Sketch-based subspace clustering of hyperspectral images

Sparse subspace clustering (SSC) techniques provide the state-of-the-art in clustering of hyperspectral images (HSIs). However, their computational complexity hinders their applicability to large-scale HSIs. In this paper, we propose a large-scale SSC-based method, which can effectively process large HSIs while also achieving improved clustering accuracy compared to the current SSC methods. We build our approach based on an emerging concept of sketched subspace clustering, which was to our knowledge not explored at all in hyperspectral imaging yet. Moreover, there are only scarce results on any large-scale SSC approaches for HSI. We show that a direct application of sketched SSC does not provide a satisfactory performance on HSIs but it does provide an excellent basis for an effective and elegant method that we build by extending this approach with a spatial prior and deriving the corresponding solver. In particular, a random matrix constructed by the Johnson-Lindenstrauss transform is first used to sketch the self-representation dictionary as a compact dictionary, which significantly reduces the number of sparse coefficients to be solved, thereby reducing the overall complexity. In order to alleviate the effect of noise and within-class spectral variations of HSIs, we employ a total variation constraint on the coefficient matrix, which accounts for the spatial dependencies among the neighbouring pixels. We derive an efficient solver for the resulting optimization problem, and we theoretically prove its convergence property under mild conditions. The experimental results on real HSIs show a notable improvement in comparison with the traditional SSC-based methods and the state-of-the-art methods for clustering of large-scale images

Effectively Grouping Named Entities From Click- Through Data Into Clusters Of Generated Keywords1

Many studies show that named entities are closely related to users\u27 search behaviors, which brings increasing interest in studying named entities in search logs recently. This paper addresses the problem of forming fine grained semantic clusters of named entities within a broad domain such as “company”, and generating keywords for each cluster, which help users to interpret the embedded semantic information in the cluster. By exploring contexts, URLs and session IDs as features of named entities, a three-phase approach proposed in this paper first disambiguates named entities according to the features. Then it properly weights the features with a novel measurement, calculates the semantic similarity between named entities with the weighted feature space, and clusters named entities accordingly. After that, keywords for the clusters are generated using a text-oriented graph ranking algorithm. Each phase of the proposed approach solves problems that are not addressed in existing works, and experimental results obtained from a real click through data demonstrate the effectiveness of the proposed approach

Human Pose Driven Object Effects Recommendation

In this paper, we research the new topic of object effects recommendation in micro-video platforms, which is a challenging but important task for many practical applications such as advertisement insertion. To avoid the problem of introducing background bias caused by directly learning video content from image frames, we propose to utilize the meaningful body language hidden in 3D human pose for recommendation. To this end, in this work, a novel human pose driven object effects recommendation network termed PoseRec is introduced. PoseRec leverages the advantages of 3D human pose detection and learns information from multi-frame 3D human pose for video-item registration, resulting in high quality object effects recommendation performance. Moreover, to solve the inherent ambiguity and sparsity issues that exist in object effects recommendation, we further propose a novel item-aware implicit prototype learning module and a novel pose-aware transductive hard-negative mining module to better learn pose-item relationships. What's more, to benchmark methods for the new research topic, we build a new dataset for object effects recommendation named Pose-OBE. Extensive experiments on Pose-OBE demonstrate that our method can achieve superior performance than strong baselines

Long-term antagonistic effect of increased precipitation and nitrogen addition on soil respiration in a semiarid steppe

Changes in water and nitrogen (N) availability due to climate change and atmospheric N deposition could have significant effects on soil respiration, a major pathway of carbon (C) loss from terrestrial ecosystems. A manipulative experiment simulating increased precipitation and atmospheric N deposition has been conducted for 9 years (2005–2013) in a semiarid grassland in Mongolian Plateau, China. Increased precipitation and N addition interactively affect soil respiration through the 9 years. The interactions demonstrated that N addition weakened the precipitation-induced stimulation of soil respiration, whereas increased precipitation exacerbated the negative impacts of N addition. The main effects of increased precipitation and N addition treatment on soil respiration were 15.8% stimulated and 14.2% suppressed, respectively. Moreover, a declining pattern and 2-year oscillation were observed for soil respiration response to N addition under increased precipitation. The dependence of soil respiration upon gross primary productivity and soil moisture, but not soil temperature, suggests that resources C substrate supply and water availability are more important than temperature in regulating interannual variations of soil C release in semiarid grassland ecosystems. The findings indicate that atmospheric N deposition may have the potential to mitigate soil C loss induced by increased precipitation, and highlight that long-term and multi-factor global change studies are critical for predicting the general patterns of terrestrial C cycling in response to global change in the future

The Synthetic Compound Norcantharidin Induced Apoptosis in Mantle Cell Lymphoma In Vivo and In Vitro through the PI3K-Akt-NF- κ

This study aimed to elucidate the antitumor activity of norcantharidin (NCTD) against human mantle cell lymphoma (MCL). Cell proliferation and apoptosis were examined by MTS and flow cytometry. Caspase-3, -8, and -9 activities were detected with a colorimetric caspase protease assay. Apoptotic proteins—including PARP, cyclin D1, Bcl-2 family proteins, XIAP, and cIAP I—were studied by western blot. The phosphoinositide 3 kinase (PI3K) inhibitor LY294002 was used to investigate the involvement of the PI3K/Akt signaling pathway. In vivo studies were performed using Z138 cell xenografts in nude mice. NCTD inhibited proliferation and induced apoptosis of Z138 and Mino cells, both in vitro and in vivo. PI3Kp110α and p-Akt expressions were downregulated by NCTD treatment. NCTD downregulated NF-κB activity by preventing NF-κB phosphorylation and nuclear translocation. This effect was correlated with the suppression of NF-κB-regulated gene products, such as cyclin D1, BAX, survivin, Bcl-2, XIAP, and cIAP. This phenomenon was blocked by the PI3K inhibitor LY294002. Our results demonstrated that NCTD can induce growth arrest and apoptosis in MCL cells and that the mechanism may involve the PI3K/Akt/NF-κB signaling pathway. NCTD may have therapeutic and/or adjuvant therapeutic applications in the treatment of MCL

PDCD1 genes may protect against extraocular manifestations in Chinese Han patients with Vogt-Koyanagi-Harada syndrome

Purpose: To analyze the potential association of programmed cell death 1 (PDCD1) with Vogt-Koyanagi-Harada (VKH) syndrome in a Chinese Han population. Methods: Three single nucleotide polymorphism (SNPs), PD-1.3G/A, PD-1.5C/T, and PD-1.6G/A, were genotyped in 247 VKH patients and 289 age-, sex-, and ethnically-matched healthy controls using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) assay. The associations of genotypes and alleles with VKH syndrome were analyzed. Results: All genotype distributions in healthy controls were in Hardy-Weinberg equilibrium. The genotype and allele frequencies of PD-1.3, PD-1.5, and PD-1.6 were not different between patients with VKH syndrome and healthy controls. No significant difference was observed according to the status of human leukocyte antigen (HLA)-DR4 and HLA-DRw53. Compared to the controls, lower frequencies of the PD-1.5C genotype and allele frequencies were observed in VKH patients with extraocular findings. Conclusions: PD-1.3 and PD-1.6 polymorphisms are not associated with the susceptibility to VKH syndrome in the Chinese Han population. However, PD-1.5 may be negatively associated with the occurrence of extraocular manifestations of VKH syndrome

Effect of Steam Explosion on the Aroma Characteristics of Tea Produced from Tender and Mature Leaves of Eucommia ulmoides Analyzed Using Electronic Nose and Headspace Solid-Phase Microextraction Combined with Gas Chromatography-Mass Spectrometry

In order to investigate the differences in volatile components and major aroma characteristics between tea made from tender and mature leaves of Eucommia ulmoides pre-treated by steam explosion (SE), an electronic nose (E-nose) and headspace solid-phase microextraction coupled to gas chromatography-mass spectrometry (HS-SPME-GC-MS) were applied to analyze the effect of SE on the volatile components in tea made from tender and mature leaves of the Eucommia ulmoides cultivar ‘Huazhong 8’. The results showed that the principal component analysis (PCA) and linear discriminant analysis (LDA) models fitted well the E-nose data, which suggested that the aroma characteristics of both tender and mature leaf tea were significantly different between with and without SE pretreatment. Altogether, 177 volatile components were identified by HS-SPME-GC-MS, among which 24 were selected as aroma active substances by orthogonal partial least squares discriminant analysis (variable importance in the projection (VIP) value ≥ 1) and Kruskal-Wallis H test (P < 0.05). The key aroma substance of tender leaf tea without SE was dihydroactinidiolide. The key aroma substances of tender leaf tea with SE were dihydroactinidiolide, nonanal, benzaldehyde and phenylacetaldehyde, contributing to citrus-like, flowery, caramelic, bitter almond-like, nutty, rose-like and chocolate-like aromas. No key aroma substances were found in mature leaf tea without SE, while dihydroactinidiolide and nonanal were identified the key aroma substances in mature leaf tea with SE, contributing to sweet peach-like, woody, citrus-like, flowery and caramelic aromas. The results of this study can provide a reference for the development of beverage products based on Eucommia ulmoides leaves