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Understanding the interface shear behavior between clay and structures is crucial in geotechnical engineering. The mechanism of the roughness effect in the shear process between the clay and structures was studied to reveal the macroscopic and microscopic interface shear behavior. The different surface protrusion shapes of the structures were produced using a three-dimensional (3D) printer. Direct shear tests were conducted to analyze the shear failure modes and peak and residual strengths under different conditions. Subsequently, a discrete element method (DEM) numerical analysis was employed to study the contact network, soil fabric evolution, shear zone, coordination number, and void ratio variations in the interface shear. The test results indicated that the shear interfaces exhibited the same failure mode under various conditions, and the peak and residual strengths showed a strong positive correlation with roughness. The results obtained from numerical calculations match the experimental findings. The contact orientations and principal stresses shifted during the shear process, and the shear zone, coordination number, and void ratio also showed regular changes with the change of roughness. The evolution of microscopic parameters in DEM can effectively help explain the macroscopic interface shear behavior.

To address the low accuracy of conventional bearing fault diagnosis methods that rely on empirical parameters in the scenarios with different noise degrees, this paper presents an adaptive bearing fault diagnosis method combining empirical mode decomposition (EMD) and tile coding. Firstly, the mature adaptive decomposition algorithm, namely the EMD, was employed to decompose the bearing vibration signal. Based on specific criteria, some components were selected as effective signals and further denoised based on spectral averaging to realize adaptive filtering of the bearing vibration signal. Secondly, feature extraction of the filtered signal was conducted using spectral coding based on tile coding. The coding results were input into the K-nearest neighbors (KNN) classifier as features. Finally, for validation, a test dataset with varying noise degrees was constructed to conduct a comparison between the proposed adaptive method and the classic adaptive filtering-based fault diagnosis methods. The results show that when the signal-to-noise ratio is greater than －10 dB, the diagnostic accuracy of the proposed approach exceeds 90% and outperforms that of other methods.

With the increasing of global energy requirements and environmental problems, the use of solar thermal energy has attracted widespread attention. The selective solar absorption coating is the most important part of a solar thermal conversion device. At present, most of the coatings work well in a vacuum at a high temperature, while not stably in the air environment. Based on the high-temperature resistant and infrared-reflective properties of ITO, a multilayer film of SiO2/Si3N4/SiO2/ITO/Cr has been designed as a selective solar absorber. The genetic algorithm is applied to optimize the material and thickness selection for each layer. The results show that the optimized multilayer film could achieve a high solar absorptance up to 90% while keeping a relatively low infrared emittance around 50% for temperature change between 600°C and 900°C. All the materials composing this film have been tested before to be chemically stable at a high temperature up to 900°C in the air environment. It is also adaptive to different incident angles from 0° to 60°. The finite-difference time-domain method was also adopted to plot the energy density distribution for different wavelengths, which provided the underlying mechanism for the selective emission spectrum. The findings in this study would provide valuable guidance to design a low-cost selective solar absorption coating without the need for vacuum generation.

The slag behaviors, directly relating with the qualities of the final cast products, are influenced by the transient surface flow of liquid steel in a continuous casting mold. A one-half scale model is used to investigate the slag behaviors and their droplets entrainment. The model based on Volume of Fluid (VOF) multiphase coupled with Large Eddy Simulation (LES) is established to further illuminate the phenomena of the liquid oil layer fluctuation, the slag “eye” regions, and the slag entrainment observed in water experiment. The effects of casting speeds on the slag behaviors and their entrained droplets are investigated. The results show that the fluctuation of the oil layer is influenced by the transient flow. The calculations for the oil layer profile, the accumulation, and protrusions of oil layer are consistent with the water experiment. The asymmetry of the slag “eye” regions is also influenced by the asymmetry of free surface and transient turbulent flow. The “eye” regions near the narrow wall show distinct asymmetric change at different casting speeds. At a lower casting speed, the slag “eye” regions change irregularly and display the alternate process of open and collapse at the two sides of the narrow walls of the model. While at a relative higher casting speed, the slag layer gathers toward the nozzle, and the slag “eye” regions gradually grow and always open. The simulation model can reveal that the mechanism of the slag entrainment includes two main modes: the cutting or dragging mode and shear layer instability. The average diameter and amount of the entrained droplets are calculated through the UDF codes of ANSYS FLUENT software, and the size distribution of the entrained droplets is also counted. When the casting speed is lower, the dominant diameters of the entrained droplets range between 2 and 3 mm. With casting speed increase, the distribution of the droplets becomes wider, and there is a gradually increase in the percentage of larger droplets with a size of 4–6 mm.

In troposphere, ozone is a toxic secondary pollutant produced when its precursors react in sunlight. An important source of ozone precursors is biomass burning. Here we investigate the impacts of 2016 Southeast U.S. Wildfires on ozone production by integrating vertical resolved ozone profiles and photochemical modeling. The results show that wildfires contributed to ozone lamina at the top of boundary layer and enhanced surface ozone up to about 10ppbv in Southeast U.S.. Ozone lidar observed a lower ozone change with respect to a fast growth of aerosol plume, of which the reason is also investigated. Current results indicate an effective integration of vertical observations and modeling for us to understand the ozone production from fires in troposphere.

Recently, we successfully demonstrated a new compact and robust ozone DIAL lidar for smaller aircraft such as the NASA B200 and the ER-2 high-altitude aircraft. This is the first NASA airborne lidar to incorporate advanced solid-state lasers to produce the required power at the required ultraviolet wavelengths, and is compact and robust enough to operate nearly autonomously on the high-altitude ER-2 aircraft. This technology development resulted in the first new NASA airborne ozone DIAL instrument in more than 15 years. The combined ozone, aerosol, and clouds measurements provide valuable information on the chemistry, radiation, and dynamics of the atmosphere. In particular, from the ER-2 it offers a unique capability to study the upper troposphere and lower stratosphere.

The Tropospheric Ozone Lidar Network (TOLNet) is a unique network of lidar systems that measure atmospheric profiles of ozone and aerosols, to contribute to air-quality studies, atmospheric modeling, and satellite validation efforts. The accurate characterization of these lidars is of critical interest, and is necessary to determine cross-instrument calibration uniformity. From July to August 2014, three lidars, the TROPospheric OZone (TROPOZ) lidar, the Tunable Optical Profiler for Aerosol and oZone (TOPAZ) lidar, and the Langley Mobile Ozone Lidar (LMOL), of TOLNet participated in the “Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality” (DISCOVER-AQ) mission and the “Front Range Air Pollution and Photochemistry Éxperiment” (FRAPPÉ) to measure sub-hourly ozone variations from near the surface to the top of the troposphere. Although large differences occur at few individual altitudes in the near field and far field range, the TOLNet lidars agree with each other within ±4%. These results indicate excellent measurement accuracy for the TOLNet lidars that is suitable for use in air-quality and ozone modeling efforts.

Ozone lidars measure continuous, high-resolution ozone profiles critical for process studies and for satellite validation in the lower troposphere. However, the effectiveness of lidar validation by using single-station data is limited. Recently, NASA initiated an interagency ozone lidar observation network under the name TOLNet to promote cooperative multiple-station ozone-lidar observations to provide highly timeresolved (few minutes) tropospheric-ozone vertical profiles useful for air-quality studies, model evaluation, and satellite validation. This article briefly describes the concept, stations, major specifications of the TOLNet instruments, and data archiving.

A real-time air quality forecasting system was developed using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to provide support for flight planning activities during the NOAA Atmospheric Emissions and Reactions Observed from Megacities to Marine Areas (AEROMMA) and NASA Synergistic TEMPO Air Quality Science (STAQS) 2023 field campaigns. The forecasting system operated on two separate domains centered on Chicago, IL, and New York City, NY, and provided 72-hour predictions of atmospheric composition, aerosols, and clouds. This study evaluates the Chicago-centered forecasting system's 1-, 2-, and 3-day ozone (O3) forecast skill for Chiwaukee Prairie, WI, a rural area downwind of Chicago that often experiences high levels of O3 pollution. Comparisons to vertical O3 profiles collected by a Tropospheric Ozone Lidar Network (TOLNet) instrument revealed that forecast skill decreases as forecast lead time increases. When compared to surface measurements, the forecasting system tended to underestimate O3 concentrations on high O3 days and overestimate on low O3 days at Chiwaukee Prairie regardless of forecast lead time. Using July 25, 2023, as a case study, analyses show that the forecasts underestimated peak O3 levels at Chiwaukee Prairie during this regionwide bad air quality day. Wind speed and direction data indicates that this underestimation can partially be attributed to lake breeze simulation errors. Surface fine particulate matter (PM2.5) measurements, Geostationary Operational Environmental Satellite-16 (GOES-16) aerosol optical depth (AOD) data, and back trajectories from the NOAA Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model show that transported Canadian wildfire smoke impacted the Lake Michigan region on this day. Errors in the forecasted chemical composition and transport of the smoke plumes also contributed to underpredictions of O3 levels at Chiwaukee Prairie on July 25, 2023. The results of this work help identify improvements that can be made for future iterations of the WRF-Chem forecasting system. Implications: Air quality forecasting is an important tool that can be used to inform the public about upcoming high pollution days so that individuals may plan accordingly to limit their exposure to health-damaging air pollutants. Forecasting also helps scientists make decisions about where to make observations during air quality field campaigns. A variety of observational datasets were used to evaluate the accuracy of an air quality forecasting system that was developed for NOAA and NASA field campaigns that occurred in the summer of 2023. These evaluations inform areas of improvement for future development of this air quality forecasting system. [ABSTRACT FROM AUTHOR]

The Tropospheric Ozone Lidar Network (TOLNet) was used to validate retrievals of ozone (O 3) profiles in the troposphere from the TROPOspheric Monitoring Instrument (TROPOMI) ultraviolet (UV), Cross-track Infrared Sounder (CrIS) infrared (IR), and a combined UV + IR wavelength retrieval from TROPOMI/CrIS. Observations from six separate ground-based lidar systems and various locations of ozonesondes distributed throughout North America and in the Netherlands were used to quantify systematic bias and random errors for each satellite retrieval. Furthermore, TOLNet data were used to intercompare idealized UV, IR, and UV + IR convolved lidar profiles of O 3 in the troposphere during case studies representative of high-O 3 events. This study shows that the improved sensitivity and vertical resolution in UV + IR retrievals in the middle- and upper-troposphere resulted in tropospheric degree of freedom (DOF) values ∼ 33 % higher compared to UV- and IR-only retrievals. The increased DOFs in the UV + IR retrievals allowed for improved reproduction of mid- and upper-tropospheric O 3 enhancements and, to a lesser degree, near-surface pollution enhancements compared to single-wavelength satellite products. The validation of O 3 profiles in the troposphere retrieved with the UV-only, IR-only, and UV + IR Tikhonov regularised Ozone Profile retrievAl with SCIATRAN (TOPAS) algorithm developed at the Institute for Environmental Physics, University of Bremen, demonstrated the utility of using TOLNet as a satellite evaluation data set. TOPAS UV-only, IR-only, and UV + IR wavelength retrievals had systematic biases, quantified with normalized mean bias, throughout the troposphere of 11.2 ppb (22.1 %), -1.7 ppb (-0.3 %), and 3.5 ppb (7.8 %), respectively, which meet the tropospheric systematic bias requirements defined by the science teams for the TROPOMI and CrIS sensors. The primary drivers of systematic bias were determined to be solar zenith angle, surface albedo, and cloud fraction. Random errors, representative of uncertainty in the retrievals and quantified by root mean squared errors (RMSEs), were large for all three retrievals, with UV-only, IR-only, and UV + IR wavelength retrievals having RMSEs throughout the troposphere of 17.4 ppb (19.8 % of mean tropospheric column values), 10.5 ppb (12.6 % of mean tropospheric column values), and 14.0 ppb (14.6 % of mean tropospheric column values), respectively. TOPAS UV-only profiles did not meet the uncertainty requirements defined for TROPOMI for the troposphere; however, CrIS IR-only retrievals did meet the uncertainty requirements defined by this mission. The larger random errors reflect the challenge of retrieving daily O 3 profiles due to the limited sensitivity and vertical resolution of these retrievals in the troposphere. Tropospheric systematic biases and random error were lower in IR-only and combined UV + IR retrievals compared to UV-only products due to the increased sensitivity in the troposphere allowing the retrievals to deviate further from the a priori profiles. Observations from TOLNet demonstrated that the performance of the three satellite products varied by season and altitude in the troposphere. TOLNet was shown to result in similar validation statistics compared to ozonesonde data, which are a commonly used satellite evaluation data source, demonstrating that TOLNet is a sufficient source of satellite O 3 profile validation data in the troposphere, which is critical as this data source is the primary product identified for the tropospheric O 3 validation of the recently launched Tropospheric Emissions: Monitoring of Pollution (TEMPO) mission. [ABSTRACT FROM AUTHOR]

Lightning is one of the primary natural sources of nitric oxide (NO), and the influence of lightning-induced NO (LNO) emission on air quality has been investigated in the past few decades. In the current study an LNO emissions model, which derives LNO emission estimates from satellite-observed lightning optical energy, is introduced. The estimated LNO emission is employed in an air quality modeling system to investigate the potential influence of LNO on tropospheric ozone. Results show that lightning produced 0.174 Tg N of nitrogen oxides (NO x = NO + NO 2) over the contiguous US (CONUS) domain between June and September 2019, which accounts for 11.4 % of the total NO x emission. In August 2019, LNO emission increased ozone concentration within the troposphere by an average of 1 %–2 % (or 0.3–1.5 ppbv), depending on the altitude; the enhancement is maximum at ∼ 4 km above ground level and minimum near the surface. The southeastern US has the most significant ground-level ozone increase, with up to 1 ppbv (or 2 % of the mean observed value) difference for the maximum daily 8 h average (MDA8) ozone. These numbers are near the lower bound of the uncertainty range given in previous studies. The decreasing trend in anthropogenic NO x emissions over the past 2 decades increases the relative contribution of LNO emissions to total NO x emissions, suggesting that the LNO production rate used in this study may need to be increased. Corrections for the sensor flash detection efficiency may also be helpful. Moreover, the episodic impact of LNO on tropospheric ozone can be considerable. Performing backward trajectory analyses revealed two main reasons for significant ozone increases: long-distance chemical transport and lightning activity in the upwind direction shortly before the event. [ABSTRACT FROM AUTHOR]

RNA imaging paves the way to investigate RNA function and regulation from the aspect of RNA subcellular localization and expression level. In the past decades, various highly precise and genetic coding fluorescent RNA, which can bind and light up the fluorophore by their specific sequence/structure, has been developed for RNA imaging, including Broccoli, Mango, SRB‐2, RhoBAST, and Pepper et al. In this Review, we summarize the RNA imaging approaches and the progress made in the development of fluorescent RNA. Next, we emphasize the application of fluorescent RNA for in situ RNA imaging in living cells. Of particular note, besides the artificially selected fluorescent RNAs, a new kind of fluorophore that can bind and light up intrinsic RNA structure is described together for the first time. Finally, a summary of current strategies for designing fluorescent RNA and future perspectives are also presented. We hope this expanding topic will inspire the study of the architecture and functions of these fascinating molecular machinery in biological systems. [ABSTRACT FROM AUTHOR]