Composition and Biomass of Aquatic Vegetation in the Poyang Lake, China

The distribution of aquatic vegetation and associated community diversity and biomass in the Poyang Lake were investigated. The results showed that (1) 43 species of aquatic vascular plants were found in the Poyang Lake watershed which belonged to 22 families; (2) the vegetation of the Poyang Lake scattered in different areas which could be divided into 31 major plant communities and 5 plant zones including amphibian, emergent, floating-leaved, submerged, and floating input; (3) there were 67 aquatic plants in the lake area, and the standing stock (fresh weight) was 1519.41 t. The number of amphibians was the dominant plant species in the Poyang Lake, and the quantity and percentage of amphibians were predominant, which was far more than the other three life forms

RCPS: Rectified Contrastive Pseudo Supervision for Semi-Supervised Medical Image Segmentation

Medical image segmentation methods are generally designed as fully-supervised to guarantee model performance, which require a significant amount of expert annotated samples that are high-cost and laborious. Semi-supervised image segmentation can alleviate the problem by utilizing a large number of unlabeled images along with limited labeled images. However, learning a robust representation from numerous unlabeled images remains challenging due to potential noise in pseudo labels and insufficient class separability in feature space, which undermines the performance of current semi-supervised segmentation approaches. To address the issues above, we propose a novel semi-supervised segmentation method named as Rectified Contrastive Pseudo Supervision (RCPS), which combines a rectified pseudo supervision and voxel-level contrastive learning to improve the effectiveness of semi-supervised segmentation. Particularly, we design a novel rectification strategy for the pseudo supervision method based on uncertainty estimation and consistency regularization to reduce the noise influence in pseudo labels. Furthermore, we introduce a bidirectional voxel contrastive loss to the network to ensure intra-class consistency and inter-class contrast in feature space, which increases class separability in the segmentation. The proposed RCPS segmentation method has been validated on two public datasets and an in-house clinical dataset. Experimental results reveal that the proposed method yields better segmentation performance compared with the state-of-the-art methods in semi-supervised medical image segmentation. The source code is available at https://github.com/hsiangyuzhao/RCPS

Hydrological evaluation of open-access precipitation and air temperature datasets using SWAT in a poorly gauged basin in Ethiopia

Precipitation and air temperature are key drivers of watershed models. Currently there are many open-access gridded precipitation and air temperature datasets at different spatial and temporal resolutions over global or quasi-global scale. Motivated by the scarcity and substantial temporal and spatial gaps in ground measurements in Africa, this study evaluated the performance of three open-access precipitation datasets (i.e. CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), TRMM (Tropical Rainfall Measuring Mission) and CFSR (Climate Forecast System Reanalysis)) and one air temperature dataset (CFSR) in driving Soil and Water Assessment Tool (SWAT) model in simulation of daily and monthly streamflow in the upper Gilgel Abay Basin, Ethiopia. The “best” available measurements of precipitation and air temperature from sparse gauge stations were also used to drive SWAT model and the results were compared with those using open-access datasets. After a comprehensive comparison of a total of eight model scenarios with different combinations of precipitation and air temperature inputs, we draw the following conclusions: (1) using measured precipitation from even sparse available stations consistently yielded better performance in streamflow simulation than using all three open-access precipitation datasets; (2) using CFSR air temperature yielded almost identical performance in streamflow simulation to using measured air temperature from gauge stations; (3) among the three open-access precipitation, overall CHIRPS yielded best performance. These results suggested that the CHIRPS precipitation available at high spatial resolution (0.05°) together with CFSR air temperature can be a promising alternative open-access data source for streamflow simulation in this data-scarce area in the case of limited access to desirable gauge data

Evaluating the TRMM Multisatellite Precipitation Analysis for Extreme Precipitation and Streamflow in Ganjiang River Basin, China

Based on the observed precipitation data and TRMM (Tropical Rainfall Measuring Mission) 3B42 RTV7 and 3B42 V7 precipitation products from 2003 to 2010, the extreme precipitation and streamflow in the Ganjiang River basin were analyzed. The VIC hydrological model was used to simulate the streamflow driven by RTV7/V7 precipitation products in the Ganjiang River basin. The results show that (1) both of the RTV7 and V7 precipitation products have good applicability in precipitation estimation in the Ganjiang River basin and the correlation between the observed precipitation and RTV7 (V7) was as higher as 0.85 (0.86); (2) the RTV7/V7 precipitation products can well be used to simulate the streamflow by using the VIC hydrological model and the correlation between the observed streamflow and simulated streamflow driven by RTV7 (V7) products was as high as 0.86 (0.89); (3) the extreme precipitation varied greatly in the Ganjiang River basin and both of the RTV7 and V7 can capture the pattern of extreme precipitation in the Ganjiang River basin; however, higher extreme precipitation can be found in the northern Ganjiang River basin; (4) the extreme streamflow simulated driven by RTV7/V7 products agreed well with the observed extreme streamflow in the Ganjiang River basin. This study indicated that the TRMM 3B42 RTV7 and V7 products can be well used in the estimation of extreme precipitation and extreme streamflow

On the Linkage between the Extreme Drought and Pluvial Patterns in China and the Large-Scale Atmospheric Circulation

China is a nation that is affected by a multitude of natural disasters, including droughts and floods. In this paper, the variations of extreme drought and pluvial patterns and their relations to the large-scale atmospheric circulation have been analyzed based on monthly precipitation data from 483 stations during the period 1958–2010 in China. The results show the following: (1) the extreme drought and pluvial events in China increase significantly during that period. During 1959–1966 timeframe, more droughts occur in South China and more pluvial events are found in North China (DSC-PNC pattern); as for the period 1997–2003 (PSC-DNC pattern), the situation is the opposite. (2) There are good relationships among the extreme drought and pluvial events and the Western Pacific Subtropical High, meridional atmospheric moisture flux, atmospheric moisture content, and summer precipitation. (3) A cyclone atmospheric circulation anomaly occurs in North China, followed by an obvious negative height anomaly and a southern wind anomaly at 850 hPa and 500 hPa for the DSC-PNC pattern during the summer, and a massive ascending airflow from South China extends to North China at ~50∘N. As for the PSC-DNC pattern, the situation contrasts sharply with the DSC-PNC pattern

Multi-objective particle swarm optimization for optimal scheduling of household microgrids

Addressing the challenge of household loads and the concentrated power consumption of electric vehicles during periods of low electricity prices is critical to mitigate impacts on the utility grid. In this study, we propose a multi-objective particle swarm algorithm-based optimal scheduling method for household microgrids. A household microgrid optimization model is formulated, taking into account time-sharing tariffs and users’ travel patterns with electric vehicles. The model focuses on optimizing daily household electricity costs and minimizing grid-side energy supply variances. Specifically, the mathematical model incorporates the actual input and output power of each distributed energy source within the microgrid as optimization variables. Furthermore, it integrates an analysis of capacity variations for energy storage batteries and electric vehicle batteries. Through arithmetic simulation within the Pareto optimal solution set, the model identifies the optimal solution that effectively mitigates fluctuations in energy input and output on the utility side. Simulation results confirm the effectiveness of this strategy in reducing daily household electricity costs. The proposed optimization approach not only improves the overall quality of electricity consumption but also demonstrates its economic and practical feasibility, highlighting its potential for broader application and impact

Probing the pan-genome of Listeria monocytogenes: new insights into intraspecific niche expansion and genomic diversification

Bacterial pathogens often show significant intraspecific variations in ecological fitness, host preference and pathogenic potential to cause infectious disease. The species of Listeria monocytogenes, a facultative intracellular pathogen and the causative agent of human listeriosis, consists of at least three distinct genetic lineages. Two of these lineages predominantly cause human sporadic and epidemic infections, whereas the third lineage has never been implicated in human disease outbreaks despite its overall conservation of many known virulence factors. Here we compare the genomes of 26 L. monocytogenes strains representing the three lineages based on both in silico comparative genomic analysis and high-density, pan-genomic DNA array hybridizations. We uncover 86 genes and 8 small regulatory RNAs that likely make L. monocytogenes lineages differ in carbohydrate utilization and stress resistance during their residence in natural habitats and passage through the host gastrointestinal tract. We also identify 2,330 to 2,456 core genes that define this species along with an open pan-genome pool that contains more than 4,052 genes. Phylogenomic reconstructions based on 3,560 homologous groups allowed robust estimation of phylogenetic relatedness among L. monocytogenes strains. Our pan-genome approach enables accurate co-analysis of DNA sequence and hybridization array data for both core gene estimation and phylogenomics. Application of our method to the pan-genome of L. monocytogenes sheds new insights into the intraspecific niche expansion and evolution of this important foodborne pathogen.https://doi.org/10.1186/1471-2164-11-50

Evaluation of TRMM Multisatellite Precipitation Analysis in the Yangtze River Basin with a Typical Monsoon Climate

Satellite-based precipitation products are expected to offer an alternative to ground-based rainfall estimates in the present and the foreseeable future. In this paper, we evaluate the performance of TRMM 3B42 precipitation products in the Yangtze River basin for the period of 2003~2010. The results are as follows: (1) the performance of RTV7 (V7) products is generally better than that of RTV6 (V6) in the Yangtze River basin, and the percentage of best performance (bias ranging within −10%~10%) for the annual mean precipitation increases from 21.72% (54.79%) to 36.70% (59.85%) as the RTV6 (V6) improved to the RTV7 (V7); (2) the TMPA products have better performance in the wet period than that in the dry period in the Yangtze River basin; (3) the performance of TMPA precipitation has been affected by the elevation and a downward trend can be found with the increasing elevation in the Yangtze River basin. The average CC between the V7 and observed precipitation in July decreases from 0.71 to 0.40 with the elevation of gauge stations increasing from 500 m below to 4000 m above in the Yangtze River basin. More attention should be paid to the influence of complex climate and topography

Uni-COAL: A Unified Framework for Cross-Modality Synthesis and Super-Resolution of MR Images

Cross-modality synthesis (CMS), super-resolution (SR), and their combination (CMSR) have been extensively studied for magnetic resonance imaging (MRI). Their primary goals are to enhance the imaging quality by synthesizing the desired modality and reducing the slice thickness. Despite the promising synthetic results, these techniques are often tailored to specific tasks, thereby limiting their adaptability to complex clinical scenarios. Therefore, it is crucial to build a unified network that can handle various image synthesis tasks with arbitrary requirements of modality and resolution settings, so that the resources for training and deploying the models can be greatly reduced. However, none of the previous works is capable of performing CMS, SR, and CMSR using a unified network. Moreover, these MRI reconstruction methods often treat alias frequencies improperly, resulting in suboptimal detail restoration. In this paper, we propose a Unified Co-Modulated Alias-free framework (Uni-COAL) to accomplish the aforementioned tasks with a single network. The co-modulation design of the image-conditioned and stochastic attribute representations ensures the consistency between CMS and SR, while simultaneously accommodating arbitrary combinations of input/output modalities and thickness. The generator of Uni-COAL is also designed to be alias-free based on the Shannon-Nyquist signal processing framework, ensuring effective suppression of alias frequencies. Additionally, we leverage the semantic prior of Segment Anything Model (SAM) to guide Uni-COAL, ensuring a more authentic preservation of anatomical structures during synthesis. Experiments on three datasets demonstrate that Uni-COAL outperforms the alternatives in CMS, SR, and CMSR tasks for MR images, which highlights its generalizability to wide-range applications