On the tortuosity factor of solid phase in solid oxide fuel cell electrodes

2014-2015 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Investigation of the electrochemical active thickness of solid oxide fuel cell anode

2014-2015 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Synthesis and Photoluminescence Properties of Porous Silicon Nanowire Arrays

Herein, we prepare vertical and single crystalline porous silicon nanowires (SiNWs) via a two-step metal-assisted electroless etching method. The porosity of the nanowires is restricted by etchant concentration, etching time and doping lever of the silicon wafer. The diffusion of silver ions could lead to the nucleation of silver nanoparticles on the nanowires and open new etching ways. Like porous silicon (PS), these porous nanowires also show excellent photoluminescence (PL) properties. The PL intensity increases with porosity, with an enhancement of about 100 times observed in our condition experiments. A “red-shift” of the PL peak is also found. Further studies prove that the PL spectrum should be decomposed into two elementary PL bands. The peak at 850 nm is the emission of the localized excitation in the nanoporous structure, while the 750-nm peak should be attributed to the surface-oxidized nanostructure. It could be confirmed from the Fourier transform infrared spectroscopy analyses. These porous SiNW arrays may be useful as the nanoscale optoelectronic devices

Artificial neural network accurately predicts hepatitis B surface antigen seroclearance

BACKGROUND & AIMS: Hepatitis B surface antigen (HBsAg) seroclearance and seroconversion are regarded as favorable outcomes of chronic hepatitis B (CHB). This study aimed to develop artificial neural networks (ANNs) that could accurately predict HBsAg seroclearance or seroconversion on the basis of available serum variables. METHODS: Data from 203 untreated, HBeAg-negative CHB patients with spontaneous HBsAg seroclearance (63 with HBsAg seroconversion), and 203 age- and sex-matched HBeAg-negative controls were analyzed. ANNs and logistic regression models (LRMs) were built and tested according to HBsAg seroclearance and seroconversion. Predictive accuracy was assessed with area under the receiver operating characteristic curve (AUROC). RESULTS: Serum quantitative HBsAg (qHBsAg) and HBV DNA levels, qHBsAg and HBV DNA reduction were related to HBsAg seroclearance (P<0.001) and were used for ANN/LRM-HBsAg seroclearance building, whereas, qHBsAg reduction was not associated with ANN-HBsAg seroconversion (P = 0.197) and LRM-HBsAg seroconversion was solely based on qHBsAg (P = 0.01). For HBsAg seroclearance, AUROCs of ANN were 0.96, 0.93 and 0.95 for the training, testing and genotype B subgroups respectively. They were significantly higher than those of LRM, qHBsAg and HBV DNA (all P<0.05). Although the performance of ANN-HBsAg seroconversion (AUROC 0.757) was inferior to that for HBsAg seroclearance, it tended to be better than those of LRM, qHBsAg and HBV DNA. CONCLUSIONS: ANN identifies spontaneous HBsAg seroclearance in HBeAg-negative CHB patients with better accuracy, on the basis of easily available serum data. More useful predictors for HBsAg seroconversion are still needed to be explored in the future.published_or_final_versio

Temporal Model Adaptation for Person Re-Identification

Person re-identification is an open and challenging problem in computer vision. Majority of the efforts have been spent either to design the best feature representation or to learn the optimal matching metric. Most approaches have neglected the problem of adapting the selected features or the learned model over time. To address such a problem, we propose a temporal model adaptation scheme with human in the loop. We first introduce a similarity-dissimilarity learning method which can be trained in an incremental fashion by means of a stochastic alternating directions methods of multipliers optimization procedure. Then, to achieve temporal adaptation with limited human effort, we exploit a graph-based approach to present the user only the most informative probe-gallery matches that should be used to update the model. Results on three datasets have shown that our approach performs on par or even better than state-of-the-art approaches while reducing the manual pairwise labeling effort by about 80%

Person Re-identification Using Clustering Ensemble Prototypes

Abstract. This paper presents an appearance-based model to deal with the person re-identification problem. Usually in a crowded scene, it is ob-served that, the appearances of most people are similar with regard to the combination of attire. In such situation it is a difficult task to distin-guish an individual from a group of alike looking individuals and yields an ambiguity in recognition for re-identification. The proper organiza-tion of the individuals based on the appearance characteristics leads to recognize the target individual by comparing with a particular group of similar looking individuals. To reconstruct a group of individual accord-ing to their appearance is a crucial task for person re-identification. In this work we focus on unsupervised based clustering ensemble approach for discovering prototypes where each prototype represents similar set of gallery image instances. The formation of each prototype depends upon the appearance characteristics of gallery instances. The estimation of k-NN classifier is employed to specify a prototype to a given probe image. The similarity measure computation is performed between the probe and a subset of gallery images, that shares the same prototype with the probe and thus reduces the number of comparisons. Re-identification perfor-mance on benchmark datasets are presented using cumulative matching characteristic (CMC) curves.

Thyroid Hormone Promotes Remodeling of Coronary Resistance Vessels

Low thyroid hormone (TH) function has been linked to impaired coronary blood flow, reduced density of small arterioles, and heart failure. Nonetheless, little is known about the mechanisms by which THs regulate coronary microvascular remodeling. The current study examined the initial cellular events associated with coronary remodeling induced by triiodothyronine (T3) in hypothyroid rats. Rats with established hypothyroidism, eight weeks after surgical thyroidectomy (TX), were treated with T3 for 36 or 72 hours. The early effects of T3 treatment on coronary microvasculature were examined morphometrically. Gene expression changes in the heart were assessed by quantitative PCR Array. Hypothyroidism resulted in arteriolar atrophy in the left ventricle. T3 treatment rapidly induced small arteriolar muscularization and, within 72 hours, restored arteriolar density to control levels. Total length of the capillary network was not affected by TX or T3 treatment. T3 treatment resulted in the coordinate regulation of Angiopoietin 1 and 2 expression. The response of Angiopoietins was consistent with vessel enlargement. In addition to the well known effects of THs on vasoreactivity, these results suggest that THs may affect function of small resistance arteries by phenotypic remodeling of vascular smooth muscle cells (VSMC)

Alterations of the extracellular matrix in ovarian cancer studied by Second Harmonic Generation imaging microscopy

<p>Abstract</p> <p>Background</p> <p>Remodeling of the extracellular matrix (ECM) has been implicated in ovarian cancer, and we hypothesize that these alterations may provide a better optical marker of early disease than currently available imaging/screening methods and that understanding their physical manifestations will provide insight into invasion.</p> <p>Methods</p> <p>For this investigation we use Second Harmonic Generation (SHG) imaging microcopy to study changes in the structure of the ovarian ECM in human normal and malignant ex vivo biopsies. This method directly visualizes the type I collagen in the ECM and provides quantitative metrics of the fibrillar assembly. To quantify these changes in collagen morphology we utilized an integrated approach combining 3D SHG imaging measurements and bulk optical parameter measurements in conjunction with Monte Carlo simulations of the experimental data to extract tissue structural properties.</p> <p>Results</p> <p>We find the SHG emission attributes (directionality and relative intensity) and bulk optical parameters, both of which are related to the tissue structure, are significantly different in the tumors in a manner that is consistent with the change in collagen assembly. The normal and malignant tissues have highly different collagen fiber assemblies, where collectively, our findings show that the malignant ovaries are characterized by lower cell density, denser collagen, as well as higher regularity at both the fibril and fiber levels. This further suggests that the assembly in cancer may be comprised of newly synthesized collagen as opposed to modification of existing collagen.</p> <p>Conclusions</p> <p>Due to the large structural changes in tissue assembly and the SHG sensitivity to these collagen alterations, quantitative discrimination is achieved using small patient data sets. Ultimately these measurements may be developed as intrinsic biomarkers for use in clinical applications.</p