Production technology for low-carbon,low-sulfur boron steel

A technology for slag formation in the ladle–furnace unit is considered; the slag is based on the CaO–SiO₂–MgO–Al₂O₃–B₂O₃ system. This technology permits both microalloying of the steel with boron (reduced from the oxide phase) and desulfurization of the steel. The resulting boron content in the steel is 0.001–0.008%; the sulfur content in low-alloy steel and pipe steel is low (0.004–0.010%); and the consumption of manganese ferroalloys is reduced to 0.5 kg/t for 08кп steel and 1.4 kg/t for 09Г2C steel. In addition, the proposed technology increases the strength of the rolled steel, without loss in its plasticity; and reduces the environmental impact thanks to the replacement of fluorspar by colemanite.     

Lecture capture with real‐time rearrangement of visual elements: impact on student performance

The primary goal of this study is to create and test a lecture‐capture system that can rearrange visual elements while recording is still taking place, in such a way that student performance can be positively influenced. The system we have devised is capable of integrating and rearranging multimedia sources, including learning content, the instructor and students' images, into lecture videos that are embedded in a website for students to review after school. The present study employed a two‐group experimental design, with 153 participants (145 females and 8 males) making up an experimental group in which lecture courses were recorded using the new lecture‐capture system, and 149 participants (140 females and 9 males) forming a control group whose lectures were recorded by traditional means. All participants were in the freshman college and studying Introduction to Computer and Information Science in one of six classes, and were randomly assigned to one of the two groups. The participants' midterm examination and final examination scores were collected as indicators of their academic performance, with their mathematics entrance scores used as a pre‐test. The findings obtained from analysis of covariance (ANCOVA) suggest that appropriate rearrangement of visual elements in lecture videos can significantly impact students' learning performance.     

基于光纤技术的采空区发火监测系统的应用

基于光纤技术的采空区发火监测系统由传感器、数据传输、数据分析与控制三大部分构成,研发新一代适合煤矿安全领域应用的先进传感器、并以此为基础构建新型煤矿安全灾害监测预警系统,对于实现煤矿安全发展具有十分重要的意义。     

The Spatial LASSO With Applications to Unmixing Hyperspectral Biomedical Images

Hyperspectral imaging (HSI) is a spectroscopic method that uses densely sampled measurements along the electromagnetic spectrum to identify the unique molecular composition of an object. Traditionally HSI has been associated with remote sensing-type applications, but recently has found increased use in biomedicine, from investigations at the cellular to the tissue level. One of the main challenges in the analysis of HSI is estimating the proportions, also called abundance fractions of each of the molecular signatures. While there is great promise for HSI in the area of biomedicine, large variability in the measurements and artifacts related to the instrumentation has slow adoption into more widespread practice. In this article, we propose a novel regularization and variable selection method called the spatial LASSO (SPLASSO). The SPLASSO incorporates spatial information via a graph Laplacian-based penalty to help improve the model estimation process for multivariate response data. We show the strong performance of this approach on a benchmark HSI dataset with considerable improvement in predictive accuracy over the standard LASSO. Supplementary materials for this article are available online.     

Phase-Structural and Electrochemical Properties of La2MgNi9 Alloys

Powder Metallurgy and Metal Ceramics - Multiphase La 2 MgNi 9 alloys are synthesized by induction melting. The crystalline structures of all phases in the alloys are determined with X-ray...