Simple measures of climate, soil properties and plant traits predict national scale grassland soil carbon stocks

1. Soil carbon (C) storage is a key ecosystem service. Soil C stocks play a vital role in soil fertility and climate regulation, but the factors that control these stocks at regional and national scales are unknown, particularly when their composition and stability are considered. As a result, their mapping relies on either unreliable proxy measures or laborious direct measurements. 2. Using data from an extensive national survey of English grasslands we show that surface soil (0-7cm) C stocks in size fractions of varying stability can be predicted at both regional and national scales from plant traits and simple measures of soil and climatic conditions. 3. Soil C stocks in the largest pool, of intermediate particle size (50-250 µm), were best explained by mean annual temperature (MAT), soil pH and soil moisture content. The second largest C pool, highly stable physically and biochemically protected particles (0.45-50 µm), was explained by soil pH and the community abundance weighted mean (CWM) leaf nitrogen (N) content, with the highest soil C stocks under N rich vegetation. The C stock in the small active fraction (250-4000 µm) was explained by a wide range of variables: MAT, mean annual precipitation, mean growing season length, soil pH and CWM specific leaf area; stocks were higher under vegetation with thick and/or dense leaves. 4. Testing the models describing these fractions against data from an independent English region indicated moderately strong correlation between predicted and actual values and no systematic bias, with the exception of the active fraction, for which predictions were inaccurate. 5. Synthesis and Applications: Validation indicates that readily available climate, soils and plant survey data can be effective in making local- to landscape-scale (1-100,000 km2) soil C stock predictions. Such predictions are a crucial component of effective management strategies to protect C stocks and enhance soil C sequestration.

Neurolinguistic measures of typological effects in multilingual transfer: introducing an ERP methodology

This article has two main objectives. First, we offer an introduction to the subfield of generative third language (L3) acquisition. Concerned primarily with modeling initial stages transfer of morphosyntax, one goal of this program is to show how initial stages L3 data make significant contributions toward a better understanding of how the mind represents language and how (cognitive) economy constrains acquisition processes more generally. Our second objective is to argue for and demonstrate how this subfield will benefit from a neuro/psycholinguistic methodological approach, such as event-related potential experiments, to complement the claims currently made on the basis of exclusively behavioral experiments.

A multifractal zeta function for Gibbs measures supported on cookie-cutter sets

Starting with the work of Lapidus and van Frankenhuysen a number of papers have introduced zeta functions as a way of capturing multifractal information. In this paper we propose a new multifractal zeta function and show that under certain conditions the abscissa of convergence yields the Hausdorff multifractal spectrum for a class of measures.

Fat mass-and obesity-associated genotype, dietary intakes and anthropometric measures in European adults: the Food4Me study

The interplay between the fat mass- and obesity-associated (FTO) gene variants and diet has been implicated in the development of obesity. The aim of the present analysis was to investigate associations between FTO genotype, dietary intakes and anthropometrics among European adults. Participants in the Food4Me randomised controlled trial were genotyped for FTO genotype (rs9939609) and their dietary intakes, and diet quality scores (Healthy Eating Index and PREDIMED-based Mediterranean diet score) were estimated from FFQ. Relationships between FTO genotype, diet and anthropometrics (weight, waist circumference (WC) and BMI) were evaluated at baseline. European adults with the FTO risk genotype had greater WC (AAv. TT: +1·4 cm; P=0·003) and BMI (+0·9 kg/m2; P=0·001) than individuals with no risk alleles. Subjects with the lowest fried food consumption and two copies of the FTO risk variant had on average 1·4 kg/m2 greater BMI (Ptrend=0·028) and 3·1 cm greater WC (Ptrend=0·045) compared with individuals with no copies of the risk allele and with the lowest fried food consumption. However, there was no evidence of interactions between FTO genotype and dietary intakes on BMI and WC, and thus further research is required to confirm or refute these findings.

Scalable and fault tolerant failure detection and consensus

Future extreme-scale high-performance computing systems will be required to work under frequent component failures. The MPI Forum's User Level Failure Mitigation proposal has introduced an operation, MPI_Comm_shrink, to synchronize the alive processes on the list of failed processes, so that applications can continue to execute even in the presence of failures by adopting algorithm-based fault tolerance techniques. This MPI_Comm_shrink operation requires a fault tolerant failure detection and consensus algorithm. This paper presents and compares two novel failure detection and consensus algorithms. The proposed algorithms are based on Gossip protocols and are inherently fault-tolerant and scalable. The proposed algorithms were implemented and tested using the Extreme-scale Simulator. The results show that in both algorithms the number of Gossip cycles to achieve global consensus scales logarithmically with system size. The second algorithm also shows better scalability in terms of memory and network bandwidth usage and a perfect synchronization in achieving global consensus.

Back to basics: how measures of lexical diversity can help discriminate between CEFR levels

This study contributes to ongoing discussions on how measures of lexical diversity (LD) can help discriminate between essays from second language learners of English, whose work has been assessed as belonging to levels B1 to C2 of the Common European Framework of Reference (CEFR). The focus is in particular on how different operationalisations of what constitutes a “different word” (type) impact on the LD measures themselves and on their ability to discriminate between CEFR levels. The results show that basic measures of LD, such as the number of different words, the TTR (Templin 1957) and the Index of Guiraud (Guiraud 1954) explain more variance in the CEFR levels than sophisticated measures, such as D (Malvern et al. 2004), HD-D (McCarthy and Jarvis 2007) and MTLD (McCarthy 2005) provided text length is kept constant across texts. A simple count of different words (defined as lemma’s and not as word families) was the best predictor of CEFR levels and explained 22 percent of the variance in overall scores on the Pearson Test of English Academic in essays written by 176 test takers.

Liquidity review: dimensions, causes, measures and empirical applications in real estate markets

Liquidity is a fundamentally important facet of investments, but there is no single measure that quantifies it perfectly. Instead, a range of measures are necessary to capture different dimensions of liquidity such as the breadth and depth of markets, the costs of transacting, the speed with which transactions can occur and the resilience of prices to trading activity. This article considers how different dimensions have been measured in financial markets and for various forms of real estate investment. The purpose of this exercise is to establish the range of liquidity measures that could be used for real estate investments before considering which measures and questions have been investigated so far. Most measures reviewed here are applicable to public real estate, but not all can be applied to private real estate assets or funds. Use of a broader range of liquidity measures could help real estate researchers tackle issues such as quantification of illiquidity premiums for the real estate asset class or different types of real estate, and how liquidity differences might be incorporated into portfolio allocation models.

Differential crosstalk between estrogen receptor (ER) alpha and ER beta and the thyroid hormone receptor isoforms results in flexible regulation of the consensus ERE

Crosstalk between nuclear receptors is important for conversion of external and internal stimuli to a physiologically meaningful response by cells. Previous studies from this laboratory have demonstrated crosstalk between the estrogen (ER) and thyroid hormone receptors (TR) on two estrogen responsive physiological promoters, the preproenkephalin and oxytocin receptor gene promoter. Since ERa and ERb are isoforms possessing overlapping and distinct transactivation properties, we hypothesized that the interaction of ERa and b with the various TR isoforms would not be equivalent. To explore this hypothesis, the consensus estrogen response element (ERE)derived from the Xenopus vitellogenin gene is used to investigate the differences in interaction between ERa and b isoforms and the different TR isoforms in fibroblast cells. Both the ER isoforms transactivate from the consensus ERE, though ERa transactivates to a greater extent than ERb. Although neither of the TRb isoforms have an effect on ERa transactivation from the consensus ERE, the liganded TRa1 inhibits the ERa transactivation from the consensus ERE. In contrast, the liganded TRa1 facilitates ERb-mediated transactivation. The crosstalk between the TRb isoforms with the ERa isoform, on the consensus ERE, is different from that with the ERb isoform. The use of a TRa1 mutant, which is unable to bind DNA, abolishes the ability of the TRa1 isoform to interact with either of the ER isoforms. These differences in nuclear receptor crosstalk reveal an important functional difference between isoforms, which provides a novel mechanism for neuroendocrine integration.

Thyroid hormone can increase estrogen-mediated transcription from a consensus estrogen response element in neuroblastoma cells

Thyroid hormones (T) and estrogens (E) are nuclear receptor ligands with at least two molecular mechanisms of action: (i) relatively slow genomic effects, such as the regulation of transcription by cognate T receptors (TR) and E receptors (ER); and (ii) relatively rapid nongenomic effects, such as kinase activation and calcium release initiated at the membrane by putative membrane receptors. Genomic and nongenomic effects were thought to be disparate and independent. However, in a previous study using a two-pulse paradigm in neuroblastoma cells, we showed that E acting at the membrane could potentiate transcription from an E-driven reporter gene in the nucleus. Because both T and E can have important effects on mood and cognition, it is possible that the two hormones can act synergistically. In this study, we demonstrate that early actions of T via TRalpha1 and TRbeta1 can potentiate E-mediated transcription (genomic effects) from a consensus E response element (ERE)-driven reporter gene in transiently transfected neuroblastoma cells. Such potentiation was reduced by inhibition of mitogen-activated protein kinase. Using phosphomutants of ERalpha, we also show that probable mitogen-activated protein kinase phosphorylation sites on the ERalpha, the serines at position 167 and 118, are important in TRbeta1-mediated potentiation of ERalpha-induced transactivation. We suggest that crosstalk between T and E includes potential interactions through both nuclear and membrane-initiated molecular mechanisms of hormone signaling.

The impact of European legislative and technology measures to reduce air pollutants on air quality, human health and climate

European air quality legislation has reduced emissions of air pollutants across Europe since the 1970s, affecting air quality, human health and regional climate. We used a coupled composition-climate model to simulate the impacts of European air quality legislation and technology measures implemented between 1970 and 2010. We contrast simulations using two emission scenarios; one with actual emissions in 2010 and the other with emissions that would have occurred in 2010 in the absence of technological improvements and end-of-pipe treatment measures in the energy, industrial and road transport sectors. European emissions of sulphur dioxide, black carbon (BC) and organic carbon in 2010 are 53%, 59% and 32% lower respectively compared to emissions that would have occurred in 2010 in the absence of legislative and technology measures. These emission reductions decreased simulated European annual mean concentrations of fine particulate matter(PM2.5) by 35%, sulphate by 44%, BC by 56% and particulate organic matter by 23%. The reduction in PM2.5 concentrations is calculated to have prevented 80 000 (37 000–116 000, at 95% confidence intervals) premature deaths annually across the European Union, resulting in a perceived financial benefit to society of US$232 billion annually (1.4% of 2010 EU GDP). The reduction in aerosol concentrations due to legislative and technology measures caused a positive change in the aerosol radiative effect at the top of atmosphere, reduced atmospheric absorption and also increased the amount of solar radiation incident at the surface over Europe. We used an energy budget approximation to estimate that these changes in the radiative balance have increased European annual mean surface temperatures and precipitation by 0.45 ± 0.11 °C and by 13 ± 0.8 mm yr−1 respectively. Our results show that the implementation of European legislation and technological improvements to reduce the emission of air pollutants has improved air quality and human health over Europe, as well as having an unintended impact on the regional radiative balance and climate.

Prospective Clinical Trial Comparing Outcome Measures Between Furlow and von Langenbeck Palatoplasties for UCLP

The goal of this prospective randomized clinical trial was to compare 2 cohorts of standardized cleft patients with regard to functional speech outcome and the presence or absence of palatal fistulae. The 2 cohorts are randomized to undergo either a conventional von Langenbeck repair with intravelar velarplasty or the double-opposing Z-plasty Furlow procedure. A prospective 2 x 2 x 2 factorial clinical trial was used in which each subject was randomly assigned to 1 of 8 different groups: 1 of 2 different lip repairs (Spina vs. Millard), 1 of 2 different palatal repair (von Langenbeck vs. Furlow), and 1 of 2 different ages at time of palatal surgery (9-12 months vs. 15-18 months). All surgeries were performed by the same 4 surgeons. A cul-de-sac test of hypernasality and a mirror test of nasal air emission were selected as primary outcome measures for velopharyngeal function. Both a surgeon and speech pathologist examined patients for the presence of palatal fistulae. In this study, the Furlow double-opposing Z-palatoplasty resulted in significantly better velopharyngeal function for speech than the von Langenbeck procedure as determined by the perceptual cul-de-sac test of hypernasality. Fistula occurrence was significantly higher for the Furlow procedure than for the von Langenbeck. Fistulas were more likely to occur in patients with wider clefts and when relaxing incisions were not used.

Comparing species and measures of landscape structure as indicators of conservation importance

P>1. The use of indicators to identify areas of conservation importance has been challenged on several grounds, but nonetheless retains appeal as no more parsimonious approach exists. Among the many variants, two indicator strategies stand out: the use of indicator species and the use of metrics of landscape structure. While the first has been thoroughly studied, the same cannot be said about the latter. We aimed to contrast the relative efficacy of species-based and landscape-based indicators by: (i) comparing their ability to reflect changes in community integrity at regional and landscape spatial scales, (ii) assessing their sensitivity to changes in data resolution, and (iii) quantifying the degree to which indicators that are generated in one landscape or at one spatial scale can be transferred to additional landscapes or scales. 2. We used data from more than 7000 bird captures in 65 sites from six 10 000-ha landscapes with different proportions of forest cover in the Atlantic Forest of Brazil. Indicator species and landscape-based indicators were tested in terms of how effective they were in reflecting changes in community integrity, defined as deviations in bird community composition from control areas. 3. At the regional scale, indicator species provided more robust depictions of community integrity than landscape-based indicators. At the landscape scale, however, landscape-based indicators performed more effectively, more consistently and were also more transferable among landscapes. The effectiveness of high resolution landscape-based indicators was reduced by just 12% when these were used to explain patterns of community integrity in independent data sets. By contrast, the effectiveness of species-based indicators was reduced by 33%. 4. Synthesis and applications. The use of indicator species proved to be effective; however their results were variable and sensitive to changes in scale and resolution, and their application requires extensive and time-consuming field work. Landscape-based indicators were not only effective but were also much less context-dependent. The use of landscape-based indicators may allow the rapid identification of priority areas for conservation and restoration, and indicate which restoration strategies should be pursued, using remotely sensed imagery. We suggest that landscape-based indicators might often be a better, simpler, and cheaper strategy for informing decisions in conservation.

Consensus Statement: Chromosomal Microarray Is a First-Tier Clinical Diagnostic Test for Individuals with Developmental Disabilities or Congenital Anomalies

Chromosomal microarray (CMA) is increasingly utilized for genetic testing of individuals with unexplained developmental delay/intellectual disability (DD/ID), autism spectrum disorders (ASD), or multiple congenital anomalies (MCA). Performing CMA and G-banded karyotyping on every patient substantially increases the total cost of genetic testing. The International Standard Cytogenomic Array (ISCA) Consortium held two international workshops and conducted a literature review of 33 studies, including 21,698 patients tested by CMA. We provide an evidence-based summary of clinical cytogenetic testing comparing CMA to G-banded karyotyping with respect to technical advantages and limitations, diagnostic yield for various types of chromosomal aberrations, and issues that affect test interpretation. CMA offers a much higher diagnostic yield (15%-20%) for genetic testing of individuals with unexplained DD/ID, ASD, or MCA than a G-banded karyotype (similar to 3%, excluding Down syndrome and other recognizable chromosomal syndromes), primarily because of its higher sensitivity for submicroscopic deletions and duplications. Truly balanced rearrangements and low-level mosaicism are generally not detectable by arrays, but these are relatively infrequent causes of abnormal phenotypes in this population (<1%). Available evidence strongly supports the use of CMA in place of G-banded karyotyping as the first-tier cytogenetic diagnostic test for patients with DD/ID, ASD, or MCA. G-banded karyotype analysis should be reserved for patients with obvious chromosomal syndromes (e.g., Down syndrome), a family history of chromosomal rearrangement, or a history of multiple miscarriages.

Building binary-tree-based multiclass classifiers using separability measures

Various popular machine learning techniques, like support vector machines, are originally conceived for the solution of two-class (binary) classification problems. However, a large number of real problems present more than two classes. A common approach to generalize binary learning techniques to solve problems with more than two classes, also known as multiclass classification problems, consists of hierarchically decomposing the multiclass problem into multiple binary sub-problems, whose outputs are combined to define the predicted class. This strategy results in a tree of binary classifiers, where each internal node corresponds to a binary classifier distinguishing two groups of classes and the leaf nodes correspond to the problem classes. This paper investigates how measures of the separability between classes can be employed in the construction of binary-tree-based multiclass classifiers, adapting the decompositions performed to each particular multiclass problem. (C) 2010 Elsevier B.V. All rights reserved.