A Low-Cost Microfluidic Method for Microplastics Identification: Towards Continuous Recognition

Plastic pollution has emerged as a growing concern worldwide. In particular, the most abundant plastic debris, microplastics, has necessitated the development of rapid and effective identification methods to track down the stages and evidence of the pollution. In this paper, we combine low-cost plastic staining technologies using Nile Red with the continuous feature offered by microfluidics to propose a low-cost 3D printed device for the identification of microplastics. It is observed that the microfluidic devices indicate comparable staining and identification performance compared to conventional Nile Red staining processes while offering the advantages of continuous recognition for long-term environmental monitoring. The results also show that concentration, temperature, and residency time possess strong effects on the identification performance. Finally, various microplastics have been applied to further demonstrate the effectiveness of the proposed devices. It is found that, among different types of microplastics, non-spherical microplastics show the maximal fluorescence level. Meanwhile, natural fibers indicate better staining quality when compared to synthetic ones

Self-Paced and Video-Based Learning: Parent Training and Language Skills in Japanese Children with ASD

While no exact information on the prevalence exists, it is assumed that the overall incidence of children with autism spectrum disorder (ASD) has risen every year in Japan. However, given the lack of resources and services for families of children with ASD in Japan, there is a dearth of practical guidance for the support for those families. This study examined the effects of an asynchronous training package (i.e., self-paced and video-based learning manual) to teach two Japanese mothers to implement incidental teaching. Effectiveness of the instruction was determined using a multiple-baseline design across mother–child dyads. Results indicated that the mother participants were able to implement the intervention with high fidelity over time. However, mixed effects of the mother-delivered intervention on target language behaviours were found across the child participants’ behaviours. This study adds an evidence to support that parents can be essential and efficient intervention agents for children with ASD

Seismogenic structures and spatiotemporal seismicity patterns of the 2022 Ms6.0 Maerkang earthquake sequence, Sichuan, China

The 2022 Ms6.0 Maerkang earthquake sequence, Sichuan, China, occurred in an unexpected area with historically rare seismicity in the Bayan Har block. Here we relocated the earthquake sequence, inverted for the focal mechanisms of the larger events, and calculated the rupture directivity of the earthquake sequence to reveal the seismogenic structures and mechanisms of this sequence. The high-precision relocations indicate that the seismogenic structures consist of several clusters that are generally parallel to the nearby NW-trending Songgang fault, and relatively small-scale conjugate faults are also identified. The seismicity migrated from cluster one in the south to cluster two in the north during the sequence. Furthermore, the hypocenters were largely located at 5–10 km depth, thereby highlighting that the seismogenic structures are buried. The vertical fault planes of the seismogenic structures are consistent with the high-dip focal mechanism solutions from seven events. A stress field inversion based on the focal mechanisms indicates that the sequence occurred in a strike-slip environment that was controlled by a NNW–SSE-striking principal compressive stress. The different rupture directivities of the Ms5.8 (southwestward) and Ms6.0 (southeastward) events prove the existence of conjugate faults. The Ms5.8 event induced a coseismic Coulomb stress change of 1.6 MPa where the Ms6.0 event subsequently occurred, thereby highlighting that the Ms5.8 event triggered the Ms6.0 event and produced the spatiotemporal seismicity pattern of the sequence. We therefore conclude that the seismogenic structures of the 2022 Ms6.0 Maerkang earthquake sequence are previously unknown concealed conjugate structures associated with the main Songgang fault. The complex seismogenic structures and their potential to generate large earthquakes warrant the need to better understand the seismogenesis of this area and the seismic risks that may be present

RITA: Boost Autonomous Driving Simulators with Realistic Interactive Traffic Flow

High-quality traffic flow generation is the core module in building simulators for autonomous driving. However, the majority of available simulators are incapable of replicating traffic patterns that accurately reflect the various features of real-world data while also simulating human-like reactive responses to the tested autopilot driving strategies. Taking one step forward to addressing such a problem, we propose Realistic Interactive TrAffic flow (RITA) as an integrated component of existing driving simulators to provide high-quality traffic flow for the evaluation and optimization of the tested driving strategies. RITA is developed with consideration of three key features, i.e., fidelity, diversity, and controllability, and consists of two core modules called RITABackend and RITAKit. RITABackend is built to support vehicle-wise control and provide traffic generation models from real-world datasets, while RITAKit is developed with easy-to-use interfaces for controllable traffic generation via RITABackend. We demonstrate RITA's capacity to create diversified and high-fidelity traffic simulations in several highly interactive highway scenarios. The experimental findings demonstrate that our produced RITA traffic flows exhibit all three key features, hence enhancing the completeness of driving strategy evaluation. Moreover, we showcase the possibility for further improvement of baseline strategies through online fine-tuning with RITA traffic flows.Comment: 8 pages, 5 figures, 3 table

Probing NaCl hydrate formation from aqueous solutions by Terahertz Time-Domain Spectroscopy

The cooling-induced formation of hydrate in aqueous NaCl solutions was probed using terahertz time-domain spectroscopy (THz-TDS). It was found that the NaCl hydrate formation is accompanied with emergence of four new absorption peaks at 1.60, 2.43, 3.34 and 3.78 THz. Combining the X-ray diffraction measurement with the solid-state based density functional theory (DFT) calculations, we assign the observed terahertz absorption peaks to the vibrational modes of the formed NaCl⋅2H2O hydrate during cooling. This work dedicates THz-TDS based analysis great potential in studying ionic hydrate and the newly revealed collective vibrational modes could be the sensitive indicators to achieve quantitative analysis in phase transitions and lattice dynamics

Numerical Study of Highway Noise Barrier Effects on Pollutant Dispersion

Roadside noise barrier helps to reduce downwind pollutants concentration from vehicle emission. This positive characteristic of the construction feature can be explained by its interaction with flow distribution and species transportation. In this thesis, 3-D numerical model has been developed to simulate highway pollutant transportation - realizable k-e model was employed to model turbulent flow; non-reaction species dispersion was applied to simulate species transport. First, numerical models were validated with experimental data. Good agreement was observed. Then detailed simulations were conducted to study double barriers’ effects on highway pollutant dispersion under different settings: noise barriers with different heights, noise barriers with and without edge effects, different atmospheric thermal boundary conditions. Results show that: (1) Noise barrier feature helps reduce downwind pollutant concentration. For 4m tall double barriers without edge effect case, 80% less concentration can be found than non-barrier case at downwind 100m; (2) Reduction of concentration increases as barrier height increases. 1m higher can lead 0.002 mol/m3 more concentration reduction at ground level. (3) Unstable condition has the least concentration and stable condition has the highest concentration at the same location. (4) Barrier with edge effect has higher concentration than barrier without edge effect downwind; (5) Oblique wind condition enlarges barrier edge effect. The larger the oblique angle is, the higher turbulence intensity can be found near barrier edges. These findings will be provide valuable input to noise barriers design so as to improve roadside neighborhood air quality

Numerical Study of Noise Barriers’ Side Edge Effects on Pollutant Dispersion near Roadside under Various Thermal Stability Conditions

Roadside noise barrier helps to reduce downwind pollutant concentrations from vehicle emission. This positive characteristic of the construction feature can be explained by its interaction with flow distribution and species dispersion. In this paper, a three-dimensional numerical model has been developed to simulate highway pollutant dispersion—a realizable k-ε model was employed to model turbulent flow, and a non-reaction species dispersion model was applied to simulate species transport. First, numerical models were validated with experimental data, and good agreement was observed. Then, detailed simulations were conducted to study double barriers’ effects on highway pollutant dispersion under different settings: noise barriers with different heights, noise barriers with and without edge effects, and different atmospheric thermal boundary conditions. Results show that: (1) Noise barriers without edge effects cause bigger downwind velocity and turbulence intensity than noise barriers with edge effects. (2) At ground level, lower downwind pollutant concentration and higher pollutant concentration, near upwind barrier and between barriers, are observed for noise barriers without edge effect cases; higher on-road pollutant concentration can be seen near barrier side edges for cases with edge effect. (3) Downwind velocity and turbulence intensity increase as barrier height increases, which causes reduced downwind pollutant concentration. (4) With the same barrier height, under unstable atmospheric boundary condition, the lowest pollutant concentration can be found for both downwind and between barriers. Overall, these findings will provide valuable inputs to noise barrier design, so as to improve roadside neighborhood air quality

A Low-Cost Microfluidic Method for Microplastics Identification: Towards Continuous Recognition

Plastic pollution has emerged as a growing concern worldwide. In particular, the most abundant plastic debris, microplastics, has necessitated the development of rapid and effective identification methods to track down the stages and evidence of the pollution. In this paper, we combine low-cost plastic staining technologies using Nile Red with the continuous feature offered by microfluidics to propose a low-cost 3D printed device for the identification of microplastics. It is observed that the microfluidic devices indicate comparable staining and identification performance compared to conventional Nile Red staining processes while offering the advantages of continuous recognition for long-term environmental monitoring. The results also show that concentration, temperature, and residency time possess strong effects on the identification performance. Finally, various microplastics have been applied to further demonstrate the effectiveness of the proposed devices. It is found that, among different types of microplastics, non-spherical microplastics show the maximal fluorescence level. Meanwhile, natural fibers indicate better staining quality when compared to synthetic ones

Development Trends of Non-thermal Plasma (NTP) Technology Used in Environmental Pollutants Treatment: A Patent-Bibiometric Analysis

Non-thermal plasma Technology (NTP) has been widely used in various fields, especially in environmental pollutants treatment field. This paper provides an overview of the global NTP patent landscape by analyzing relative patents based on CNABS and DWPI, selected from 1987 to 2019, which covers patenting activity related to technologies in pollutant removal from the process in the above-mentioned areas. The most common technologies for each area were identified and their developments were analyzed over time. Information related to the main countries, key applicants, current activities and the technology strength were identified by synthesizing important findings from qualitative research and quantitative literature analysis

Land Subsidence Prediction Induced by Multiple Factors Using Machine Learning Method

In the Beijing Plain, land subsidence is one of the most prominent geological problems, which is affected by multiple factors. Groundwater exploitation, thickness of the Quaternary deposit and urban development and construction are important factors affecting the formation and development of land subsidence. Here we choose groundwater level change, thickness of the Quaternary deposit and index-based built-up index (IBI) as influencing factors, and we use the influence factors to predict the subsidence amount in the Beijing Plain. The Sentinel-1 radar images and the persistent scatters interferometry (PSI) were adopted to obtain the information of land subsidence. By using Google Earth Engine platform and Landsat8 optical images, IBI was extracted. Groundwater level change and thickness of the Quaternary deposit were obtained from hydrogeological data. Machine learning algorithms Linear Regression and Principal Component Analysis (PCA) were used to investigate the relationship between land subsidence and influencing factors. Based on the results obtained by Linear Regression and PCA, a suitable machine learning algorithm was selected to predict the subsidence amount in the Beijing Plain in 2018 through influencing factors. In this study, we found that the maximum subsidence rate in the Beijing Plain had reached 115.96 mm/y from 2016 to 2018. The land subsidence was serious in eastern Chaoyang and northwestern Tongzhou. In addition, the area where thickness of the Quaternary deposit reached 150–200 m was prone to more serious land subsidence in the Beijing Plain. In groundwater exploitation, the second confined aquifer had the greatest impact on land subsidence. Through Linear Regression and PCA, we found that the relationship between land subsidence and influencing factors was nonlinear. XGBoost was feasible to predict subsidence amount. The prediction accuracy of XGBoost on the subsidence amount reached 0.9431, and the mean square error was controlled at 15.97. By using XGBoost to predict the subsidence amount, our research provides a new idea for land subsidence prediction