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Graph-based dimensionality reduction methods have attracted substantial attention due to their successful applications in many tasks, including classification and clustering. However, most classical graph-based dimensionality reduction approaches are only applied to data from one view. Hence, combining information from different data views has attracted considerable attention in the literature. Although various multi-view graph-based dimensionality reduction algorithms have been proposed, the graph construction strategies utilized in them do not adequately take noise and different importance of multiple views into account, which may degrade their performance. In this paper, we propose a novel algorithm, namely, Low-Rank Graph Optimization for Multi-View Dimensionality Reduction (LRGO-MVDR), that overcomes these limitations. First, we construct a low-rank shared matrix and a sparse error matrix from the graph that corresponds to each view for capturing potential noise. Second, an adaptive nonnegative weight vector is learned to explore complementarity among views. Moreover, an effective optimization procedure based on the Alternating Direction Method of Multipliers scheme is utilized. Extensive experiments are carried out to evaluate the effectiveness of the proposed algorithm. The experimental results demonstrate that the proposed LRGO-MVDR algorithm outperforms related methods.

Growth hormone (GH) is an important hormone released by the pituitary gland that plays a key role in the growth and development of organisms. In our study, TargetScan analysis and the dual luciferase reporter assays were used to predict and screen for miRNAs that might act on the rat Gh1 gene, and we identified miR-543-5p. Then, the GH3 cell line and the primary rat pituitary cells were transfected with miRNA mimic, inhibitor, and siRNA. We detected the Gh1 gene expression and the GH secretion by real-time PCR and ELISAs, respectively, to verify the regulatory effect of miR-543-5p on GH secretion. The results showed that miR-543-5p can inhibit Gh1 mRNA expression and reduce GH secretion. MiR-543-5p inhibitor upregulated Gh1 mRNA expression and increased GH secretion compared with the negative control. In summary, miR-543-5p downregulates Gh1 expression, resulting in a decrease in GH synthesis and secretion, which demonstrates the important role of miRNAs in regulating GH and animal growth and development.

Analyzing geological drilling hole images acquired by Axial View Panoramic Borehole Televiewer (APBT) is a key step to explore the geological structure in a geological exploration. Conventionally, the borehole images are examined by technicians, which is inefficient and subjective. In this paper, three dominant types of borehole-wall images on coal-rock mass structure, namely, border images, fracture images and intact rock mass images are mainly studied. The traditional image classification methods based on unified feature extraction algorithm and single classifier is not effect for the borehole images. Therefore, this paper proposes a novel two-stage classification approach to improve the classification performance of borehole images. In the first-stage classification, the border images are identified from three kinds of images based on texture features and gray-scale histograms features. For the remaining two types of images, in the second-stage classification, Gabor filter is first applied to segment the region of interest (ROI) (such as microfracture, absciss layer and horizontal cracks, etc.) and the central interference region. Then, using the same feature vector after eliminating the central interference region, fracture images are separated from intact rock mass images. We test our two-stage classification system with real borehole images. The results of experimental show that the two-stage classification method can effectively classify three major borehole-wall images with the correction rate of 95.55% in the first stage and 95% in the second stage.

Non-human primates face major environmental changes due to increased human impacts all over the world. Although some species are able to survive in certain landscapes with anthropogenic impact, their long-term viability and fitness may be decreased due to chronic stress. Here we assessed long-term stress levels through cortisol analysis in chimpanzee hair obtained from sleeping nests in northwestern Uganda, in order to estimate welfare in the context of ecotourism, forest fragmentation with human-wildlife conflicts, and illegal logging with hunting activity (albeit not of primates), compared with a control without human contact or conflict. Concerning methodological issues, season [F(2,129) = 37.4, p < 0.0001, r2 = 0.18] and the age of nests [F(2,178) = 20.3, p < 0.0001, r2 = 0.11] significantly predicted hair cortisol concentrations (HCC). With regard to effects of anthropogenic impacts, our results neither showed elevation of HCC due to ecotourism, nor due to illegal logging compared to their control groups. We did, however, find significantly increased HCC in the fragment group compared to chimpanzees living in a nearby intact forest [F(1,88) = 5.0, p = 0.03, r2 = 0.20]. In conclusion, our results suggest that hair cortisol analysis is a powerful tool that can help understanding the impact of anthropogenic disturbances on chimpanzee well-being and could be applied to other great ape species.

Disrupted white matter integrity and abnormal cortical thickness are widely reported in the pathophysiology of obsessive-compulsive disorder (OCD). However, the relationship between alterations in white matter connectivity and cortical thickness in OCD is unclear. In addition, the heritability of this relationship is poorly understood. To investigate the relationship of white matter microstructure with cortical thickness, we measure fractional anisotropy (FA) of white matter in 30 OCD patients, 19 unaffected siblings and 30 matched healthy controls. Then, we take those regions of significantly altered FA in OCD patients compared with healthy controls to perform fiber tracking. Next, we calculate the fiber quantity in the same tracts. Lastly, we compare cortical thickness in the target regions of those tracts. Patients with OCD exhibited decreased FA in cingulum, arcuate fibers near the superior parietal lobule, inferior longitudinal fasciculus near the right superior temporal gyrus and uncinate fasciculus. Siblings showed reduced FA in arcuate fibers near the superior parietal lobule and anterior limb of internal capsule. Significant reductions in both fiber quantities and cortical thickness in OCD patients and their unaffected siblings were also observed in the projected brain areas when using the arcuate fibers near the left superior parietal lobule as the starting points. Reduced FA in the left superior parietal lobule was observed not only in patients with OCD but also in their unaffected siblings. Originated from the superior parietal lobule, the number of fibers was also found to be decreased and the corresponding cortical regions were thinner relative to controls. The linkage between disrupted white matter integrity and the abnormal cortical thickness may be a vulnerability marker for OCD.