Nonnegative Matrix Factorization Numerical Method for Integrated Photonic Cavity Based Spectroscopy

Nonnegative matrix factorization numerical method has been used to improve the spectral resolution of integrated photonic cavity based spectroscopy. Based on the experimental results for integrated photonic cavity device on Optics Letters 32, 632 (2007), the theoretical results show that the spectral resolution can be improved more than 3 times from 5.5 nm to 1.8 nm. It is a promising way to release the difficulty of fabricating high-resolution devices

Study on cosmogenic activation in copper for rare event search experiments

The rare event search experiments using germanium detectors are performed in the underground laboratories to prevent cosmic rays. However, the cosmogenic activation of the cupreous detector components on the ground will generate long half-life radioisotopes and contribute continually to the expected background level. We present a study on the cosmogenic activation of copper after 504 days of exposure at an altitude of 2469.4 m outside the China Jinping Underground Laboratory (CJPL). The specific activities of the cosmogenic nuclides produced in the copper bricks were measured using a low background germanium gamma-ray spectrometer at CJPL. The production rates at sea level, in units of nuclei/kg/day, are 18.6 \pm 2.0 for Mn-54, 9.9 \pm 1.3 for Co-56, 48.3 \pm 5.5 for Co-57, 51.8 \pm 2.5 for Co-58 and 39.7 \pm 5.7 for Co-60, respectively. Given the expected exposure history of the germanium detectors, a Monte Carlo simulation is conducted to assess the cosmogenic background contributions of the detectors' cupreous components.Comment: 6 pages, 4 figure

Validation of the neural network for 3D photon radiation field reconstruction under various source distributions

Introduction: This paper proposes a five-layer fully connected neural network for predicting radiation parameters in a radiation space based on detector readings.Methods: The network is trained and tested using gamma flux values from individual detector positions as input, and is used to predict the gamma radiation field in 3D space under different source term distributions. The method is evaluated using the mean percentage change error (PCT) for the test set under different source term distributions.Results: The results show that the neural network method can accurately predict radiation parameters with an average PCT error range of 0.53% to 3.11%, within the given measurement input error range of ± 10%. The method also demonstrates its ability to directly reconstruct the 3D radiation field with some simple source terms.Discussion: The proposed method has practical value in real operations within radiation spaces, and can be used to improve the accuracy and efficiency of predicting radiation parameters. Further research could explore the use of more complex source term distributions and the integration of other types of sensors for improved accuracy

Targeting epithelial-mesenchymal transition and cancer stem cells for chemoresistant ovarian cancer

Chemoresistance is the main challenge for the recurrent ovarian cancer therapy and responsible for treatment failure and unfavorable clinical outcome. Understanding mechanisms of chemoresistance in ovarian cancer would help to predict disease progression, develop new therapies and personalize systemic therapy. In the last decade, accumulating evidence demonstrates that epithelial-mesenchymal transition and cancer stem cells play important roles in ovarian cancer chemoresistance and metastasis. Treatment of epithelial-mesenchymal transition and cancer stem cells holds promise for improving current ovarian cancer therapies and prolonging the survival of recurrent ovarian cancer patients in the future. In this review, we focus on the role of epithelial-mesenchymal transition and cancer stem cells in ovarian cancer chemoresistance and explore the therapeutic implications for developing epithelial-mesenchymal transition and cancer stem cells associated therapies for future ovarian cancer treatment