Lubricant as a sticking-scale inhibitor on high temperature sliding contact

Sticking oxide scale is one of the most serious concerns on moving steel surfaces at elevated temperature. However, there has been limited research dedicated to overcoming this issue. In the present work, pin-on-disc testing was carried out to reveal the effects of lubrication on wear characteristics of High Speed Steel sliding against Stainless Steel 316 at 700 °C. Apart from improved friction behavior, the use of inorganic lubricant significantly inhibits material transfer onto the HSS surface which otherwise suffers growing adhered scale during dry sliding contact. In addition, it was found that prolonged exposure to lubrication induces phase transformation of the subsurface iron oxides. The Hematite-to-Magnetite conversion is believed to be a result of complex oxidation and tribological reactions. Multiple characterization techniques were used to thoroughly analyze the worn surfaces, the underlying oxide microstructure and the chemical nature of lubricated interface

Understanding the tribological impacts of alkali element on lubrication of binary borate melt

Melt lubricants have been regarded as an effective class to deliver lubrication on moving mechanical contacts at extreme temperatures. Among the elementary constituents, alkali elements play a critical role in governing the physical-chemical characteristics of the lubricant despite the obscurity regarding their intrinsic roles on the rubbing interfaces. The present study attempts to unfold the effects of sodium on the tribological responses of mating steel pair under borate melt lubrication. It has been found that the involvement of Na inspires a total reversal in lubricating potentials of the lone B2O3melt manifested by remarkable friction reduction, wear inhibition and prolonged load-bearing capacity. These exceptional performances are attributed to the accretion of nanothin Na layers on the contact interfaces. The interfacial occurrences are interpreted from a physico-chemistry perspective while the influences of surface microstructure are also discussed in detail. Multiple characterizations are employed to thoroughly examine the sliding interfaces in multi-dimensions including Scanning Electron Microscopy (SEM), Scanning Transmission Electron Microscopy (STEM) and Atomic Force Microscopy (AFM). In addition, chemical fingerprints of relevant elements are determined by Energy Dispersive Spectroscopy (EDS) and Electron Loss Energy Spectroscopy (EELS)

Identifying Computer-Translated Paragraphs using Coherence Features

We have developed a method for extracting the coherence features from a paragraph by matching similar words in its sentences. We conducted an experiment with a parallel German corpus containing 2000 human-created and 2000 machine-translated paragraphs. The result showed that our method achieved the best performance (accuracy = 72.3%, equal error rate = 29.8%) when it is compared with previous methods on various computer-generated text including translation and paper generation (best accuracy = 67.9%, equal error rate = 32.0%). Experiments on Dutch, another rich resource language, and a low resource one (Japanese) attained similar performances. It demonstrated the efficiency of the coherence features at distinguishing computer-translated from human-created paragraphs on diverse languages.Comment: 9 pages, PACLIC 201

Cloning and expression of gene FanC-2NT encoding K99-2NT fimbrial antigen of enterotoxigenic Escherichia coli from diarrheic post-weaning piglets

Background and Purpose: The K99 (F5) is one pilus adhesin that mediates the attachment of enterotoxigenic E. coli (ETEC) strains to small intestines to cause to diarrhea in piglets, lambs and newborn calves. In this work, we carried out cloning and expression of the mature peptide of FanC subunit, K99 fimbriae, one of the most common adhesive antigens in E. coli. Materials and Methods: E. coli 2NT strain was isolated from fecal samples of post-weaning piglets with diarrhea. The coding sequence of the mature peptide of K99-2NT subunit was isolated by PCR amplification and cloned into pGEM®-T Easy vector for sequencing using fluorescent dideoxy-terminator method. Expression of K99-2NT protein which was inserted into pET200/D-TOPO vector induced with IPTG. The PCR product and expression level of protein was examined by agarose gel electrophoresis and sodium dodecyl sulfate-polyacrylamide gel electrophoresis, respectively. Results and Conclusions: We cloned and expressed successfully the mature peptide of K99 subunit with molecular weight of approximately 17.5 kDa from E. coli 2NT strain (named K99-2NT). Nucleotide sequence of the K99-2NT subunit coding region of fanC-2NT gene is 477 bp in length and is 99% similarity with that of fanC gene (accession no: M35282). Highest expression level occurred after 12 h of induction with 0.75 mM IPTG at 37oC. This subunit antigen will be tested for immune response of rat in the next time

Transformation on Computer-Generated Facial Image to Avoid Detection by Spoofing Detector

Making computer-generated (CG) images more difficult to detect is an interesting problem in computer graphics and security. While most approaches focus on the image rendering phase, this paper presents a method based on increasing the naturalness of CG facial images from the perspective of spoofing detectors. The proposed method is implemented using a convolutional neural network (CNN) comprising two autoencoders and a transformer and is trained using a black-box discriminator without gradient information. Over 50% of the transformed CG images were not detected by three state-of-the-art spoofing detectors. This capability raises an alarm regarding the reliability of facial authentication systems, which are becoming widely used in daily life.Comment: Accepted to be Published in Proceedings of the IEEE International Conference on Multimedia and Expo (ICME) 2018, San Diego, US

Predicting Academic Performance: A Systematic Literature Review

The ability to predict student performance in a course or program creates opportunities to improve educational outcomes. With effective performance prediction approaches, instructors can allocate resources and instruction more accurately. Research in this area seeks to identify features that can be used to make predictions, to identify algorithms that can improve predictions, and to quantify aspects of student performance. Moreover, research in predicting student performance seeks to determine interrelated features and to identify the underlying reasons why certain features work better than others. This working group report presents a systematic literature review of work in the area of predicting student performance. Our analysis shows a clearly increasing amount of research in this area, as well as an increasing variety of techniques used. At the same time, the review uncovered a number of issues with research quality that drives a need for the community to provide more detailed reporting of methods and results and to increase efforts to validate and replicate work.Peer reviewe

Tribochemistry and lubrication of alkaline glass lubricants in hot steel manufacturing

Nowadays, the increasing demand to reduce energy consumption and improve process reliability requires an alternative lubricant with an effective tribological performance and environmentally friendly properties to replace traditional lubricants in hot steel manufacturing. The current work reviews recent comprehensive experimental and theoretical investigations in a new generation of alkaline-based glass lubricants, with phosphate, borate, and silicate being intensively researched. This class of lubricants showed an outstanding friction reduction, anti-wear, and anti-oxidation performance on coupled steel pairs over a wide range of temperatures (from 650 °C to 1000 °C). Each type had different tribochemical reactions within itself and with oxidized steel surfaces, which were largely determined by their chemical nature. In addition, the critical role of each structural component was also determined and corroborated by computational simulation. The theoretical studies at quantum and atomic levels reinforced our experimental findings by providing insights into the reaction mechanism using the static and dynamic simulations of the adsorption of lubricant molecules onto iron oxide surfaces. Additionally, the new reactive molecular dynamics (MD) model developed for alkali phosphate will need to be extended further to consider the realistic operating conditions of these lubricants at the atomic scale