Exploring the link between more negative osmotic potential and ryegrass summer performance

This paper outlines recent research studying within-population variation in selected New Zealand perennial ryegrass cultivars, for traits related to tolerance of summer moisture deficit. Two clonal replicates of 220 genotypes from ‘Grasslands Nui’ (Nui, n=50), ‘Grasslands Samson’ Samson, n=80), and ‘Trojan’ (n=90) were exposed to a 1 month of moisture deficit challenge, with plant water relations measurements performed to evaluate putative drought-response mechanisms. Water use of individual genotypes ranged from 1000 g water/g DM indicating large within-population variation for this trait. Mean WUE for Nui, Samson, and Trojan was, respectively, 424±16, 412±10, and 319±9 g water/g DW (P<0.001), suggesting that commercial plant breeding may have indirectly reduced water use in modern cultivars without specific focus on water relations. Principal component analysis indicated more negative osmotic potential may contribute to reduced water use while maintaining yield under water deficit, giving a potential focus for future breeding selection targeting summer water deficit tolerance.fals

Unsupervised Feature Selection with Adaptive Structure Learning

The problem of feature selection has raised considerable interests in the past decade. Traditional unsupervised methods select the features which can faithfully preserve the intrinsic structures of data, where the intrinsic structures are estimated using all the input features of data. However, the estimated intrinsic structures are unreliable/inaccurate when the redundant and noisy features are not removed. Therefore, we face a dilemma here: one need the true structures of data to identify the informative features, and one need the informative features to accurately estimate the true structures of data. To address this, we propose a unified learning framework which performs structure learning and feature selection simultaneously. The structures are adaptively learned from the results of feature selection, and the informative features are reselected to preserve the refined structures of data. By leveraging the interactions between these two essential tasks, we are able to capture accurate structures and select more informative features. Experimental results on many benchmark data sets demonstrate that the proposed method outperforms many state of the art unsupervised feature selection methods

Linear Dynamic Sparse Modelling for functional MR imaging

The reconstruction quality of a functional MRI sequence is determined by reconstruction algorithms as well as the information obtained from measurements. In this paper, we propose a Linear Dynamic Sparse Modelling method which is composed of measurement design and reconstruction processes to improve the image quality from both aspects. This method models an fMRI sequence as a linear dynamic sparse model which is based on a key assumption that variations of functional MR images are sparse over time in the wavelet domain. The Hierarchical Bayesian Kalman filter which follows the model is employed to implement the reconstruction process. To accomplish the measurement design process, we propose an Informative Measurement Design (IMD) method. The IMD method addresses the measurement design problem of selecting k feasible measurements such that the mutual information between the unknown image and measurements is maximised, where k is a given budget and the mutual information is extracted from the linear dynamic sparse model. The experimental results demonstrated that our proposed method succeeded in boosting the quality of functional MR images

Formation and observation of a quasi-two-dimensional dxyd_{xy} electron liquid in epitaxially stabilized Sr2−x_{2-x}Lax_{x}TiO4_{4} thin films

We report the formation and observation of an electron liquid in Sr$_{2-x}$La$_{x}$TiO$_4$, the quasi-two-dimensional counterpart of SrTiO$_3$, through reactive molecular-beam epitaxy and {\it in situ} angle-resolved photoemission spectroscopy. The lowest lying states are found to be comprised of Ti 3$d_{xy}$ orbitals, analogous to the LaAlO$_3$/SrTiO$_3$ interface and exhibit unusually broad features characterized by quantized energy levels and a reduced Luttinger volume. Using model calculations, we explain these characteristics through an interplay of disorder and electron-phonon coupling acting co-operatively at similar energy scales, which provides a possible mechanism for explaining the low free carrier concentrations observed at various oxide heterostructures such as the LaAlO$_3$/SrTiO$_3$ interface