EGT intervention significantly improved d -galactose induced oxidative stress, neuroinflammation, and mitochondrial function, resulting in the alleviation of memory injury.
In recent years, there has been a prevalence of search engines being employed to find useful information in the Web as they efficiently explore hyperlinks between web pages which define a natural graph structure that yields a good ranking. Unfortunately, current search engines cannot effectively rank those relational data, which exists on dynamic websites supported by online databases. In this study, to rank such structured data (i.e., find the best items), we propose an integrated online system consisting of compressed data structure to encode the dominant relationship of the relational data. Efficient querying strategies and updating scheme are devised to facilitate the ranking process. Extensive experiments illustrate the effectiveness and efficiency of our methods. As such, we believe the work in this paper can be complementary to traditional search engines.
Video retargeting is a technique that resizes the aspect ratio and resolution of a video in a content aware manner. There are three main challenges in the video retargeting: visual saliency preservation, deformation prevention and temporal consistency preservation. Existing video retargeting methods can be roughly classified into seam carving based methods and warping based methods. These methods effectively protect important regions in video, but can hardly deal with deformations and temporal incoherence, especially for videos whose foreground and background are both in motion. In this paper, we propose a novel shape preserving video retargeting method to reduce deformations and maintain temporal consistency via matching salient curves in the video frames. Our method transforms the anti-deformation and temporal consistency problems in video retargeting into a curve matching cost minimization problem. By incorporating a deformation cost and temporal inconsistency cost into the seam carving framework, the quality of the retargeted videos can be significantly improved. Experimental results also show that the proposed method achieves better performance compared with other two state-of-the-art methods.
Due to the importance of skyline query in many applications, it has been attracted much attention recently. Given an N-dimensional dataset D, a point p is said to dominate another point q if p is better than q in at least one dimension and equal to or better than q in the remaining dimensions. Recently, Li et al. [9] proposed to analyze more general dominant relationship in a business model that, users are more interested in the details of the dominant relationship in a dataset, i.e., a point p dominates how many other points. In this paper, we further generalize this problem that, users are more interested in whom these dominated points are. We show that the framework proposed in [9] can not efficiently solve this problem. We find the interrelated connection between the partial order and the dominant relationship. Based on this discovery, we propose efficient algorithms to answer the general dominant relationship queries by querying the partial order representation of spatial datasets. Extensive experiments illustrate the effectiveness and efficiency of our methods.
Aroma plays a pivotal role in defining tea quality and distinctiveness, and tea producers have often observed that specific drought conditions are closely associated with the formation and accumulation of characteristic aroma compounds in tea leaves. However, there is still limited understanding of the differential strategies employed by various tea cultivars in response to drought stress for the accumulation of key volatile aroma compounds in fresh tea leaves, as well as the associated metabolic pathways involved in aroma formation. In this study, two widely cultivated tea cultivars in China, Fuding Dabai (FD) and Wuniuzao (WNZ), were examined to assess the impact of mild field drought stress on the composition and accumulation of key volatile aroma compounds in fresh leaves using headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) and headspace solid phase micro-extraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) technologies. Results revealed that drought stress led to a substantial increase in the diversity of volatile compounds (VOCs) in FD, while WNZ exhibited a notable rise in low-threshold VOC concentrations, amplifying sweet, floral, fruity, and earthy aroma profiles in post-drought fresh leaves. Through partial least squares discriminant analysis (PLS-DA) of HS-GC-IMS and HS-SPME-GC-MS data, integrating variable importance projection (VIP) scores and odor activity values (OAVs) above 1, 9, and 13, key odor-active compounds were identified as potential markers distinguishing the drought responses in the two cultivars. These compounds serve as crucial indicators of the aromatic profile shifts induced by drought, providing insights into the differential metabolic strategies of the cultivars. Additionally, KEGG enrichment analysis revealed 12 metabolic pathways, such as terpenoid biosynthesis, fatty acid synthesis, cutin, suberine, and wax biosynthesis, and phenylalanine metabolism, which may play crucial roles in the formation and accumulation of VOCs in tea leaves under drought stress. These findings provide a comprehensive framework for understanding the cultivar-specific mechanisms of aroma formation and accumulation in tea leaves under mild drought conditions.
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