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Selenium (Se) is involved in the growth and development of plants. More importantly, Se from plant foods is a primary source of Se intake for humans and animals. Improving the Se content in vegetables through biofortification is an effective way to solve the hidden hunger induced by Se deficiency. This study demonstrated the effect of different exogenous Se application concentrations on the growth, antioxidative capacity, and nutritional quality of purple lettuce (Lactuca sativa var. crispa L. “Purple Rome”) at the seedling stage. The low Se application concentration (≤8 μM) significantly promoted the lettuce seedling growth. Conversely, the high Se application concentration (16 μM) inhibited the seedling growth and overproduced the reactive oxygen species in lettuce root tips, which caused oxidative damage to membrane lipids and cell death. Furthermore, the enzyme activities and gene expression of the antioxidant enzymes, superoxide dismutase-peroxidase, and catalase, were significantly increased under exogenous Se application. The exogenous Se application significantly increased the accumulation of nutrients in purple lettuce at the seedling stage. Remarkably, the exogenous Se application concentrations were significantly positively related to the Se and anthocyanin contents. The gene expression levels of chalcone synthase were positively correlated with the anthocyanin contents under exogenous Se application. This study contributes to the role of Se in lettuce growth and provides a reference for producing high-quality purple lettuce rich in Se and anthocyanins.

The main purpose of this article is to explore the mechanism of action of carbon-based materials in the anaerobic digestion (AD) production of medium-chain carboxylic acids (MCCA). Currently, there are various methods to increase production, but there is no review on how carbon-based materials improve MCCA. This paper first introduced the chain elongation (CE) technology, focusing on the factors affecting the production of MCCA by AD, such as pH, temperature, the ratio of electron donor (ED) to an electron acceptor (EA), substrate type, and other related factors. This article introduces the preparation and characteristics of carbon-based materials, as well as the effect and mechanism of adding carbon-based materials to AD acid production. Finally, the shortcomings of the current research were pointed out, and future research directions were prospected, aiming to provide a reference for improving the efficiency of AD of MCCA using carbon-based materials.

Rural land consolidation projects (RLCPs) have become one of the largest organized human activities to change land use patterns and impact terrestrial ecosystems, and it may also be an important precondition to improving ecosystem service value (ESV). Evaluating the change in ecosystem service value (ESV) is an important basis for measuring the effectiveness of RLCPs. Therefore, this paper, taking RLCPs implemented at County Level in Hubei Province, China, as an example, uses the improved ESV evaluation model to analyze the spatial differentiation of ESV change in RLCPs and then adopts geographic detectors and a geographically weighted regression model to identify the dominant factors affecting the ESV change in RLCPs. The results showed that (1) although RLCPs make the unevenness of land use obvious, they reduce the complexity of land use evidently and improve the dominance of land use significantly; (2) The ESV of RLCPs in 71 counties of Hubei Province increased, with an average increase of USD 2.37 × 107 a−1. The ESV increase is large in central Hubei, while small in eastern and western Hubei. However, the increase rate of ESV is high in eastern and central-north Hubei, while low in western and central-south Hubei. This indicates that RLCPs can effectively promote ESV, but there are significant regional differences, and (3) the ESV increase is positively correlated with GDP and construction scale, but negatively linked with investment and per capita income of rural residents. The ESV increase rate is negatively associated with cultivated land proportion and land use diversification index change, but it is positively related to the change in the land use evenness index. However, their driving effects have significant spatial heterogeneity.

The development of diversity-oriented synthesis based on fluorine-containing building blocks has been one of the hot research fields in fluorine chemistry. β-CF3-1,3-enynes, as one type of fluorine-containing building blocks, have attracted more attention in the last few years due to their distinct reactivity. Numerous value-added trifluoromethylated or non-fluorinated compounds which have biologically relevant structural motifs, such as O-, N-, and S-heterocycles, carboncycles, fused polycycles, and multifunctionalized allenes were synthesized from these fluorine-containing building blocks. This review summarizes the most significant developments in the area of synthesis of organofluorine compounds based on β-CF3-1,3-enynes, providing a detailed overview of the current state of the art.

In recent years, supervised learning, represented by deep learning, has shown good performance in remote sensing image scene classification with its powerful feature learning ability. However, this method requires large-scale and high-quality handcrafted labeled datasets, which leads to a high cost of obtaining annotated samples. Self-supervised learning can alleviate this problem by using unlabeled data to learn the image’s feature representation and then migrate to the downstream task. In this study, we use an encoder–decoder structure to construct a self-supervised learning architecture. In the encoding stage, the image mask is used to discard some of the image patches randomly, and the image’s feature representation can be learned from the remaining image patches. In the decoding stage, the lightweight decoder is used to recover the pixels of the original image patches according to the features learned in the encoding stage. We constructed a large-scale unlabeled training set using several public scene classification datasets and Gaofen-2 satellite data to train the self-supervised learning model. In the downstream task, we use the encoder structure with the masked image patches that have been removed as the backbone network of the scene classification task. Then, we fine-tune the pre-trained weights of self-supervised learning in the encoding stage on two open datasets with complex scene categories. The datasets include NWPU-RESISC45 and AID. Compared with other mainstream supervised learning methods and self-supervised learning methods, our proposed method has better performance than the most state-of-the-art methods in the task of remote sensing image scene classification.

Inappropriate organic fertilizer application may cause serious environmental risks, especially nitrogen (N) and phosphorus (P) losses. To achieve a win–win for high yield and environmental protection in organic agriculture, it was essential to demonstrate the relationship between the organic fertilizer input, rice yields, and risks of N and P losses. Based on a rice and green manure cropping rotation field experiment in the Yangtze River Delta of China, the effects of organic fertilization rates on the dynamics of surface water N and P concentrations and rice grain yields were determined. The results showed that the N (total N, ammonium-nitrogen, nitrate-nitrogen) and P (total P and dissolved P) concentrations in surface water immediately and greatly reached the highest values 1 day after basal fertilization and topdressing fertilization. Then, the N and P concentrations sharply decreased and were maintained at a relatively low level. The initial 3 and 7 days after organic fertilization were the high-risk periods for controlling N and P runoff losses. The surface water N and P concentrations had a positive correlation with the organic fertilization rate in high-risk periods. Besides, the effects of organic fertilization on surface water P concentrations existed longer than those of N concentrations. The rice grain yields increased with the increase in organic fertilization rates, but high organic fertilizer input (>225 kg N per hectare) did not increase the grain yield. Meanwhile, the high organic fertilizer input had the highest risks for N and P losses. Therefore, in organic rice farming, organic fertilization rates with 150~200 kg N per hectare are the optimal organic fertilizer input, with relatively high grain yields and low N and P losses.

In view of the differences of land use structure and ecological environment changes caused by land consolidation projects with different features and landforms, this paper uses the modified ecosystem service value estimation model to quantitatively evaluate the change patterns of the ecosystem service value (ESV) of land consolidation, development and arrangement projects in Hubei Province under plains, hills and mountains to provide a theoretical basis for the ecological transformation of land consolidation. The results show that, compared with the pre-land consolidation period, (1) the total amount of ESV in the land consolidation project areas has increased, whereas the land development and arrangement project areas have decreased. Under the same nature, the growth rate of land consolidation project areas is as follows: hills < plains < mountains, and the loss rate of land development and arrangement project areas are as follows: mountains > plains > hills and hills > mountains > plains, respectively. Under the same landform, the total loss rate of ESV in land development project areas is slightly lower than that in land arrangement project areas. (2) The total amount of ESV in the land consolidation project areas under different natures and landforms of the supply service function shows a decreasing trend, and the total amount of ESV of the adjustment service, support service and cultural service function shows an increasing trend in the land consolidation project areas, whereas the land development and arrangement project areas show a decreasing trend. There is an obvious value transformation process of “ecology for production” in the land development and arrangement areas.

In blasting operation, some undesirable impacts, such as fly-rock, fragmentation, and back break, are induced. If the blasting design is not optimized, these mentioned impacts would reduce the blasting efficiency. To improve and optimize the blast design, blasting effect evaluation is essential. Due to the complexity of interactions among blasting parameters, empirical methods may not be appropriate for blast design optimization. A two-level mathematical model based on fuzzy mathematics, is proposed in this work. In total, 11 typical parameters were chosen and classified into three groups. The blasting effect is evaluated from three aspects, and then the comprehensive evaluation is given. A blasting effect evaluation system was developed based on the mentioned method on the platform of VC++. Some other techniques, such as image processing, were integrated into the system, which allowed for obtaining all of the parameters rapidly and conveniently. The system was applied in practical bench blast engineering. The results obtained from the system can provide effective information for the optimization of the next blast design.

Object tracking is a crucial research subfield in computer vision and it has wide applications in navigation, robotics and military applications and so on. In this paper, the real-time visualization of 3D point clouds data based on the VLP-16 3D Light Detection and Ranging (LiDAR) sensor is achieved, and on the basis of preprocessing, fast ground segmentation, Euclidean clustering segmentation for outliers, View Feature Histogram (VFH) feature extraction, establishing object models and searching matching a moving spherical target, the Kalman filter and adaptive particle filter are used to estimate in real-time the position of a moving spherical target. The experimental results show that the Kalman filter has the advantages of high efficiency while adaptive particle filter has the advantages of high robustness and high precision when tested and validated on three kinds of scenes under the condition of target partial occlusion and interference, different moving speed and different trajectories. The research can be applied in the natural environment of fruit identification and tracking, robot navigation and control and other fields.