is further minimized by aligning the covariance of the source and target EEG feature distributions. Finally, the classification loss and adaptation loss are optimized simultaneously to achieve sufficient discriminative classification performance and low feature distribution divergence. Extensive experiments on three EEG datasets demonstrate that our proposed method can effectively reduce the distribution divergence between the source and target EEG data. The results show that our proposed method delivers outperformance (an average classification accuracy of 92.9% for within-session, an average kappa value of 0.761 for cross-session, and an average classification accuracy of 83.3% for cross-subject) in two-class classification tasks compared to other state-of-the-art methods.

Leaching of di-2-ethylhexyl phthalate from biodegradable and conventional microplastics and the potential risks.

There has been a growing concern about plastic pollution, both from a health and ecological perspective. One of the major concerns with plastic debris, especially microplastics (MPs) relates to their strong potential for releasing additives and chemicals. Di-2-ethylhexyl phthalate (DEHP) is a common plastic additive widely used as plasticizer in plastic products, and is of global concern due to its widespread contamination in the environment. In this study, two conventional nondegradable plastics (polyethylene (PE) bags and PE mulch) and two biodegradable plastics (poly(butylene adipate co-terephtalate)-starch-based-polylactic acid bags (PBAT/PLA bags) and PLA mulch) were selected to investigate the release of DEHP to seawater. The results showed that leaching potentials of DEHP from different types of MPs varied. Among the four selected MPs, PE mulch had the highest leaching potential (6.88 µg/g), followed by PE bags (4.24 µg/g), PLA mulch (1.10 µg/g) and PBAT/PLA bags (0.89 µg/g). The DEHP leaching kinetic curves of the four MPs were all in line with the pseudo first order model. The potential risk of environmental and human exposure to the leached DEHP was assessed using the average Phthalate Pollution Index (PPI). The calculated PPI indicated low pollution risks of DEHP released by the four MPs in seawater.

Micro- and nanoplastics released from biodegradable and conventional plastics during degradation: Formation, aging factors, and toxicity.

The use of biodegradable plastics may solve the pollution caused by conventional plastics in the future. However, microplastics and nanoplastics are produced during the aging process of biodegradable plastics. This work evaluated the formation of secondary microplastics and nanoplastics and the effects of aging factors (UV radiation and mechanical forces) during the degradation processes of various biodegradable plastics (poly(butylene adipate co-terephtalate) (PBAT), poly(butylene succinate) (PBS), and polylactic acid (PLA)) and conventional plastics (polyethylene (PE), polystyrene (PS), and polyvinyl chloride (PVC)). This study also assessed the combined toxicity of secondary microplastics and Triclosan (TCS) on Tigriopus japonicas. The results showed that PLA and PBS could produce many microplastics. Most secondary microplastics were smaller than 50 µm. Primary pellets were more likely to generate microplastics through mechanical degradation than via photooxidation. In contrast, PBAT/PLA and PE bags were more likely to form microplastics through photooxidation than mechanical degradation. The secondary microplastics did not affect the survival of T. japonicas and the toxicity of TCS. This study highlights that risk assessment of biodegradable plastics, especially secondary microplastics, and nanoplastics, should be assessed in future studies.

Efficient Coagulation Removal of Fluoride Using Lanthanum Salts: Distribution and Chemical Behavior of Fluorine.

La-loaded absorbents have been widely reported for fluoride removal due to the strong affinity of La3+ towards fluoride ion. Herein, chemical removal of fluoride from flue gas scrubbing wastewater using lanthanum salt is investigated. The retaining free F- concentration, phase composition and morphology of filtration residues, and the distribution of fluorine have been investigated using ion-selective electrode, analytical balance, scanning electron microscopy, and X-ray diffractor. The results show that at La/F molar ratio ≥1:3.05, the majority of fluorine exists as LaF x 3-x complexes, leading to the failure of fluoride removal. At 1:3.20 ≤ La/F molar ratio ≤1:3.10, the formation of LaF3 is facilitated. However, co-existing LaF x 3-x tends to absorb on the surface of LaF3 particles, leading to the formation of colloidal solution with large numbers of LaF3·LaF x 3-x suspended solids. At an optimized La/F molar ratio of 1:3.10, a fluoride removal of 97.86% is obtained with retaining fluorine concentration of 6.42 mg L-1. Considering the existing of positively charged LaF x 3-x and LaF3·LaF x 3-x , coagulation removal of fluoride is proposed and investigated using lanthanum salts and negatively charged SiO2·nH2O colloidal particles, which is in-situ provided via Na2SiO3 hydrolysis at pH near 5.5. At a La/F molar ratio of 1:3.00 and Na2SiO3 dose of 0.50 g L-1, a fluoride removal of 99.25% is obtained with retaining fluorine concentration of 2.24 mg L-1. When Na2SiO3 dose increases to 1.00 g L-1, the retaining fluorine concentration could be further reduced to 0.80 mg L-1.

Frequency-Modulated Continuous Wave Radar Respiratory Pattern Detection Technology Based on Multifeature.

Respiratory diseases including apnea are often accompanied by abnormal respiratory depth, frequency, and rhythm. If different abnormal respiratory patterns can be detected and recorded, with their depth, frequency, and rhythm analyzed, the detection and diagnosis of respiratory diseases can be achieved. High-frequency millimeter-wave radar (76-81 GHz) has low environmental impact, high accuracy, and small volume, which is more suitable for respiratory signal detection and recognition compared with other contact equipment. In this paper, the experimental platform of frequency-modulated continuous wave (FMCW) radar was built at first, realizing the noncontact measurement of vital signs. Secondly, the energy intensity and threshold of respiration signal during each period were calculated by using the rectangular window, and the accurate judgment of apnea was realized via numerical comparison. Thirdly, the features of respiratory and heart rate signals, the number of peaks and valleys, the difference between peaks and valleys, the average and the standard deviation of normalized short-term energy, and the average and the standard deviation and the minimum of instantaneous frequency, were extracted and analyzed. Finally, support vector machine (SVM) and K-nearest neighbor (KNN) were used to classify the extracted features, and the accuracy was 98.25% and 88.75%, respectively. The classification and recognition of respiratory patterns have been successfully realized.

Rhodamine B dye staining for visualizing microplastics in laboratory-based studies.

In the recent years, microplastics have attracted much attention as new emerging environmental pollutants. Previously, several studies were performed to understand the source and fate of microplastics in the environment, organisms, and food webs. To track microplastics and improve their legibility, labeling them is a very effective method during laboratory experiments. This study presents an effective Rhodamine B dye (RhB) staining method for microplastics. The method is crucial for the visual observation of white or transparent plastics by dyeing them in purple or pink, as well as makes the microplastics to fluoresce under common microscope fluorescence filter ranges. Five types of microplastic polymers, namely polyethylene, polypropylene, polystyrene, polyvinyl chloride, and polyurethane were used as the test materials. The efficiencies of ethanol, acetone, and distilled water as possible solvents for dissolving RhB were investigated. Next, the fluorescence stability in various conditions was assessed. The results indicated that ethanol was the most appropriate solvent in dissolving RhB used in staining the microplastics. RhB was fluorescently stable under varying conditions (light and gut fluid) or different solutions (KOH, nitric acid, and saturated NaCl). Additionally, RhB staining exhibited an insignificant effect on the Raman spectra of the microplastics. Our proposed method is simple and robust and helps to visualize the different types of microplastic polymers tested in laboratory experiments, particularly the transparent, white, and small size microplastics.

Adsorption and Desorption of Triclosan on Biodegradable Polyhydroxybutyrate Microplastics.

Biodegradable plastics have been increasingly used as a solution to the problem of plastic pollution in recent years. However, there are few studies on the negative effects of biodegradable microplastics. Triclosan, a widely used disinfectant, is a highly toxic substance. In the present study, the adsorption and desorption processes of triclosan on a type of biodegradable plastics, polyhydroxybutyrate (PHB), were investigated and also compared with one conventional plastic type, polyethylene. The adsorption equilibrium quantities of polyethylene and PHB were 3431.85 and 9442.27 µg/g, respectively. The adsorption rate and equilibrium adsorption capacity of triclosan on PHB are much higher than on polyethylene. Physical adsorption of triclosan on PHB and polyethylene microplastics may play a dominant role in this process. The desorption hysteresis indices are all less than zero; this indicates that triclosan is easily released from PHB and polyethylene microplastics under physiological conditions. Our results indicate that biodegradable PHB microplastics are stronger carriers for triclosan than the conventional polyethylene microplastics in the aquatic environment. Environ Toxicol Chem 2021;40:72-78. © 2020 SETAC.

Occurrence and identification of microplastics in tap water from China.

Microplastics as new emerging pollutants in aquatic environments have received much attention in recent years. However, up to now, microplastic contamination in tap water has only been investigated by few studies. Therefore, this study investigated the presence of microplastics in tap water. 38 tap water samples were taken at different cities of China. The amount of microplastics in tap water varied from 440 ± 275 particles L-1. Particles smaller than 50 µm significantly predominated in most of the tap water samples. Further, according to the shape of these particles, fragments, fibers and spheres were found in tap water samples, while fragments were the most abundant morphotype in most samples. Despite these particles were identified as 14 different materials by micro-Raman spectroscopy, the majority of the microplastics comprised of polyethylene and polypropylene. Based on this investigation, drinking water treatment plants seemingly have to face the problem of microplastic pollution in tap water due to their potential eco-toxicological effects on humans.