A Multimodal Visual Encoding Model Aided by Introducing Verbal Semantic Information

Biological research has revealed that the verbal semantic information in the brain cortex, as an additional source, participates in nonverbal semantic tasks, such as visual encoding. However, previous visual encoding models did not incorporate verbal semantic information, contradicting this biological finding. This paper proposes a multimodal visual information encoding network model based on stimulus images and associated textual information in response to this issue. Our visual information encoding network model takes stimulus images as input and leverages textual information generated by a text-image generation model as verbal semantic information. This approach injects new information into the visual encoding model. Subsequently, a Transformer network aligns image and text feature information, creating a multimodal feature space. A convolutional network then maps from this multimodal feature space to voxel space, constructing the multimodal visual information encoding network model. Experimental results demonstrate that the proposed multimodal visual information encoding network model outperforms previous models under the exact training cost. In voxel prediction of the left hemisphere of subject 1's brain, the performance improves by approximately 15.87%, while in the right hemisphere, the performance improves by about 4.6%. The multimodal visual encoding network model exhibits superior encoding performance. Additionally, ablation experiments indicate that our proposed model better simulates the brain's visual information processing

Effects of Anthropogenic Emission Control and Meteorology Changes on the Inter-Annual Variations of PM2.5–AOD Relationship in China

We identified controlling factors of the inter-annual variations of surface PM2.5–aerosol optical depth (AOD) relationship in China from 2006 to 2017 using a nested 3D chemical transport model—GEOS-Chem. We separated the contributions from anthropogenic emission control and meteorological changes by fixing meteorology at the 2009 level and fixing anthropogenic emissions at the 2006 level, respectively. Both observations and model show significant downward trends of PM2.5/AOD ratio (η, p < 0.01) in the North China Plain (NCP), the Yangtze River Delta (YRD) and the Pearl River Delta (PRD) in 2006–2017. The model suggests that the downward trends are mainly attributed to anthropogenic emission control. PM2.5 concentration reduces faster at the surface than aloft due to the closeness of surface PM2.5 to emission sources. The Pearson correlation coefficient of surface PM2.5 and AOD (rPM-AOD) shows strong inter-annual variations (±27%) but no statistically significant trends in the three regions. The inter-annual variations of rPM-AOD are mainly determined by meteorology changes. Except for the well-known effects from relative humidity, planetary boundary layer height and wind speed, we find that temperature, tropopause pressure, surface pressure and atmospheric instability are also important meteorological elements that have a strong correlation with inter-annual variations of rPM-AOD in different seasons. This study suggests that as the PM2.5–AOD relationship weakens with reduction of anthropogenic emissions, validity of future retrieval of surface PM2.5 using satellite AOD should be carefully evaluated

Effects of Meteorology Changes on Inter-Annual Variations of Aerosol Optical Depth and Surface PM2.5 in China—Implications for PM2.5 Remote Sensing

PM2.5 retrieval from satellite-observed aerosol optical depth (AOD) is still challenging due to the strong impact of meteorology. We investigate influences of meteorology changes on the inter-annual variations of AOD and surface PM2.5 in China between 2006 and 2017 using a nested 3D chemical transport model, GEOS-Chem, by fixing emissions at the 2006 level. We then identify major meteorological elements controlling the inter-annual variations of AOD and surface PM2.5 using multiple linear regression. We find larger influences of meteorology changes on trends of AOD than that of surface PM2.5. On the seasonal scale, meteorology changes are beneficial to AOD and surface PM2.5 reduction in spring (1–50%) but show an adverse effect on aerosol reduction in summer. In addition, major meteorological elements influencing variations of AOD and PM2.5 are similar between spring and fall. In winter, meteorology changes are favorable to AOD reduction (−0.007 yr−1, −1.2% yr−1; p < 0.05) but enhanced surface PM2.5 between 2006 and 2017. The difference in winter is mainly attributed to the stable boundary layer that isolates surface PM2.5 from aloft. The significant decrease in AOD over the years is related to the increase in meridional wind speed at 850 hPa in NCP (p < 0.05). The increase of surface PM2.5 in NCP in winter is possibly related to the increased temperature inversion and more stable stratification in the boundary layer. This suggests that previous estimates of wintertime surface PM2.5 using satellite measurements of AOD corrected by meteorological elements should be used with caution. Our findings provide potential meteorological elements that might improve the retrieval of surface PM2.5 from satellite-observed AOD on the seasonal scale

Mercury speciation, transformation, and transportation in soils, atmospheric flux, and implications for risk management : a critical review

Mercury (Hg) is a potentially harmful trace element in the environment and one of the World Health Organization's foremost chemicals of concern. The threat posed by Hg contaminated soils to humans is pervasive, with an estimated 86 Gg of anthropogenic Hg pollution accumulated in surface soils worldwide. This review critically examines both recent advances and remaining knowledge gaps with respect to cycling of mercury in the soil environment, to aid the assessment and management of risks caused by Hg contamination. Included in this review are factors affecting Hg release from soil to the atmosphere, including how rainfall events drive gaseous elemental mercury (GEM) flux from soils of low Hg content, and how ambient conditions such as atmospheric O3 concentration play a significant role. Mercury contaminated soils constitute complex systems where many interdependent factors, including the amount and composition of soil organic matter and clays, oxidized minerals (e.g. Fe oxides), reduced elements (e.g. S2−), as well as soil pH and redox conditions affect Hg forms and transformation. Speciation influences the extent and rate of Hg subsurface transportation, which has often been assumed insignificant. Nano-sized Hg particles as well as soluble Hg complexes play important roles in soil Hg mobility, availability, and methylation. Finally, implications for human health and suggested research directions are put forward, where there is significant potential to improve remedial actions by accounting for Hg speciation and transportation factors

Exploring the mechanism of Suanzaoren decoction in treatment of insomnia based on network pharmacology and molecular docking

Objective: To explore the functional mechanisms of Suanzaoren decoction (SZRD) for treating insomnia using network pharmacology and molecular docking.Methods: The active ingredients and corresponding targets of SZRD were obtained from the Traditional Chinese Medicine Systems Pharmacology database, and then, the names of the target proteins were standardized using the UniProt database. The insomnia-related targets were obtained from the GeneCards, DisGeNET, and DrugBank databases. Next, a Venn diagram comprising the drug and disease targets was created, and the intersecting targets were used to draw the active ingredient-target network diagram using Cytoscape software. Next, the STRING database was used to build a protein-protein interaction network, followed by cluster analysis using the MCODE plug-in. The Database for Annotation, Visualization, Integrated Discovery (i.e., DAVID), and the Metascape database were used for Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. AutoDock Vina and Pymol software were used for molecular docking.Results: SZRD contained 138 active ingredients, corresponding to 239 targets. We also identified 2,062 insomnia-related targets, among which, 95 drug and disease targets intersected. The GO analysis identified 490, 62, and 114 genes related to biological processes, cellular components, and molecular functions, respectively. Lipid and atherosclerosis, chemical carcinogen-receptor activation, and neuroactive ligand-receptor interaction were the most common pathways in the KEGG analysis. Molecular docking demonstrated that the primary active components of SZRD for insomnia had good binding capabilities with the core proteins in PPI network.Conclusion: Insomnia treatment with SZRD involves multiple targets and signaling pathways, which may improve insomnia by reducing inflammation, regulating neurotransmitters

Cost estimate of multi-pollutant abatement from the power sector in the Yangtze River Delta region of China

Multi-pollutant emission data with various control measure information are provided. We use LP algorithm to optimize the cost estimate of multi-pollutant abatements. High reduction percent will raise the cost exponentially for different regions. For different regions, the cost for the same removal percentage can vary dramatically. a r t i c l e i n f o t r a c t Coal-fired power plants in China have emitted multiple pollutants including sulfur dioxide, nitrogen oxides and fine particulates, contributing to serious environmental impairments and human health issues. To meet ambient air quality standards, the installation of effective pollution control technologies are required and consequently, the cost of installing or retrofitting control technologies is an important economic and political concern. A multi-pollutant control cost model, CoST CE, is developed to calculate the cost of multipollutant control strategies in the Yangtze River Delta region (YRD) of China, adopting an LP algorithm to optimize the sorting of control technology costs and quickly obtain a solution. The output shows that total costs will increase along with emission abatement. Meanwhile, the slope becomes steeper as greater emission reductions are pursued, due to the need to install highly effective, but expensive, technologies like SCR and FF. Moreover, it is evident that the cost curve shapes, maximum abatement potential and total cost for the three provinces in the YRD region are quite different due to differences in power plant type and technologies, current emission levels and existing pollution controls. The results from this study can aid policy makers to develop cost-effective control strategies for the power sector

Implementing the Minamata Convention on Mercury: Will China Deliver?

China has undertaken a major shift in its position on mercury as an environmental problem over the last decade and a half. It ratified the Minamata Convention (MC) in 2016 and by doing so has committed to implement the treaty objectives. This article asks: How do we explain China’s will and ability to implement its MC obligations? There is little systematic knowledge about the main factors underlying implementation of international mercury objectives in China, hence this article contributes new research on this important topic. We examine the implementation process, focusing on the coal sector and differentiate between indirect effects from other policies and direct efforts to implement obligations. We find that China has moved toward stricter regulation of mercury emissions and direct implementation of the Minamata Convention in the coal sector. However, our study shows that local implementation capacity needs improvement.Implementing the Minamata Convention on Mercury: Will China Deliver?acceptedVersio