The effect of pre-warming on performance during simulated firefighting exercise

This study examined the effect of active pre-warming on speed and quality of performance during simulated firefighting exercise. Twelve male firefighters performed two trials in counterbalanced order. They were either pre-warmed by 20-min cycling at 1.5 Watt kg⁻¹ body mass (WARM) or remained thermoneutral (CON) prior to a simulated firefighting activity. After the pre-warming, gastrointestinal temperature (P < 0.001), skin temperature (P = 0.002), and heart rate (P < 0.001) were higher in WARM than in CON. During the firefighting activity, rating of perceived exertion, thermal sensation and discomfort were higher for WARM than for CON. Finish time of the firefighting activity was similar, but the last task of the activity was completed slower in WARM than in CON (P = 0.04). In WARM, self-reported performance quality was lower than in CON (P = 0.04). It is concluded that pre-warming reduces the speed during the last part of simulated firefighting activity and reduces self-reported quality of performance.     

Regressing Local to Global Shape Properties for Online Segmentation and Tracking

We propose a novel regression based framework that uses online learned shape information to reconstruct occluded object contours. Our key insight is to regress the global, coarse, properties of shape from its local properties, i.e. its details. We do this by representing shapes using their 2D discrete cosine transforms and by regressing low frequency from high frequency harmonics. We learn this regression model using Locally Weighted Projection Regression which expedites online, incremental learning. After sufficient observation of a set of unoccluded shapes, the learned model can detect occlusion and recover the full shapes from the occluded ones. We demonstrate the ideas using a level-set based tracking system that provides shape and pose, however, the framework could be embedded in any segmentation-based tracking system. Our experiments demonstrate the efficacy of the method on a variety of objects using both real data and artificial data.     

Laser Specular Reflectance and the Optical rms Roughness of Alumina

Using laser specular reflectance, the optical rms roughnesses (σ₀'S) of 42 polycrystalline aluminas (PCA's) were determined. From these conventional experimental results, a nomogram was constructed so that single grazing angle (α) measurements could be used to predict σ₀. Subsequently, the nomogram was reassessed using five commercially important PCA's and one single-crystal sapphire (SC). The outcomes were twofold: that this nomogram was valid for PCA's over the range of 0.28 σ₀ 0.10 μm, but that the nomogram was invalid for SC sapphire. When the conventional experimental method was compared with the nomogram method at three different single-angle values, a 1:1 correspondence was observed for α= 78°, 80°, and 82°. The present noncontact method is advocated for speed and cleanliness, particularly when a quality assurance method is desired.     

Morphology and properties of poly(vinyl chloride)–polyurethane blends

The objective of this research was to study the morphology and properties of PVC–polyurethane blends. Studies on blends of a segmented polyether polyurethane with PVC were carried out utilizing differential scanning calorimetry, Rheovibron, stress–strain, infrared peak position studies, and infrared dichroism experiments. This thermodynamically incompatible system was made kinetically compatible by precipitation from tetrahydrofuran (THF) solutions. THF–dioxane solution casting and melt processing produced an incompatible system. The compatible polyurethane–PVC system contains a well-mixed PVC–polyether matrix phase as evidenced by T_g shifts, orientation characteristics, and infrared peak position changes. The aromatic urethane segments which exhibit microphase separation in the pure polyurethane are not solubilized by blending with PVC by any of sample preparation methods used in this study.     

Preliminary report on the nutritional significance of bound gossypol in cottonseed meal

Summary A procedure is described by which bound or inactivated gossypol can be removed from cottonseed meal without the application of heat which might damage the protein. The removal of bound gossypol increased the nutritional value of the protein as determined by chick feeding tests, rat protein-repletion tests, and lysine availability tests. A procedure is described for the preparation of a gossypol-cottonseed protein complex without heating the materials. As a result of the combination of the protein with gossypol, marked reduction in nutritional value occurred. The nitrogen solubility of the complex was only about half that of the original protein. The results are in accord with the concept that the inactivation of gossypol during the processing of cottonseed meal is accomplished through the formation of an insoluble, inert gossypol-protein complex which results not only in rendering the gossypol harmless but also in the loss of part of the nutritional value of the protein.     

METIS-II: low resource machine translation

METIS-II was an EU-FET MT project running from October 2004 to September 2007, which aimed at translating free text input without resorting to parallel corpora. The idea was to use “basic” linguistic tools and representations and to link them with patterns and statistics from the monolingual target-language corpus. The METIS-II project has four partners, translating from their “home” languages Greek, Dutch, German, and Spanish into English. The paper outlines the basic ideas of the project, their implementation, the resources used, and the results obtained. It also gives examples of how METIS-II has continued beyond its lifetime and the original scope of the project. On the basis of the results and experiences obtained, we believe that the approach is promising and offers the potential for development in various directions.     

Modelling and condition-based control of a flexible and hybrid disassembly system with manual and autonomous workstations using reinforcement learning

Journal of Intelligent Manufacturing - Remanufacturing includes disassembly and reassembly of used products to save natural resources and reduce emissions. While assembly is widely understood in...     

Coupling and comparing a spatially- and temporally-detailed eutrophication model with an ecosystem network model: An initial application to Chesapeake Bay

Coastal waters are modeled for a variety of purposes including eutrophication remediation and fisheries management. Combining these two approaches provides insights which are not available from either approach independently. Coupling is confounded, however, by differences in model formulations and “currencies.” We present here an initial coupling of a spatially- and temporally-detailed eutrophication model, CE-QUAL-ICM, with a network fisheries model, Ecopath. We list commonalities between the models and present algorithms and software for the exchange of information. The models are applied to the central portion of Chesapeake Bay for a contemporary summer period. After comparison of the representations of Chesapeake Bay by the two models, an illustrative example one-way, off-line, coupling is presented. In an initial examination of a 20% increase in predation on phytoplankton by a small, highly-exploited fish (Atlantic menhaden, Brevoortia tyrannus), computed reduction in phytoplankton biomass is accompanied by increased production due to enhanced nutrient recycling. Minimal impact on the structure of the food web or on biomass of higher-trophic level organisms is computed. The algorithms and software can be adapted to alternate eutrophication models and Ecopath applications and provide the first, necessary, steps for subsequent coupling with the time-variable Ecosim model.     

Branch-and-Bound Methods for Euclidean Registration Problems

In this paper, we propose a practical and efficient method for finding the globally optimal solution to the problem of determining the pose of an object. We present a framework that allows us to use point-to-point, point-to-line, and point-to-plane correspondences for solving various types of pose and registration problems involving euclidean (or similarity) transformations. Traditional methods such as the iterative closest point algorithm or bundle adjustment methods for camera pose may get trapped in local minima due to the nonconvexity of the corresponding optimization problem. Our approach of solving the mathematical optimization problems guarantees global optimality. The optimization scheme is based on ideas from global optimization theory, in particular convex underestimators in combination with branch-and-bound methods. We provide a provably optimal algorithm and demonstrate good performance on both synthetic and real data. We also give examples of where traditional methods fail due to the local minima problem.