Application of response surface methodology to laser-induced breakdown spectroscopy : influences of hardware configuration

Response Surface Methodology (RSM) was employed to optimise LIBS analysis of single crystal silicon at atmospheric pressure and under vacuum conditions (pressure ~10-6mbar). Multivariate analysis software (StatGraphics 5.1) was used to design and analyse several multi-level, full factorial RSM experiments. A Quality Factor (QF) was conceived as the response parameter for the experiments, representing the quality of the LIBS spectrum captured for a given hardware configuration. The QF enabled the hardware configuration to be adjusted so that a best compromise between resolution, signal intensity and signal noise could be achieved. The effect on the QF of simultaneously adjusting spectrometer gain, gate delay, gate width, lens position and spectrometer slit width was investigated, and the conditions yielding the best QF determined

Physiological response of cocoa (Theobroma cacao L. ) genotypes to drought

Drought is one of the major environmental stresses affecting crop productivity worldwide. Climate change is expected to result in a rise in the number and intensity of drought events in the coming decades, so climate-resilient crops that can withstand this stress are in high demand. There are few genotypes in cocoa where it can tolerate water deficit conditions. The objective of the current investigation was to evaluate the effect of drought stress on the photosynthetic and physiological parameters of six cocoa genotypes (Theobroma cacao L.) with two irrigation regimes (100% field capacity and 40% field capacity) under greenhouse conditions at Cocoa Research Station, Kerala Agricultural University, Thrissur. The effect of water deficit conditions on gas exchange and physiological parameters such as relative water content, membrane stability index, chlorophyll stability index, and chlorophyll content were evaluated. Drought stress conditions resulted in reduced photosynthetic rate, relative water content, chlorophyll content, chlorophyll stability and membrane stability. All genotypes revealed significant differences for most parameters with two irrigation regimes. Among the cocoa genotypes, P.IV 19.9, which is classified as a highly tolerant genotype, recorded better results for all the parameters studied under water deficit conditions at 40 per cent FC. The findings of this study support the classification of these genotypes as highly tolerant, tolerant, and susceptible. These parameters may be used as the most promising indicators to screen for drought tolerance in cocoa. The results of the study revealed that photosynthetic and physiological parameters have a significant role in imparting drought stress tolerance to cocoa. Furthermore, these selected drought-tolerant genotypes can be used in future crop improvement programmes in cocoa

Numerical studies towards practical large-eddy simulation

Large-eddy simulation developments and validations are presented for an improved simulation of turbulent internal flows. Numerical methods are proposed according to two competing criteria: numerical qualities (precision and spectral characteristics), and adaptability to complex configurations. First, methods are tested on academic test-cases, in order to abridge with fundamental studies. Consistent results are obtained using adaptable finite volume method, with higher order advection fluxes, implicit grid filtering and "low-cost" shear-improved Smagorinsky model. This analysis particularly focuses on mean flow, fluctuations, two-point correlations and spectra. Moreover, it is shown that exponential averaging is a promising tool for LES implementation in complex geometry with deterministic unsteadiness. Finally, adaptability of the method is demonstrated by application to a configuration representative of blade-tip clearance flow in a turbomachine

Status, Testosterone, and Human Intellectual Performance: Stereotype Threat as Status Concern

Results from two experiments suggest that stereotype-threat effects are special cases of a more general process involving the need to maintain or enhance status. We hypothesized that situations capable of confirming a performance stereotype might represent either a threat to status or an opportunity for enhancement of status, depending on the nature of the stereotype. The positive relationship between baseline testosterone and status sensitivity led us to hypothesize that high testosterone levels in males and females would amplify existing performance expectations when gender-based math-performance stereotypes were activated. In Study 1, high-testosterone females performed poorly on a math test when a negative performance stereotype was primed. In Study 2, high-testosterone males excelled on a math test when a positive performance stereotype was primed. The moderating effect of testosterone on performance suggests that a stereotype-relevant situation is capable of conferring either a loss or a gain of status on targets of the stereotype.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

An assessment of the carbon balance of Arctic tundra:Comparisons among observations, process models, and atmospheric inversions

Although Arctic tundra has been estimated to cover only 8% of the global land surface, the large and potentially labile carbon pools currently stored in tundra soils have the potential for large emissions of carbon (C) under a warming climate. These emissions as radiatively active greenhouse gases in the form of both CO<sub>2</sub> and CH<sub>4</sub> could amplify global warming. Given the potential sensitivity of these ecosystems to climate change and the expectation that the Arctic will experience appreciable warming over the next century, it is important to assess whether responses of C exchange in tundra regions are likely to enhance or mitigate warming. In this study we compared analyses of C exchange of Arctic tundra between 1990 and 2006 among observations, regional and global applications of process-based terrestrial biosphere models, and atmospheric inversion models. Syntheses of flux observations and inversion models indicate that the annual exchange of CO<sub>2</sub> between Arctic tundra and the atmosphere has large uncertainties that cannot be distinguished from neutral balance. The mean estimate from an ensemble of process-based model simulations suggests that Arctic tundra has acted as a sink for atmospheric CO<sub>2</sub> in recent decades, but based on the uncertainty estimates it cannot be determined with confidence whether these ecosystems represent a weak or a strong sink. Tundra was 0.6 °C warmer in the 2000s compared to the 1990s. The central estimates of the observations, process-based models, and inversion models each identify stronger sinks in the 2000s compared with the 1990s. Some of the process models indicate that this occurred because net primary production increased more in response to warming than heterotrophic respiration. Similarly, the observations and the applications of regional process-based models suggest that CH<sub>4</sub> emissions from Arctic tundra have increased from the 1990s to 2000s because of the sensitivity of CH<sub>4</sub> emissions to warmer temperatures. Based on our analyses of the estimates from observations, process-based models, and inversion models, we estimate that Arctic tundra was a sink for atmospheric CO<sub>2</sub> of 110 Tg C yr<sup>−1</sup> (uncertainty between a sink of 291 Tg C yr<sup>−1</sup> and a source of 80 Tg C yr<sup>−1</sup>) and a source of CH<sub>4</sub> to the atmosphere of 19 Tg C yr<sup>−1</sup> (uncertainty between sources of 8 and 29 Tg C yr<sup>−1</sup>). The suite of analyses conducted in this study indicate that it is important to reduce uncertainties in the observations, process-based models, and inversions in order to better understand the degree to which Arctic tundra is influencing atmospheric CO<sub>2</sub> and CH<sub>4</sub> concentrations. The reduction of uncertainties can be accomplished through (1) the strategic placement of more CO<sub>2</sub> and CH<sub>4</sub> monitoring stations to reduce uncertainties in inversions, (2) improved observation networks of ground-based measurements of CO<sub>2</sub> and CH<sub>4</sub> exchange to understand exchange in response to disturbance and across gradients of climatic and hydrological variability, and (3) the effective transfer of information from enhanced observation networks into process-based models to improve the simulation of CO<sub>2</sub> and CH<sub>4</sub> exchange from Arctic tundra to the atmosphere

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants

Cross-ancestry genome-wide association analysis of corneal thickness strengthens link between complex and Mendelian eye diseases

Central corneal thickness (CCT) is a highly heritable trait associated with complex eye diseases such as keratoconus and glaucoma. We perform a genome-wide association meta-analysis of CCT and identify 19 novel regions. In addition to adding support for known connective tissue-related pathways, pathway analyses uncover previously unreported gene sets. Remarkably, >20% of the CCT-loci are near or within Mendelian disorder genes. These included FBN1, ADAMTS2 and TGFB2 which associate with connective tissue disorders (Marfan, Ehlers-Danlos and Loeys-Dietz syndromes), and the LUM-DCN-KERA gene complex involved in myopia, corneal dystrophies and cornea plana. Using index CCT-increasing variants, we find a significant inverse correlation in effect sizes between CCT and keratoconus (r =-0.62, P = 5.30 × 10-5) but not between CCT and primary open-angle glaucoma (r =-0.17, P = 0.2). Our findings provide evidence for shared genetic influences between CCT and keratoconus, and implicate candidate genes acting in collagen and extracellular matrix regulation