A photoelastic substrate technique for dynamic measurements of forces exerted by moving organisms

The forces produced by small moving organisms have been quantitatively measured by having the organisms move on a polymeric substrate which transduces the applied stress into an optical birefringence signal (photoelastic effect). The optical signal can be rigorously interpreted to give static force measurements, and by calibrating the substrate empirically, dynamic measurements are obtained. The technique measures stresses, forces applied to an area, so it is not possible to determine ultimate sensitivity of the technique for measurements of forces without regard to area. The technique is especially useful when small forces are exerted over very small areas as, for example, may be the situation with moving tissue cells. The technique is noninvasive, requires minimal equipment, and is easily performed on microscopes adapted for polarized light measurements. Gelatin has the highest sensitivity and adaptability as a photoelastic substrate.     

A computer algorithm for accurate and repeatable profile analysis using anodization and stripping of silicon

The increased need for accurate and repeatable impurity profiling of shallow junction devices places stringent requirements on the profiling procedures and subsequent data reduction. A computer algorithm is described which simplifies the conversion of sheet resistance to impurity profile as required by the anodization and stripping technique. Error magnification commonly found in discrete data differentiation is avoided. Empirical mobility vs carrier concentration expressions are derived from several sources, and a self-contained computer algorithm is given which allows for data reduction on commonly available minicomputers using Fortran. The experimenter is provided with a check on the accuracy of the profile information.     

Processing of thermotropic liquid crystalline polymers and their blends—analysis of melt-spinning TLCP fibers

Isothermal melt-spinning of two thermotropic liquid crystalline polymers (TLCPs), a wholly aromatic copolyester KU-9211 (also named K161 from Bayer AG) and an aliphatic containing TLCP, PET/PHB60 (Tennessee Eastman), was studied to analyze the effect of processing conditions on fiber properties. Fibers were melt-spun from a capillary rheometer equipped with an isothermal chamber in which cross-flowed air was used as the cooling medium. The processing variables studied included the extrusion temperature, the extrusion rate, the cooling conditions, and the draw ratio. As-spun fibers were characterized by measuring storage moduli and molecular orientation parameters as a function of draw ratio under various processing conditions. Among the processing variables studied, the draw ratio was the primary factor in determining both the fiber modulus and the molecular orientation. The extrusion rate did not appear to affect the fiber properties within the range studied. The properties of K161 fibers were also dependent on the extrusion and cooling temperatures, while PET/PHB60 fibers were rather insensitive to the processing temperatures within data scatter and temperatures studied. A composite model based on a rigid-rod rotation mechanism and the deformation of nematic domains in an elongational flow field was used to model the experimental results and was compared with other theories available. Conformance of data to the composite model was obtained by use of a single temperature dependent parameter n, suggesting that the rigid-rod rotation mechanism could be used to predict the orientation development of TLCPs. The Halpin-Tsai equations and the orthotropic equation for angular dependence were used to describe the elastic properties of the TLCP fibers.     

Renovation and Innovation: It’s Time for the Great Lakes Regime to Respond

This commentary reports on a project to explore and evaluate options for Great Lakes governance renewal in anticipation of the 2006–2007 review of the Canada–US Great Lakes Water Quality Agreement (GLWQA). The research included expert interviews and scholarly analysis of governance regimes in 2006, leading to a Great Lakes St. Lawrence River Governance Expert Workshop held in June 2007 (Krantzberg et al. 2007). The two authors have been participants and at times leaders in the institutions this commentary addresses, Krantzberg with the International Joint Commission and Ontario Ministry of the Environment and Manno with the New York Great Lakes Research Consortium and Great Lakes United. Our familiarity with the topic and many of the people involved was helpful in gaining participation and is in itself a rich source of knowledge and experience. In discussing a topic of contemporary controversy, it also understandably can make readers question the objectivity of our assessment. We are also trained in social science scholarship and have taken precautions against biasing the outcomes. This is not intended to be merely a presentation of data. We believe our experience is a net asset in addressing these questions but we leave it to the interested reader to review the reports referenced herein and judge for themselves whether our findings are fairly presented.     

Algorithm for Increasing the Speed of Evolutionary Optimization and its Accuracy in Multi-objective Problems

Optimization algorithms are important tools for the solution of combinatorial management problems. Nowadays, many of those problems are addressed by using evolutionary algorithms (EAs) that move toward a near-optimal solution by repetitive simulations. Sometimes, such extensive simulations are not possible or are costly and time-consuming. Thus, in this study a method based on artificial neural networks (ANN) is proposed to reduce the number of simulations required in EAs. Specifically, an ANN simulator is used to reduce the number of simulations by the main simulator. The ANN is trained and updated only for required areas in the decision space. Performance of the proposed method is examined by integrating it with the non-dominated sorting genetic algorithm (NSGAII) in multi-objective problems. In terms of density and optimality of the Pareto front, the hybrid NSGAII-ANN is able to extract the Pareto front with much less simulation time compared to the sole use of the NSGAII algorithm. The proposed NSGAII-ANN methodology was examined using three standard test problems (FON, KUR, and ZDT1) and one real-world problem. The latter addresses the operation of a reservoir with two objectives (meeting demand and flood control). Thus, based on this study, use of the NSGAII-ANN integrative algorithm in problems with time-consuming simulators reduces the required time for optimization up to 50 times. Results of the real-world problem, despite lower computational-time requirements, show a performance similar to that achieved in the aforementioned test problems.     

Discussion of “Assessments of Impacts of Climate Change and Human Activities on Runoff with SWAT for the Huifa River Basin, Northeast China” by Aijing Zhang; Chi Zhang; Guobin Fu; Bende Wang; Zhenxin Bao; and Hongxing Zheng

Zhang et al. (Water Resour Manag doi:10.1007/s11269-012-0182-2, 2012) studied the impacts of climate change and human activities on the runoff for the Huifa River basin. They employed a soil and water assessment tool (SWAT), which was calibrated for the baseline period 1956–1964, and then used to reconstruct the natural runoff for the climate change period 1965–2000. Results showed that both climate change and human activities decrease the observed runoff. Climate change impacts on annual runoff were ?37.7, ?59.5, +36.9, and ?45.2 mm/a for 1965–1975, 1976–1985, 1986–1995, and 1996–2005 respectively, compared with the baseline period 1956–1964. Human activities decreased runoff and caused a relatively larger magnitude impact than those of climate change after 1985. Human activities decreased the annual runoff by ?32.9, ?46.8, ?67.8, and ?54.9 mm/a for 1965–1975, 1976–1985, 1986–1995, and 1996–2005 respectively. Human activities further decreased runoff in wet years due to regulation and storage of water projects.     

On the psychology of eyewitness testimony.

Investigated various aspects of eyewitness testimony in a simulated courtroom setting. 80 undergraduates were shown a filmed murder and then testified about their observations in one of several experimental conditions. Testimony was rated for accuracy and quantity. Significant main effects were found for sex of witness, immediacy of testimony (immediately or after a 1-wk delay), testimony structure (unstructured free recall or response to questions), question type (open-ended, leading, and multiple choice), and question bias (positive, negative, and neutral). Results also support a predicted cognitive-set hypothesis, relating accuracy and quantity of testimony to the specificity of the questioning situation. The strong findings attest to the efficacy of empirically investigating aspects of courtroom procedures as a viable research paradigm. (27 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Honey-Bees Mating Optimization (HBMO) Algorithm: A New Heuristic Approach for Water Resources Optimization

Over the last decade, evolutionary and meta-heuristic algorithms have been extensively used as search and optimization tools in various problem domains, including science, commerce, and engineering. Their broad applicability, ease of use, and global perspective may be considered as the primary reason for their success. The honey-bees mating process may also be considered as a typical swarm-based approach to optimization, in which the search algorithm is inspired by the process of real honey-bees mating. In this paper, the honey-bees mating optimization algorithm (HBMO) is presented and tested with few benchmark examples consisting of highly non-linear constrained and/or unconstrained real-valued mathematical models. The performance of the algorithm is quite comparable with the results of the well-developed genetic algorithm. The HBMO algorithm is also applied to the operation of a single reservoir with 60 periods with the objective of minimizing the total square deviation from target demands. Results obtained are promising and compare well with the results of other well-known heuristic approaches.