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Bathyarchaeia (formerly Bathyarchaeota) is a group of highly abundant archaeal communities that play important roles in global biogeochemical cycling. Bathyarchaeia is predominantly found in sediments and hot springs. However, their presence in arable soils is relatively limited. In this study, we aimed to investigate the spatial distributions and diversity of Bathyarchaeia in paddy soils across eastern China, which is a major rice production region. The relative abundance of Bathyarchaeia among total archaea ranged from 3 to 68% in paddy soils, and Bathy-6 was the dominant subgroup among the Bathyarchaeia (70–80% of all sequences). Bathyarchaeia showed higher migration ability and wider niche width based on the neutral and null model simulations. Bathy-6 was primarily assembled by deterministic processes. Soil pH and C/N ratio were identified as key factors influencing the Bathyarchaeia composition, whereas C/N ratio and mean annual temperature influenced the relative abundance of Bathyarchaeia. Network analysis showed that specific Bathyarchaeia taxa occupied keystone positions in the archaeal community and co-occurred with some methanogenic archaea, including Methanosarcina and Methanobacteria, and ammonia-oxidizing archaea belonging to Nitrososphaeria. This study provides important insights into the biogeography and niche differentiation of Bathyarchaeia particularly in paddy soil ecosystems.

Bathyarchaeia (formerly Bathyarchaeota) is a group of highly abundant archaeal communities that play important roles in global biogeochemical cycling. Bathyarchaeia is predominantly found in sediments and hot springs. However, their presence in arable soils is relatively limited. In this study, we aimed to investigate the spatial distributions and diversity of Bathyarchaeia in paddy soils across eastern China, which is a major rice production region. The relative abundance of Bathyarchaeia among total archaea ranged from 3 to 68% in paddy soils, and Bathy-6 was the dominant subgroup among the Bathyarchaeia (70–80% of all sequences). Bathyarchaeia showed higher migration ability and wider niche width based on the neutral and null model simulations. Bathy-6 was primarily assembled by deterministic processes. Soil pH and C/N ratio were identified as key factors influencing the Bathyarchaeia composition, whereas C/N ratio and mean annual temperature influenced the relative abundance of Bathyarchaeia. Network analysis showed that specific Bathyarchaeia taxa occupied keystone positions in the archaeal community and co-occurred with some methanogenic archaea, including Methanosarcina and Methanobacteria, and ammonia-oxidizing archaea belonging to Nitrososphaeria. This study provides important insights into the biogeography and niche differentiation of Bathyarchaeia particularly in paddy soil ecosystems.

Accurate identification of End-Diastolic (ED) and End-Systolic (ES) frames is key for cardiac function assessment through echocardiography. However, traditional methods face several limitations: they require extensive amounts of data, extensive annotations by medical experts, significant training resources, and often lack robustness. Addressing these challenges, we proposed an unsupervised and training-free method, our novel approach leverages unsupervised segmentation to enhance fault tolerance against segmentation inaccuracies. By identifying anchor points and analyzing directional deformation, we effectively reduce dependence on the accuracy of initial segmentation images and enhance fault tolerance, all while improving robustness. Tested on Echo-dynamic and CAMUS datasets, our method achieves comparable accuracy to learning-based models without their associated drawbacks. The code is available at https://github.com/MRUIL/DDSB

Ice albedo feedback amplifies climate change signals and thus affects the global climate. Global long-term records on sea-ice albedo are important to characterize the regional or global energy budget. As the successor of MODIS (Moderate Resolution Imaging Spectroradiometer), VIIRS (Visible Infrared Imaging Radiometer Suite) started its observation from October 2011 on S-NPP (Suomi National Polar-orbiting Partnership). It has improved upon the capabilities of the operational Advanced Very High Resolution Radiometer (AVHRR) and provides observation continuity with MODIS. We used a direct estimation algorithm to produce a VIIRS sea-ice albedo (VSIA) product, which will be operational in the National Oceanic and Atmospheric Administration’s (NOAA) S-NPP Data Exploration (NDE) version of the VIIRS albedo product. The algorithm is developed from the angular bin regression method to simulate the sea-ice surface bidirectional reflectance distribution function (BRDF) from physical models, which can represent different sea-ice types and vary mixing fractions among snow, ice, and seawater. We compared the VSIA with six years of ground measurements at 30 automatic weather stations from the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) and the Greenland Climate Network (GC-NET) as a proxy for sea-ice albedo. The results show that the VSIA product highly agreed with the station measurements with low bias (about 0.03) and low root mean square error (RMSE) (about 0.07) considering the Joint Polar Satellite System (JPSS) requirement is 0.05 and 0.08 at 4 km scale, respectively. We also evaluated the VSIA using two datasets of field measured sea-ice albedo from previous field campaigns. The comparisons suggest that VSIA generally matches the magnitude of the ground measurements, with a bias of 0.09 between the instantaneous albedos in the central Arctic and a bias of 0.077 between the daily mean albedos near Alaska. The discrepancy is mainly due to the scale differenc

China has been seriously affected by particulate matter (PM) and gaseous pollutants in the atmosphere. In this study, we systematically analyse the spatio-temporal patterns of PM2.5, PM10, SO2, CO, NO2, and O3 and the associated health risks, using data collected from 1498 national air quality monitoring sites. An analysis of the averaged data from all the sites indicated that, from 2015 to 2018, annual mean concentrations of PM2.5, PM10, SO2 and CO declined by 3.2 μg m−3, 3.7 μg m−3, 3.9 μg m−3, and 0.1 mg m−3, respectively. In contrast, those of NO2 and O3 increased at rates of 0.4 and 3.1 μg m−3, respectively. Except for O3, the annual mean concentrations of all pollutants were generally the highest in North China and lowest in the Tibetan Plateau. The concentrations were generally higher in the north of the country than in the south. In all regions of China, the pollutant concentrations were the highest in winter and lowest in summer, except for O3, which showed an opposite seasonal pattern. Overall, the seasonal mean concentrations of all the pollutants (except for O3) significantly decreased between the same seasons in 2018 and 2015, whereas the seasonal mean O3 concentrations generally significantly increased, and/or remained at stable levels in all four seasons except for winter. Diurnal variations of all pollutants (except for O3) exhibited a bimodal pattern with peaks between 8:00 and 11:00 a.m. and 9:00 and 12:00 p.m., whereas O3 exhibited a unimodal pattern with maximum values between 5:00 and 7:00 p.m. No significant differences in the daily mean concentrations of all pollutants were found between weekdays and weekends in all regions, except for PM2.5 and PM10 in Northeast China. In Northwest China and Southeast China, PM2.5 showed stronger correlations with NO2 relative to SO2, suggesting that NOx emission control may be more effective than SO2 emission control for alleviating PM2.5 formation. Compared with 2015, the total PM2.5-attributable mortality

Pyrene, a representative polycyclic aromatic hydrocarbon (PAH) compound produced mainly from incomplete combustion of fossil fuels, is hazardous to ecosystem health. However, long-term exposure studies did not detect any significant effects of pyrene on soil microorganism. In this study, short-term microcosm experiments were conducted to identify the immediate effect of pyrene on soil bacterial communities. A freshlycollected pristine red soil was spiked with pyrene at 0, 10, 100, 200, and 500 mg·kg–1 and incubated for one day and seven days. The bacterial communities in the incubated soils were analyzed using 16S rRNA sequencing and terminal restriction fragment length polymorphism (TRFLP) methods. The results revealed high bacterial diversity in both unspiked and pyrene-spiked soils. Only at the highest pyrene-spiking rate of 500 mg·kg–1, two minor bacteria groups of the identified 14 most abundant bacteria groups were completely suppressed. Short-term exposure to pyrene resulted in dominance of Proteobacteria in soil, followed by Acidobacteria, Firmutes, and Bacteroidetes. Our findings showed that bacterial community structure did respond to the presence of pyrene but recovered rapidly from the perturbation. The intensity of impact and the rate of recovery showed some pyrene dosage-dependent trends. Our results revealed that different levels of pyrene may affect the bacterial community structure by suppressing or selecting certain groups of bacteria. It was also found that the bacterial community was most susceptible to pyrene within one day of the chemical addition.

Pyrene, a representative polycyclic aromatic hydrocarbon (PAH) compound produced mainly from incomplete combustion of fossil fuels, is hazardous to ecosystem health. However, long-term exposure studies did not detect any significant effects of pyrene on soil microorganism. In this study, short-term microcosm experiments were conducted to identify the immediate effect of pyrene on soil bacterial communities. A freshlycollected pristine red soil was spiked with pyrene at 0, 10, 100, 200, and 500 mg·kg–1 and incubated for one day and seven days. The bacterial communities in the incubated soils were analyzed using 16S rRNA sequencing and terminal restriction fragment length polymorphism (TRFLP) methods. The results revealed high bacterial diversity in both unspiked and pyrene-spiked soils. Only at the highest pyrene-spiking rate of 500 mg·kg–1, two minor bacteria groups of the identified 14 most abundant bacteria groups were completely suppressed. Short-term exposure to pyrene resulted in dominance of Proteobacteria in soil, followed by Acidobacteria, Firmutes, and Bacteroidetes. Our findings showed that bacterial community structure did respond to the presence of pyrene but recovered rapidly from the perturbation. The intensity of impact and the rate of recovery showed some pyrene dosage-dependent trends. Our results revealed that different levels of pyrene may affect the bacterial community structure by suppressing or selecting certain groups of bacteria. It was also found that the bacterial community was most susceptible to pyrene within one day of the chemical addition.