Determination of the Mg/Mn ratio in foraminiferal coatings: An approach to correct Mg/Ca temperatures for Mn-rich contaminant phases

The occurrence of manganese-rich coatings on foraminifera can have a significant effect on their bulk Mg/Ca ratios thereby biasing seawater temperature reconstructions. The removal of this Mn phase requires a reductive cleaning step, but this has been suggested to preferentially dissolve Mg-rich biogenic carbonate, potentially introducing an analytical bias in paleotemperature estimates. In this study, the geochemical composition of foraminifera tests from Mn-rich sediments from the Antarctic Southern Ocean (ODP Site 1094) was investigated using solution-based and laser ablation ICP-MS in order to determine the amount of Mg incorporated into the coatings. The analysis of planktonic and benthic foraminifera revealed a nearly constant Mg/Mn ratio in the Mn coating of ∼0.2 mol/mol. Consequently, the coating Mg/Mn ratio can be used to correct for the Mg incorporated into the Mn phase by using the down core Mn/Ca values of samples that have not been reductively cleaned. The consistency of the coating Mg/Mn ratio obtained in this study, as well as that found in samples from the Panama Basin, suggests that spatial variation of Mg/Mn in foraminiferal Mn overgrowths may be smaller than expected from Mn nodules and Mn–Ca carbonates. However, a site-specific assessment of the Mg/Mn ratio in foraminiferal coatings is recommended to improve the accuracy of the correction.We acknowledge the financial support provided by ETH Research Grant ETH-04 11-1 (A.P.H.), and the Swiss National Science Foundation grants PZ00P2_141424 (A.M.-G.) and PP00P2_144811 (S.L.J.). This work was also funded (in part) by The European Research Council (ERC grant 2010-NEWLOG ADG-267931 HE)

Local Difference Measures between Complex Networks for Dynamical System Model Evaluation

Acknowledgments We thank Reik V. Donner for inspiring suggestions that initialized the work presented herein. Jan H. Feldhoff is credited for providing us with the STARS simulation data and for his contributions to fruitful discussions. Comments by the anonymous reviewers are gratefully acknowledged as they led to substantial improvements of the manuscript.Peer reviewedPublisher PD

Quantum Criticality in Heavy Fermion Metals

Quantum criticality describes the collective fluctuations of matter undergoing a second-order phase transition at zero temperature. Heavy fermion metals have in recent years emerged as prototypical systems to study quantum critical points. There have been considerable efforts, both experimental and theoretical, which use these magnetic systems to address problems that are central to the broad understanding of strongly correlated quantum matter. Here, we summarize some of the basic issues, including i) the extent to which the quantum criticality in heavy fermion metals goes beyond the standard theory of order-parameter fluctuations, ii) the nature of the Kondo effect in the quantum critical regime, iii) the non-Fermi liquid phenomena that accompany quantum criticality, and iv) the interplay between quantum criticality and unconventional superconductivity.Comment: (v2) 39 pages, 8 figures; shortened per the editorial mandate; to appear in Nature Physics. (v1) 43 pages, 8 figures; Non-technical review article, intended for general readers; the discussion part contains more specialized topic

Homoplasy corrected estimation of genetic similarity from AFLP bands, and the effect of the number of bands on the precision of estimation

AFLP is a DNA fingerprinting technique, resulting in binary band presence–absence patterns, called profiles, with known or unknown band positions. We model AFLP as a sampling procedure of fragments, with lengths sampled from a distribution. Bands represent fragments of specific lengths. We focus on estimation of pairwise genetic similarity, defined as average fraction of common fragments, by AFLP. Usual estimators are Dice (D) or Jaccard coefficients. D overestimates genetic similarity, since identical bands in profile pairs may correspond to different fragments (homoplasy). Another complicating factor is the occurrence of different fragments of equal length within a profile, appearing as a single band, which we call collision. The bias of D increases with larger numbers of bands, and lower genetic similarity. We propose two homoplasy- and collision-corrected estimators of genetic similarity. The first is a modification of D, replacing band counts by estimated fragment counts. The second is a maximum likelihood estimator, only applicable if band positions are available. Properties of the estimators are studied by simulation. Standard errors and confidence intervals for the first are obtained by bootstrapping, and for the second by likelihood theory. The estimators are nearly unbiased, and have for most practical cases smaller standard error than D. The likelihood-based estimator generally gives the highest precision. The relationship between fragment counts and precision is studied using simulation. The usual range of band counts (50–100) appears nearly optimal. The methodology is illustrated using data from a phylogenetic study on lettuce

Comprehensive evaluation of matrix factorization methods for the analysis of DNA microarray gene expression data

<p>Abstract</p> <p>Background</p> <p>Clustering-based methods on gene-expression analysis have been shown to be useful in biomedical applications such as cancer subtype discovery. Among them, Matrix factorization (MF) is advantageous for clustering gene expression patterns from DNA microarray experiments, as it efficiently reduces the dimension of gene expression data. Although several MF methods have been proposed for clustering gene expression patterns, a systematic evaluation has not been reported yet.</p> <p>Results</p> <p>Here we evaluated the clustering performance of orthogonal and non-orthogonal MFs by a total of nine measurements for performance in four gene expression datasets and one well-known dataset for clustering. Specifically, we employed a non-orthogonal MF algorithm, BSNMF (Bi-directional Sparse Non-negative Matrix Factorization), that applies bi-directional sparseness constraints superimposed on non-negative constraints, comprising a few dominantly co-expressed genes and samples together. Non-orthogonal MFs tended to show better clustering-quality and prediction-accuracy indices than orthogonal MFs as well as a traditional method, K-means. Moreover, BSNMF showed improved performance in these measurements. Non-orthogonal MFs including BSNMF showed also good performance in the functional enrichment test using Gene Ontology terms and biological pathways.</p> <p>Conclusions</p> <p>In conclusion, the clustering performance of orthogonal and non-orthogonal MFs was appropriately evaluated for clustering microarray data by comprehensive measurements. This study showed that non-orthogonal MFs have better performance than orthogonal MFs and <it>K</it>-means for clustering microarray data.</p

HPV vaccine decision making in pediatric primary care: a semi-structured interview study

<p>Abstract</p> <p>Background</p> <p>Despite national recommendations, as of 2009 human papillomavirus (HPV) vaccination rates were low with < 30% of adolescent girls fully vaccinated. Research on barriers to vaccination has focused separately on parents, adolescents, or clinicians and not on the decision making process among all participants at the point of care. By incorporating three distinct perspectives, we sought to generate hypotheses to inform interventions to increase vaccine receipt.</p> <p>Methods</p> <p>Between March and June, 2010, we conducted qualitative interviews with 20 adolescent-mother-clinician triads (60 individual interviews) directly after a preventive visit with the initial HPV vaccine due. Interviews followed a guide based on published HPV literature, involved 9 practices, and continued until saturation of the primary themes was achieved. Purposive sampling balanced adolescent ages and practice type (urban resident teaching versus non-teaching). Using a modified grounded theory approach, we analyzed data with NVivo8 software both within and across triads to generate primary themes.</p> <p>Results</p> <p>The study population was comprised of 20 mothers (12 Black, 9 < high school diploma), 20 adolescents (ten 11-12 years old), and 20 clinicians (16 female). Nine adolescents received the HPV vaccine at the visit, eight of whom were African American. Among the 11 not vaccinated, all either concurrently received or were already up-to-date on Tdap and MCV4. We did not observe systematic patterns of vaccine acceptance or refusal based on adolescent age or years of clinician experience. We identified 3 themes: (1) Parents delayed, rather than refused vaccination, and when they expressed reluctance, clinicians were hesitant to engage them in discussion. (2) Clinicians used one of two strategies to present the HPV vaccine, either presenting it as a routine vaccine with no additional information or presenting it as optional and highlighting risks and benefits. (3) Teens considered themselves passive participants in decision making, even when parents and clinicians reported including them in the process.</p> <p>Conclusions</p> <p>Programs to improve HPV vaccine delivery in primary care should focus on promoting effective parent-clinician communication. Research is needed to evaluate strategies to help clinicians engage reluctant parents and passive teens in discussion and measure the impact of distinct clinician decision making approaches on HPV vaccine delivery.</p

Sea ice dynamics across the Mid-Pleistocene transition in the Bering Sea.

Sea ice and associated feedback mechanisms play an important role for both long- and short-term climate change. Our ability to predict future sea ice extent, however, hinges on a greater understanding of past sea ice dynamics. Here we investigate sea ice changes in the eastern Bering Sea prior to, across, and after the Mid-Pleistocene transition (MPT). The sea ice record, based on the Arctic sea ice biomarker IP25 and related open water proxies from the International Ocean Discovery Program Site U1343, shows a substantial increase in sea ice extent across the MPT. The occurrence of late-glacial/deglacial sea ice maxima are consistent with sea ice/land ice hysteresis and land-glacier retreat via the temperature-precipitation feedback. We also identify interactions of sea ice with phytoplankton growth and ocean circulation patterns, which have important implications for glacial North Pacific Intermediate Water formation and potentially North Pacific abyssal carbon storage

Self-Compassion, emotion regulation and stress among australian psychologists: Testing an emotion regulation model of self-compassion using structural equation modeling

Psychologists tend to report high levels of occupational stress, with serious implications for themselves, their clients, and the discipline as a whole. Recent research suggests that selfcompassion is a promising construct for psychologists in terms of its ability to promote psychological wellbeing and resilience to stress; however, the potential benefits of self-compassion are yet to be thoroughly explored amongst this occupational group. Additionally, while a growing body of research supports self-compassion as a key predictor of psychopathology, understanding of the processes by which self-compassion exerts effects on mental health outcomes is limited. Structural equation modelling (SEM) was used to test an emotion regulation model of self-compassion and stress among psychologists, including postgraduate trainees undertaking clinical work (n = 198). Self-compassion significantly negatively predicted emotion regulation difficulties and stress symptoms. Support was also found for our preliminary explanatory model of self-compassion, which demonstrates the mediating role of emotion regulation difficulties in the self-compassion-stress relationship. The final self-compassion model accounted for 26.2% of variance in stress symptoms. Implications of the findings and limitations of the study are discussed

Southern Ocean carbon sink enhanced by sea-ice feedbacks at the Antarctic Cold Reversal

The Southern Ocean occupies some 14% of the planet’s surface and plays a fundamental role in the global carbon cycle and climate. It provides a direct connection to the deep ocean carbon reservoir through biogeochemical processes that include surface primary productivity, remineralisation at depth, and the upwelling of carbon-rich water masses. However, the role of these different processes in modulating past and future air-sea carbon flux remains poorly understood. A key period in this regard is the Antarctic Cold Reversal (ACR, 14.6-12.7 kyr BP), a period of mid- to high-latitude cooling that coincided with a sustained plateau in deglacial atmospheric rise in CO2 globally. Here we reconstruct high-latitude Southern Ocean surface productivity from marine derived aerosols captured in a highly-resolved horizontal ice core. Our multiproxy reconstruction reveals a coherent signal of enhanced productivity across the ACR. Transient climate modelling indicates this period coincided with maximum seasonal variability in sea-ice extent, implying that sea-ice biological feedbacks enhanced CO2 sequestration, creating a significant regional marine carbon sink that contributed to the sustained plateau in CO2 at the ACR. Our results highlights the role Antarctic sea ice plays in controlling global CO2, and demonstrates the need to incorporate such feedbacks in climate-carbon models