Stabilization of 6H-Hexagonal SrMnO3 Polymorph by Al2O3 insertion

We demonstrate the structural evolution of polymorphic phases in Al₂O₃-inserted SrMnO₃ ceramics synthesized by solid state reaction. While the 4H-hexagonal phase is predominant in pure SrMnO₃ ceramics, a small amount of 6H-hexagonal polymorph is identified in addition to the primary 4H-hexagonal SrMnO₃ and the secondary hexagonal SrAl₂O₄ phases in the as-sintered ceramics, evidenced by x-ray diffraction and subsequent Rietveld refinement analyses. The existence of the 6H-hexagonal SrMnO₃ phase is corroborated using Raman spectroscopy. The chemical compositions and electronic structures of the Al₂O₃-inserted SrMnO₃ compounds are also examined using energy dispersive spectroscopy and x-ray photoelectron spectroscopy, respectively. The first-principles calculations reveal that there is no clear difference between the total energies of 4H- and 6H-hexagonal polymorphs regardless of the presence/absence of Sr and oxygen vacancies. Possible origins are discussed with the estimation of actual strain based on the refined lattice parameter of 6H SrMnO₃.     

A 1 GHz CMOS analog front-end for a generalized PRML read channel

A 1 GHz CMOS analog front-end for general partial response maximum likelihood (GPRML) read channel in hard disk drive application has been implemented in 0.35 /spl mu/m CMOS. A continuous time analog filter fulfills the relaxed equalization for GPRML detection and can save up to 35% power consumption for the whole read channel. An analog DFE-based timing recovery loop is implemented to avoid the extremely long latency in the digital signal processing path (Viterbi decoder). The measured performances is 1.1 dB off simulations at 800 MHz and 1.6 dB off at 1GHz. The chip draws 240 mW from a 3.3 V supply at 800MHz clock and 380 mW from a 3.6 V supply at 1 GHz clock.     

Synthesis and thermomechanical characterization of polyurethane elastomers extended with α,ω‐alkane diols

A series of polyurethane (PU) elastomers was prepared by the reaction of poly(?‐caprolactone) and 4,4′‐diphenylmethane diisocyanate, which was extended with a series of chain extenders (CEs) having 2–10 methylene units in their structure. The completion of the reaction was confirmed by Fourier transform infrared spectroscopy. The chemical structures of the synthesized PU samples were characterized with Fourier transform infrared, ¹H‐NMR, and ¹³C‐NMR spectroscopy, and the thermal properties were determined by thermogravimetric analysis, DSC, and dynamic mechanical thermal analysis techniques. The mechanical properties were also studied and are discussed. The thermogravimetric analysis and DSC analysis showed that CE length had a considerable effect on the thermal properties of the prepared samples. The dynamic mechanical thermal analysis and damping peaks were also affected by the number of methylene units in the CE length. The elastomer extended with 1,2‐ethane diol exhibited optimum thermal properties, whereas the elastomer based on 1,10‐decane diol displayed the worst thermal properties. Tensile strength and elongation at break decreased with increasing CE length, whereas hardness showed the opposite trend. The glass‐transition temperature moved toward lower temperatures with increasing CE length. The decrease in the glass‐transition temperature and tensile properties were interpreted in terms of decreasing hard segments and increasing chain flexibility. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Hero Wavelength Spectral Sampling

We present a spectral rendering technique that offers a compelling set of advantages over existing approaches. The key idea is to propagate energy along paths for a small, constant number of changing wavelengths. The first of these, the hero wavelength, is randomly sampled for each path, and all directional sampling is solely based on it. The additional wavelengths are placed at equal distances from the hero wavelength, so that all path wavelengths together always evenly cover the visible range. A related technique, spectral multiple importance sampling, was already introduced a few years ago. We propose a simplified and optimised version of this approach which is easier to implement, has good performance characteristics, and is actually more powerful than the original method. Our proposed method is also superior to techniques which use a static spectral representation, as it does not suffer from any inherent representation bias. We demonstrate the performance of our method in several application areas that are of critical importance for production work, such as fidelity of colour reproduction, sub‐surface scattering, dispersion and volumetric effects. We also discuss how to couple our proposed approach with several technologies that are important in current production systems, such as photon maps, bidirectional path tracing, environment maps, and participating media.     

3D Simulation Research on Urea-SCR DeNO<em>x Catalyst for Diesel Engine

In order to reduce oxides of nitrogen (NOx) emanated from a diesel eng ine, a comprehensive urea selective catalyst reduction (SCR) DeNOx catalys t was modeled in which numerical simulations were used as a complementary tool f or the experimental investigations to make the design decisions, and hence short en the development process. In this approach, relevant conversion reactions were studied in 1D model, and the parameters obtained in this way were transferred t o 3D simulations. According to the results ...     

直觉线性μ-演算

线性mu-演算(μTL)是线性时序逻辑(LTL)的不动点扩展.LTL是一个便于规范和论证反应式系统的方法.μTL作为比LTL表达能力更强的逻辑,用LTL表示的性质度可由μTL表示.类似于LTL的直觉线性时序逻辑(ILTL),提出一种基于直觉解释的μTL,称为直觉μTL(IμTL).确立了IμTL和ILTL的关系,比较了它们之间的表达能力.讨论了使用IμTL与安全性质和活性描述的关系以及描述"假设-保证"规范的问题.     

直觉线性μ-演算中的合成推理

讨论了以基于前缀封闭集合的Heyting代数的直觉解释的线性μ-演算(IμTL)作为描述“假设-保证”的逻辑基础的问题,提出了一个基于IμTL的“假设-保证”规则.该规则比往常应用线性时序逻辑(LTL)作为规范语言的那些规则具有更好的表达能力,扩展了对形如“always ?”等安全性质的“假设-保证”的范围,具备更一般的“假设-保证”推理能力及对循环推理的支持.     

Nutratherapeutics approach against cancer: tomato‐mediated synthesised gold nanoparticles

In this study, an eco‐friendly biosynthesis of stable gold nanoparticles (T‐GNPs) was carried out using different concentrations of tomato juice (nutraceuticals) as a reducing agent and tetrachloroauric acid as a metal precursor to explore their potential application in cancer therapeutics. The synthesis of T‐GNPs was monitored by UV‐visible absorption spectroscopy, which unveiled their formation by exhibiting the typical surface plasmon absorption maxima at 522 nm. The size of T‐GNPs was found to be 10.86 ± 0.6 nm. T‐GNPs were characterised by dynamic light scattering, zeta potential, transmission electron microscopy analysis and Fourier transform infrared spectroscopy. T‐GNPs were further investigated for their anti‐cancer activity against human lung carcinoma cell line (A ₅₄₉) and human cervical cancer cell line wherein the IC₅₀ values were found to be 0.286 and 0.200 mM, respectively. T‐GNPs inhibited the growth of cancer cells by generating ROS and inducing apoptosis. T‐GNPs were found highly effective by virtue of their size, metallic property and capping molecules. Thus, this study opens up the prospects of using nutraceutical (tomato juice) as nutratherapeutic agent (T‐GNPs) against critical diseases like lung cancer and cervical cancer.Inspec keywords: gold, nanoparticles, particle size, cancer, ultraviolet spectra, visible spectra, electrokinetic effects, transmission electron microscopy, Fourier transform infrared spectra, cellular biophysics, spectrochemical analysis, nanomedicine, nanofabricationOther keywords: tomato‐mediated synthesised gold nanoparticles, tomato juice, reducing agent, tetrachloroauric acid, cancer therapeutics, UV‐visible absorption spectroscopy, surface plasmon absorption, dynamic light scattering, zeta potential, transmission electron microscopy analysis, Fourier transform infrared spectroscopy, human lung carcinoma cell line, anticancer activity, human cervical cancer cell line, nutratherapeutic agent, lung cancer, Au     

End-to-End 2D Convolutional Neural Network Architecture for Lung Nodule Identification and Abnormal Detection in Cloud

The extent of the peril associated with cancer can be perceived from the lack of treatment, ineffective early diagnosis techniques, and most importantly its fatality rate. Globally, cancer is the second leading cause of death and among over a hundred types of cancer; lung cancer is the second most common type of cancer as well as the leading cause of cancer-related deaths. Anyhow, an accurate lung cancer diagnosis in a timely manner can elevate the likelihood of survival by a noticeable margin and medical imaging is a prevalent manner of cancer diagnosis since it is easily accessible to people around the globe. Nonetheless, this is not eminently efficacious considering human inspection of medical images can yield a high false positive rate. Ineffective and inefficient diagnosis is a crucial reason for such a high mortality rate for this malady. However, the conspicuous advancements in deep learning and artificial intelligence have stimulated the development of exceedingly precise diagnosis systems. The development and performance of these systems rely prominently on the data that is used to train these systems. A standard problem witnessed in publicly available medical image datasets is the severe imbalance of data between different classes. This grave imbalance of data can make a deep learning model biased towards the dominant class and unable to generalize. This study aims to present an end-to-end convolutional neural network that can accurately differentiate lung nodules from non-nodules and reduce the false positive rate to a bare minimum. To tackle the problem of data imbalance, we oversampled the data by transforming available images in the minority class. The average false positive rate in the proposed method is a mere 1.5 percent. However, the average false negative rate is 31.76 percent. The proposed neural network has 68.66 percent sensitivity and 98.42 percent specificity.     

On a new class of analytic functions associated with conic domain

The aim of this paper is to generalize the conic domain defined by Kanas and Wisniowska, and define the class of functions which map the open unit disk E onto this generalized conic domain. A brief comparison between these conic domains is the main motivation of this paper. A correction is made in selecting the range interval of order of conic domain.