Development of lanthanum nickelate as a cathode for use in intermediate temperature solid oxide fuel cells

The performance of lanthanum nickelate, La2NiO4+δ (LNO), as a cathode in IT-SOFCs with the electrolyte cerium gadolinium oxide, Ce0.9Gd0.1O2−δ (CGO), has been investigated by AC impedance spectroscopy of symmetrical cells. A significant reduction in the area specific resistance (ASR) has been achieved with a layered cathode structure consisting of a thin compact LNO layer between the dense electrolyte and porous electrode. This decrease in ASR is believed to be a result of contact at the electrolyte/cathode boundary enhancing the oxygen ion transfer to the electrolyte. An ASR of 1.0 Ω cm2 at 700 °C was measured in a symmetrical cell with this layered structure, compared to an ASR of 7.4 Ω cm2 in a cell without the compact layer. In addition, further improvements were observed by enhancing the cell current collection and it is anticipated that a symmetrical cell consisting of a layered structure with adequate current collection would lower these ASR values further

Investigation of Graded La2NiO4+ Cathodes to Improve SOFC Electrochemical Performance

Mixed ionic and electronic conducting MIEC oxides are promising materials for use as cathodes in solid oxide fuel cells SOFCs due to their enhanced electrocatalytic activity compared with electronic conducting oxides. In this paper, the MIEC oxide La2NiO4+ was prepared by the sol-gel route. Graded cathodes were deposited onto yttria-stabilized zirconia YSZ pellets by dip-coating, and electrochemical impedance spectroscopy studies were performed to characterize the symmetrical cell performance. By adapting the slurries, cathode layers with different porosities and thicknesses were obtained. A ceria gadolinium oxide CGO barrier layer was introduced, avoiding insulating La2Zr2O7 phase formation and thus reducing resistance polarization of the cathode. A systematic correlation between microstructure, composition, and electrochemical performance of these cathodes has been performed. An improvement of the electrochemical performance has been demonstrated, and a reduction in the area specific resistance ASR by a factor of 4.5 has been achieved with a compact interlayer of La2NiO4+ between the dense electrolyte and the porous La2NiO4+ cathode layer. The lowest observed ASR of 0.11 cm2 at 800°C was obtained from a symmetrical cell composed of a YSZ electrolyte, a CGO interlayer, an intermediate compact La2NiO4+ layer, a porous La2NiO4+ electrode layer, and a current collection layer of platinum paste

Using multiple classifiers for predicting the risk of endovascular aortic aneurysm repair re-intervention through hybrid feature selection.

Feature selection is essential in medical area; however, its process becomes complicated with the presence of censoring which is the unique character of survival analysis. Most survival feature selection methods are based on Cox's proportional hazard model, though machine learning classifiers are preferred. They are less employed in survival analysis due to censoring which prevents them from directly being used to survival data. Among the few work that employed machine learning classifiers, partial logistic artificial neural network with auto-relevance determination is a well-known method that deals with censoring and perform feature selection for survival data. However, it depends on data replication to handle censoring which leads to unbalanced and biased prediction results especially in highly censored data. Other methods cannot deal with high censoring. Therefore, in this article, a new hybrid feature selection method is proposed which presents a solution to high level censoring. It combines support vector machine, neural network, and K-nearest neighbor classifiers using simple majority voting and a new weighted majority voting method based on survival metric to construct a multiple classifier system. The new hybrid feature selection process uses multiple classifier system as a wrapper method and merges it with iterated feature ranking filter method to further reduce features. Two endovascular aortic repair datasets containing 91% censored patients collected from two centers were used to construct a multicenter study to evaluate the performance of the proposed approach. The results showed the proposed technique outperformed individual classifiers and variable selection methods based on Cox's model such as Akaike and Bayesian information criterions and least absolute shrinkage and selector operator in p values of the log-rank test, sensitivity, and concordance index. This indicates that the proposed classifier is more powerful in correctly predicting the risk of re-intervention enabling doctor in selecting patients' future follow-up plan

The discovery of lensed radio and X-ray sources behind the Frontier Fields cluster MACS J0717.5+3745 with the JVLA and Chandra

We report on high-resolution JVLA and Chandra observations of the Hubble Space Telescope (HST) Frontier Cluster MACS J0717.5+3745. MACS J0717.5+3745 offers the largest contiguous magnified area of any known cluster, making it a promising target to search for lensed radio and X-ray sources. With the high-resolution 1.0–6.5 GHz JVLA imaging in A and B configuration, we detect a total of 51 compact radio sources within the area covered by the HST imaging. Within this sample, we find seven lensed sources with amplification factors larger than two. None of these sources are identified as multiply lensed. Based on the radio luminosities, the majority of these sources are likely star-forming galaxies with star-formation rates (SFRs) of 10–50 M_☉ yr^(−1) located at 1 ≾ z ≾ 2. Two of the lensed radio sources are also detected in the Chandra image of the cluster. These two sources are likely active galactic nuclei, given their 2–10 keV X-ray luminosities of ~10^(43–44) erg s^(−1). From the derived radio luminosity function, we find evidence for an increase in the number density of radio sources at 0.6 < z < 2.0, compared to a z < 0.3 sample. Our observations indicate that deep radio imaging of lensing clusters can be used to study star-forming galaxies, with SFRs as low as ~10 M_⊙ yr^(−1), at the peak of cosmic star formation history

HerMES: a search for high-redshift dusty galaxies in the HerMES Large Mode Survey – catalogue, number counts and early results

Selecting sources with rising flux densities towards longer wavelengths from Herschel/Spectral and Photometric Imaging Receiver (SPIRE) maps is an efficient way to produce a catalogue rich in high-redshift (z > 4) dusty star-forming galaxies. The effectiveness of this approach has already been confirmed by spectroscopic follow-up observations, but the previously available catalogues made this way are limited by small survey areas. Here we apply a map-based search method to 274 deg^2 of the Herschel Multi-tiered Extragalactic Survey (HerMES) Large Mode Survey and create a catalogue of 477 objects with SPIRE flux densities S_(500) > S_(350) > S_(250) and a 5σ cut-off S_(500) > 52 mJy. From this catalogue we determine that the total number of these ‘red’ sources is at least an order of magnitude higher than predicted by galaxy evolution models. These results are in agreement with previous findings in smaller HerMES fields; however, due to our significantly larger sample size we are also able to investigate the shape of the red source counts for the first time. We have obtained spectroscopic redshift measurements for two of our sources using the Atacama Large Millimeter/submillimeter Array. The redshifts z = 5.1 and 3.8 confirm that with our selection method we can indeed find high-redshift dusty star-forming galaxies

Thermodynamic Profiles of Galaxy Clusters from a Joint X-ray/SZ Analysis

We jointly analyze Bolocam Sunyaev-Zeldovich (SZ) effect and Chandra X-ray data for a set of 45 clusters to derive gas density and temperature profiles without using spectroscopic information. The sample spans the mass and redshift range $3 \times 10^{14} M_{\odot} \le M_{500} \le 25 \times 10^{14} M_{\odot}$ and $0.15\le z \le 0.89$. We define cool-core (CC) and non-cool core (NCC) subsamples based on the central X-ray luminosity, and 17/45 clusters are classified as CC. In general, the profiles derived from our analysis are found to be in good agreement with previous analyses, and profile constraints beyond $r_{500}$ are obtained for 34/45 clusters. In approximately 30% of the CC clusters our analysis shows a central temperature drop with a statistical significance of $>3\sigma$; this modest detection fraction is due mainly to a combination of coarse angular resolution and modest S/N in the SZ data. Most clusters are consistent with an isothermal profile at the largest radii near $r_{500}$, although 9/45 show a significant temperature decrease with increasing radius. The sample mean density profile is in good agreement with previous studies, and shows a minimum intrinsic scatter of approximately 10% near $0.5 \times r_{500}$. The sample mean temperature profile is consistent with isothermal, and has an intrinsic scatter of approximately 50% independent of radius. This scatter is significantly higher compared to earlier X-ray-only studies, which find intrinsic scatters near 10%, likely due to a combination of unaccounted for non-idealities in the SZ noise, projection effects, and sample selection.Comment: 42 pages, 52 figure

Analysis of Johne\u27s disease ELISA status and associated performance parameters in Irish dairy cows

Background Infection with Mycobacterium avium subspecies paratuberculosis (MAP) has been associated with reductions in milk production in dairy cows and sub optimal fertility. The aim of this study was to highlight the production losses associated with testing MAP ELISA positive in Irish dairy cows. Secondary objectives included investigation of risk factors associated with testing MAP ELISA positive. A survey of management practices on study farms was also conducted, with examination of associations between management practices and herd MAP status. Blood samples were collected from 4188 breeding animals on 22 farms. Samples were ELISA tested using the ID Screen Paratuberculosis Indirect Screening Test. Production parameters examined included milk yield, milk fat, milk protein, somatic cell count, and calving interval. The association between MAP ELISA status and production data was investigated using multi-level mixed models. Logistic regression was used to identify risk factors for testing JD blood ELISA positive at individual cow level and to identify associations between farm management practices and herd MAP status. Results Data were available for 3528 cows. The apparent prevalence recorded was 7.4 %. Mixed model analysis revealed no statistically significant association between testing MAP ELISA positive and dairy cow production parameters. Risk factors associated with testing positive included larger sized herds being over twice more likely to test positive than smaller herds (OR 2.4 P = \u3c0.001). Friesians were less likely to test positive relative to other breeds. A number of study farmers were engaged in management practices that have previously been identified as high risk for MAP transmission e.g., 73.1 % pooled colostrum and 84.6 % of study farmers used the calving area to house sick animals throughout the year. No significant associations however, were identified between farm management practices and herd MAP status. Conclusion No production losses were identified; however an apparent prevalence of 7.4 % was recorded. With the abolition of EU milk quotas herd size in Ireland is expanding, as herds included in this study were larger than the national average, results may be indicative of future JD levels if no JD control programmes are implemented to minimise transmission

Analysis of Johne’s disease ELISA status and associated performance parameters in Irish dairy cows

Infection with Mycobacterium avium subspecies paratuberculosis (MAP) has been associated with reductions in milk production in dairy cows and sub optimal fertility. The aim of this study was to highlight the production losses associated with testing MAP ELISA positive in Irish dairy cows. Secondary objectives included investigation of risk factors associated with testing MAP ELISA positive. A survey of management practices on study farms was also conducted, with examination of associations between management practices and herd MAP status. Blood samples were collected from 4188 breeding animals on 22 farms. Samples were ELISA tested using the ID Screen Paratuberculosis Indirect Screening Test. Production parameters examined included milk yield, milk fat, milk protein, somatic cell count, and calving interval. The association between MAP ELISA status and production data was investigated using multi-level mixed models. Logistic regression was used to identify risk factors for testing JD blood ELISA positive at individual cow level and to identify associations between farm management practices and herd MAP status. Results Data were available for 3528 cows. The apparent prevalence recorded was 7.4 %. Mixed model analysis revealed no statistically significant association between testing MAP ELISA positive and dairy cow production parameters. Risk factors associated with testing positive included larger sized herds being over twice more likely to test positive than smaller herds (OR 2.4 P = \u3c0.001). Friesians were less likely to test positive relative to other breeds. A number of study farmers were engaged in management practices that have previously been identified as high risk for MAP transmission e.g., 73.1 % pooled colostrum and 84.6 % of study farmers used the calving area to house sick animals throughout the year. No significant associations however, were identified between farm management practices and herd MAP status. Conclusion No production losses were identified; however an apparent prevalence of 7.4 % was recorded. With the abolition of EU milk quotas herd size in Ireland is expanding, as herds included in this study were larger than the national average, results may be indicative of future JD levels if no JD control programmes are implemented to minimise transmission

A Search for Cosmic Microwave Background Anisotropies on Arcminute Scales with Bolocam

We have surveyed two science fields totaling one square degree with Bolocam at 2.1 mm to search for secondary CMB anisotropies caused by the Sunyaev- Zel'dovich effect (SZE). The fields are in the Lynx and Subaru/XMM SDS1 fields. Our survey is sensitive to angular scales with an effective angular multipole of l_eff = 5700 with FWHM_l = 2800 and has an angular resolution of 60 arcseconds FWHM. Our data provide no evidence for anisotropy. We are able to constrain the level of total astronomical anisotropy, modeled as a flat bandpower in C_l, with frequentist 68%, 90%, and 95% CL upper limits of 590, 760, and 830 uKCMB^2. We statistically subtract the known contribution from primary CMB anisotropy, including cosmic variance, to obtain constraints on the SZE anisotropy contribution. Now including flux calibration uncertainty, our frequentist 68%, 90% and 95% CL upper limits on a flat bandpower in C_l are 690, 960, and 1000 uKCMB^2. When we instead employ the analytic spectrum suggested by Komatsu and Seljak (2002), and account for the non-Gaussianity of the SZE anisotropy signal, we obtain upper limits on the average amplitude of their spectrum weighted by our transfer function of 790, 1060, and 1080 uKCMB^2. We obtain a 90% CL upper limit on sigma8, which normalizes the power spectrum of density fluctuations, of 1.57. These are the first constraints on anisotropy and sigma8 from survey data at these angular scales at frequencies near 150 GHz.Comment: 68 pages, 17 figures, 2 tables, accepted for publication in Ap