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In this paper, a graph regularized nonlinear ridge regression (RR) model is proposed for remote sensing data analysis, including hyper-spectral image classification and atmospheric aerosol retrieval. The RR is an efficient linear regression method, especially in handling cases with a small number of training samples or with correlated features. However, large amounts of unlabeled samples exist in remote sensing data analysis. To sufficiently explore the information in unlabeled samples, we propose a graph regularized RR (GRR) method, where the vertices denote labeled or unlabeled samples and the edges represent the similarities among different samples. A natural assumption is that the predict values of neighboring samples are close to each other. To further address the nonlinearly separable problem in remote sensing data caused by the complex acquisition process as well as the impacts of atmospheric and geometric distortions, we extend the proposed GRR into a kernelized nonlinear regression method, namely KGRR. To evaluate the proposed method, we apply it to both classification and regression tasks and compare with representative methods. The experimental results show that KGRR can achieve favorable performance in terms of predictability and computation time. [ABSTRACT FROM PUBLISHER]

In this article, we propose a novel data-driven regression model for aerosol optical depth (AOD) retrieval. First, we adopt a low-rank representation (LRR) model to learn a powerful representation of the spectral response. Then, a graph regularization is incorporated into the LRR model to capture the local structure information and the non-linear property of the remote-sensing data. Since it is easy to acquire the rich results retrieved by satellite, we use them as a baseline to construct the graph. Finally, the learned feature representation is fed into Support Vector Machines (SVMs) to retrieve AOD. Experiments are conducted on two widely used data sets acquired by different sensors, and the experimental results show that the proposed method can achieve superior performance compared to the physical models and other state-of-the-art empirical models. [ABSTRACT FROM AUTHOR]

Novel low-molecular-weight organic gelators (LMOGs) with propeller-shaped triphenylamine as a 'core' and tiny methyl acrylate groups as 'tails,' are developed, which would not be thought to be a candidate for gel formation due to the absence of planar rigid aromatic building blocks and long-chain alkyls. The sensitive gel-sol transformation can be easily achieved upon heating or cooling accompanied by molecular aggregation or disaggregation. H-H 2D NOESY is employed to prove that the π-π stacking between the interlaced tiny 'tails' and the interaction between the superimposed phenyl and carbonyl groups of adjacent mole­cules are the dominant interaction forces. What is more, this soft interaction model can be regarded as a powerful tool in the design and construction of supramolecular structures in the future. At present, tris(4-methyl cinnamate)amine synthesized by a single step, but with a gel-formation ability and an aggrega­tion-induced fluorescence emission property, has great potential application as functional soft matter in amorphous materials, photoelectric materials, and so on. [ABSTRACT FROM AUTHOR]

Objective: To compare the efficacy of radiotherapy (RT) plus chemotherapy (CMT) versus RT alone for early stage nasal natural killer (NK)/T-cell lymphoma., Methods: All the eligible studies were searched by PubMed, Medline, Embase and the Cochrane Library. The meta-analysis was performed to compare odds ratios (ORs) for overall survival (OS), disease-free survival (DFS) and progression-free survival (PFS)., Results: Eight studies were included in the meta-analysis. Chemotherapy group did not significantly differ from RT group. The pooled OR and 95% confidence interval (CI) for 1-year, 3-year, 5-year and 10-year OS was 1.25 [0.84, 1.87], 1.10 [0.76, 1.58], 0.83 [0.59, 1.17] and 1.05 [0.70, 1.56]. In addition, the combined OR and 95% CI for 5-year DFS and PFS were 0.96 [0.53, 1.73] and 0.71 [0.45, 1.12]., Conclusions: The current evidence suggests that CMT was not superior to RT alone. Radiotherapy may be still the main method in the treatment of early stage nasal NK/T-cell lymphoma.