Majorana neutrino signals at Belle-II and ILC

For some theoretical and experimental considerations, the relatively light Majorana neutrinos at the GeV scale have been attracting some interest. In this article we consider a scenario with only one Majorana neutrino $N$, negligible mixing with the active neutrinos $\nu_{L}$, where the Majorana neutrino interactions could be described in a model independent approach based on an effective theory. Under such a framework, we particularly study the feasibility of observing the $N$ with mass in the range 0$-$30 GeV via the process e^+ e^- \to \nu N \to\gamma + \slashed E in the future Belle-II and ILC experiments. The results show that it is unpromising for Belle-II to observe the signal, while ILC may easily make a discovery for the Majorana neutrino.Comment: 14 pages, 7 figures, 2 table

The semi-leptonic form factors of Λb→Λc\Lambda_{b}\to\Lambda_{c} and Ξb→Ξc\Xi_{b}\to\Xi_{c} in QCD sum rules

In this work, the full leading order results of the form factors for $\Xi_{b}\to\Xi_{c}$ and $\Lambda_{b}\to\Lambda_{c}$ are obtained in QCD sum rules. Contributions from up to dim-5 have been considered. For completeness, we also study the two-point correlation function to obtain the pole residues of $\Xi_{Q}$ and $\Lambda_{Q}$, and higher accuracy is achieved. For the three-point correlation function, since stable Borel regions can not be found, about $20\%$ uncertainties are introduced for the form factors of $\Xi_{b}\to\Xi_{c}$ and $\Lambda_{b}\to\Lambda_{c}$. Our results for the form factors are consistent with those of the Lattice QCD within errors.Comment: 17 pages, 5 figure

Polymorphisms and a Haplotype in Heparanase Gene Associations with the Progression and Prognosis of Gastric Cancer in a Northern Chinese Population

Background: Human heparanase plays an important role in cancer development and single nucleotide polymorphisms (SNPs) in the heparanase gene (HPSE) have been shown to be correlated with gastric cancer. The present study examined the associations between individual SNPs or haplotypes in HPSE and susceptibility, clinicopathological parameters and prognosis of gastric cancer in a large sample of the Han population in northern China. Methodology/Principal Findings: Genomic DNA was extracted from formalin-fixed, paraffin-embedded normal gastric tissue samples from 404 patients and from blood from 404 healthy controls. Six SNPs were genotyped by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. A chi-square (x2) test and unconditional logistic regression were used to analyze the risk of gastric cancer; a Log-rank test and Cox proportional hazards model were used to produce survival analysis and a Kaplan-Meier method was used to map survival curves. The mean genotyping success rates were more than 99 % in both groups. Haplotype CA in the block composed of rs11099592 and rs4693608 had a greater distribution in the group of Borrmann types 3 and 4 (P = 0.037), the group of a greater number of lymph node metastases (N3 vs N0 group, P = 0.046), and moreover was correlated to poor survival (CG vs CA: HR = 0.645, 95%CI: 0.421–0.989, P = 0.044). In addition, genotypes rs4693608 AA and rs4364254 TT were associated with poor survival (P = 0.030, HR = 1.527, 95%CI: 1.042–2.238 for rs4693608 AA; P = 0.013, HR = 1.546, 95%CI: 1.096–2.181 for rs4364254 TT). There were n

GAP-type low-temperature polycrystalline silicon thin film transistors for light sensing photo-transistor application

Recently, ultra-high resolution with biometric recognitions such as fingerprint sensing has been a major trend throughout the whole display industry. In order to meet the needs of high screen ratio, high sensitivity to read out, low temperature polycrystalline silicon (LTPS) thin film transistor (TFT) is considered one of the candidates for sensing application. Unlike photodiode, LTPS photo-transistor structured as transistor makes it possible to sensing under different region (off-state or on state) with relatively small sensing area. Please click Download on the upper right corner to see the full abstract