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With the continuous development of space and sensor technologies during the last 40 years, ocean remote sensing has entered into the big-data era with typical five-V (volume, variety, value, velocity and veracity) characteristics. Ocean remote-sensing data archives reach several tens of petabytes and massive satellite data are acquired worldwide daily. To precisely, efficiently and intelligently mine the useful information submerged in such ocean remote-sensing data sets is a big challenge. Deep learning—a powerful technology recently emerging in the machine-learning field—has demonstrated its more significant superiority over traditional physical- or statistical-based algorithms for image-information extraction in many industrial-field applications and starts to draw interest in ocean remote-sensing applications. In this review paper, we first systematically reviewed two deep-learning frameworks that carry out ocean remote-sensing-image classifications and then presented eight typical applications in ocean internal-wave/eddy/oil-spill/coastal-inundation/sea-ice/green-algae/ship/coral-reef mapping from different types of ocean remote-sensing imagery to show how effective these deep-learning frameworks are. Researchers can also readily modify these existing frameworks for information mining of other kinds of remote-sensing imagery. [ABSTRACT FROM AUTHOR]

Metal-insulator-semiconductor (MIS) photocathodes offer a simple alternative to p-n junction photocathodes in photoelectrochemical water splitting. However, the parasitic light absorption of catalysts and metal layers in the MIS junction, as well as the lack of low work function metals to form a large band offset with p-Si, severely limit their performance. This paper describes an MIS photocathode fabricated from n-Si, rather than the commonly used p-Si, to spatially decouple light absorption from reaction sites, which enables the majority carriers, instead of the commonly used minority carriers, to drive the surface reaction, making it possible to place the reaction sites far away from the light absorption region. Thus, the catalysts could be moved to the backside of the MIS junction to avoid light shielding. Moreover, the adoption of n-Si unlocks a variety of high work function materials for photovoltage generation. The obtained n-Si MIS photocathode exhibits an applied bias photon-to-current efficiency of 10.26% with a stability up to 300 h. [ABSTRACT FROM AUTHOR]

The SARS-CoV-2 B.1.617.2 (Delta) variant flared up in late May in Guangzhou, China. Transmission characteristics of Delta variant were analysed for 153 confirmed cases and two complete transmission chains with seven generations were fully presented. A rapid transmission occurred in five generations within 10 days. The basic reproduction number (R0) was 3.60 (95% confidence interval: 2.50–5.30). After redefining the concept of close contact, the proportion of confirmed cases discovered from close contacts increased from 43% to 100%. With the usage of a yellow health code, the potential exposed individuals were self-motivated to take a nucleic acid test and regained public access with a negative testing result. Facing the massive requirement of screening, novel facilities like makeshift inflatable laboratories were promptly set up as a vital supplement and 17 cases were found, with 1 pre-symptomatic. The dynamic adjustment of these three interventions resulted in the decline of Rt from 5.00 to 1.00 within 9 days. By breaking the transmission chain and eliminating the transmission source through extending the scope of the close-contact tracing, health-code usage and mass testing, the Guangzhou Delta epidemic was effectively contained. [ABSTRACT FROM AUTHOR]

Forty-five years after the Apollo and Luna missions returned lunar samples, China's Chang'E-5 (CE-5) mission collected new samples from the mid-latitude region in the northeastern Oceanus Procellarum of the Moon. Our study shows that 95% of CE-5 lunar soil sizes are found to be within the range of 1.40–9.35 μm, while 95% of the soils by mass are within the size range of 4.84–432.27 μm. The bulk density, true density and specific surface area of CE-5 soils are 1.2387 g/cm3, 3.1952 g/cm3 and 0.56 m2/g, respectively. Fragments from the CE-5 regolith are classified into igneous clasts (mostly basalt), agglutinate and glass. A few breccias were also found. The minerals and compositions of CE-5 soils are consistent with mare basalts and can be classified as low-Ti/low-Al/low-K type with lower rare-earth-element contents than materials rich in potassium, rare earth element and phosphorus. CE-5 soils have high FeO and low Mg index, which could represent a new class of basalt. [ABSTRACT FROM AUTHOR]