Two-phase incremental kernel PCA for learning massive or online datasets

As a powerful nonlinear feature extractor, kernel principal component analysis (KPCA) has been widely adopted in many machine learning applications. However, KPCA is usually performed in a batch mode, leading to some potential problems when handling massive or online datasets. To overcome this drawback of KPCA, in this paper, we propose a two-phase incremental KPCA (TP-IKPCA) algorithm which can incorporate data into KPCA in an incremental fashion. In the first phase, an incremental algorithm is developed to explicitly express the data in the kernel space. In the second phase, we extend an incremental principal component analysis (IPCA) to estimate the kernel principal components. Extensive experimental results on both synthesized and real datasets showed that the proposed TP-IKPCA produces similar principal components as conventional batch-based KPCA but is computationally faster than KPCA and its several incremental variants. Therefore, our algorithm can be applied to massive or online datasets where the batch method is not available

Two-phase incremental kernel PCA for learning massive or online datasets

As a powerful nonlinear feature extractor, kernel principal component analysis (KPCA) has been widely adopted in many machine learning applications. However, KPCA is usually performed in a batch mode, leading to some potential problems when handling massive or online datasets. To overcome this drawback of KPCA, in this paper, we propose a two-phase incremental KPCA (TP-IKPCA) algorithm which can incorporate data into KPCA in an incremental fashion. In the first phase, an incremental algorithm is developed to explicitly express the data in the kernel space. In the second phase, we extend an incremental principal component analysis (IPCA) to estimate the kernel principal components. Extensive experimental results on both synthesized and real datasets showed that the proposed TP-IKPCA produces similar principal components as conventional batch-based KPCA but is computationally faster than KPCA and its several incremental variants. Therefore, our algorithm can be applied to massive or online datasets where the batch method is not available

Nematic topological superconducting phase in Nb-doped Bi2Se3

A nematic topological superconductor has an order parameter symmetry, which spontaneously breaks the crystalline symmetry in its superconducting state. This state can be observed, for example, by thermodynamic or upper critical field experiments in which a magnetic field is rotated with respect to the crystalline axes. The corresponding physical quantity then directly reflects the symmetry of the order parameter. We present a study on the superconducting upper critical field of the Nb-doped topological insulator NbxBi2Se3 for various magnetic field orientations parallel and perpendicular to the basal plane of the Bi2Se3 layers. The data were obtained by two complementary experimental techniques, magnetoresistance and DC magnetization, on three different single crystalline samples of the same batch. Both methods and all samples show with perfect agreement that the in-plane upper critical fields clearly demonstrate a two-fold symmetry that breaks the three-fold crystal symmetry. The two-fold symmetry is also found in the absolute value of the magnetization of the initial zero-field-cooled branch of the hysteresis loop and in the value of the thermodynamic contribution above the irreversibility field, but also in the irreversible properties such as the value of the characteristic irreversibility field and in the width of the hysteresis loop. This provides strong experimental evidence that Nb-doped Bi2Se3 is a nematic topological superconductor similar to the Cu- and Sr-doped Bi2Se3

Involvement of claudin-7 in HIV infection of CD4(-) cells

BACKGROUND: Human immunodeficiency virus (HIV) infection of CD4(-) cells has been demonstrated, and this may be an important mechanism for HIV transmission. RESULTS: We demonstrated that a membrane protein, claudin-7 (CLDN-7), is involved in HIV infection of CD4(-) cells. A significant increase in HIV susceptibility (2- to 100-fold) was demonstrated when CLDN-7 was transfected into a CD4(-) cell line, 293T. In addition, antibodies against CLDN-7 significantly decreased HIV infection of CD4(-) cells. Furthermore, HIV virions expressing CLDN-7 on their envelopes had a much higher infectivity for 293T CD4(-) cells than the parental HIV with no CLDN-7. RT-PCR results demonstrated that CLDN-7 is expressed in both macrophages and stimulated peripheral blood leukocytes, suggesting that most HIV virions generated in infected individuals have CLDN-7 on their envelopes. We also found that CLDN-7 is highly expressed in urogenital and gastrointestinal tissues. CONCLUSION: Together these results suggest that CLDN-7 may play an important role in HIV infection of CD4(-) cells

Organic coating on sulfate and soot particles during late Summer in the Svalbard Archipelago

14 pages, 8 figures, 1 table, supplement https://doi.org/10.5194/acp-19-10433-2019Interaction of anthropogenic particles with radiation and clouds plays an important role in Arctic climate change. The mixing state of aerosols is a key parameter to influence aerosol radiation and aerosol–cloud interactions. However, little is known of this parameter in the Arctic, preventing an accurate representation of this information in global models. Here we used transmission electron microscopy with energy-dispersive X-ray spectrometry, scanning electron microscopy, nanoscale secondary ion mass spectrometry, and atomic forces microscopy to determine the size and mixing state of individual sulfate and carbonaceous particles at 100 nm to 2 µm collected in the Svalbard Archipelago in summer. We found that 74 % by number of non-sea-salt sulfate particles were coated with organic matter (OM); 20 % of sulfate particles also had soot inclusions which only appeared in the OM coating. The OM coating is estimated to contribute 63 % of the particle volume on average. To understand how OM coating influences optical properties of sulfate particles, a Mie core–shell model was applied to calculate optical properties of individual sulfate particles. Our result shows that the absorption cross section of individual OM-coated particles significantly increased when assuming the OM coating as light-absorbing brown carbon. Microscopic observations here suggest that OM modulates the mixing structure of fine Arctic sulfate particles, which may determine their hygroscopicity and optical propertiesThis work was funded by the National Natural Science Foundation of China (41622504, 41575116, 31700475) and the Hundred Talents Program in Zhejiang University. Zongbo Shi acknowledges funding from NERC (NE/S00579X/1)Peer Reviewe