Separation of hematite from banded hematite jasper (BHJ) by magnetic coating

The separation of iron oxide from banded hematite jasper(BHJ) assaying 47.8% Fe, 25.6% Si O2 and 2.30%Al2O3 using selective magnetic coating was studied. Characterization studies of the low grade ore indicate that besides hematite and goethite,jasper, a microcrystalline form of quartzite, is the major impurity associated with this ore. Beneficiation by conventional magnetic separation technique could yield a magnetic concentrate containing 60.8% Fe with 51% Fe recovery. In order to enhance the recovery of the iron oxide minerals, fine magnetite, colloidal magnetite and oleate colloidal magnetite were used as the coating material. When subjected to magnetic separation, the coated ore produces an iron concentrate containing 60.2% Fe with an enhanced recovery of56%. The AFM studies indicate that the coagulation of hematite particles with the oleate colloidal magnetite facilitates the higher recovery of iron particles from the low grade BHJ iron ore under appropriate conditions.     

Potentiometric sensors with plastized poly(vinyl chloride) membranes selective to penicillin antibiotics: Properties and applications

Potentiometric sensors with plasticized poly(vinyl chloride) membranes based on β-lactam–tetraalkylammonium ion associates sensitive to penicillin antibiotics are proposed. The physicochemical characteristics (solubility product constants and dissociation constants) of active membrane components and the electrode, transport, and selective properties of the membranes of liquidand solid-contact sensors have been studied. The quantitative characteristics of membrane transport (penetrability, ion flux, and transport rate) have been evaluated. The main charge carriers in the membranes and at the membrane/solution interface have been determined from the membrane transport characteristics. The potentiometric sensors are shown to be applicable to the determination of penicillin antibiotics in biological fluids (blood serum and oral fluid) from patients with urinary tract infection.     

Measuring equipment and test bench to control evolution of acoustic-deformation and heat fields induced in solids under failure by fluids

The authors have developed a procedure and a test bench for studying evolution of various nature physical fields in modeling geomedium fracture by fluids. The test bench performs synchronous recording of macro- and micro-deformation, heat and acoustic emission induced in physical models of geomedium under loading to discontinuity. The experimental procedure has been trialed. The analysis of the synchronized test data allows a conclusion on the existence of time–space relationship between different nature physical fields induced during failure of solids.     

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.     

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.