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Abstract The contradiction between the demand of urban economic development and ecological environmental protection is becoming more and more prominent, and the reasonable construction of ecological corridors is of great significance for the protection of urban ecosystems. Taking Changle District of Fuzhou coastal city as an example, this study proposes an ecological source identification method from the perspective of “structure-function” by combining Morphological Spatial Pattern Analysis (MSPA) and Remote Sensing Ecological Index (RSEI) methods, and constructs and optimizes ecological corridors by means of the model of Minimum Cumulative Resistance (MCR) and Circuit Theory. The results show that: (1) a total of 20 ecological sources were extracted based on MSPA-RSEI; (2) a total of 31 ecological corridors were extracted based on Linkage Mapper, including 8 Level 1 corridors, 13 Level 2 corridors, and 10 Level 3 corridors; (3) the Pinch Point and Barrier Mapper software was utilized to identify 6.01 km2 and 2.59 km2, respectively, as Level 1 “pinch points” and barrier points within the study area. The land use types of these areas were as follows: The majority of “pinch points” were forested (60.72%), while the majority of barrier points were composed of construction land (55.27%), bare land (17.27%), and cultivated land (13.90%). (4) the optimal width of the corridor was determined by using the buffer zone method and gradient analysis: 30 m for the Level 1 corridor, 60 m for the Level 2 and Level 3 corridors, and the average current density before and after the construction of the eco-corridor was increased from 0.1881 to 0.4992. The results of the study can provide a reference for the decision-making of the ecological construction of the Changle District and the coastal urban areas of eastern China.

Abstract Aqueous rechargeable batteries using abundant multi‐ion cations have received increasing attention in the energy storage field for their high safety and low cost. Layered double hydroxides (LDHs) possess a two‐dimensional structure and exhibit great potential as cathodes for multi‐ion intercalation. However, the insufficient active sites of LDHs result in low capacities in the discharging process. Interestingly, the LDHs after the deprotonation process exhibit favorable electrochemical performance of multi‐cation intercalation. The deprotonation process of LDHs has been widely found in the oxygen evolution reaction and energy storage field, where LDHs lose H in laminates and converts to deprotonated γ‐phase MOOHs (MOOs). Herein, we take a comprehensive overview of the dynamics structure transformation of the deprotonation process of LDHs. Furthermore, the development of advanced aqueous battery cathode and metal battery anode based on deprotonated LDHs for energy storage is explored and summarized. Finally, the perspective of deprotonated LDHs in the energy storage field is discussed.

Abstract Selenium (Se), the world's oldest optoelectronic material, has been widely applied in various optoelectronic devices such as commercial X‐ray flat‐panel detectors and photovoltaics. However, despite the rare and widely‐dispersed nature of Se element, a sustainable recycling of Se and other valuable materials from spent Se‐based devices has not been developed so far. Here a sustainable strategy is reported that makes use of the significantly higher vapor pressure of volatile Se compared to other functional layers to recycle all of them from end‐of‐life Se‐based devices through a closed‐space evaporation process, utilizing Se photovoltaic devices as a case study. This strategy results in high recycling yields of ≈ 98% for Se and 100% for other functional materials including valuable gold electrodes and glass/FTO/TiO2 substrates. The refabricated photovoltaic devices based on these recycled materials achieve an efficiency of 12.33% under 1000‐lux indoor illumination, comparable to devices fabricated using commercially sourced materials and surpassing the current indoor photovoltaic industry standard of amorphous silicon cells.

Under the new demand model of Agriculture 4.0, automated spraying is a very complex task in precision agriculture, which needs to be combined with a computerized vision perception system to distinguish the plant leaf density and execute the spraying operation in real-time accordingly. Aiming at the accurate determination of grape leaf density, an image leaf density determination method based on the lightweight Vision Transformer (ViT) architecture is proposed, which designs a fusion data augmentation method containing a dual augmentation spatial extension and weather data augmentation method, where the former adopts the pixel augmentation and spatial augmentation for the original image processing, and the latter realizes the data augmentation from the empirical point of view adapted to the agricultural operation environment, and fuses the two in order to expand the sample capacity of the grape leaf density image, which then enhances the model's generalization ability and robustness. The lightweight ViT model has self-attention that can automatically and efficiently extract high-frequency local feature representations and use the two-branch structure to mix high-frequency and low-frequency information to form grapevine-leaf density features in the region of interest. The semantic analysis of the feature extraction layer is parsed using t-SNE and histogram methods, which improves the transparency of the model from the multidimensional with frequency domain distribution space. The experimental results show that the fusion data augmentation method can effectively improve the model recognition accuracy, and the accuracy of comparing the included data augmentation methods is improved by 0.55 % and 3.46 %, respectively. The accuracy of recognizing all four types of grape leaf densities exceeded 94 %, and the MCC reached 90.39 %. In addition, the proposed lightweight ViT improves the accuracy by at least 0.34 % with FLOPs of only 0.6 G compared to the popular MobileViT. The proposed method of this work has high recognition speed and accuracy, which can provide practical technical support for plant protection spraying robots and improve the profitability of growers based on the reduction of pesticide residues.

Recent advances in luminescent materials have highlighted zero-dimensional (0D) hybrid metal halides as highly efficient candidates. Notably, In3+-based organic-inorganic metal halides (OIMHs) are increasingly recognized as promising materials for solid-state light emission. However, the relatively low light yields of these materials significantly limit their application in advanced optoelectronic devices. In this study, we designed a novel 0D hybrid indium halide, (C13H14N3)3InBr6, where C13H14N3 represents 1,3-diphenylguanidine. This compound features a structure in which the halogen anionic polyhedron is completely isolated by large guanidine cations and is regularly arranged at considerable distances on these cations, thus forming an almost ideal host-guest structure. Impressively, the 0D indium halide exhibits intrinsic broadband yellow-orange light emission, achieving a photoluminescence quantum yield (PLQY) of 86.12%, which is the highest PLQY ever reported for In-based OIMHs. Additionally, we successfully fabricated white-light-emitting diodes (WLEDs) using (C13H14N3)3InBr6 as a yellow phosphor, thereby demonstrating the potential of novel guanidine-based indium halides in solid-state lighting applications. [ABSTRACT FROM AUTHOR]

Mycotoxins, ubiquitous contaminants in food, present a global threat to human health and well-being. Mitigation efforts, such as the implementation of sound agricultural practices, thorough food processing, and the advancement of mycotoxin control technologies, have been instrumental in reducing mycotoxin exposure and associated toxicity. To comprehensively assess mycotoxins and their toxicodynamic implications, the deployment of effective and predictive strategies is imperative. Understanding the manner of action, transformation, and cumulative toxic effects of mycotoxins, moreover, their interactions with food matrices can be gleaned through gene expression and transcriptome analyses at cellular and molecular levels. MicroRNAs (miRNAs) govern the expression of target genes and enzymes that play pivotal roles in physiological, pathological, and toxicological responses, whereas acute phase proteins (APPs) exert regulatory control over the metabolism of therapeutic agents, both endogenously and posttranscriptionally. Consequently, this review aims to consolidate current knowledge concerning the regulatory role of miRNAs in the initiation of toxicological pathways by mycotoxins and explores the potential of APPs as biomarkers following mycotoxin exposure. The findings of this research highlight the potential utility of miRNAs and APPs as indicators for the detection and management ofmycotoxins in food through biological processes. Thesemarkers offer promising avenues for enhancing the safety and quality of food products. [ABSTRACT FROM AUTHOR]