Guangxi Normal University

About: Guangxi Normal University is a education organization based out in Guilin, China. It is known for research contribution in the topics: Catalysis & Computer science. The organization has 7075 authors who have published 7068 publications receiving 85917 citations. The organization is also known as: GNU & Guǎngxī shīfàn dàxué.

Efficient kNN Classification With Different Numbers of Nearest Neighbors

Abstract: ${k}$ nearest neighbor (kNN) method is a popular classification method in data mining and statistics because of its simple implementation and significant classification performance. However, it is impractical for traditional kNN methods to assign a fixed ${k}$ value (even though set by experts) to all test samples. Previous solutions assign different $k$ values to different test samples by the cross validation method but are usually time-consuming. This paper proposes a kTree method to learn different optimal $k$ values for different test/new samples, by involving a training stage in the kNN classification. Specifically, in the training stage, kTree method first learns optimal $k$ values for all training samples by a new sparse reconstruction model, and then constructs a decision tree (namely, kTree) using training samples and the learned optimal $k$ values. In the test stage, the kTree fast outputs the optimal $k$ value for each test sample, and then, the kNN classification can be conducted using the learned optimal $k$ value and all training samples. As a result, the proposed kTree method has a similar running cost but higher classification accuracy, compared with traditional kNN methods, which assign a fixed ${k}$ value to all test samples. Moreover, the proposed kTree method needs less running cost but achieves similar classification accuracy, compared with the newly kNN methods, which assign different ${k}$ values to different test samples. This paper further proposes an improvement version of kTree method (namely, k*Tree method) to speed its test stage by extra storing the information of the training samples in the leaf nodes of kTree, such as the training samples located in the leaf nodes, their kNNs, and the nearest neighbor of these kNNs. We call the resulting decision tree as k*Tree, which enables to conduct kNN classification using a subset of the training samples in the leaf nodes rather than all training samples used in the newly kNN methods. This actually reduces running cost of test stage. Finally, the experimental results on 20 real data sets showed that our proposed methods (i.e., kTree and k*Tree) are much more efficient than the compared methods in terms of classification tasks.

Observation of a charged charmoniumlike structure in e+ e- → (D* D*)± π∓ at √s = 4.26 GeV.

Abstract: We study the process e(+)e(-) -> pi(+)pi(-) J/psi at a center-of-mass energy of 4.260 GeV using a 525 pb(-1) data sample collected with the BESIII detector operating at the Beijing Electron Positron Collider. The Born cross section is measured to be (62.9 +/- 1.9 +/- 3.7) pb, consistent with the production of the Y(4260). We observe a structure at around 3.9 GeV/c(2) in the pi(+/-) J/psi mass spectrum, which we refer to as the Z(c)(3900). If interpreted as a new particle, it is unusual in that it carries an electric charge and couples to charmonium. A fit to the pi(+/-) J/psi invariant mass spectrum, neglecting interference, results in a mass of (3899.0 +/- 3.6 +/- 4.9) MeV/c(2) and a width of (46 +/- 10 +/- 20) MeV. Its production ratio is measured to be R = (sigma(e(+)e(-) -> pi(+/-) Z(c)(3900)(-/+) -> pi(+)pi(-) J/psi)/sigma(e(+)e(-) -> pi(+)pi(-) J/psi)) = (21.5 +/- 3.3 +/- 7.5)%. In all measurements the first errors are statistical and the second are systematic.

Rigid Pillars and Double Walls in a Porous Metal-Organic Framework: Single-Crystal to Single-Crystal, Controlled Uptake and Release of Iodine and Electrical Conductivity

Abstract: A highly stable pillared and double-walled zinc(II) metal-organic framework with regular nanochannels displays single-crystal to single-crystal transformation upon desolvation and a large quantity of iodine uptake, controlled release, and electrical conductivity elevation due to synergy between the iodine guests and the host framework.

PD-L1-mediated gasdermin C expression switches apoptosis to pyroptosis in cancer cells and facilitates tumour necrosis

Abstract: Although pyroptosis is critical for macrophages against pathogen infection, its role and mechanism in cancer cells remains unclear. PD-L1 has been detected in the nucleus, with unknown function. Here we show that PD-L1 switches TNFα-induced apoptosis to pyroptosis in cancer cells, resulting in tumour necrosis. Under hypoxia, p-Stat3 physically interacts with PD-L1 and facilitates its nuclear translocation, enhancing the transcription of the gasdermin C (GSDMC) gene. GSDMC is specifically cleaved by caspase-8 with TNFα treatment, generating a GSDMC N-terminal domain that forms pores on the cell membrane and induces pyroptosis. Nuclear PD-L1, caspase-8 and GSDMC are required for macrophage-derived TNFα-induced tumour necrosis in vivo. Moreover, high expression of GSDMC correlates with poor survival. Antibiotic chemotherapy drugs induce pyroptosis in breast cancer. These findings identify a non-immune checkpoint function of PD-L1 and provide an unexpected concept that GSDMC/caspase-8 mediates a non-canonical pyroptosis pathway in cancer cells, causing tumour necrosis.

Iodine Release and Recovery, Influence of Polyiodide Anions on Electrical Conductivity and Nonlinear Optical Activity in an Interdigitated and Interpenetrated Bipillared-Bilayer Metal–Organic Framework

Abstract: {[Cu6(pybz)8(OH)2]·I5–·I7–}n (1), obtained hydrothermally by using iodine molecules as a versatile precursor template, consists of a cationic framework with two types of zigzag channels, which segregate I5– and I7– anions. The framework exhibits the first observed bipillared-bilayer structure featuring both interdigitation and interpenetration. 1 displays high framework stability in both acidic (HCl) and alkaline (NaOH) solutions. 1 slowly releases iodine in dry methanol to give [Cu6(pybz)8(OH)2](I–)2·3.5CH3OH (1′) and partially recovers iodine from cyclohexane to form [Cu6(pybz)8(OH)2](I–)2·xI2 (1″). Differences of up to 100 times in electrical conductivity and of 4 times in nonlinear optical activity (NLO) have been measured between 1 and 1′. This compound is one of few displaying multifunctionality, electrical conductivity, NLO, and crystal–crystal stability upon release and recovery of iodine. It is also unique in the iodine release from polyiodide anions in a metal–organic framework.