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Abstract Recently, tremendous research interest has been aroused in clathrate superhydrides. However, their microscopic properties, especially the superconducting (SC) gap and electron-phonon coupling (EPC) strength, are largely unexplored experimentally. Here, we investigate the time-resolved ultrafast spectroscopy of a superconductor LaH10±δ under an ultrahigh pressure of 165 GPa. By analyzing the ultrafast dynamics of the quasiparticles, we experimentally obtain the SC gap Δ(0) = 53 ± 5 meV, revealing a gap ratio 2Δ(0)/k B T c = 5.6 and a gap parameter ϑ = 1.95. Significantly, we experimentally estimate $$\lambda \langle {\Omega }^{2}\rangle$$ λ ⟨ Ω 2 ⟩ = (2.4 ± 0.1) × 104 (meV)2, which corresponds to an EPC strength λ = 2.58 ± 0.11. These results together provide direct experimental evidence that strong EPC is responsible for the near-room-temperature superconductivity in clathrate superhydrides. Our investigation significantly advances the experimental exploration of superhydrides, and contributes to the ultrafast dynamics investigations of quantum materials under high pressures.

Geometric errors in LoD2 building models can be caused by the modeling algorithm but are often related to the quality of input data. One approach to tackling the modeling errors caused by the quality of input data is to collect additional data with a UAV and remodel the buildings. However, no flight planning approach exists specifically designed for efficient data recollection for model improvement. In this paper, we propose an innovative flight planning approach for this purpose. Contrary to the conventional method that recollects the data covering the entire building roof, our approach only collects the data over the erroneous region and uses it to improve the erroneous model part later. Our algorithm utilizes the existing LiDAR survey data to automatically detect model errors and design the camera networks by considering the roof geometry. We optimize the trajectory that connects the viewpoints with a genetic algorithm and develops an obstacle avoidance function with ray-casting to ensure a collision-free path. The proposed flight plan is implemented in a real-world scene. Our result shows an improved point cloud created through dense image matching with the collected UAV image data. The generated point cloud is successfully used for creating partial building models for improving the original models.

Image classification is one of the main drivers of the rapid developments in deep learning with convolutional neural networks for computer vision. So is the analogous task of scene classification in remote sensing. However, in contrast to the computer vision community that has long been using well-established, large-scale standard datasets to train and benchmark high-capacity models, the remote sensing community still largely relies on relatively small and often application-dependend datasets, thus lacking comparability. With this paper, we present a classification-oriented conversion of the SEN12MS dataset. Using that, we provide results for several baseline models based on two standard CNN architectures and different input data configurations. Our results support the benchmarking of remote sensing image classification and provide insights to the benefit of multi-spectral data and multi-sensor data fusion over conventional RGB imagery.

Severe acute respiratory syndrome–associated coronavirus 2 has caused a global public health crisis with high rates of infection and mortality. Treatment and prevention approaches include vaccine development, the design of small-molecule antiviral drugs, and macromolecular neutralizing antibodies. Polymers have been designed for effective virus inhibition and as antiviral drug delivery carriers. This review summarizes recent progress and provides a perspective on polymer-based approaches for the treatment and prevention of coronavirus infection. These polymer-based partners include polyanion/polycations, dendritic polymers, macromolecular prodrugs, and polymeric drug delivery systems that have the potential to significantly improve the efficacy of antiviral therapeutics.

This paper attempts to identify key factor(s) for highly reflective silver (Ag) coatings. Investigation was made over the crystal orientation and surface roughness, using several types of surfaces, including electroplated Ag polycrystal films, physical vapour deposited polycrystal Ag films, and single crystal Ag foils with different crystal orientations. In each type of the surfaces, surface roughness was varied so that, for different combinations of crystal orientation, roughness would elucidate the key factors towards highly reflective Ag coatings. It is found that surface roughness plays a critical role in determining the reflectance, while the crystal orientation has negligible effect. The mean reflectance and one-way ANOVA analysis indicate that the single crystal Ag foils with three orientations performed statistically the same in the same roughness group at significance level α = 0.05. Moreover, correlation between the surface reflectance and surface roughness has been proposed for the benefit of coating design. Refection data obtained from the polycrystalline silver samples are used to verify the accuracy of the proposed correlations. It was observed that the development surface area ratio, Sdr, is a better roughness indicator in predicting the reflectance of polycrystalline silver films than the arithmetic average roughness, Ra.

The electrochemical processes in solutions with a much lower amount of free cyanide (

To investigate the physico-chemical properties of aerosols in Taiwan, an observation network was initiated in 2003. In this work, the measurements of the mass concentration and carbonaceous composition of PM10 and PM2.5 are presented. Analysis on the data collected in the first 5-years, from 2003 to 2007, showed that there was a very strong contrast in the aerosol concentration and composition between the rural and the urban/suburban stations. The five-year means of EC at the respective stations ranged from 0.9±0.04 to 4.2±0.1 μgC m−3. In rural areas, EC accounted for 2–3% of PM10 and 3–5% of PM2.5 mass loadings, comparing to 4–6% of PM10 and 4–8% of PM2.5 in the urban areas. It was found that the spatial distribution of EC was consistent with CO and NOx across the network stations, suggesting that the levels of EC over Taiwan were dominated by local sources. The measured OC was split into POC and SOC counterparts following the EC tracer method. Five-year means of POC ranged from 1.8±0.1 to 9.7±0.2 μgC m−3 among the stations. It was estimated that the POM contributed 5–17% of PM10 and 7–18% of PM2.5 in Taiwan. On the other hand, the five-year means of SOC ranged from 1.5±0.1 to 3.8±.3 μgC m−3. The mass fractions of SOM were estimated to be 9–19% in PM10 and 14–22% in PM2.5. The results showed that the SOC did not exhibit significant urban-rural contrast as did the POC and EC. A significant cross-station correlation between SOC and total oxidant was observed, which means the spatial distribution of SOC in Taiwan was dominated by the oxidant mixing ratio. Besides, correlation was also found between SOC and particulate nitrate, implying that the precursors of SOA were mainly from local anthropogenic sources. In addition to the spatial distribution, the carbonaceous aerosols also exhibited distinct seasonality. In northern Taiwan, the concentrations of all the three carbonaceous components (EC, POC, and SOC) reached their respective minima in the fall season. POC and EC increased drastically in winter and peaked in spring, whereas the SOC was characterized by a bimodal pattern with the maximal concentration in winter and a second mode in summertime. In southern Taiwan, minimal levels of POC and EC occurred consistently in summer and the maxima were observed in winter, whereas the SOC peaked in summer and declined in wintertime. The discrepancies in the seasonality of carbonaceous aerosols between northern and southern Taiwan were most likely caused by the seasonal meteorological settings that dominated the dispersion of air pollutants. Moreover, it was inferred that the Asian pollution outbreaks could have shifted the seasonal maxima of air pollutants from winter to spring in the northern Taiwan, and that the increases in biogenic SOA precursors and the enhancement in SOA yield were responsible for the elevated SOC concentrations in summer.

The air layer between the nocturnal boundary layer and the top of the daily mixing layer in an ozone-polluted area is known to serve as an ozone reservoir since the ozone that is produced in the mixing layer on the preceding day is effectively preserved throughout the night in the air layer. Ozone reservoir layers existing at night can enhance the accumulation of surface ozone on the following day. However, our knowledge of the characteristics of ozone reservoir layers and their effects on the daily ozone accumulations is limited. In this work, ozone reservoir layers were experimentally investigated at a coastal, near-mountain site in southern Taiwan, 30 km away from the coastline. Tethered ozone soundings were performed to obtain vertical profiles of ozone and meteorological variables during a four-day ozone episode in November 2006. Observation-based methods are adopted to evaluate the effects of the ozone reservoir layers on the surface ozone accumulation during the four-day ozone episode. Ozone reservoir layers were found to develop every evening with a depth of 1200–1400 m. Ozone concentrations within the reservoir layers reached over 140 parts per billion (ppb). From each evening to midnight, the size of the ozone reservoir layer and the ozone concentration inside dramatically changed. As a result, a concentrated, elevated ozone reservoir layer formed with a depth of 400 m at 800–1200 m every midnight. For the rest of each night, the elevated ozone reservoir layer gradually descended until it reached 500–900 m in the next morning. The observed ozone reservoir layer is formed by the invasion of a cool, marine air mass into a relatively warm, ozone-rich mixing layer in the evening. The descending is related to nocturnal coastal subsidence as well. The ozone concentration at the study site was maximal at 15:00–17:00 LT daily because of the addition of the daily produced ozone on the preceding day. The rate of increase of surface ozone concentration due to the downward mixing of the ozone in the ozone reservoir layers can be as high as 12–24 ppb/h in the late morning. The contribution of the ozone carried over from the preceding day can be 60–85 ppb, which contributes over 50% to the daily ozone pollution as compared with ozone produced on the study day.