Hot corrosion is the accelerated oxidation of materials at elevated temperatures induced by a thin film of fused salt deposit. Because of its high thermodynamic stability in the mutual presence of sodium and sulfur impurities in an oxidizing gas, Na 2 50 4 is often found to be the dominant salt in the deposit. The corrosive oxyanion-fused salts are usually ionica/ly conducting electrolytes that exhibit an acid/base chemistry, so that hot corrosion must occur by an electrochemical mechanism that may involve fluxing of the protective oxides. With the aid of hightemperature reference electrodes to quantify an acid/base scale, the solubilities for various metal oxides in fused Na 2 50 4 have been measured, and these show remarkable agreement with the theoretical expectations from the thermodynamic phase stability diagrams for the relevant Na-Metal-5-O systems. The solubilities of several oxides in fused Na 2 50 4 -NaV0 3 salt solutions have also been measured and modeled. Such information is important both in evaluating the corrosion resistance of materials and in interpreting any oxide flu xing/reprecipitation mechanisms. Various electrochemical measurements have identified the 5P/-anion (dissolved 503) as the oxidant that is reduced in the hot corrosion process . Electrochemical polarization studies have elucidated the corrosion reactions and clarified the corrosion kinetics of alloys. Mechanistic models for Type I and Type II hot corrosion are discussed briefly .

Recent years have witnessed an ever-mounting interest in the research of sparse representation. The framework, Sparse Representation-based Classification (SRC), has been widely applied as a classifier in numerous domains, among which Synthetic Aperture Radar (SAR) target recognition is really challenging because it still is an open problem to interpreting the SAR image. In this paper, SRC is utilized to classify a 10-class moving and stationary target acquisition and recognition (MSTAR) target, which is a standard SAR data set. Before the classification, the sizes of the images need to be normalized to maintain the useful information, target and shadow, and to suppress the speckle noise. Specifically, a preprocessing method is recommended to extract the feature vectors of the image, and the feature vectors of the test samples can be represented by the sparse linear combination of basis vectors generated by the feature vectors of the training samples. Then the sparse representation is solved by l 1 -norm minimization. Finally, the identities of the test samples are inferred by the reconstructive errors calculated through the sparse coefficient. Experimental results demonstrate the good performance of SRC. Additionally, the average recognition rate under different feature spaces and the recognition rate of each target are discussed.

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This study aimed to investigate the potential associations between carotid intima-media thickness and cognitive impairment among patients with acute ischemic stroke and to identify the clinical implications. We measured carotid intima-media thickness (IMT) and performed the Mini-Mental State Examination (MMSE) upon the admission of 1,826 acute ischemic stroke patients. The association between IMT and cognitive impairment evaluated by the MMSE was assessed with a multivariate regression analysis. Other clinical variables of interest were also assessed. After adjusting for potential confounders, participants in the highest IMT quartile had a higher likelihood of having cognitive impairments compared with the lowest IMT quartile (odds ratio: 3.01, 95% confidence interval: 2.07–4.37, p < 0.001). Stratified analyses indicated that this positive correlation was similar for the maxIMT and meanIMT of carotid artery measurements. A positive correlation was found between IMT and cognitive impairment in participants with acute ischemic stroke.

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The experimentally well-known alumina solubility in the range of acidic to neutral cryolite-base melts has been modeled thermodynamically in terms of several oxyfluoride solutes. For an acidic melt, cryolite ratio r ϭ 1.5, the dominant solute is monoxygen Na 2 Al 2 OF 6 . In a less acidic regime, dioxygen Na 2 Al 2 O 2 F 4 is dominant, whereas for neutral compositions (r ϭ 3), Na 4 Al 2 O 2 F 6 starts to gain importance. The fit of the model to the experimental solubility data is virtually perfect. The values of the equilibrium constants for the formation of the individual solutes are reported. The formation and conversion of these oxyfluoride complexes serve as an effective buffer opposing change in the melt basicity.

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Appreciable global efforts are underway to develop processes for fabricating three‐dimensional (3‐D) nanostructured assemblies for advanced devices. Widespread commercialization of such devices will require: (i) precise 3‐D fabrication of chemically tailored structures on a fine scale and (ii) mass production of such structures on a large scale. These often‐conflicting demands can be addressed with a revolutionary new paradigm that couples biological self‐assembly with synthetic chemistry: Bioclastic and Shape‐preserving Inorganic Conversion (BaSIC). Nature provides numerous examples of microorganisms that assemble biominerals into intricate 3‐D structures. Among the most spectacular of these microorganisms are diatoms (unicellular algae). Each of the tens of thousands of diatom species assembles silica nanoparticles into a microshell with a distinct 3‐D shape and pattern of fine (nanoscale) features. The repeated doubling associated with biological reproduction enables enormous numbers of such 3‐D microshells to be generated (e.g., only 40 reproduction cycles can yield >1 trillion 3‐D replicas!). Such genetic precision and massive parallelism are highly attractive for device manufacturing. However, the natural chemistries assembled by diatoms (and other microorganisms) are rather limited. With BaSIC processes, biogenic assemblies can be converted into a wide variety of new functional chemistries, while preserving the 3‐D morphologies. Ongoing advances in genetic engineering promise to yield microorganisms tailored to assemble nanoparticle structures with device‐specific shapes. Large‐scale culturing of such genetically tailored microorganisms, coupled with shape‐preserving chemical conversion (via BaSIC processes), would then provide low‐cost 3‐D Genetically Engineered Micro/nano‐devices (3‐D GEMs).