Multi-stage feature decorrelation constraints for improving CNN classification performance

For the convolutional neural network (CNN) used for pattern classification, the training loss function is usually applied to the final output of the network, except for some regularization constraints on the network parameters. However, with the increasing of the number of network layers, the influence of the loss function on the network front layers gradually decreases, and the network parameters tend to fall into local optimization. At the same time, it is found that the trained network has significant information redundancy at all stages of features, which reduces the effectiveness of feature mapping at all stages and is not conducive to the change of the subsequent parameters of the network in the direction of optimality. Therefore, it is possible to obtain a more optimized solution of the network and further improve the classification accuracy of the network by designing a loss function for restraining the front stage features and eliminating the information redundancy of the front stage features .For CNN, this article proposes a multi-stage feature decorrelation loss (MFD Loss), which refines effective features and eliminates information redundancy by constraining the correlation of features at all stages. Considering that there are many layers in CNN, through experimental comparison and analysis, MFD Loss acts on multiple front layers of CNN, constrains the output features of each layer and each channel, and performs supervision training jointly with classification loss function during network training. Compared with the single Softmax Loss supervised learning, the experiments on several commonly used datasets on several typical CNNs prove that the classification performance of Softmax Loss+MFD Loss is significantly better. Meanwhile, the comparison experiments before and after the combination of MFD Loss and some other typical loss functions verify its good universality

Enhanced flux pinning in YBa2Cu3O7-d films by nano-scaled substrate surface roughness

Nano-scaled substrate surface roughness is shown to strongly influence the critical current density Jc in YBCO films made by pulse-laser-deposition on the crystalline LaAlO3 substrates consisting of two separate twin-free and twin-rich regions. The nano-scaled corrugated surface was created in the twin-rich region during the deposition process. Using magneto-optical imaging techniques coupled with optical and atomic force microscopy, we observed an enhanced flux pinning in the YBCO films in the twin-rich region, resulted in \~30% increase in Jc, which was unambiguously confirmed by the direct transport measurement.Comment: 16 pages, 3 figures, accepted by Applied Physics Letter

Integrated analysis of WGCNA and machine learning identified diagnostic biomarkers in dilated cardiomyopathy with heart failure

The etiologies and pathogenesis of dilated cardiomyopathy (DCM) with heart failure (HF) remain to be defined. Thus, exploring specific diagnosis biomarkers and mechanisms is urgently needed to improve this situation. In this study, three gene expression profiling datasets (GSE29819, GSE21610, GSE17800) and one single-cell RNA sequencing dataset (GSE95140) were obtained from the Gene Expression Omnibus (GEO) database. GSE29819 and GSE21610 were combined into the training group, while GSE17800 was the test group. We used the weighted gene co-expression network analysis (WGCNA) and identified fifteen driver genes highly associated with DCM with HF in the module. We performed the least absolute shrinkage and selection operator (LASSO) on the driver genes and then constructed five machine learning classifiers (random forest, gradient boosting machine, neural network, eXtreme gradient boosting, and support vector machine). Random forest was the best-performing classifier established on five Lasso-selected genes, which was utilized to select out NPPA, OMD, and PRELP for diagnosing DCM with HF. Moreover, we observed the up-regulation mRNA levels and robust diagnostic accuracies of NPPA, OMD, and PRELP in the training group and test group. Single-cell RNA-seq analysis further demonstrated their stable up-regulation expression patterns in various cardiomyocytes of DCM patients. Besides, through gene set enrichment analysis (GSEA), we found TGF-β signaling pathway, correlated with NPPA, OMD, and PRELP, was the underlying mechanism of DCM with HF. Overall, our study revealed NPPA, OMD, and PRELP serving as diagnostic biomarkers for DCM with HF, deepening the understanding of its pathogenesis

Development of natural products as drugs acting on central nervous system

We have recenty studied several natural product constituents which have effects on the CNS. (1) Tetrahydropalmatine (THP) and its analogues were isolated from Corydalis ambigua and various species of Stephania. (+)-THP and (-)-THP posses not only analgesic activity, but also exert sedative-tranquillizing and hypnotic actions. Results of receptor binding assay and their pre-and post-synaptic effects on dopaminergic system indicate that (-)-THP and (-)-stepholidine are dopamine receptor antagonists while (+)-THP is a selective dopamine depletor. (2) 3-Acetylaconitine (AAC) is an alkaloid isolated from Aconitum flavum. The relative potency of analgesic action of AAC was 5.1-35.6 and 1250-3912 times that of morphine and aspirin, respectively. The analgesic effect of AAC was antagonized by naloxone, but was eliminated by reserpine. In monkeys, after AAC was injected for 92 days, no abstinence syndrome was seen after sudden AAC withdrawal or when challenged with nalorphine. (3) Huperzine A (Hup-A) is an alkaloid isolated from Huperzia serrata which was found to be a selective ChE inhibitor and could improve learning and retrieval process. Preliminary clinical studies showed that Hup-A improve short-and long-term memory in patients of cerebral arteriosclerosis with memory impairment. (4) Ranamargarin is a new tetradecapeptide isolated from the skin of the Chines frog Rana margaratae. This peptide may mainly act on NK-1 receptor

Optical and magnetic properties of Ni nanoparticles in rutile formed by Ni ion implantation

Crystalline Ni nanoparticles in the near surface of TiO2TiO2 (rutile) have been synthesized by Ni ion beam implantation at room temperature to a fluence of 1×1017/cm21×1017∕cm2. Transmission electron microscopy, optical absorption spectroscopy, and a superconducting quantum interference device magnetometer have been utilized to characterize the nanostructure, optical and magnetic properties of Ni particles in TiO2TiO2. Crystalline Ni nanoparticles with dimensions ranging 3–20 nm formed in the near surface of rutile, which caused a broad absorption band from 700 nm in the optical absorption spectrum. Magnetic measurement indicated that the coercive force of Ni nanoparticles was about 210 Oe at 10 K. The superparamagnetism of the nanoparticles was observed above blocking temperature T = 85 KT=85K.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87774/2/043107_1.pd

Clinical study on the optic nerve protection of calcium dobesilate in treating glaucoma

AIM:To observe the protective effect of calcium dobesilate on optic nerve of glaucoma patients whose intraocular pressure has been under control through operation.<p>METHODS: A total of 78 inpatients(89 eyes)with glaucoma in this hospital from January, 2011 to February, 2012 were enrolled. All patients were randomly divided into treatment group and control group with 6 months in a course. The visual acuity, visual field(mean sensibility, MS), and intraocular pressure were measured at the experiment onset and 6 months later to evaluate the clinical effect.<p>RESULTS: There were no statistically significant differences in the visual acuity, intraocular pressure between the two groups neither at the experiment onset nor after 6 months(<i>P</i>>0.05). The mean sensibility(MS)of the treatment group was obviously improved(14.56±5.03 <i>vs </i>18.9±5.77, <i>P</i><0.05)with statistically significant differences before and after the treatment, while the MS remained unchanged in the control group(14.75±5.17 <i>vs </i>13.48±4.69). There are statistically significant difference between the treatment group and the control group. Compared to the ratio of improvement, stability, and deterioration in the control group(10.3%, 48.7%, 41.0%), the indexes were changed obviously in the treatment group(64.1%, 28.2%, 7.7%,<i>P</i><0.05)with statistically significant difference between the two groups.<p>CONCLUSION:Calcium dobesilate can improve mean retinal sensitivity and protect the optic nerve in glaucoma patients whose intraocular pressure has been controlled