Abstract: Matrix assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOFMS) is a soft ionization mass spectrometry technology and widely used in the analysis of various molecules such as proteins, polypeptides, nucleic acids and polymers, etc. However, the application of MALDI-TOF MS on detection of low molecular weight compounds (LMWC) is limited due to the matrix related peak interference and inhomogeneous crystallization of matrix/analyte. In recent years, a variety of novel matrixes have been developed for detection of LMWC. This paper reviews the matrix of MALDI-TOF MS in recent 10 years from three aspects, including new inorganic material matrix, organic compound matrix and other matrix (metal organic framework, ionic liquid matrix, reactive matrix, etc.) The research progress of determination of LMWC by To address the lack of in-depth understanding of avian behavioral intent in traditional airport bird situation analysis, this paper proposes a method for mining bird behavior patterns based on avian radar. The method is based on real-world bird track data collected by a digital array avian radar. It constructs multi-dimensional kinematic "track profiles" including average speed, average altitude, straightness, root mean square of horizontal turn rate, and duration. An unsupervised partitioning clustering method, which aims to minimize the sum of squared distances from samples to their assigned centroids, is then employed for pattern mining. The optimal number of clusters is determined to be five by combining the Elbow Method and objective evaluation metrics such as the Calinski-Harabasz Index. At K=5, the Calinski-Harabasz Index reached a peak of 10263.09, strongly supporting this choice of K. Furthermore, to validate the clustering effectiveness, a comparison with a Gaussian Mixture Model demonstrated the superiority of the selected method, both quantitatively and visually. The study identified five statistically distinct flight behavior patterns: mid-low altitude high-speed transit, low-altitude slow milling, mid-low altitude meandering movement, mid-low altitude long-duration loitering,and high-altitude migration/anomaly. By combining UMAP(Uniform Manifold Approximation and Projection) dimensionality reduction visualization with typical 3D trajectory reconstruction analysis, the objective existence and separability of these behavior patterns in the feature space were visually verified. This research elevates bird situation analysis from traditional target identification to an understanding of flight intent, providing a new perspective and technical support for the fine-grained assessment and intelligent early warning of airport bird strike risks.