The moduli space of hypersurfaces whose singular locus has high dimension

Let $k$ be an algebraically closed field and let $b$ and $n$ be integers with $n\geq 3$ and $1\leq b \leq n-1.$ Consider the moduli space $X$ of hypersurfaces in $\mathbb{P}^n_k$ of fixed degree $l$ whose singular locus is at least $b$-dimensional. We prove that for large $l$, $X$ has a unique irreducible component of maximal dimension, consisting of the hypersurfaces singular along a linear $b$-dimensional subspace of $\mathbb{P}^n$. The proof will involve a probabilistic counting argument over finite fields.Comment: Final version, including the incorporation of all comments by the refere

Drivers of price formation and predictive properties of the forward curve, geographical distance, trade flow, and currency markets for global commodity trading

This thesis examines various drivers of commodity trade flows and it quantifies their predictability and impact on the prices of key industrial commodities. The first empirical chapter discusses how short-term change in the position and gradient of the crude oil market forward curve can contribute to the formation of speculative supply shock. The conditions for causality between the forward curve position, its slope steepness, and oil supply are examined. Evidence of causality and, therefore, of a speculative supply shock is detected, resulting in the development of a structural model of the global crude oil market that allows for a speculative supply shock as a result of a forward curve shift and steepness. The second empirical chapter investigates the dynamics between price and cross-border trade flows of the EU electricity market. First, I study the impact of the relative strength of economic activity and distance between two countries on their net cross-border electricity flow. The effect from changes of electricity flow between two markets on flows between another pair of markets is also examined. Lastly, I investigate the relationship between crossborder electricity flows and electricity prices. Evidence of causality between flow and price, flow and flow and the gravity of the trade coefficient and flow, is also documented. VAR/VEC model framework is employed to identify and trace the shocks introduced to the system of inter-connected markets, a short-term electricity trading model is proposed. The third empirical chapter of the thesis examines the role of global foreign exchange markets in the formation of supply and demand shocks for key energy, metal, grain, and shipping commodity markets. Difference in the predictive power of the currencies of exporters and importers is investigated and an S&D model based exclusively on foreign exchange signals is proposed. The results provide evidence that currencies of importers have higher explanatory power than the currencies of exporters - a major departure from the established consensus in the literature. Additionally, the currency-based S&D model is found to possess a stronger predictive power over the price of commodity compared to the predictive power of each of its constituents, which improves the explanatory power of the proposed VEC model

Functional QTL mapping and genomic prediction of canopy height in wheat measured using a robotic field phenotyping platform

Genetic studies increasingly rely on high-throughput phenotyping, but the resulting longitudinal data pose analytical challenges. We used canopy height data from an automated field phenotyping platform to compare several approaches to scanning for quantitative trait loci (QTLs) and performing genomic prediction in a wheat recombinant inbred line mapping population based on up to 26 sampled time points (TPs). We detected four persistent QTLs (i.e. expressed for most of the growing season), with both empirical and simulation analyses demonstrating superior statistical power of detecting such QTLs through functional mapping approaches compared with conventional individual TP analyses. In contrast, even very simple individual TP approaches (e.g. interval mapping) had superior detection power for transient QTLs (i.e. expressed during very short periods). Using spline-smoothed phenotypic data resulted in improved genomic predictive abilities (5–8% higher than individual TP prediction), while the effect of including significant QTLs in prediction models was relatively minor (<1–4% improvement). Finally, although QTL detection power and predictive ability generally increased with the number of TPs analysed, gains beyond five or 10 TPs chosen based on phenological information had little practical significance. These results will inform the development of an integrated, semi-automated analytical pipeline, which will be more broadly applicable to similar data sets in wheat and other crops

Preparation and characterization of superhydrophobic surfaces based on hexamethyldisilazane-modified nanoporous alumina

Superhydrophobic nanoporous anodic aluminum oxide (alumina) surfaces were prepared using treatment with vapor-phase hexamethyldisilazane (HMDS). Nanoporous alumina substrates were first made using a two-step anodization process. Subsequently, a repeated modification procedure was employed for efficient incorporation of the terminal methyl groups of HMDS to the alumina surface. Morphology of the surfaces was characterized by scanning electron microscopy, showing hexagonally ordered circular nanopores with approximately 250 nm in diameter and 300 nm of interpore distances. Fourier transform infrared spectroscopy-attenuated total reflectance analysis showed the presence of chemically bound methyl groups on the HMDS-modified nanoporous alumina surfaces. Wetting properties of these surfaces were characterized by measurements of the water contact angle which was found to reach 153.2 ± 2°. The contact angle values on HMDS-modified nanoporous alumina surfaces were found to be significantly larger than the average water contact angle of 82.9 ± 3° on smooth thin film alumina surfaces that underwent the same HMDS modification steps. The difference between the two cases was explained by the Cassie-Baxter theory of rough surface wetting

Genetic relationships between spring emergence, canopy phenology and biomass yield increase the accuracy of genomic prediction in Miscanthus

Miscanthus has potential as a bioenergy crop but the rapid development of high-yielding varieties is challenging. Previous studies have suggested that phenology and canopy height are important determinants of biomass yield. Furthermore, while genome-wide prediction was effective for a broad range of traits, the predictive ability for yield was very low. We therefore developed models clarifying the genetic associations between spring emergence, consequent canopy phenology and dry biomass yield. The timing of emergence was a moderately strong predictor of early-season elongation growth (genetic correlation >0.5), but less so for growth later in the season and for the final yield (genetic correlation <0.1). In contrast, early-season canopy height was consistently more informative than emergence for predicting biomass yield across datasets for two species in Miscanthus and two growing seasons. We used the associations uncovered through these models to develop selection indices that are expected to increase the response to selection for yield by as much as 21% and improve the performance of genome-wide prediction by an order of magnitude. This multivariate approach could have an immediate impact in operational breeding programmes, as well as enable the integration of crop growth models and genome-wide predictionpublishersversionPeer reviewe

Dielectric properties of bismuth titanate ceramics containing SiO2 and Nd2O3 as additives

Bismuth-titanate ceramics containing SiO2 and Nd2O3 as additives are synthesized by melt quenching method in the system Bi2O3-TiO2-Nd2O3-SiO2 in the temperature range of 1250–1500 °C. The phase composition of the obtained materials is determined by X-ray diffraction analysis and energy dispersive spectroscopy. Using scanning electron microscopy different microstructures are observed in the samples depending on the composition. Different values of conductivity, dielectric losses and relative permittivity are obtained depending on the composition. It is established that all investigated samples are dielectric materials with conductivity between 10^-9 and 10^-13 (Ω·cm)^-1 at room temperature, dielectric permittivity from 1000 to 3000 and dielectric losses tgδ between 0.0002 and 0.1

Genome-wide association studies and prediction of 17 traits related to phenology, biomass and cell wall composition in the energy grass Miscanthus sinensis

Increasing demands for food and energy require a step change in the effectiveness, speed and flexibility of crop breeding. Therefore, the aim of this study was to assess the potential of genome-wide association studies (GWASs) and genomic selection (i.e. phenotype prediction from a genome-wide set of markers) to guide fundamental plant science and to accelerate breeding in the energy grass Miscanthus. We generated over 100 000 single-nucleotide variants (SNVs) by sequencing restriction site-associated DNA (RAD) tags in 138 Micanthus sinensis genotypes, and related SNVs to phenotypic data for 17 traits measured in a field trial. Confounding by population structure and relatedness was severe in naïve GWAS analyses, but mixed-linear models robustly controlled for these effects and allowed us to detect multiple associations that reached genome-wide significance. Genome-wide prediction accuracies tended to be moderate to high (average of 0.57), but varied dramatically across traits. As expected, predictive abilities increased linearly with the size of the mapping population, but reached a plateau when the number of markers used for prediction exceeded 10 000–20 000, and tended to decline, but remain significant, when cross-validations were performed across subpopulations. Our results suggest that the immediate implementation of genomic selection in Miscanthus breeding programs may be feasible