Publications by authors named "Kejie Xu"

Article Synopsis
  • Major Depressive Disorder (MDD) is a common mental disorder that affects cognitive functions, and this study investigates brain network properties to identify MDD patients.
  • The research used resting-state functional MRI to analyze brain connectivity, revealing that while small-worldness didn't change significantly, certain properties like local efficiency and clustering coefficient showed potential in differentiating MDD patients from healthy individuals.
  • Techniques like support vector machine and shapley additive explanations were used to assess the effectiveness of brain network properties, indicating that changes mainly occur in the default mode network, which could aid in understanding MDD's underlying mechanisms through deep learning approaches.
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Phenoxy acetophenones were usually employed as β-O-4' lignin models for chemical conversion. Herein, an iridium-catalyzed dehydrogenative annulation between 2-aminobenzylalcohols and phenoxy acetophenones was demonstrated to prepare valuable 3-oxo quinoline derivatives, which are hard to prepare using previous methods. This operationally simple reaction tolerated a wide scope of substrates and enabled successful gram-scale preparation.

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Scene classification of high spatial resolution (HSR) images can provide data support for many practical applications, such as land planning and utilization, and it has been a crucial research topic in the remote sensing (RS) community. Recently, deep learning methods driven by massive data show the impressive ability of feature learning in the field of HSR scene classification, especially convolutional neural networks (CNNs). Although traditional CNNs achieve good classification results, it is difficult for them to effectively capture potential context relationships.

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