New Solutions of the Yang-Baxter Equation Based on Root of 1 Representations of the Para-Bose Superalgebra Uq_q[osp(1/2)]

New solutions of the quantum Yang-Baxter equation, depending in general on three arbitrary parameters, are written down. They are based on the root of unity representations of the quantum orthosymplectic superalgebra \\U, which were found recently. Representations of the braid group $B_N$ are defined within any $N^{th}$ tensorial power of root of 1 \\U modules.Comment: 11 pages, PlainTe

Farmer experiences of Tiyeni’s ‘deep-bed farming’ conservation agriculture system in Malawi

In the context of increasing NGO interest in the capacity of conservation agriculture methods to support sustainable agriculture across sub-Saharan Africa, this paper explores the experiences of farmers (n = 111) adopting the Tiyeni NGO’s deep-bed farming (DBF) system in northern Malawi. The results of a field survey suggest that whilst DBF delivers significant livelihood benefits for farmers relative to traditional techniques (a factor arguably driving its rapid spontaneous adoption throughout the area), some asset-poor farmers are unable to sustain DBF due to its labor demands. We argue that to widen its beneficial impacts in a manner that can be sustained, there is a need for Tiyeni’s DBF to be less prescriptive and more adaptive to specific social-ecological contexts

Catalytic residues in hydrolases: analysis of methods designed for ligand-binding site prediction

The comparison of eight tools applicable to ligand-binding site prediction is presented. The methods examined cover three types of approaches: the geometrical (CASTp, PASS, Pocket-Finder), the physicochemical (Q-SiteFinder, FOD) and the knowledge-based (ConSurf, SuMo, WebFEATURE). The accuracy of predictions was measured in reference to the catalytic residues documented in the Catalytic Site Atlas. The test was performed on a set comprising selected chains of hydrolases. The results were analysed with regard to size, polarity, secondary structure, accessible solvent area of predicted sites as well as parameters commonly used in machine learning (F-measure, MCC). The relative accuracies of predictions are presented in the ROC space, allowing determination of the optimal methods by means of the ROC convex hull. Additionally the minimum expected cost analysis was performed. Both advantages and disadvantages of the eight methods are presented. Characterization of protein chains in respect to the level of difficulty in the active site prediction is introduced. The main reasons for failures are discussed. Overall, the best performance offers SuMo followed by FOD, while Pocket-Finder is the best method among the geometrical approaches