Kernel Feature Extraction for Hyperspectral Image Classification Using Chunklet Constraints

A novel semi-supervised kernel feature extraction algorithm to combine an efficient metric learning method, i.e. relevant component analysis (RCA), and kernel trick is presented for hyperspectral imagery land-cover classification. This method obtains projection of the input data by learning an optimal nonlinear transformation via a chunklet constraints-based FDA criterion, and called chunklet-based kernel relevant component analysis (CKRCA). The proposed method is appealing as it constructs the kernel very intuitively for the RCA method and does not require any labeled information. The effectiveness of the proposed CKRCA is successfully illustrated in hyperspectral remote sensing image classification. Experimental results demonstrate that the proposed method can greatly improve the classification accuracy compared with traditional linear and conventional kernel-based methods

Studies on the effect of Celastrus orbiculatus (Celastraceae) extract on chemosensitivity of liver cancer cells via Wnt/β-catenin pathway

Purpose: To examine the efficacy of Celastrus orbiculatus extract (COE) on the chemosensitivity of liver cancer (LC) cells and its mechanism of action.Methods: Hep G2/ADM cells in the logarithmic growth phase were assigned to a control group (no treatment for cell culture medium only) and a study group (120 μg/ml COE added to the culture medium). After 48 h of incubation, the biological responses were compared. The study group wasdivided into groups A and B, while control group was divided into groups C and D, with 1 μmol/L XAV939 added in groups A and C. Cell proliferation, cell invasion, cell apoptosis rate, and apoptosis protein in the four groups were evaluated.Results: The study group showed significantly lower values in terms of cell proliferation and cell invasiveness (p < 0.05) and a higher apoptotic rate than the control group (p < 0.05)). The study group also demonstrated an elevated pro-apoptotic protein Bax level and a declined anti-apoptotic protein Bcl-2  level. In contrast to group B, the proliferation and invasiveness of Hep G2/ADM cells in group A treated with the inhibitor, XAV939, were significantly lower (p < 0.05), while the apoptotic rate exhibited a significant increase (p < 0.05). There was a rise in the level of pro-apoptotic protein, Bax, and a fall in the anti-apoptotic protein Bcl-2 level in group A. Lower levels of β-catenin, c-Myc, and cyclin D1 protein were observed in the study group compared with the control group (p < 0.05). Compared with other groups, the multiplication capacity and invasiveness of cells in group A treated with COE and inhibitor XAV939 significantly declined, while the apoptotic rate increased (p < 0.05).Conclusion: COE reverses drug resistance in chemotherapy by inhibiting the expression of Wnt/β-catenin pathway in LC cells. Therefore, COE has potentials for use along with chemotherapeutic agents in the management of liver cancer

Hyperspectral Band Selection for Lithologic Discrimination and Geological Mapping

Classification techniques applied to hyperspectral images are very useful for lithologic discrimination and geological mapping. Classifiers are often applied either to all spectral channels or only to absorption spectral channels. However, it is difficult to obtain different lithology information using specific absorption regions from the narrow bandwidth and contiguous spectral channels due to spectral variability among rocks. In this article, we propose a band selection (BS) method for hyperspectral lithologic discrimination, in which the lithological superpixels are first gathered. A spectral bands selection criterion is learned by measuring the homogeneity and the variation of the lithological superpixels, and lithologic discriminating bands are identified by an efficient clustering algorithm based on affinity propagation. In this article, two geologic test sites, i.e., the Airborne Visible/Infrared Imaging Spectrometer data of the Cuprite, Nevada, USA, including 11 lithologic units (9 types of rocks) and the Hyperion data of Junggar, China, with 5 lithologic units, are chosen for validation. The performance of the proposed BS method is compared with those of using all the bands, specific absorption spectral channels, and two literature BS techniques. Experimental results show that the proposed method improves mapping accuracy by selecting fewer bands with higher lithologic discrimination capability than the other considered methods

The Modulatory Properties of Astragalus membranaceus Treatment on Triple-Negative Breast Cancer: An Integrated Pharmacological Method.

Background: Studies have shown that the natural products of Astragalus membranaceus (AM) can effectively interfere with a variety of cancers, but their mechanism of action on breast cancer remains unclear. Triple-negative breast cancer (TNBC) is associated with a severely poor prognosis due to its invasive phenotype and lack of biomarker-driven-targeted therapies. In this study, the potential mechanism of the target composition acting on TNBC was explored by integrated pharmacological models and in vitro experiments. Materials and Methods: Based on the Gene Expression Omnibus (GEO) database and the relational database of Traditional Chinese Medicines (TCMs), the drug and target components were initially screened to construct a common network module, and multiattribute analysis was then used to characterize the network and obtain key drug-target information. Furthermore, network topology analysis was used to characterize the betweenness and closeness of key hubs in the network. Molecular docking was used to evaluate the affinity between compounds and targets and obtain accurate combination models. Finally, in vitro experiments verified the key component targets. The cell counting kit-8 (CCK-8) assay, invasion assay, and flow cytometric analysis were used to assess cell viability, invasiveness, and apoptosis, respectively, after Astragalus polysaccharides (APS) intervention. We also performed western blot analysis of key proteins to probe the mechanisms of correlated signaling pathways. Results: We constructed "compound-target" (339 nodes and 695 edges) and "compound-disease" (414 nodes and 6458 edges) networks using interaction data. Topology analysis and molecular docking were used as secondary screens to identify key hubs of the network. Finally, the key component APS and biomarkers PIK3CG, AKT, and BCL2 were identified. The in vitro experimental results confirmed that APS can effectively inhibit TNBC cell activity, reduce invasion, promote apoptosis, and then counteract TNBC symptoms in a dose-dependent manner, most likely by inhibiting the PIK3CG/AKT/BCL2 pathway. Conclusion: This study provides a rational approach to discovering compounds with a polypharmacology-based therapeutic value. Our data established that APS intervenes with TNBC cell invasion, proliferation, and apoptosis via the PIK3CG/AKT/BCL2 pathway and could thus offer a promising therapeutic strategy for TNBC

Impact of Inorganic Solutes’ Release in Groundwater during Oil Shale In Situ Exploitation

Oil shale can produce oil and shale gas by heating the oil shale at 300–500 °C. The high temperature and the release of organic matter can change the physical and mechanical properties of rocks and make the originally tight impervious layer become a permeable layer under in situ exploitation conditions. To realize the potential impact of the in situ exploitation of oil shale on groundwater environments, a series of water–rock interaction experiments under different temperatures was conducted. The results show that, with the increase of the reaction temperature, the anions and cations in the aqueous solution of oil shale, oil shale–ash, and the surrounding rock show different trends, and the release of anions and cations in the oil shale–ash solution is most affected by the ambient temperature. The hydrochemical type of oil shale–ash solution is HCO3-SO4-Na-K at 80 °C and 100 °C, which changes the water quality. The main reasons are that (1) the high temperature (≥80 °C) can promote the dissolution of FeS in oil shale and (2) the porosity of oil shale increases after pyrolysis, making it easier to react with water. This paper is an important supplement to the research on the impact of the in situ exploitation of oil shale on the groundwater environment. Therefore, the impacts of in situ mining on groundwater inorganic minerals should be taken into consideration when evaluating in situ exploitation projects of oil shale

Discriminative Feature Metric Learning in the Affinity Propagation Model for Band Selection in Hyperspectral Images

Traditional supervised band selection (BS) methods mainly consider reducing the spectral redundancy to improve hyperspectral imagery (HSI) classification with class labels and pairwise constraints. A key observation is that pixels spatially close to each other in HSI have probably the same signature, while pixels further away from each other in the space have a high probability of belonging to different classes. In this paper, we propose a novel discriminative feature metric-based affinity propagation (DFM-AP) technique where the spectral and the spatial relationships among pixels are constructed by a new type of discriminative constraint. This discriminative constraint involves chunklet and discriminative information, which are introduced into the BS process. The chunklet information allows for grouping of spectrally-close and spatially-close pixels together without requiring explicit knowledge of their class labels, while discriminative information provides important separability information. A discriminative feature metric (DFM) is proposed with the discriminative constraints modeled in terms of an optimal criterion for identifying an efficient distance metric learning method, which involves discriminative component analysis (DCA). Following this, the representative subset of bands can be identified by means of an exemplar-based clustering algorithm, which is also known as the process of affinity propagation. Experimental results show that the proposed approach yields a better performance in comparison with several representative class label and pairwise constraint-based BS algorithms. The proposed DFM-AP improves the classification performance with discriminative constraints by selecting highly discriminative bands with low redundancy

Uranium-Bearing Layers of Sandstone Type Uranium Deposits Identification and Three-Dimensional Reconstruction in the Northern Ordos Basin, North-Central China

Sandstone type uranium is the most valuable and has the most potential for mining among the known uranium deposits. In the process of forming, the hydrolytic migration and enrichment of uranium require special basin sedimentary environment and tectonic background. Therefore, the mineralization process of sandstone type uranium deposits has certain layering characteristics and distribution rules in the underground vertical depth space. It is important to mine the spatial distribution characteristics of vertical uranium-bearing layers, and thus, reconstruct the three-dimensions of uranium orebodies. In this paper, according to the metallogenic law and distribution characteristics of sandstone type uranium in the underground vertical space, a nonlinear uranium-bearing layers identification (NULI) method of sandstone type uranium is proposed by using different types, resolutions and scales of borehole data. Then, the depth of uranium mineralization for the Daying uranium deposit within northern Ordos Basin is identified accurately and the spatial distribution characteristics of the uranium-bearing layer on the exploration line are obtained. Finally, the occurrence mode of the underground uranium orebodies are presented by using three-dimensional reconstruction analysis. It provides a basis for the prediction, exploration and mining of sandstone type uranium deposits within the Ordos Basin

The Crimping and Expanding Performance of Self-Expanding Polymeric Bioresorbable Stents: Experimental and Computational Investigation

Polymeric bioresorbable stents (PBRSs) are considered the most promising devices to treat cardiovascular diseases. However, the mechanical weakness still hampers their application. In general, PBRSs are crimped into small sheathes and re-expanded to support narrowed vessels during angioplasty. Accordingly, one of the most significant requirements of PBRSs is to maintain mechanical efficacy after implantation. Although a little research has focused on commercial balloon-expanding PBRSs, a near-total lack has appeared on self-expanding PBRSs and their deformation mechanisms. In this work, self-expanding, composite polymeric bioresorbable stents (cPBRSs) incorporating poly(p-dioxanone) (PPDO) and polycaprolactone (PCL) yarns were produced and evaluated for their in vitro crimping and expanding potential. Furthermore, the polymer time-reliable viscoelastic effects of the structural and mechanical behavior of the cPBRSs were analyzed using computational simulations. Our results showed that the crimping process inevitably decreased the mechanical resistance of the cPBRSs, but that this could be offset by balloon dilatation. Moreover, deformation mechanisms at the yarn level were discussed, and yarns bonded in the crossings showed more viscous behavior; this property might help cPBRSs to maintain their structural integrity during implantation