The flavin-containing monooxygenase 2 gene (FMO2) of humans, but not of other primates, encodes a truncated, nonfunctional protein

Flavin-containing monooxygenases (FMOs) are NADPH-dependent flavoenzymes that catalyze the oxidation of heteroatom centers in numerous drugs and xenobiotics. FMO2, or "pulmonary" FMO, one of five forms of the enzyme identified in mammals, is expressed predominantly in lung and differs from other FMOs in that it can catalyze the N-oxidation of certain primary alkylamines. We describe here the isolation and characterization of cDNAs for human FMO2. Analysis of the sequence of the cDNAs and of a section of the corresponding gene revealed that the major FMO2 allele of humans encodes a polypeptide that, compared with the orthologous protein of other mammals, lacks 64 amino acid residues from its C terminus. Heterologous expression of the cDNA revealed that the truncated polypeptide was catalytically inactive. The nonsense mutation that gave rise to the truncated polypeptide, a C --> T transition in codon 472, is not present in the FMO2 gene of closely related primates, including gorilla and chimpanzee, and must therefore have arisen in the human lineage after the divergence of the Homo and Pan clades. Possible mechanisms for the fixation of the mutation in the human population and the potential significance of the loss of functional FMO2 in humans are discussed.     

Stature and seat position as factors affecting fractionated response time in motor vehicle drivers

Motor vehicle accident fatalities are a cause for concern internationally; all drivers need to selectively attend to environmental changes, and to react swiftly and appropriately. The focus of the present paper was to investigate the effect of stature and seat positioning on fractionated response time. Eighty four young South African adults spanning a range of statures from 1.48 m to 2.00 m were tested in two extreme seat positions (near and far) using a European designed car-shell. Significant differences (p < 0.05) in knee flexion angle, but not in reaction or movement times were identified. Separation of tallest (X 1.93 m) and shortest (X 1.56 m) subjects (n = 20) revealed no significant stature-related differences in response times. However, the tall group showed significantly improved results when seated in the far position and the short group when seated in the near position. The results indicate that correct seat positioning will exert a significant effect on the overall response time of the driver, which in turn will affect the braking distance whilst driving.     

PAC Learning of One-Dimensional Patterns

Developing the ability to recognize a landmark from a visual image of a robot's current location is a fundamental problem in robotics. We consider the problem of PAC-learning the concept class of geometric patterns where the target geometric pattern is a configuration ofk points on the real line. Each instance is a configuration ofn points on the real line, where it is labeled according to whether or not it visually resembles the target pattern. To capture the notion of visual resemblance we use the Hausdorff metric. Informally, two geometric patternsP andQ resemble each other under the Hausdorff metric if every point on one pattern is close to some point on the other pattern. We relate the concept class of geometric patterns to the landmark matching problem and then present a polynomial-time algorithm that PAC-learns the class of one-dimensional geometric patterns. We also present some experimental results on how our algorithm performs.     

Natural perspective projections for head-mounted displays

The display units integrated in today's head-mounted displays (HMDs) provide only a limited field of view (FOV) to the virtual world. In order to present an undistorted view to the virtual environment (VE), the perspective projection used to render the VE has to be adjusted to the limitations caused by the HMD characteristics. In particular, the geometric field of view (GFOV), which defines the virtual aperture angle used for rendering of the 3D scene, is set up according to the display field of view (DFOV). A discrepancy between these two fields of view distorts the geometry of the VE in a way that either minifies or magnifies the imagery displayed to the user. It has been shown that this distortion has the potential to affect a user's perception of the virtual space, sense of presence, and performance on visual search tasks. In this paper, we analyze the user's perception of a VE displayed in a HMD, which is rendered with different GFOVs. We introduce a psychophysical calibration method to determine the HMD's actual field of view, which may vary from the nominal values specified by the manufacturer. Furthermore, we conducted two experiments to identify perspective projections for HMDs, which are identified as natural by subjects--even if these perspectives deviate from the perspectives that are inherently defined by the DFOV. In the first experiment, subjects had to adjust the GFOV for a rendered virtual laboratory such that their perception of the virtual replica matched the perception of the real laboratory, which they saw before the virtual one. In the second experiment, we displayed the same virtual laboratory, but restricted the viewing condition in the real world to simulate the limited viewing condition in a HMD environment. We found that subjects evaluate a GFOV as natural when it is larger than the actual DFOV of the HMD--in some cases up to 50 percent--even when subjects viewed the real space with a limited field of view.     

A survey of problems,solution techniques,and future challenges in scheduling semiconductor manufacturing operations

In this paper, we discuss scheduling problems in semiconductor manufacturing. Starting from describing the manufacturing process, we identify typical scheduling problems found in semiconductor manufacturing systems. We describe batch scheduling problems, parallel machine scheduling problems, job shop scheduling problems, scheduling problems with auxiliary resources, multiple orders per job scheduling problems, and scheduling problems related to cluster tools. We also present important solution techniques that are used to solve these scheduling problems by means of specific examples, and report on known implementations. Finally, we summarize some of the challenges in scheduling semiconductor manufacturing operations.     

Recognition is not parsing — SPPF-style parsing from cubic recognisers

In their recogniser forms, the Earley and RIGLR algorithms for testing whether a string can be derived from a grammar are worst-case cubic on general context free grammars (CFG). Earley gave an outline of a method for turning his recognisers into parsers, but it turns out that this method is incorrect. Tomita’s GLR parser returns a shared packed parse forest (SPPF) representation of all derivations of a given string from a given CFG but is worst-case unbounded polynomial order. The parser version of the RIGLR algorithm constructs Tomita-style SPPFs and thus is also worst-case unbounded polynomial order. We have given a modified worst-case cubic GLR algorithm, that, for any string and any CFG, returns a binarised SPPF representation of all possible derivations of a given string. In this paper we apply similar techniques to develop worst-case cubic Earley and RIGLR parsing algorithms.     

Uncertainty propagation in puff-based dispersion models using polynomial chaos

Atmospheric dispersion is a complex nonlinear physical process with numerous uncertainties in model parameters, inputs, source parameters, initial and boundary conditions. Accurate propagation of these uncertainties through the dispersion models is crucial for a reliable prediction of the probability distribution of the states and assessment of risk. A simple three-dimensional Gaussian puff-based dispersion model is used as a test case to study the effect of uncertainties in the model parameters and initial conditions on the output concentration. A polynomial chaos based approach is used to numerically investigate the evolution of the model output uncertainties due to initial condition and parametric uncertainties. The polynomial chaos solution is found to be an accurate approximation to ground truth, established by Monte Carlo simulation, while offering an efficient computational approach for large nonlinear systems with a relatively small number of uncertainties.     

Self-assembly of discrete self-similar fractals

In this paper, we search for theoretical limitations of the Tile Assembly Model (TAM), along with techniques to work around such limitations. Specifically, we investigate the self-assembly of fractal shapes in the TAM. We prove that no self-similar fractal weakly self-assembles at temperature 1 in a locally deterministic tile assembly system, and that certain kinds of discrete self-similar fractals do not strictly self-assemble at any temperature. Additionally, we extend the fiber construction of Lathrop et al. (2009) to show that any discrete self-similar fractal belonging to a particular class of “nice” discrete self-similar fractals has a fibered version that strictly self-assembles in the TAM.     

Elements that Influence the Implementation of Crisis Preparedness Measures by Meeting Planners

The purpose of this study was to analyse the adoption of crisis preparedness measures by meeting planners. The study sought to determine how the adoption of crisis preparedness measures relates to meeting planner characteristics and identify the elements that influence their adoption (or lack of adoption) of these measures. A survey of professional meeting planners identified significant differences in the frequency of use of some key core crisis preparedness measures. Additionally, 10 categories of elements influencing the adoption of or failure to adopt crisis preparedness measures were identified. The findings of this study should be of interest to meeting organizers and professionals who want to make their meetings more crisis prepared rather than crisis prone.