Enzyme activities and glyphosate biodegradation in a riparian soil affected by simulated saltwater incursion

Soil salinization due to saltwater incursion, is a major threat to biochemical activities and thus strongly alters biogeochemical processes in a freshwater riparian of coastal estuary region. A pot incubation experiment was conducted to investigate the effects of simulated saltwater incursion on some key enzymatic activities and biodegradation dynamics of herbicide glyphosate in a riparian soil in Chongming Island located in the Yangtze River estuary, China. The results showed that saltwater addition with 10% artificial seawater significantly increased the biodegradation efficiency of glyphosate with the lowest residual concentration among all the treatments. However, glyphosate degradation was markedly decreased in the riparian soil with high levels of saltwater treatment. As compared with no saltwater treatment, the half-lives for 20% and 50% seawater treatments were prolonged by 4.9% and 21.1%, respectively. Throughout the incubation period, saltwater addition with 10% seawater stimulated the enzymatic activities in the glyphosate-spiked riparian soil, as compared to the treatment with 0% seawater. Flourescein diacetate (FDA) hydrolysis rate, dehydrogenase activity (DHA), catalase activity, and alkaline phosphatase activity in the glyphosate-spiked riparian soil treated with 10% seawater were 68.5%, 49.2%, 38.7%, and 28.6% higher than those for no saltwater treatment, respectively. The effect of 20% seawater treatment on the glyphosate-spiked riparian soil enzymatic activities fluctuated between promotion and inhibition depending on the type of enzymes. Soil enzymatic activities were severely depressed by increasing salinity level with 50% seawater treatment significantly inhibited, relative to no saltwater treatment. Especially, FDA hydrolysis rate and DHA were decreased by 73.8% and 64.8%, respectively, as compared to no saltwater treatment. Glyphosate degradation percentages were strongly positively correlated to the FDA hydrolysis rate and DHA, indicating that as compared to the other enzymes, the two enzymes contributed more to the herbicide biodegradation in the salt-affected riparian soil

From Text to Mask: Localizing Entities Using the Attention of Text-to-Image Diffusion Models

Diffusion models have revolted the field of text-to-image generation recently. The unique way of fusing text and image information contributes to their remarkable capability of generating highly text-related images. From another perspective, these generative models imply clues about the precise correlation between words and pixels. In this work, a simple but effective method is proposed to utilize the attention mechanism in the denoising network of text-to-image diffusion models. Without re-training nor inference-time optimization, the semantic grounding of phrases can be attained directly. We evaluate our method on Pascal VOC 2012 and Microsoft COCO 2014 under weakly-supervised semantic segmentation setting and our method achieves superior performance to prior methods. In addition, the acquired word-pixel correlation is found to be generalizable for the learned text embedding of customized generation methods, requiring only a few modifications. To validate our discovery, we introduce a new practical task called "personalized referring image segmentation" with a new dataset. Experiments in various situations demonstrate the advantages of our method compared to strong baselines on this task. In summary, our work reveals a novel way to extract the rich multi-modal knowledge hidden in diffusion models for segmentation

Optimal filter design for power converters regulated by FCS-MPC in the MEA

For the DC electrical power distribution system onboard more electric aircraft, the voltage quality of DC bus is of a great concern since there could be significant harmonics distortions when feeding different power electronics loads. This problem can be potentially addressed by introducing a dc filter to the point-of-load converters regulated by the finite control set model predictive control (FCS-MPC). To optimize this filter, Genetic Algorithm (GA) is utilized for searching the optimal design which guarantees a low mass and low power losses. Different from the conventional filter design methods, the proposed method treats LC as design variables which need to be optimised while ensuring the output power quality. First, relations among variables, operation conditions and constraints are built based on commercial data and circuit simulations. Then, the design and optimization are developed with these relations and a Pareto-front is finally given by GA. After that, the best design is obtained by an index integrating two objectives. Lastly, the design approach is verified by experiment where an FCS-MPC regulated converter was used as a particular example fed by three different LC filters

The Composite Face Effect Between Young and Older Chinese Adults Remains Stable

Holistic face perception is often considered to be a cornerstone of face processing. However, the development of the ability to holistically perceive faces in East Asian individuals is unclear. Therefore, we measured and compared holistic face processing in groups of Chinese children, young adults, and older adults by employing the complete composite face paradigm. The results demonstrate a similar magnitude of the composite effect in all three groups although face recognition performance in the task was better in young adults than in the two other groups. These findings suggest that holistic face perception in Eastern individuals is stable from late childhood to at least age 60, whereas face memory may be subject to later development and earlier decline.Peer Reviewe

Analysis and prediction of marine heatwaves in the Western North Pacific and Chinese coastal region

Over the past decade, marine heatwaves (MHWs) research has been conducted in almost all of the world’s oceans, and their catastrophic effects on the marine environment have gradually been recognized. Using the second version of the Optimal Interpolated Sea Surface Temperature analysis data (OISSTV2) from 1982 to 2014, this study analyzes six MHWs characteristics in the Western North Pacific and Chinese Coastal region (WNPCC, 100°E ∼ 180°E, 0° ∼ 65°N). MHWs occur in most WNPCC areas, with an average frequency, duration, days, cumulative intensity, maximum intensity, and mean intensity of 1.95 ± 0.21 times/year, 11.38 ± 1.97 days, 22.06 ± 3.84 days, 18.06 ± 7.67 °Cdays, 1.84 ± 0.50°C, and 1.49 ± 0.42 °C, respectively, in the historical period (1982 ~ 2014). Comparing the historical simulation results of 19 models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) with the OISSTV2 observations, five best-performing models (GFDL-CM4, GFDL-ESM4, AWI-CM-1-1-MR, EC-Earth3-Veg, and EC-Earth3) are selected for MHWs projection (2015 ~ 2100). The MHWs characteristics projections from these five models are analyzed in detail under the Shared Socio-economic Pathway (SSP) 1-2.6, 2-4.5 and 5-8.5 scenarios. The projected MHWs characteristics under SSP5-8.5 are more considerable than those under SSP1-2.6 and 2-4.5, except for the MHWs frequency. The MHWs cumulative intensity is 96.36 ± 56.30, 175.44 ± 92.62, and 385.22 ± 168.00 °Cdays under SSP1-2.6, 2-4.5 and 5-8.5 scenarios, respectively. This suggests that different emission scenarios have a crucial impact on MHW variations. Each MHWs characteristic has an obvious increasing trend except for the annual occurrences. The increase rate of MHWs cumulative intensity for these three scenarios is 1.02 ± 0.83, 3.83 ± 1.43, and 6.70 ± 2.61 °Cdays/year, respectively. The MHWs occurrence area in summer is slightly smaller than in winter, but the MHWs average intensity is stronger in summer than in winter