Probability of Detection in Corrosion Monitoring with Fe-C Coated LPFG Sensors

This project aims to develop two statistical methods for determining the probability of detection in corrosion monitoring using long period fiber gratings (LPFG) sensors with thin Fe-C coating, validate these methods from independent laboratory tests, and determine the steel mass loss at 90% probability of detection and the largest steel mass loss that may miss from a corrosion inspection at 95% upper confidence bounds. LPFG sensors could reflect the corrosion process by the wavelength shift in the transmission spectrum due to the change of the refractive index of the Fe-C coating. POD is a method used to determine the capability of an inspection as a function of defect type and defect size. The two statistical methods are referred to as the Mass Loss-at-Detection (MLaD) method and the Random- Effects Generalization (REG) method

RESEARCH ON THE BATTNG MECHANISM OF BASEBALL

The purpose of this study is to improve the batting technique of Chinese baseball athletes through the application of biomechanical analysis. In order to perform successfully, the batting technique of Chinese baseball players requires immediate improvement. The best approach is to improve the traditional batting technique, training methods, and to introduce a new batting mechanism. In practice, batters must emphasize contraction of the muscles around the last joints of arm. The accuracy of batting is of primary importance. The batter starts to swing when the distance between the coming ball and the front line of rubber is about 3.4m. The swinging and batting time should not exceed 0.1s, and the vertical displacement of the gravity of body is near zero during batting. In the instant of contact, the arm is bent and the wrist turns over. These results with the new batting mechanism have been used in practice for more than 3 years, and the feedback from China Baseball Team indicates that the research results have been effective and can be applied easily

New predictions on the mass of the 1−+1^{-+} light hybrid meson from QCD sum rules

We calculate the coefficients of the dimension-8 quark and gluon condensates in the current-current correlator of $1^{-+}$ light hybrid current $g\bar{q}(x)\gamma_{\nu}iG_{\mu\nu}(x)q{(x)}$. With inclusion of these higher-power corrections and updating the input parameters, we re-analyze the mass of the $1^{-+}$ light hybrid meson from Monte-Carlo based QCD sum rules. Considering the possible violation of factorization of higher dimensional condensates and variation of $\langle g^3G^3\rangle$, we obtain a conservative mass range 1.72--2.60\,GeV, which favors $\pi_{1}(2015)$ as a better hybrid candidate compared with $\pi_{1}(1600)$ and $\pi_{1}(1400)$.Comment: 12pages, 2 figures, the version appearing in JHE

Natural Gas Induced Vegetation Stress Identification and Discrimination from Hyperspectral Imaging for Pipeline Leakage Detection

Remote Sensing Detection of Natural Gas Leaks Remains Challenging When using Ground Vegetation Stress to Detect Underground Pipeline Leaks. Other Natural Stressors May Co-Present and Complicate Gas Leak Detection. This Study Explores the Feasibility of Identifying and Distinguishing Gas-Induced Stress from Other Natural Stresses by Analyzing the Hyperspectral Reflectance of Vegetation. the Effectiveness of This Discrimination is Assessed Across Three Distinct Spectral Ranges (VNIR, SWIR, and Full Spectra). Greenhouse Experiments Subjected Three Plant Species to Controlled Environmental Stressors, Including Gas Leakage, Salinity Impact, Heavy-Metal Contamination, and Drought Exposure. Spectral Curves Obtained from the Experiments Underwent Preprocessing Techniques Such as Standard Normal Variate, First-Order Derivative, and Second-Order Derivative. Principal Component Analysis Was Then Employed to Reduce Dimensionality in the Spectral Feature Space, Facilitating Input for Linear/quadratic Discriminant Analysis (LDA/QDA) to Identify and Discriminate Gas Leaks. Results Demonstrate an Average Accuracy of 80% in Identifying Gas-Stressed Plants from Unstressed Ones using LDA. Gas Leakage Can Be Discriminated from Scenarios Involving a Single Distracting Stressor with an Accuracy Ranging from 76.4% to 84.6%, with Drought Treatment Proving the Most Successful. Notably, First-Order Derivative Processing of VNIR Spectra Yields the Highest Accuracy in Gas Leakage Detection