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The key to hyperspectral image (HSI) anomaly detection is effectively distinguishing anomalies from the background. Various detectors, such as low-rank sparse representation and background estimation, have been proposed. However, they usually exhibit poor performance due to complex backgrounds and similar anomalies and backgrounds. Considering that most of the pixels in HSI are background, the autoencoder can emphatically and automatically extract and reconstruct background features. And background suppression can further enhance the spectral differentiation of the anomalies and backgrounds. Therefore, we propose a new anomaly detector by integrating autoencoder and background suppression. First, the anomaly coefficient of HSI data is extracted via the local characteristics. The HSI data is fed into the 2Dimensional (2D) convolution autoencoder to reconstruct the background. Since the reconstruction background contains incorrect anomalies, the anomaly coefficient isused to suppress the reconstruction image. Then, the detection map is obtained with the Mahalanobis distance. The experiment is performed in different HSI datasets. The results illustrate that the proposed method is effective and outperforms other advanced methods in terms of detection performance. [ABSTRACT FROM AUTHOR]

The Madden–Julian Oscillation (MJO) is a crucial predictability source on a subseasonal-to-seasonal (S2S) timescale. Therefore, the models participating in the World Weather Research Programme and the World Climate Research Programme (WWRP/WCRP) S2S prediction project focus on accurately predicting and analyzing the MJO. This study provides a detailed description of the configuration within the Institute of Atmospheric Physics at the Chinese Academy of Sciences (IAP-CAS) S2S forecast system. We assess the accuracy of the IAP-CAS model's MJO forecast using traditional Real-time Multivariate MJO (RMM) analysis and cluster analysis. Then, we explain the reasons behind any bias observed in the MJO forecast. Comparing the 20-year hindcast with observations, we found that the IAP-CAS ensemble mean has a skill of 24 d. However, the ensemble spread still has potential for improvement. To examine the MJO structure in detail, we use cluster analysis to classify the MJO events during boreal winter into four types: fast-propagating, slow-propagating, standing, and jumping patterns of MJO. The model exhibits biases of overestimated amplitude and faster propagation speed in the propagating MJO events. Upon further analysis, it was found that the model forecasted a wetter background state. This leads to stronger forecasted convection and coupled waves, especially in the fast MJO events. The overestimation of the strength and length of MJO-coupled waves results in a faster MJO mode and quicker dissipation in the IAP-CAS model. These findings show that the IAP-CAS skillfully forecasts signals of MJO and its propagation, and they also provide valuable guidance for improving the current MJO forecast by developing the ensemble system and moisture forecast. [ABSTRACT FROM AUTHOR]

Automated harvesting systems rely heavily on precise and real-time fruit recognition, which is essential for improving efficiency and reducing labor costs. Strawberries, due to their delicate structure and complex growing environments, present unique challenges for automated recognition systems. Current methods predominantly utilize pixel-level and box-based approaches, which are insufficient for real-time applications due to their inability to accurately pinpoint strawberry locations. To address these limitations, this study proposes StrawSnake, a contour-based detection and segmentation network tailored for strawberries. By designing a strawberry-specific octagonal contour and employing deep snake convolution (DSConv) for boundary feature extraction, StrawSnake significantly enhances recognition accuracy and speed. The Multi-scale Feature Reinforcement Block (MFRB) further strengthens the model by focusing on crucial boundary features and aggregating multi-level contour information, which improves global context comprehension. The newly developed TongStraw_DB database and the public StrawDI_Db1 database, consisting of 1080 and 3100 high-resolution strawberry images with manually segmented ground truth contours, respectively, serves as a robust foundation for training and validation. The results indicate that StrawSnake achieves real-time recognition capabilities with high accuracy, outperforming existing methods in various comparative tests. Ablation studies confirm the effectiveness of the DSConv and MFRB modules in boosting performance. StrawSnake's integration into automated harvesting systems marks a substantial step forward in the field, promising enhanced precision and efficiency in strawberry recognition tasks. This innovation underscores the method's potential to transform automated harvesting technologies, making them more reliable and effective for practical applications. [ABSTRACT FROM AUTHOR]

Fuel cell vehicles are considered as the direct alternative to fuel vehicles due to their similar driving range and refueling time. The United Nations World Forum for Harmonization of Vehicle Regulations (UN/WP29) released the Global Technical Regulation on Hydrogen and Fuel Cell Vehicles (GTR13) in July 2013, which was the first international regulation in the field of fuel cell vehicles. There exist some differences between GTR13 and the existing safety technical specifications and standards in China. This paper studied the safety requirements of the GTR13 compressed hydrogen storage system, analyzed the current hydrogen storage safety standards for fuel cell vehicles in China, and integrated the advantages of GTR13 to propose relevant suggestions for future revision of hydrogen storage standards for fuel cell vehicle in China. [ABSTRACT FROM AUTHOR]

Electrolytes with anion‐dominated solvation are promising candidates to achieve dendrite‐free and high‐voltage potassium metal batteries. However, it's challenging to form anion‐reinforced solvates at low salt concentrations. Herein, we construct an anion‐reinforced solvation structure at a moderate concentration of 1.5 M with weakly coordinated cosolvent ethylene glycol dibutyl ether. The unique solvation structure accelerates the desolvation of K+, strengthens the oxidative stability to 4.94 V and facilitates the formation of inorganic‐rich and stable electrode‐electrolyte interface. These enable stable plating/stripping of K metal anode over 2200 h, high capacity retention of 83.0 % after 150 cycles with a high cut‐off voltage of 4.5 V in K0.67MnO2//K cells, and even 91.5 % after 30 cycles under 4.7 V. This work provides insight into weakly coordinated cosolvent and opens new avenues for designing ether‐based high‐voltage electrolytes. [ABSTRACT FROM AUTHOR]

A novel synthesis method has been developed for the construction of functionalized 2,4-diarylpyridines. The reaction involves several key processes, including a reduction reaction, Michael reaction, decarboxylation, intramolecular cyclization, oxidation, ring-opening and aromatization reaction. All of these processes are facilitated by heating a mixture of the starting materials in an environmentally benign solvent, propylene carbonate (PC), with the oxidant (air) and the catalyst Cu(OAc)2. This cascade reaction not only forms two new bonds but also cleaves three existing bonds in a single pot. The protocol presented in this study is a valuable tool for synthesizing functionalized unsymmetrical 2,4-diarylpyridines. [ABSTRACT FROM AUTHOR]

Tea (Camellia sinensis L.), an important economic crop in China, is highly favored by the population. Microorganisms can help plants acquire soil nutrients and cope with various stresses, and the diversity and structural composition of the rhizosphere microbial community of tea plants are crucial for ensuring the growth and quality of tea leaves. Therefore, we studied the differences in soil nutrients, enzyme activities and microbial communities between two different tea gardens (a tableland tea garden and an ancient tea plantation) in different ecological niches (rhizosphere and bulk soil), as well as the impacts they experienced. The results show that the soil pH levels in the ancient tea plantation were within the optimal range (4.5–5.5), and both rhizosphere and bulk soil nutrients in the ancient tea plantation were higher than those in the tableland tea garden, except for TP; the nutrients in the rhizospheres of ancient tea trees were more abundant. Moreover, higher enzyme activities were observed in the rhizosphere soil than those in the bulk soil in both tea gardens, and both the tableland and ancient tea garden soils were subjected to a certain degree of C&N limitations. The microbial communities of the two tea gardens were dominated by bacteria, but the α-diversity of the bacterial and fungal communities in the rhizosphere soil of the tableland tea garden was higher than that in the ancient tea plantation. The bacterial communities were largely dominated by Proteobacteria and Acidobacteriota, and the fungal communities were largely dominated by Ascomycota and Basidiomycota in the two tea gardens. The structure and composition of soil bacterial communities in the two tea gardens were similar, whereas significant differences were observed in the fungal communities. In addition, soil pH and SWC were the key factors influencing the fungal community in both the rhizosphere and bulk soil in the two tea gardens, whereas the bacterial community was more significantly affected by soil TN, NH4+-N, SWC and DON. These findings provide essential foundational information for the preservation of ancient tea plantations, the ecological adaptability of ancient tea trees and the management of tableland tea gardens. [ABSTRACT FROM AUTHOR]

Rikenella microfusus is an essential intestinal probiotic with great potential. The latest research shows that imbalance in the intestinal flora are related to the occurrence of various diseases, such as intestinal diseases, immune diseases, and metabolic diseases. Rikenella may be a target or biomarker for some diseases, providing a new possibility for preventing and treating these diseases by monitoring and optimizing the abundance of Rikenella in the intestine. However, the current monitoring methods have disadvantages, such as long detection times, complicated operations, and high costs, which seriously limit the possibility of clinical application of microbiome-based treatment options. Therefore, the intention of this study was to evolve an enriched aptamer library to be used for specific labeling of R. microfusus, allowing rapid and low-cost detection methods and, ultimately the construction of aptamer-based biosensors. In this study, we used Rikenella as the target bacterium for an in vitro whole Cell-SELEX (Systematic Evolution of Ligands by EXponential Enrichment) to evolve and enrich specific DNA oligonucleotide aptamers. Five other prominent anaerobic gut bacteria were included in this process for counterselection and served as control cells. The aptamer library R.m-R13 was evolved with high specificity and strong affinity (Kd = 9.597 nM after 13 rounds of selection). With this enriched aptamer library, R. microfusus could efficiently be discriminated from the control bacteria in complex mixtures using different analysis techniques, including fluorescence microscopy or fluorometric suspension assays, and even in human stool samples. These preliminary results open new avenues toward the development of aptamer-based microbiome bio-sensing applications for fast and reliable monitoring of R. microfusus.