Correct measurements of the efficiency of solar cells as a basis for their comparative techno-economic analysis

The comparative techno-economic analysis of different PV cells and their technologies should be based on the correct measurements of the efficiency of these cells. For this purpose the special procedure was implemented into practice, which includes the following steps: the choice of the standard spectrum, calibration of the reference solar cells, measurements on sun simulators of high quality, and calculation of spectral difference between the reference and mass-produced solar cells. The steps of this procedure as well as the types of terrestrial solar radiation simulators and methods of reference cells calibration are described here.     

Lack of mutagenicity of products formed by ammoniation of gossypol

Gossypol distributed on an inert gel carrier was treated in a pressurized ammoniation chamber used to detoxify aflatoxin-contaminated cottonseed meal. Ames tests for mutagenicity were performed on untreated gossypol and on fractions eluted sequentially from the gel. Nonammoniated gossypol was not mutagenic nor were any of the products formed from gossypol by ammoniation.     

Approximately dominating representatives

We propose and investigate from the algorithmic standpoint a novel form of fuzzy query called approximately dominating representatives or ADRs. The ADRs of a multidimensional point set consist of a few points guaranteed to contain an approximate optimum of any monotone Lipschitz continuous combining function of the dimensions. ADRs can be computed by appropriately post-processing Pareto, or “skyline”, queries [Kian-Lee Tan, Pin-Kwang Eng, Beng Chin Ooi, Efficient progressive skyline computation, in: VLDB, 2001, pp. 301–310; Wolf-Tilo Balke, Ulrich Güntzer, Jason Xin Zheng, Efficient distributed skylining for web information systems, in: EDBT, 2004.  [14]]. We show that the problem of minimizing the number of points returned, for a user-specified desired approximation, can be solved in polynomial time in two dimensions; for three and more it is NP-hard but has a polynomial-time logarithmic approximation. Finally, we present a polynomial-time, constant factor approximation algorithm for three dimensions.