Effects of Some Wood Chip Properties on Pulp Quality
A series of TMP experiments were performed at CIPP’s TMP pilot plant, and some pulp properties were measured. By comparing chip and pulp properties, and using projections to latent structures (PLS) analysis, we were able to demonstrate that on-line CMS measurements can be used to predict some pulp properties. It should be pointed out that the focus of this paper is to show how CMS measurements can be used to predict some pulp properties. This prediction will suggest ways to control chip quality so as to ensure pulp quality. We tried to explain some important chip properties included in the measurements, but did not try to model them.
Laser-excited fluorescence spectra of eastern SPF wood species. An optical technique for identification and separation of wood species?
SummaryUse of UV-laser excitation to produce fluorescence spectra for heartwood and sapwood from jack pine (Pinus banksiana), white spruce (Picea glauca) and balsam fir (Abies balsamea) was examined. Spectra were fairly broad without sharp spectral features and overlap of spectra between species was common. Sample to sample and in-sample variation of the recorded fluorescence spectra was observed. The fluorescence spectra obtained from heartwood samples of jack pine showed evidence of photochemical bleaching as a result of the multiple laser pulses needed to produce a complete spectrum. Bleaching may have obscured differences between species. For the mix of species examined no sapwood nor heartwood samples were distinguishable by this technique with the detector used. Use of an optical multichannel analyzer (OMA) could reduce the number of laser pulses needed to obtain an entire spectrum. Under these conditions it would be possible to determine whether the minor differences in spectral features observed for the different species are more pronounced in the first few laser pulses and if they are characteristic of species. Certain aspects of the data suggest that with improved analytical equipment UV-fluorescence might prove to be a useful technique for the identification of certain species.
Complexity, Network-Decisions And Alternative Risk Premia: Some New Theories Of Structural Change And Portfolio Decisions.
Structural Change is the basis for many decisions such as government fiscal and monetary policies, government interventions, corporate-expenditure decisions, corporate strategic decisions, portfolio management decisions in finance; household allocation decisions, etc.. Structural change in industries and national economies is increasingly more difficult to detect partly because of the growth and dominance of Complex Systems and “Networks” in modern industries and economies – such Networks and Complex Systems include GVCs (global value chains), retail store networks; franchising networks; internet networks; services networks; credit-chains in industries; online social networks; etc.. The relationship between Complexity and Structural Change is well established in the physics, applied math and economic dynamics literatures. Traditional definitions and modeling of structural change have erroneously focused on changes in labor, technological progress, market share, and or capital – which are grossly inadequate in the new economy and post- global financial crisis (as confirmed by changes in the global retailing and housing industries and other industries). Also the modeling of structural change seems to be constrained by the availability of data, and often omits the relationship between structural change on one hand, and globalization, financial stability and international financial contagion. This article: i) introduces the Operations Strategy Model of structural change, explains how it differs from the Lewis Model of Structural Change; and explains the often omitted relationship between operations strategy (of companies and government agencies) and structural change; ii) introduces other new Complexity-based models/theories of Structural Change in industries; iii) reviews the relationships among Operations Research, Complexity and Structural Change; iv) explains the symbiotic relationship between structural change on one hand, and economic growth, financial stability, financial contagion and globalization; v) discusses the significant gap between academic research and practice and explains some issues and factors that should be considered in the development and testing of structural change models; vi) explains how alternative risk premia can be generated from new models of Structural Change.