Perceptions of Gauteng Beef Farmers on Significance of Practising Climate Smart Agriculture

Farmers are crucial role-players in agriculture, especially in beef farming. Daily farm activities affect climate change, either negatively or positively. Therefore, farmers’ ability to relate climate change with farm activities is highly imperative. A study was conducted to investigate perceptions of Gauteng beef farmers on significance of practising climate smart agriculture (CSA). Semi-structured key informant interviews were conducted with 57 beef cattle farmers from three areas (Bronkhorstspruit, Rust de Winter and Cullinan) of Tshwane region (Gauteng province). A fully detailed ethical statement was used to explain the study and request farmers’ participation. Data analysis was done using a Statistical Package for Social Sciences (SPSS) software version 20 with a significance of P \u3c 0.05. Majority (71%) of farmers who participated were males. Most (43%) of participated farmers were middle age, which indicates that farmers are now considering beef farming as a full-time job. Majority (60%) of participants had access to enough land (\u3e 700 hectares), which makes them suitable for practising CSA, provided they get appropriate training. Few participants showed good understanding of climate change (14%), global warming (14%), climate change reduction strategies (29%), cattle contribution to climate change (14%), adaptation strategies for climate change (29%) and the role played by CSA on reduction of farm operational costs (14%). Majority of farmers had average understanding of climate change (86%), global warming (86%), cattle contribution on global warming (71%), climate change adaptation strategies (71%), climate change reduction strategies (71%), recommendation of climate smart feed resource (71%) and impact of CSA on economic development (86%). Majority (71%) of participants identified water pollution as the only environmental hazard associated with beef farming, whereas few (29%) identified air pollution due to greenhouse gases emissions from poorly managed cattle manure. All participants (100%) showed good understanding regarding the benefits of practising CSA and its impact on food security. Furthermore, they were willing to adopt CSA and promote it to fellow farmers. There is a need for farmers’ training on CSA

The Quantum Affine Origin of the AdS/CFT Secret Symmetry

We find a new quantum affine symmetry of the S-matrix of the one-dimensional Hubbard chain. We show that this symmetry originates from the quantum affine superalgebra U_q(gl(2|2)), and in the rational limit exactly reproduces the secret symmetry of the AdS/CFT worldsheet S-matrix.Comment: 22 page

Novel Mechanism of Supersolid of Ultracold Polar Molecules in Optical Lattices

We study the checkerboard supersolid of the hard-core Bose-Hubbard model with the dipole-dipole interaction. This supersolid is different from all other supersolids found in lattice models in the sense that superflow paths through which interstitials or vacancies can hop freely are absent in the crystal. By focusing on repulsive interactions between interstitials, we reveal that the long-range tail of the dipole-dipole interaction have the role of increasing the energy cost of domain wall formations. This effect produces the supersolid by the second-order hopping process of defects. We also perform exact quantum Monte Carlo simulations and observe a novel double peak structure in the momentum distribution of bosons, which is a clear evidence for supersolid. This can be measured by the time-of-flight experiment in optical lattice systems

Secret Symmetries in AdS/CFT

We discuss special quantum group (secret) symmetries of the integrable system associated to the AdS/CFT correspondence. These symmetries have by now been observed in a variety of forms, including the spectral problem, the boundary scattering problem, n-point amplitudes, the pure-spinor formulation and quantum affine deformations.Comment: 20 pages, pdfLaTeX; Submitted to the Proceedings of the Nordita program `Exact Results in Gauge-String Dualities'; Based on the talk presented by A.T., Nordita, 15 February 201

Asymptotic Bethe equations for open boundaries in planar AdS/CFT

We solve, by means of a nested coordinate Bethe ansatz, the open-boundaries scattering theory describing the excitations of a free open string propagating in $AdS_5\times S^5$, carrying large angular momentum $J=J_{56}$, and ending on a maximal giant graviton whose angular momentum is in the same plane. We thus obtain the all-loop Bethe equations describing the spectrum, for $J$ finite but large, of the energies of such strings, or equivalently, on the gauge side of the AdS/CFT correspondence, the anomalous dimensions of certain operators built using the epsilon tensor of SU(N). We also give the Bethe equations for strings ending on a probe D7-brane, corresponding to meson-like operators in an $\mathcal N=2$ gauge theory with fundamental matter.Comment: 30 pages. v2: minor changes and discussion section added, J.Phys.A version

Sparsest factor analysis for clustering variables: a matrix decomposition approach

We propose a new procedure for sparse factor analysis (FA) such that each variable loads only one common factor. Thus, the loading matrix has a single nonzero element in each row and zeros elsewhere. Such a loading matrix is the sparsest possible for certain number of variables and common factors. For this reason, the proposed method is named sparsest FA (SSFA). It may also be called FA-based variable clustering, since the variables loading the same common factor can be classified into a cluster. In SSFA, all model parts of FA (common factors, their correlations, loadings, unique factors, and unique variances) are treated as fixed unknown parameter matrices and their least squares function is minimized through specific data matrix decomposition. A useful feature of the algorithm is that the matrix of common factor scores is re-parameterized using QR decomposition in order to efficiently estimate factor correlations. A simulation study shows that the proposed procedure can exactly identify the true sparsest models. Real data examples demonstrate the usefulness of the variable clustering performed by SSFA

Tensor Regression with Applications in Neuroimaging Data Analysis

Classical regression methods treat covariates as a vector and estimate a corresponding vector of regression coefficients. Modern applications in medical imaging generate covariates of more complex form such as multidimensional arrays (tensors). Traditional statistical and computational methods are proving insufficient for analysis of these high-throughput data due to their ultrahigh dimensionality as well as complex structure. In this article, we propose a new family of tensor regression models that efficiently exploit the special structure of tensor covariates. Under this framework, ultrahigh dimensionality is reduced to a manageable level, resulting in efficient estimation and prediction. A fast and highly scalable estimation algorithm is proposed for maximum likelihood estimation and its associated asymptotic properties are studied. Effectiveness of the new methods is demonstrated on both synthetic and real MRI imaging data.Comment: 27 pages, 4 figure

The Impact of Mixing Modes on Reliability in Longitudinal Studies

Mixed-mode designs are increasingly important in surveys, and large longitudinal studies are progressively moving to or considering such a design. In this context, our knowledge regarding the impact of mixing modes on data quality indicators in longitudinal studies is sparse. This study tries to ameliorate this situation by taking advantage of a quasi-experimental design in a longitudinal survey. Using models that estimate reliability for repeated measures, quasi-simplex models, 33 variables are analyzed by comparing a single-mode CAPI design to a sequential CATI-CAPI design. Results show no differences in reliabilities and stabilities across mixed modes either in the wave when the switch was made or in the subsequent waves. Implications and limitations are discussed. </jats:p

Josephson Plasma Resonance as a Structural Probe of Vortex Liquid

Recent developments of the Josephson plasma resonance and transport c-axis measurements in layered high T$_{c}$ superconductors allow to probe Josephson coupling in a wide range of the vortex phase diagram. We derive a relation between the field dependent Josephson coupling energy and the density correlation function of the vortex liquid. This relation provides a unique opportunity to extract the density correlation function of pancake vortices from the dependence of the plasma resonance on the $ab$-component of the magnetic field at a fixed $c$-axis component.Comment: 4 pages, 1 fugure, accepted to Phys. Rev. Let