SLWE-Net: An improved lightweight U-Net for Sargassum extraction from GOCI images.

The Sargassum bloom has severely impacted the ecological environment of the East China Sea and the Yellow Sea, causing significant economic losses. In recent years, deep learning has seen extensive development due to its outstanding feature extraction capabilities. However, the deep learning process typically involves a large number of parameters and computations. To address this issue, this paper proposes a lightweight deep learning network based on the U-Net framework, called SLWE-NET, which uses lightweight modules to replace the feature extraction modules in U-Net. In this experiment, SLWE-Net performed the best in both extraction accuracy and model lightweight. Compared to the formal U-Net, the number of parameters decreased by 65.83 %, the model size reduced from 94.97 MB to 32.51 MB, and the mIoU increased to 93.81 %. Therefore, the method proposed in this paper is beneficial for Sargassum extraction and provides a basis for operational monitoring.

Fast Semantic Segmentation of Remote Sensing Images Using a Network That Integrates Global and Local Information.

Efficient processing of ultra-high-resolution images is increasingly sought after with the continuous advancement of photography and sensor technology. However, the semantic segmentation of remote sensing images lacks a satisfactory solution to optimize GPU memory utilization and the feature extraction speed. To tackle this challenge, Chen et al. introduced GLNet, a network designed to strike a better balance between GPU memory usage and segmentation accuracy when processing high-resolution images. Building upon GLNet and PFNet, our proposed method, Fast-GLNet, further enhances the feature fusion and segmentation processes. It incorporates the double feature pyramid aggregation (DFPA) module and IFS module for local and global branches, respectively, resulting in superior feature maps and optimized segmentation speed. Extensive experimentation demonstrates that Fast-GLNet achieves faster semantic segmentation while maintaining segmentation quality. Additionally, it effectively optimizes GPU memory utilization. For example, compared to GLNet, Fast-GLNet's mIoU on the Deepglobe dataset increased from 71.6% to 72.1%, and GPU memory usage decreased from 1865 MB to 1639 MB. Notably, Fast-GLNet surpasses existing general-purpose methods, offering a superior trade-off between speed and accuracy in semantic segmentation.

A Multi-Step Fusion Network for Semantic Segmentation of High-Resolution Aerial Images.

The demand for semantic segmentation of ultra-high-resolution remote sensing images is becoming increasingly stronger in various fields, posing a great challenge with concern to the accuracy requirement. Most of the existing methods process ultra-high-resolution images using downsampling or cropping, but using this approach could result in a decline in the accuracy of segmenting data, as it may cause the omission of local details or global contextual information. Some scholars have proposed the two-branch structure, but the noise introduced by the global image will interfere with the result of semantic segmentation and reduce the segmentation accuracy. Therefore, we propose a model that can achieve ultra-high-precision semantic segmentation. The model consists of a local branch, a surrounding branch, and a global branch. To achieve high precision, the model is designed with a two-level fusion mechanism. The high-resolution fine structures are captured through the local and surrounding branches in the low-level fusion process, and the global contextual information is captured from downsampled inputs in the high-level fusion process. We conducted extensive experiments and analyses using the Potsdam and Vaihingen datasets of the ISPRS. The results show that our model has extremely high precision.

Shale gas wastewater characterization: Comprehensive detection, evaluation of valuable metals, and environmental risks of heavy metals and radionuclides.

Shale gas wastewater (SGW) has great potential for the recovery of valuable elements, but it also poses risks in terms of environmental pollution, with heavy metals and naturally occurring radioactive materials (NORM) being of major concerns. However, many of these species have not been fully determined. For the first time, we identify the elements present in SGW from the Sichuan Basin and consequently draw a comprehensive periodic table, including 71 elements in 15 IUPAC groups. Based on it, we analyze the elements possessing recycling opportunities or with risk potentials. Most of the metal elements in SGW exist at very low concentrations (< 0.2 mg/L), including rare earth elements, revealing poor economic feasibility for recovery. However, salts, strontium (Sr), lithium (Li), and gallium (Ga) are in higher concentrations and have impressive market demands, hence great potential to be recovered. As for environmental burdens related to raw SGW management, salinity, F, Cl, Br, NO3-, Ba, B, and Fe, Cu, As, Mn, V, and Mo pose relatively higher threats in view of the concentrations and toxicity. The radioactivity is also much higher than the safety range, with the gross α activity and gross ß activity in SGW ranging from 3.71-83.4 Bq/L, and 1.62-18.7 Bq/L, respectively and radium-226 as the main component. The advanced combined process "pretreatment-disk tube reverse osmosis (DTRO)" with pilot-scale is evaluated for the safe reuse of SGW. This process has high efficiency in the removal of metals and total radioactivity. However, the gross α activity of the effluent (1.3 Bq/L) is slightly higher than the standard for discharge (1 Bq/L), which is thus associated with potential long-term environmental hazards.

Isotope tracers for lead and strontium sources in the Tieguanyin tea garden soils and tea leaves.

The concentrations of Pb & Sr in Tieguanyin tea leaves and soils from 15 tea gardens of Anxi, China, were determined and the sources of Pb & Sr in soil and leaf samples were analysed using isotope tracing technology. The results showed pH in soils had significant correlations to both acid-extractable Pb & Sr in soils and new leaves. The Pb concentration in leaves was significantly lower than that in soils, especially the acid-extractable Pb in soils. The low Bio-concentration Factor (BCF) indicated the bioavailable Pb in soils could not easily be transferred to leaves. The contribution rates of parent material were 61%-100% and 45%-100% for total Pb isotope and acid-extractable Pb isotope in soils, respectively, indicating a low impact of human activity. A sizeable influence of parent material for leaves was also observed, suggesting that Pb may be present in the dust-fall. Although Sr concentrations in leaves were not high, they exceeded that in soils. The high BCF also indicated that tea has a high capacity to accumulate Sr, with the coincidence that Sr87/Sr86 in the acid-extractable isotope in soils were similar to new leaves. A Pb-Sr joint tracer indicated that Sr in old and new leaves may be influenced by parent material and anthropogenic sources, respectively.

[Migration and Source Analysis of Heavy Metals in Vertical Soil Profiles of the Drylands of Xiamen City].

The concentrations of eight heavy metal elements (V, Cr, Co, Ni, Cu, Zn, Sr, and Pb) and the isotopic composition of Pb and Sr were determined in vertical soil profiles of the drylands of Xiamen City using ICP-MS and TIMS. The vertical distributions and leaching migration patterns of the heavy metals were also analyzed. The results showed that most of the heavy metals (except for Sr) were not enriched relative background values at most profile depths, which indicated that heavy metal content is less affected by exogenous sources. The migration coefficients of Sr were greater than 0 throughout the entire soil profile; Zn and Co were enriched in the surface soil; and Cr, Ni, and Cu were depleted throughout the profile. V and Pb were less influenced by external activities. Sr and Pb showed clear vertical migration characteristics, and the migration depth of Sr was greater than that of Pb. Factor analysis showed that the heavy metals mainly originated from natural sources, followed by agricultural activities, transportation, and other complex anthropogenic activities. Enrichment factor analysis showed that Sr was affected by exogenous sources to varying extents. The isotopic composition analysis of Pb and Sr showed that Pb was mainly derived from the parent material, whereas Sr was interpreted as deriving from both the parent material and anthropogenic activities, and tended to migrate to the subsurface soil horizons (30-70 cm).

Circadian clock associates with tumor microenvironment in thoracic cancers.

The application of cancer chronotherapy is to treat cancers based on at specific times during circadian rhythms. Previous studies have characterized the impact of circadian clock on tumorigenesis and specific immune cells. Here, by using multi-omics computation techniques, we systematically characterized the distinct roles of core circadian clock genes in thoracic cancers including lung adenocarcinoma, lung squamous cell carcinoma, and esophageal carcinoma. Strikingly, a wide range of core clock genes are epigenetically altered in lung adenocarcinomas and lung squamous cell carcinomas but not esophageal carcinomas. Further cancer hallmark analysis reveals that several core clock genes highly correlate with apoptosis and cell cycle such as RORA and PER2. Interestingly, our results reveal that CD4 and CD8 T cells are correlated with core clock molecules especially in lung adenocarcinomas and lung squamous cell carcinomas, indicating that chrono-immunotherapy may serve as a candidate option for future cancer management.

Chemical characteristics, sources, and formation mechanisms of PM2.5 before and during the Spring Festival in a coastal city in Southeast China.

Severe pollution caused by atmospheric particulate matter (PM) has become a global environmental issue. Samples of atmospheric PM were collected before and during the Chinese Spring Festival in Xiamen, a coastal city in Southeast China, to investigate their chemical characteristics, sources, and formation mechanisms. The results indicated that PM2.5 mass concentrations comprised 53.60% and 56.31% of total suspended particulates before and during the Spring Festival, respectively. Due to the halt of factory production and construction and the reduction of vehicle flow during the Spring Festival, the concentrations of organic carbon, elemental carbon and water soluble ions in PM2.5 decreased by 78.56%, 84.19% and 27.53%, respectively, compared with those before the Spring Festival. However, the concentrations of K+, Mg2+, Al, Sr, and Ba increased by 3121.76%, 571.67%, 183.71%, 180.15%, and 137.58%, respectively, resulting from the display of fireworks and firecrackers during the Spring Festival. Analysis of backward air mass trajectory indicated that the concentrations of PM2.5 and its components were dominated by local pollution sources before and during the Spring Festival. The relationships between meteorological conditions and pollutant concentrations showed that the secondary organic aerosol was generated from the heterogeneous reaction before the Spring Festival, and the secondary inorganic aerosol was formed by the photochemical reaction during the Spring Festival.

Changes in precipitating snow chemistry with seasonality in the remote Laohugou glacier basin, western Qilian Mountains.

Trace elements in the atmosphere could provide information about regional atmospheric pollution. This study presented a whole year of precipitation observation data regarding the concentrations of trace metals (e.g., Cr, Ni, Cu, Mn, Cd, Mo, Pb, Sb, Ti, and Zn), and a TEM-EDX (transmission electron microscope-energy dispersive X-ray spectrometer) analysis from June 2014 to September 2015 at a remote alpine glacier basin in Northwest China, the Laohugou (LHG) basin (4200 m a.s.l.), to determine the regional scale of atmospheric conditions and chemical processing in the free troposphere in the region. The results of the concentrations of trace metals showed that, although the concentrations generally were lower compared with that of surrounding rural areas (and cities), they showed an obviously higher concentration and higher EFs in winter (DJF) and a relatively lower concentration and lower EFs in summer (JJA) and autumn (SON), implying clearly enhanced winter pollution of the regional atmosphere in Northwest China. The TEM observed residue in precipitation that was mainly composed of types of dust, salt-dust, BC-fly ash-soot, and organic particles in precipitation, which also showed remarked seasonal change, showing an especially high ratio of BC-soot-fly ash particles in winter precipitation compared with that of other seasons (while organic particles were higher in the summer), indicating significant increased anthropogenic particles in the winter atmosphere. The source of increased winter anthropogenic pollutants mainly originated from emissions from coal combustion, e.g., the regional winter heating supply for residents and cement factories in urban and rural regions of Northwest China. Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric optical depth (AOD) also showed a significant influence of regional atmospheric pollutant emissions over the region in winter. In total, this work indicated that the atmospheric environment in western Qilian Mountains also showed enhanced anthropogenic pollution in winter, probably mainly caused by regional fossil fuel combustion.

Quantification of the impact of land-use changes on ecosystem services: a case study in Pingbian County, China.

Pingbian Miao Autonomous County is one of the poorest rural areas in China. Land-use changes, mainly driven by agricultural expansion and deforestation, may significantly impact ecosystem services and functions, but such effects are difficult to quantify. In the present study, Landsat image data were combined with the published coefficients about the world and China ecosystem to quantify land-use and ecosystem service changes in the mountainous area. A sensitivity analysis was employed to determine the effect of manipulating these coefficients on the estimated values. Our results show that during the past decades (from 1973 to 2004) forests and grasslands were converted into shrubland and cropland, respectively, resulting in a continuous decrease in ecosystem service (from 124.5 US$ x 10(6) in 1973 to 100.4 US$ x 10(6) in 2004). We found that the decrease of mixed forest in the study area was the largest contributor (i.e., 25.4 US$ x 10(6)) to the decline of the ecosystem service. Therefore we propose that future land-use policy should pay more attention to the crucial ecosystem functions of these forests (including tropical forest), and that it is necessary to balance the relationship between the livelihood of local farmers and environmental protection in order to maintain a healthy and stable ecosystem.