Why Cotton as Linen? The Use of Wool in Beds in Norway

Cotton is the “natural” choice and the dominating material in bed linen and sleepwear in Norway as in many other European countries. Regulation of temperature and humidity are important for good sleep, but they are not cotton’s strong points. There must have been other than the functional reasons which made cotton the winner in the bedding market. This article builds on literature about bedding in Norway from the 1800s and survey questions from 1951. We ask the question: what materials have been used and why? Wool was used in all bed textiles, both closest to the body and the layers over and under, from the cheapest chopped rags to the most costly textiles. The decline was seen throughout the 1800 and 1900s, but only in the 1960s does wool become totally absent as a next to skin bed textile. The cheap imports of cotton made cottage industry and home production unprofitable and the new emphasis on cleanliness gave cotton a clear leverage.     

Invertase immobilized on spacer‐arm attached poly(hydroxyethyl methacrylate) membrane: Preparation and properties

Microporous poly(2‐hydroxyethyl methacrylate) (pHEMA) membrane was prepared by UV‐initiated photopolymerization. The spacer arm (i.e., hexamethylene diamine) was attached covalently and then invertase was immobilized by the condensation reaction of the amino groups of the spacer arm with carboxyl groups of the enzyme in the presence of carbodiimides. The values of the Michael's constant K_m of invertase were significantly larger (ca. 2.5 times) upon immobilization, indicating decreased affinity by the enzyme for its substrate, whereas V_max was smaller for the immobilized invertase. Immobilization improved the pH stability of the enzyme as well as its temperature stability. Thermal stability was found to increase with immobilization and at 70°C the half times for the activity decay were 12 min for the free enzyme and 41 min for the immobilized enzyme. The immobilized enzyme activity was found to be quite stable in repeated experiments. © 2000 John Wiley & Sons, Inc. J Appl Polym Sci 75: 1685–1692, 2000     

Optimization of course locations in fiber-placed panels for general fiber angle distributions

Fiber-reinforced composites are usually designed using constant fiber orientation in each ply. In certain cases, however, a varying fiber angle might be favorable for structural performance. This possibility can be fully utilized using tow placement technology. Because of the fiber angle variation, tow-placed courses may overlap and ply thickness will build-up on the surface. This thickness buildup affects manufacturing time, structural response, and surface quality of the finished product.     

Tachykinins influence interdigestive rhythm and contractile strength of human small intestine

The effect of the putative enteric neurotransmitters neurokinin A and substance P were investigated on human small intestinal motility. Either neurokinin A, at doses of 6-25 pmol/kg/min, or substance P at doses of 1-6 pmol/kg/min were administered intravenously to healthy volunteers over 4 hr. Neurokinin A dose-dependently increased the fraction of phase II of the migrating motor complex, contraction frequency, motility index, and amplitude of contractions. At the highest dose, neurokinin A induced a phase II-like pattern, disrupting the migrating myoelectric complex. Substance P dose-dependently increased phase II of the migrating motor complex. The contraction frequency increased slightly at the highest dose, but neither motility index nor contraction amplitude changed. It is concluded that neurokinin A and substance P stimulate small intestinal motility in man, and it can be speculated that they play a role in the control of human small intestinal motility.     

Comparison of driving simulator performance with real driving after alcohol intake: A randomised,single blind,placebo-controlled,cross-over trial

The purpose of this study was to establish and validate a driving simulator method for assessing drug effects on driving. To achieve this, we used ethanol as a positive control, and examined whether ethanol affects driving performance in the simulator, and whether these effects are consistent with performance during real driving on a test track, also under the influence of ethanol. Twenty healthy male volunteers underwent a total of six driving trials of 1 h duration; three in an instrumented vehicle on a closed-circuit test track that closely resembled rural Norwegian road conditions, and three in the simulator with a driving scenario modelled after the test track. Test subjects were either sober or titrated to blood alcohol concentration (BAC) levels of 0.5 g/L and 0.9 g/L. The study was conducted in a randomised, cross-over, single-blind fashion, using placebo drinks and placebo pills as confounders. The primary outcome measure was standard deviation of lateral position (SDLP; “weaving”). Eighteen test subjects completed all six driving trials, and complete data were acquired from 18 subjects in the simulator and 10 subjects on the test track, respectively. There was a positive dose–response relationship between higher ethanol concentrations and increases in SDLP in both the simulator and on the test track (p < 0.001 for both). In the simulator, this dose–response was evident already after 15 min of driving. SDLP values were higher and showed a larger inter-individual variability in the simulator than on the test track. Most subjects displayed a similar relationship between BAC and SDLP in the simulator and on the test track; however, a few subjects showed striking dissimilarities, with very high SDLP values in the simulator. This may reflect the lack of perceived danger in the simulator, causing reckless driving in a few test subjects. Overall, the results suggest that SDLP in the driving simulator is a sensitive measure of ethanol impaired driving. The comparison with real driving implies relative external validity of the simulator.     

Derivative based approximation for predicting the effect of changes in laminate stacking sequence

Derivatives of buckling loads of stiffened panels with respect to ply thicknesses are easy to calculate. Consequently, such derivatives are often available in computer programs that calculate buckling loads of composite structures. These derivatives can be used to construct approximations of the dependence of the buckling load on ply thicknesses. The present work demonstrates the use of derivatives of buckling loads with respect to ply thicknesses to approximate the effects of changes in stacking sequence and ply orientations on buckling load of a laminate. Examples of unstiffened and stiffened panels are used to demonstrate the effectiveness of the proposed approximation.     

A FORTRAN 90 genetic algorithm module for composite laminate structure design

The design of the stacking sequence for a composite laminate involves a set of discrete variables (plymaterial and ply orientation), and is thus well-suited to genetic algorithms for design optimization. Such algorithms have typically been custom-designed in FORTRAN 77 to suit specific optimization problems. Fortran 90 is a modern, powerful language with features that support important programming concepts, including those used in object-oriented programming. The Fortran 90 genetic algorithm module is used to define genetic data types, the functions which use these data types, and to provide a general framework for solving composite laminate structure design problems. The language's support of abstract data types is used to build genetic structures such as populations, subpopulations, individuals, chromosomes, and genes, and these data types are combined and manipulated by module subroutines. The use of abstract data types and long variable names makes the code useful and easily understood, while dynamic memory allocation makes the module flexible enough to be used in design problems of varying size and specification.     

Analyzing the solutions of DEA through information visualization and data mining techniques: SmartDEA framework

Data envelopment analysis (DEA) has proven to be a useful tool for assessing efficiency or productivity of organizations, which is of vital practical importance in managerial decision making. DEA provides a significant amount of information from which analysts and managers derive insights and guidelines to promote their existing performances. Regarding to this fact, effective and methodologic analysis and interpretation of DEA results are very critical. The main objective of this study is then to develop a general decision support system (DSS) framework to analyze the results of basic DEA models. The paper formally shows how the results of DEA models should be structured so that these solutions can be examined and interpreted by analysts through information visualization and data mining techniques effectively. An innovative and convenient DEA solver, SmartDEA, is designed and developed in accordance with the proposed analysis framework. The developed software provides DEA results which are consistent with the framework and are ready-to-analyze with data mining tools, thanks to their specially designed table-based structures. The developed framework is tested and applied in a real world project for benchmarking the vendors of a leading Turkish automotive company. The results show the effectiveness and the efficacy of the proposed framework.     

Decentralized risk-sensitive controller design for strict-feedback systems

This paper studies decentralized control of uncertain systems. The class of systems focused on is a set of stochastic strict-feedback systems which interact through their outputs, and performance is measured with respect to a risk sensitive cost criterion. The unknown nonlinear interconnection terms are assumed to be bounded by some known functions of the outputs of the subsystems, multiplied by some unknown parameters. The controllers designed for each subsystem have access only to the information available with regard to the respective subsystem, and they achieve an arbitrarily small value for the risk-sensitive cost for the overall system. Under this completely decentralized control scheme, all closed-loop signals remain bounded in probability.     

Online calibrated forecasts: Memory efficiency versus universality for learning in games

We provide a simple learning process that enables an agent to forecast a sequence of outcomes. Our forecasting scheme, termed tracking forecast, is based on tracking the past observations while emphasizing recent outcomes. As opposed to other forecasting schemes, we sacrifice universality in favor of a significantly reduced memory requirements. We show that if the sequence of outcomes has certain properties—it has some internal (hidden) state that does not change too rapidly—then the tracking forecast is weakly calibrated so that the forecast appears to be correct most of the time. For binary outcomes, this result holds without any internal state assumptions. We consider learning in a repeated strategic game where each player attempts to compute some forecast of the opponent actions and play a best response to it. We show that if one of the players uses a tracking forecast, while the other player uses a standard learning algorithm (such as exponential regret matching or smooth fictitious play), then the player using the tracking forecast obtains the best response to the actual play of the other players. We further show that if both players use tracking forecast, then under certain conditions on the game matrix, convergence to a Nash equilibrium is possible with positive probability for a larger class of games than the class of games for which smooth fictitious play converges to a Nash equilibrium.