A quantitative research on S- and SO2-poisoning Pt/Vulcan carbon fuel cell catalyst

A quantitative research on S and SO2 poisoning Pt/Vulcan carbon (Pt/VC) catalysts for fuel cells was conducted by the three-electrode method. Pt/VC electrodes were contaminated by submersion in a SO2-containing solution made up of 0.2 mM Na2SO3 and 0.5 M H2SO4 for different periods of time, and held at 0.05 V (vs. RHE) in 0.5 M H2SO4 solutions in order to gain zero-valence sulfur (S-0) poisoned electrodes. The sulfur coverage of Pt was determined from the total charge consumed as the sulfur was oxidized from S-0 at 0.05 V (vs. RHE) to sulfate at >1.1 V (vs. RHE). The summation of initial coverage of S-0 (theta(S)) and coverage of H (theta(H)) are approximately equal to 1 (theta(H) + theta(S) = 1) when 0.5 < theta(H) < 1, which gives an easy way to figure out the quantity of sulfur adsorbed on Pt/VC. As to SO2 poisoned Pt/VC, the catalytic activity of oxygen reduction reaction (ORR) decreases linearly with the amount of SO2 adsorbed on the Pt nanoparticles when 0.45 < theta(H) < 0.81. When the adsorbed SO2 was reduced to S-0 the mass activity was greatly recovered, and the area specific activity was even higher than the unpoisoned Pt/VC. (C) 2012 Elsevier Ltd. All rights reserved

Substantial Differences in Crop Yield Sensitivities Between Models Call for Functionality‐Based Model Evaluation

Crop models are often used to project future crop yield under climate and global change and typically show a broad range of outcomes. To understand differences in modeled responses, we analyzed modeled crop yield response types using impact response surfaces along four drivers of crop yield: carbon dioxide (C), temperature (T), water (W), and nitrogen (N). Crop yield response types help to understand differences in simulated responses per driver and their combinations rather than aggregated changes in yields as the result of simultaneous changes in various drivers. We find that models' sensitivities to the individual drivers are substantially different and often more different across models than across regions. There is some agreement across models with respect to the spatial patterns of response types but strong differences in the distribution of response types across models and their configurations suggests that models need to undergo further scrutiny. We suggest establishing standards in model evaluation based on emergent functionality not only against historical yield observations but also against dedicated experiments across different drivers to analyze emergent functional patterns of crop models

Effects of exposure to facial expression variation in face learning and recognition.

Facial expression is a major source of image variation in face images. Linking numerous expressions to the same face can be a huge challenge for face learning and recognition. It remains largely unknown what level of exposure to this image variation is critical for expression-invariant face recognition. We examined this issue in a recognition memory task, where the number of facial expressions of each face being exposed during a training session was manipulated. Faces were either trained with multiple expressions or a single expression, and they were later tested in either the same or different expressions. We found that recognition performance after learning three emotional expressions had no improvement over learning a single emotional expression (Experiments 1 and 2). However, learning three emotional expressions improved recognition compared to learning a single neutral expression (Experiment 3). These findings reveal both the limitation and the benefit of multiple exposures to variations of emotional expression in achieving expression-invariant face recognition. The transfer of expression training to a new type of expression is likely to depend on a relatively extensive level of training and a certain degree of variation across the types of expressions

The unfolded protein response in immunity and inflammation.

The unfolded protein response (UPR) is a highly conserved pathway that allows the cell to manage endoplasmic reticulum (ER) stress that is imposed by the secretory demands associated with environmental forces. In this role, the UPR has increasingly been shown to have crucial functions in immunity and inflammation. In this Review, we discuss the importance of the UPR in the development, differentiation, function and survival of immune cells in meeting the needs of an immune response. In addition, we review current insights into how the UPR is involved in complex chronic inflammatory diseases and, through its role in immune regulation, antitumour responses.This work was supported by the Netherlands Organization for Scientific Research Rubicon grant 825.13.012 (J.G.); US National Institutes of Health (NIH) grants DK044319, DK051362, DK053056 and DK088199, and the Harvard Digestive Diseases Center (HDDC) grant DK034854 (R.S.B.); National Institutes of Health grants DK042394, DK088227, DK103183 and CA128814 (R.J.K.); and European Research Council (ERC) Starting Grant 260961, ERC Consolidator Grant 648889, and the Wellcome Trust Investigator award 106260/Z/14/Z (A.K.).This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/nri.2016.6

A functional RANKL polymorphism associated with younger age at onset of rheumatoid arthritis

We previously reported association of co-occurrence of HLA-DRB1 shared epitope (SE) and RANKL SNPs with younger age of RA onset in 182 rheumatoid factor positive (RF) European American (EA) early RA patients. Here, we fine-mapped the 48 kb RANKL region in the extended 210 EA RF-positive early RA cohort, sought replication of RA-associated SNPs in additional 501 EA and 298 African-Americans (AA) RA cohorts, and explored functional consequences of RA-associated SNPs

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe