Effects of Chloride Deposit and Coal Ash on High-Temperature Corrosion of Chromia-Forming Alloys

Oxy-fuel combustion is a promising technology being trialled in power generation plants to allow easier CO2 separation and subsequent sequestration. However, the highly corrosive CO2-H2O rich flue gas is detrimental to commonly used boiler alloys. This situation becomes even worse in the presence of ash and salt produced during coal combustion process. In this work, the effect of chloride salts (NaCl-KCl) on Fe-based (ferritic and austenitic) and Ni-based alloys was first investigated in Ar-60CO2-H2O at 550oC, 650oC, and 750oC. After that, the effect of coal ash (industrial Eraring ash) was examined by study the corrosion behaviour of chromia-forming alloys with the presence of coal ash + chloride salt (10, 50, 75wt%) at 550oC, 650oC, and 750oC. A model ferritic Fe-25wt% Cr alloy exposed to an Ar-60CO2-20H2O gas mixture at 550oC and 650C experienced rapid oxide scale growth and simultaneous internal carburization, while a thin protective scale was formed on Fe-25wt%Cr after gas-only reaction at 750oC. When a deposit of NaCl-KCl was present on the alloy surface, external porosity of the oxides increased at all temperatures, and the protective scale was interrupted by Fe-rich oxide nodules at 750oC. In the absence of salt, alloy additions of Mn+Si led to improved protection: slow oxide scaling and no carburization at all different temperatures. In the presence of salt, this protection was much reduced at 550oC and 650oC, and at 750oC the protective effect of Mn and Si disappeared. These effects are attributed to oxide volatilisation by chlorination and ferrite chromium depletion by carburization. Fe-25wt%Cr-20wt%Ni underwent breakaway oxidation in the gas-only case at all three temperatures. The porosity increased in both outer and inner oxide layers in the presence of chloride salts, and the subsurface porosities were also observed. The alloy with the additional Mn + Si performed protectively in the gas-only case at all three temperatures, while in the presence of salt, this protection was completely gone with even thicker oxide scales formed on 310SS at 650oC and 750oC. For Ni-25wt%Cr, thick internal oxidation zones (IOZs) and external oxide scales were formed without salt deposits at 650oC and 750oC, and the scale thickness slightly decreased at 550oC. The oxide structure was the same at all three temperatures. Localised structure consisted of external thick chromia with subsurface voids appeared in the presence of chloride salts, and the area occupancy of this localised structure increased with increasing temperature. Ni-25wt%Cr-2wt%Mn-1wt%Si formed a protective layer in the gas-only case at all temperatures, but almost no such a protective layer was observed in the presence of chloride salts, especially at 650oC. In the condition of coexistence of salt and ash, corrosion behaviours of the alloys varied with the temperature. At 550oC, all alloys except Fr-25wt%Cr underwent most severe corrosion in the 75wt% and 100wt% salt cases with the increased extent of corrosion with increasing salt content in the deposit. However, for Fe-25wt%Cr, the scales formed in the ash + salt cases are thinner than the gas-only and 100wt% chloride cases. At 650oC, Fe-25wt%Cr performed similarly to the 550oC case. In both the gas-only and 100% chloride cases, a thick multilayer scale formed on Fe-25wt%Cr, while the scale is much thinner on the ash + salt cases. All other alloys, however, underwent severe corrosion in the 50wt%, 75wt%, and 100wt% salt cases, and comparatively thinner scale formed in the gas-only, ash-only, and 10% salt cases. At 750oC, Fe-25wt%Cr performed protectively in the gas-only case, and Fe-rich oxide nodules formed after adding chloride deposits on the alloy surface. In the case of ash + salt deposits coated, Fe-25 wt% Cr alloy formed an oxide scales with more uniform thicknesses. The overall thicknesses of the scales formed on Fe-25wt%Cr-20wt%Ni in different cases were similar. Both external and internal porosity increased with increasing the presence of chloride salt. Subsurface porosity was found on Fe-25wt%Cr-20wt%Ni in the 75wt% salt case. Fe-25wt%Cr-2wt%Mn-1wt%Si and 310SS performed more protectively in the gas-only and 10wt% salt cases, but formed thicker multilayer scales in the cases with more salt contents in the deposits. For the two Ni-based alloys, two oxide structure found in the presence of chloride salt, and the proportion of the localised subsurface voids with upper thick Cr2O3 structure increased with increasing amount of salt deposit. This structure occupied the whole sample surface in the 75wt% salt case. Overall, the presence of chloride salt accelerated corrosion by forming porous oxide salts as a result of the active oxidation. The beneficial effect of Mn + Si was eliminated with the presence of chloride deposits by forming volatilising metal chlorides. The presence of ash particles tended to alleviate the effect of chloride salts by acting as a physical impeder to gas access and/or adsorbing part of salts to reduce the detrimental effect of chlorides

Sparse Group Lasso: Optimal Sample Complexity, Convergence Rate, and Statistical Inference

In this paper, we study sparse group Lasso for high-dimensional double sparse linear regression, where the parameter of interest is simultaneously element-wise and group-wise sparse. This problem is an important instance of the simultaneously structured model -- an actively studied topic in statistics and machine learning. In the noiseless case, we provide matching upper and lower bounds on sample complexity for the exact recovery of sparse vectors and for stable estimation of approximately sparse vectors, respectively. In the noisy case, we develop upper and matching minimax lower bounds for estimation error. We also consider the debiased sparse group Lasso and investigate its asymptotic property for the purpose of statistical inference. Finally, numerical studies are provided to support the theoretical results

Robust saliency detection via regularized random walks ranking

In the field of saliency detection, many graph-based algorithms heavily depend on the accuracy of the pre-processed superpixel segmentation, which leads to significant sacrifice of detail information from the input image. In this paper, we propose a novel bottom-up saliency detection approach that takes advantage of both region-based features and image details. To provide more accurate saliency estimations, we first optimize the image boundary selection by the proposed erroneous boundary removal. By taking the image details and region-based estimations into account, we then propose the regularized random walks ranking to formulate pixel-wised saliency maps from the superpixel-based background and foreground saliency estimations. Experiment results on two public datasets indicate the significantly improved accuracy and robustness of the proposed algorithm in comparison with 12 state-of-the-art saliency detection approaches

In vivo quantitative evaluation of gold nanocages' kinetics in sentinel lymph nodes by photoacoustic tomography

As a new class of sentinel lymph node (SLN) tracers for photoacoustic (PA) imaging, Au nanocages offer the advantages of noninvasiveness, strong optical absorption in the near-infrared region (for deep penetration), and accumulation in higher concentrations than the initial injected solution. By monitoring the amplitude changes of PA signals in an animal model, we quantified the accumulations of nanocages in SLNs over time. Based on this method, we quantitatively evaluated the kinetics of gold nanocages in SLN in terms of concentration, size, and surface modification. We could detect the SLN at an Au nanocage injection concentration of 50 pM and a dose of 100 μL in vivo. This concentration is about 40 times less than the previously reported value. We also investigated the influence of nanocages' size (50 nm and 30 nm in edge length), and the effects of surface modification (with positive, or neutral, or negative surface charges). The results are helpful to develop this AuNC-based PA imaging system for noninvasive lymph node mapping, providing valuable information about metastatic cancer staging

DeepGene: an advanced cancer type classifier based on deep learning and somatic point mutations

BACKGROUND: With the developments of DNA sequencing technology, large amounts of sequencing data have become available in recent years and provide unprecedented opportunities for advanced association studies between somatic point mutations and cancer types/subtypes, which may contribute to more accurate somatic point mutation based cancer classification (SMCC). However in existing SMCC methods, issues like high data sparsity, small volume of sample size, and the application of simple linear classifiers, are major obstacles in improving the classification performance. RESULTS: To address the obstacles in existing SMCC studies, we propose DeepGene, an advanced deep neural network (DNN) based classifier, that consists of three steps: firstly, the clustered gene filtering (CGF) concentrates the gene data by mutation occurrence frequency, filtering out the majority of irrelevant genes; secondly, the indexed sparsity reduction (ISR) converts the gene data into indexes of its non-zero elements, thereby significantly suppressing the impact of data sparsity; finally, the data after CGF and ISR is fed into a DNN classifier, which extracts high-level features for accurate classification. Experimental results on our curated TCGA-DeepGene dataset, which is a reformulated subset of the TCGA dataset containing 12 selected types of cancer, show that CGF, ISR and DNN all contribute in improving the overall classification performance. We further compare DeepGene with three widely adopted classifiers and demonstrate that DeepGene has at least 24% performance improvement in terms of testing accuracy. CONCLUSIONS: Based on deep learning and somatic point mutation data, we devise DeepGene, an advanced cancer type classifier, which addresses the obstacles in existing SMCC studies. Experiments indicate that DeepGene outperforms three widely adopted existing classifiers, which is mainly attributed to its deep learning module that is able to extract the high level features between combinatorial somatic point mutations and cancer types

Hsa-miR-125b suppresses bladder cancer development by down-regulating oncogene SIRT7 and oncogenic long non-coding RNA MALAT1

AbstractMicroRNAs mainly inhibit coding genes and long non-coding RNA expression. Here, we report that hsa-miR-125b and oncogene SIRT7/oncogenic long non-coding RNA MALAT1 were inversely expressed in bladder cancer. Hsa-miR-125b mimic down-regulated, whereas hsa-miR-125b inhibitor up-regulated the expression of SIRT7 and MALAT1. Binding sites were confirmed between hsa-miR-125b and SIRT7/MALAT1. Up-regulation of hsa-miR-125b or down-regulation of SIRT7 inhibited proliferation, motility and increased apoptosis. The effects of up-regulation of hsa-miR-125b were similar to that of silencing MALAT1 in bladder cancer as we had previously described. These data suggest that hsa-miR-125b suppresses bladder cancer development via inhibiting SIRT7 and MALAT1

Vitamin D Signaling through Induction of Paneth Cell Defensins Maintains Gut Microbiota and Improves Metabolic Disorders and Hepatic Steatosis in Animal Models.

Metabolic syndrome (MetS), characterized as obesity, insulin resistance, and non-alcoholic fatty liver diseases (NAFLD), is associated with vitamin D insufficiency/deficiency in epidemiological studies, while the underlying mechanism is poorly addressed. On the other hand, disorder of gut microbiota, namely dysbiosis, is known to cause MetS and NAFLD. It is also known that systemic inflammation blocks insulin signaling pathways, leading to insulin resistance and glucose intolerance, which are the driving force for hepatic steatosis. Vitamin D receptor (VDR) is highly expressed in the ileum of the small intestine, which prompted us to test a hypothesis that vitamin D signaling may determine the enterotype of gut microbiota through regulating the intestinal interface. Here, we demonstrate that high-fat-diet feeding (HFD) is necessary but not sufficient, while additional vitamin D deficiency (VDD) as a second hit is needed, to induce robust insulin resistance and fatty liver. Under the two hits (HFD+VDD), the Paneth cell-specific alpha-defensins including α-defensin 5 (DEFA5), MMP7 which activates the pro-defensins, as well as tight junction genes, and MUC2 are all suppressed in the ileum, resulting in mucosal collapse, increased gut permeability, dysbiosis, endotoxemia, systemic inflammation which underlie insulin resistance and hepatic steatosis. Moreover, under the vitamin D deficient high fat feeding (HFD+VDD), Helicobacter hepaticus, a known murine hepatic-pathogen, is substantially amplified in the ileum, while Akkermansia muciniphila, a beneficial symbiotic, is diminished. Likewise, the VD receptor (VDR) knockout mice exhibit similar phenotypes, showing down regulation of alpha-defensins and MMP7 in the ileum, increased Helicobacter hepaticus and suppressed Akkermansia muciniphila. Remarkably, oral administration of DEFA5 restored eubiosys, showing suppression of Helicobacter hepaticus and increase of Akkermansia muciniphila in association with resolving metabolic disorders and fatty liver in the HFD+VDD mice. An in vitro analysis showed that DEFA5 peptide could directly suppress Helicobacter hepaticus. Thus, the results of this study reveal critical roles of a vitamin D/VDR axis in optimal expression of defensins and tight junction genes in support of intestinal integrity and eubiosis to suppress NAFLD and metabolic disorders

In vivo quantitative evaluation of gold nanocages' kinetics in sentinel lymph nodes by photoacoustic tomography

As a new class of sentinel lymph node (SLN) tracers for photoacoustic (PA) imaging, Au nanocages offer the advantages of noninvasiveness, strong optical absorption in the near-infrared region (for deep penetration), and accumulation in higher concentrations than the initial injected solution. By monitoring the amplitude changes of PA signals in an animal model, we quantified the accumulations of nanocages in SLNs over time. Based on this method, we quantitatively evaluated the kinetics of gold nanocages in SLN in terms of concentration, size, and surface modification. We could detect the SLN at an Au nanocage injection concentration of 50 pM and a dose of 100 μL in vivo. This concentration is about 40 times less than the previously reported value. We also investigated the influence of nanocages' size (50 nm and 30 nm in edge length), and the effects of surface modification (with positive, or neutral, or negative surface charges). The results are helpful to develop this AuNC-based PA imaging system for noninvasive lymph node mapping, providing valuable information about metastatic cancer staging