Virulence of Aspergillus fumigatus double mutants lacking restriction and an alkaline protease in a low-dose model of invasive pulmonary aspergillosis

To investigate the pathogenicity of Aspergillus fumigatus mutants lacking putative virulence factors, we have developed a new murine model of invasive pulmonary aspergillosis based on neutropenia, the major factor predisposing patients to this infection. Mice were treated with cyclophosphamide and inoculated by the intranasal route with 5 x 10(3) conidia, a significant reduction from inoculum levels used in previous models. Evidence for the production of the extracellular alkaline protease (Alp) in lung tissue was obtained by using a fungal transformant harboring an alp::lacZ reporter gene fusion. The pathogenicities of single mutant strains lacking either Alp or the ribotoxin restrictocin and of a double mutant strain lacking both proteins were assessed in this infection model. There were no significant differences between the mutant and the wild-type strains in terms of mortality or histological-features. Inoculations with mixtures of conidia showed that the double mutant strain is slightly less virulent than the wild-type strain. We conclude that Alp and restrictocin are not important virulence determinants in pulmonary infection.     

Development of an indoor rowing machine with manual FES controller for total body exercise in paraplegia

Concept 2 indoor rowing machine (Concept 2 Inc., USA) was modified for functional electrical stimulation (FES) rowing exercise in paraplegia. A new seating system provides trunk stability and constrains the leg motion to the sagittal plane. A 4-channel electrical stimulator activates the quadriceps and hamstrings in Drive and Recovery phases of the rowing cycle, respectively. Two force-sensing resistors (FSR) on the handle measure the thumb press as the command signal to the electrical stimulator. Optical encoders measure the positions of the seat and handle during rowing. To synchronize the voluntarily controlled upper body movement with the FES controlled leg movement, a novel manual control system was developed. It uses the voluntary thumb presses to control the timing of the stimulation to the paralyzed leg muscles. The manual control system was intuitive and easy to learn and resulted in well-coordinated rowing. Evaluation of the modified rower by paraplegic volunteers showed that it is effective, safe, and affordable exercise alternative for paraplegics.     

Model-based testing of a real-time adaptive motion planning system

Abstract

To enable effective and safe operations of autonomous robots in environments with unknowns and unpredictability, a key practical problem is how to test the functionality and assess the performance of real-time motion planning systems. This is a challenge because the underlying algorithms are real-time, sensing-based, and often non-deterministic. These systems’ performance depends on task environments, which can vary in countless ways. Existing testing techniques are designed heavily based on testers’ experience and hardly provide a good coverage of possible test scenarios. This paper introduces a systematic model-based testing (MBT) approach to evaluate the functionality and performance of a real-time adaptive motion planning (RAMP) system. The MBT approach uses the formal communicating extended finite state machine model to model RAMP’s concurrent components and leverage graph traversal algorithms to systematically generate behavioral test cases. First, component integration is considered by modeling the RAMP components and their interactions. Next, system-level testing is considered by modeling mobile obstacles of unpredictable motion behavior. The behavior models are leveraged to generate Abstract Behavioral Test Cases, which are transformed by test data into executable test cases. The test results demonstrate the effectiveness of applying the systematic MBT approach to the evaluation of real-time robotic systems.     

Unpredication, unscheduling, unspeculation: reverse engineering Itanium executables

EPIC (explicitly parallel instruction computing) architectures, exemplified by the Intel Itanium, support a number of advanced architectural features, such as explicit instruction-level parallelism, instruction predication, and speculative loads from memory. However, compiler optimizations that take advantage of these features can profoundly restructure the program's code, making it potentially difficult to reconstruct the original program logic from an optimized Itanium executable. This paper describes techniques to undo some of the effects of such optimizations and thereby improve the quality of reverse engineering such executables.     

Parallel Algorithms for Maximum Matching in Complements of Interval Graphs and Related Problems

Given a set of n intervals representing an interval graph, the problem of finding a maximum matching between pairs of disjoint (nonintersecting) intervals has been considered in the sequential model. In this paper we present parallel algorithms for computing maximum cardinality matchings among pairs of disjoint intervals in interval graphs in the EREW PRAM and hypercube models. For the general case of the problem, our algorithms compute a maximum matching in O( log ³ n) time using O(n/ log ² n) processors on the EREW PRAM and using n processors on the hypercubes. For the case of proper interval graphs, our algorithm runs in O( log n ) time using O(n) processors if the input intervals are not given already sorted and using O(n/ log n ) processors otherwise, on the EREW PRAM. On n -processor hypercubes, our algorithm for the proper interval case takes O( log n log log n ) time for unsorted input and O( log n ) time for sorted input. Our parallel results also lead to optimal sequential algorithms for computing maximum matchings among disjoint intervals. In addition, we present an improved parallel algorithm for maximum matching between overlapping intervals in proper interval graphs. Received November 20, 1995; revised September 3, 1998.     

Eliciting information about organizational culture via laddering

Abstract. Eliciting information about organizational culture is an important part of system analysis and design. However, eliciting knowledge of this sort is difficult. Laddering is an established technique that is particularly suitable for eliciting information about goals and for eliciting explanations, which are important issues when investigating organizational culture. This paper describes the method, its strengths and limitations, its use in several case studies and its relation to other elicitation techniques. Recommendations for further work are given.     

The identification of peaks in physiological signals.

The identification of peaks is fundamental in the processing of physiological signals. For example, it is common to the analysis of electrocardiograms, electroencephalograms, sympathetic neuronal activity, pulse oximetry, respiratory movement, hormone pulse secretion, and even chromatography. Often it is necessary to detect peaks in real time, but the task is frequently complicated by baseline wander and other interference. Current approaches to the problem tend to be complicated, specific to a particular domain, and reliant on several tunable parameters. There is a need for a simple and general mathematical formalization of peaks and troughs that has easily examinable properties and is readily implementable as an efficient algorithm. In this paper we present such a mathematical model together with an algorithm for the detection of peaks and troughs. We illustrate the generality of the method with some actual physiological data.     

Measurement-based modeling of contact forces and textures for haptic rendering

Haptic texture represents the fine-grained attributes of an object's surface and is related to physical characteristics such as roughness and stiffness. We introduce an interactive and mobile scanning system for the acquisition and synthesis of haptic textures that consists of a visually tracked handheld touch probe. The most novel aspect of our work is an estimation method for the contact stiffness of an object based solely on the acceleration and forces measured during stroking of its surface with the handheld probe. We establish an experimental relationship between the estimated stiffness and the contact stiffness observed during compression. We also measure the height-displacement profile of an object's surface enabling us to generate haptic textures. We show an example of mapping the textures on to a coarse surface mesh obtained with an image-based technique, but the textures may also be combined with coarse surface meshes obtained by manual modeling.