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Radar emitter signal sorting (RESS) is a crucial process in contemporary electronic battlefield situation awareness. Separating pulses belonging to the same radar emitter from interleaved radar pulse sequences with a lack of prior information, high density, strong overlap, and wide parameter distribution has attracted increasing attention. In order to improve the accuracy of RESS under scenarios with limited labeled samples, this paper proposes an RESS model called TR-RAGCN-AFF-RESS. This model transforms the RESS problem into a pulse-by-pulse classification task. Firstly, a novel weighted adjacency matrix construction method was proposed to characterize the structural relationships between pulse attribute parameters more accurately. Building upon this foundation, two networks were developed: a Transformer(TR)-based interleaved pulse sequence temporal feature extraction network and a residual attention graph convolutional network (RAGCN) for extracting the structural relationship features of attribute parameters. Finally, the attention feature fusion (AFF) algorithm was introduced to fully integrate the temporal features and attribute parameter structure relationship features, enhancing the richness of feature representation for the original pulses and achieving more accurate sorting results. Compared to existing deep learning-based RESS algorithms, this method does not require many labeled samples for training, making it better suited for scenarios with limited labeled sample availability. Experimental results and analysis confirm that even with only 10% of the training samples, this method achieves a sorting accuracy exceeding 93.91%, demonstrating high robustness against measurement errors, lost pulses, and spurious pulses in non-ideal conditions. [ABSTRACT FROM AUTHOR]

Artificial photosynthesis has been regarded as a promising solution toward solar energy conversion, generating storable and transportable chemical fuels such as hydrogen (H2) and hydrogen peroxide (H2O2). However, the design of robust catalytic sites not only affects the activity, but also identify the atomic‐level correlation between active sites and natural photosynthesis performance. Herein, a synthesis method of single‐atomic Iron (Fe) active sites anchored on novel covalent organic framework (COF) for the production of H2O2 under visible light irradiation. When benzyl alcohol is the most sacrificial agent, the state‐of‐the‐art Fe‐based COF exhibits an excellent H2O2 generation rate of 4130 µmol g−1 h−1, over 5.3 times higher than that of pristine COF, achieving an apparent quantum yield of 6.4% at 420 nm. The enhanced photocatalytic performance is ascribed to the synergistic effect of atomically dispersed Fe sites and COF hosts, reducing the reaction energy barrier for the formation of *OOH intermediates and optimizing the adsorption of O2 and thus promoting two‐electron oxygen reduction reaction (ORR). This work establishes an atomic‐level engineering approach to build atomically dispersed Fe active sites on COF photocatalysts and provides in‐depth insight upon the ORR mechanism for promising artificial photosynthesis of H2O2. [ABSTRACT FROM AUTHOR]

8,9-Dimethoxyphenanthridine derivatives, as potential antitumor drugs, need modification to improve their biocompatibility and water solubility. Reported here is a strategy to access C-heteroaryl glycosides by photoredox catalysis. C6-glycosylated phenanthridine derivatives are synthesized from biphenyl isocyanides and glycosyl bromides. The reaction conditions are mild and widely applicable, with anomeric α selectivity and good functional group tolerance. [ABSTRACT FROM AUTHOR]

The technology and service modes of logistics industry are changing greatly in smart economy, and innovation is becoming new development engine, which promotes the urgent transformation requirement of teaching system of logistics engineering majors in universities. Based on the data from logistics engineering majors in Chinese universities in 2021, a relevant study on the undergraduate logistics engineering major is carried out. Along with 'ability-motivation-opportunity' (AMO) theory, this paper analyses the influence of ability, motivation and opportunity on the transformation. The current situation of teaching system, the existing problems and the improvement measures are investigated. Based on the above analysis, this paper puts forward the relevant suggestions to promote the cultivation of innovative talents, mainly including planning and designing the training programme system for logistics engineering major, placing more emphasis on logistics practice courses, promoting undergraduate students' participation in various logistics contests, and increasing the level of teaching investment and guarantee. [ABSTRACT FROM AUTHOR]

The COVID-19 inflicted worldwide heavy losses and exposed the vulnerability of the global supply chain. Since then, the number of research works exploring the supply chain-related issues raised by this terrible pandemic steadily increases, making a structured review a necessity. To this end, this paper figured out three major tasks: (1) 166 relevant articles are identified, along with a macro-level analysis in terms of general information of the literature; (2) through mapping the relevant research works from the problem-oriented and methodology-driven perspective, the present research hotspots and methodologies/theories used in these studies are revealed; and (3) a research agenda with the consideration of supply chain disruptions and 3Rs in the supply chain is proposed. Research findings may shed more light on the discussion of the COVID-19's impacts on supply chains, and providing academical guides for researchers and managerial insights for decision-makers to develop appropriate responses to the pandemic. [ABSTRACT FROM AUTHOR]