Spectroscopic Features and Formation Conditions of Sphalerite in the Lead-Zinc Deposit, Guangdong,China

Electron paramagnetic resonance spectra, absorption spectra, cathodoluminescence spectra and infrared spectra of sphalerite from the Lechang remoulded sedimentary lead-zinc deposit have been studied so as to provide microscopic evidence for the formation conditions and mineralization stages of the deposit as well as the geochemical processes of mineralization. On the basis of thermodynamic calculations, the stable fields of sphalerite from different mineralization stages were determined and are shown in logfs_2-logfo_2 diagrams; furthermore. the physico-chemical conditions of mineralization and the properties of mineralization solutions are discussed so that reliability of the genetic information provided by the spectroscopy of sphalerite may also be verified. It is suggested that the temperature and pH value of the mineralization system decrease, and so do the fugacities of O_2, S_2, H_2. and H_2S and the activities of HS^- and SO_4^(2-) from the early to late stages of minerahzation.

Model-free conditional independence feature screening for ultrahigh dimensional data

Feature screening plays an important role in ultrahigh dimensional data analysis.This paper is concerned with conditional feature screening when one is interested in detecting the association between the response and ultrahigh dimensional predictors(e.g.,genetic makers)given a low-dimensional exposure variable(such as clinical variables or environmental variables).To this end,we first propose a new index to measure conditional independence,and further develop a conditional screening procedure based on the newly proposed index.We systematically study the theoretical property of the proposed procedure and establish the sure screening and ranking consistency properties under some very mild conditions.The newly proposed screening procedure enjoys some appealing properties.(a)It is model-free in that its implementation does not require a specification on the model structure;(b)it is robust to heavy-tailed distributions or outliers in both directions of response and predictors;and(c)it can deal with both feature screening and the conditional screening in a unified way.We study the finite sample performance of the proposed procedure by Monte Carlo simulations and further illustrate the proposed method through two real data examples.