438 research outputs found

    Moving into higher dimensions of geometric constraint solving

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    Journal ArticleIn this paper, we present an approach to geometric constraint solving, based on degree of freedom analysis. Any geometric primitive (point, line, circle, plane, etc.) possesses an intrinsic degree of freedom in its embedding space which is usually two or three dimensional. Constraints reduce the degrees of freedom of an object (or a set of objects). We use graph algorithms to determine upper and lower bounds for the degrees of freedom of a set of constrained objects, symbolically. This analysis is then used to establish dependency graphs and evaluation schemes for symbolic or numeric solutions to constraint problems. The approach has been generalized for n-dimensional space, which, among other things, allows for a uniform handling of 2-D and 3-D constraint problems or algebraic constraints between scalar dimension. Also, higher than three dimensional solutions can be interpreted as approaches to over- and under- constrained problems. In this paper, we will present the theoretical background of the approach, and demonstrate how it can be applied within an interactive design environment

    An interactive N-Dimensional constraint system

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    Journal ArticleIn this paper, we present a graph-based approach to geometric constraint solving. Geometric primitives (points, lines, circles, planes, etc.) possess intrinsic degrees of freedom in their embedding space. Constraints reduce the degrees of freedom of a set of objects. A constraint graph is created with objects as the nodes, and the constraints as the arcs. A graph algorithm transforms the undirected constraint graph into a directed acyclic dependency graph which can be directly used to derive a sequence of construction operations as a symbolic solution to the constraint problem. The approach has been generalized to an n-dimensional space, which, among other things, allows for a uniform handling of 2-D and 3-D constraint problems or algebraic constraints between scalar dimension. Solutions of arbitrary dimensions can be interpreted as approaches to over- and under- constrained problems. In this paper, we present the theoretical background of the approach, and report the results of it's application within an interactive modeling system

    A new approach to tolerance analysis

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    Journal ArticleTolerance analysis is seen as part of a more general problem, namely handling data with uncertainty. Uncertain geometric data arises when interpreting measured data, but also in solid modeling where floating point approximations are common, when representing design tolerances, or when dealing with limited manufacturing precision. The common question is whether parts with uncertain shape fulfill certain functional specification. The question is expressed as geometrical relationship between toleranced objects. Unfortunately, tolerance based relations are often inconsistent, unlike relations between exactly represented objects. In this paper we survey current tolerance representation and analysis methods. We then derive our method of intuitionistic tolerance handling from a method developed for robust solid modeling. A new representational framework is proposed, which serves as the basis for robust geometric modeling and tolerance analysis. We illustrate the framework with examples of assembly design

    Impact of Heavy Metals in Ambient Air in Insulin Resistance of Shipyard Welders in Northern Taiwan

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    Exposure to metals poses potential health risks, including insulin resistance (IR), to those exposed to them in excess. Limited studies have examined such risks in occupational workers, including welders, and these have yielded inconsistent results. Thus, we examined the associations between exposure to welding metals and IR in welders. We recruited 78 welders and 75 administrative staff from a shipyard located in northern Taiwan. Personal exposure to heavy metals, including chromium (Cr), manganese (Mn), iron (Fe), nickel (Ni), copper (Cu), zinc (Zn), and cadmium (Cd), was monitored through particulate matter with an aerodynamic diameter of less than 2.5 Ī¼m (PM2.5) and urine analysis by inductively coupled plasma mass spectrometry (ICPā€“MS). After each participant fasted overnight, blood samples were collected and analyzed for IR assessment through updated homeostasis model assessment (HOMA2) modeling. Air sampling in the personal breathing zone was performed during a Monday shift prior to the blood and urine sample collection the following morning. The weldersā€™ median personal Cr, Mn, Fe, Ni, Cu, and Zn airborne PM2.5 levels and urinary Cd levels were significantly higher than those of the administrative staff. After adjustment for covariates, logarithmic PM2.5-Mn, PM2.5-Fe, PM2.5-Cu, and PM2.5-Zn levels were positively correlated with logarithmic fasting plasma glucose (P-FGAC) levels (PM2.5-Mn: Ī² = 0.0105, 95% C.I.: 0.0027ā€“0.0183; PM2.5-Fe: Ī² = 0.0127, 95% C.I.: 0.0027ā€“0.0227; PM2.5-Cu: Ī² = 0.0193, 95% C.I.: 0.0032ā€“0.0355; PM2.5-Zn: Ī² = 0.0132, 95% C.I.: 0.0005ā€“0.0260). Logarithmic urinary Zn was positively correlated with logarithmic serum insulin and HOMA2-IR levels and negatively correlated with logarithmic HOMA2-insulin sensitivity (%S; Ī²insulin = 0.2171, 95% C.I.: 0.0025ā€“0.4318; Ī²IR = 0.2179, 95% C.I.: 0.0027ā€“0.4330; Ī²%S = āˆ’0.2180, 95% C.I.: āˆ’0.4334 to āˆ’0.0026). We observed that glucose homeostasis was disrupted by Mn, Fe, Cu, and Zn exposure through increasing P-FGAC and IR levels in shipyard welders

    Outcome of lung cancer patients with acute respiratory failure requiring mechanical ventilation

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    AbstractTo assess the weaning outcome of lung cancer patients with acute respiratory failure (ARF) requiring mechanical ventilation, we retrospectively analyzed the database of the respiratory intensive care unit at a university-affiliated tertiary care hospital.Charts were reviewed for cancer status, biochemistries before respiratory failure, causes of respiratory failure, acute physiology and chronic health evaluation (APACHE) III score, ventilatory settings, data recorded during spontaneous breathing, duration of ventilator days, and weaning outcome. Ninety-five consecutive respiratory failure events in 81 patients were recorded from January 1, 1995 through June 30, 1999.Twenty-six episodes ended with successful weaning (27.4%). Age, gender, and cancer status did not affect the weaning outcome. Serum albumin level, APACHE III score, highest fractional inspired O2 (FiO2) and highest positive end-expiratory pressure, organ failure, ability to shift to partial ventilatory support, and duration of mechanical ventilation could significantly influence the weaning outcome statistically. The overall hospital mortality rate was 85.2%.Our results suggested that lung cancer patients with ARF will have a better chance to wean if the initial APACHE III score was less than 70, use of FiO2 never exceeded 0.6, or less than 2 additional organ systems failed during the treatment course
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