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PubMed1993

Extending the critical gerontology perspective: cultural dimensions. Introduction.

This introduction outlines how the emerging framework of critical gerontology (CG) may be enhanced by greater emphasis on understanding the cultural influences on research and practice in gerontology. CG pursues empirical insights into the historical and cultural forces shaping the sense of the problem for study, that is, the formulation of topics and ways of defining issues. Illustrations are drawn from a recent GSA symposium. The articles following this introduction document, in relation to two key constructs, the need to understand how cultural-historical contexts complexly inform the focus of core topics of attention, how these are operationalized for research and policy, and their role in shaping the course of American gerontology.

Aged↗
PubMed2006

Predicting gene expression level from codon usage bias.

The "expression measure" of a gene, E(g), is a statistic devised to predict the level of gene expression from codon usage bias. E(g) has been used extensively to analyze prokaryotic genome sequences. We discuss 2 problems with this approach. First, the formulation of E(g) is such that genes with the strongest selected codon usage bias are not likely to have the highest predicted expression levels; indeed the correlation between E(g) and expression level is weak among moderate to highly expressed genes. Second, in some species, highly expressed genes do not have unusual codon usage, and so codon usage cannot be used to predict expression levels. We outline a simple approach, first to check whether a genome shows evidence of selected codon usage bias and then to assess the strength of bias in genes as a guide to their likely expression level; we illustrate this with an analysis of Shewanella oneidensis.

Codon↗
PubMedDate not supplied

Liver transplantation: key nursing diagnoses.

The last decade has seen the growth of liver transplantation as a recognized treatment modality for forms of end-stage hepatic disease. This innovative advancement in health care has challenged the critical care nurse to formulate nursing diagnoses to recognize actual problems, prevent potential problems, and manage this complex patient.

Humans↗
PubMed1996

A dynamic model for evaluating radionuclide distribution in forests from nuclear accidents.

The Chernobyl Nuclear Power Plant accident in 1986 caused radionuclide contamination in most countries in Eastern and Western Europe. A prime example is Belarus where 23% of the total land area received chronic levels; about 1.5 x 10(6) ha of forested lands were contaminated with 40--190 kBq m-2 and 2.5 x 10(4) ha received greater than 1,480 kBq m-2 of 137Cs and other long-lived radionuclides such as 90Sr and 239,240Pu. Since the radiological dose to the forest ecosystem will tend to accumulate over long time periods (decades to centuries), we need to determine what countermeasures can be taken to limit this dose so that the affected regions can, once again, safely provide habitat and natural forest products. To address some of these problems, our initial objective is to formulate a generic model, FORESTPATH, which describes the major kinetic processes and pathways of radionuclide movement in forests and natural ecosystems and which can be used to predict future radionuclide concentrations. The model calculates the time-dependent radionuclide concentrations in different compartments of the forest ecosystem based on the information available on residence half-times in two forest types: coniferous and deciduous. The results show that the model reproduces well the radionuclide cycling pattern found in the literature for deciduous and coniferous forests. Variability analysis was used to access the relative importance of specific parameter values in the generic model performance. The FORESTPASTH model can be easily adjusted for site-specific applications.

Biological Transport, Active↗
PubMed1982

The research question.

When the seeds of a research idea begin to germinate, researchers use a systematic and rational process to develop the idea into a refined research question and then determine the appropriate study design. Knowledge of the characteristics of a good research question helps researchers formulate a valid statement of the problem under study and then narrow it to a researchable question. A simple visual mechanism simplifies conceptualization of the study area. Finally, a building-block approach helps researchers organize knowledge from the existing research literature, so as to refine the question and select the appropriate level of testing. At the end of this phase, researchers have refined the initial research idea to an explicit statement, ready for testing.

Research Design↗
PubMed1998

Randomized, double-blind, one-year study of the safety and tolerability of cyclosporine microemulsion compared with conventional cyclosporine in renal transplant patients. International Sandimmun Neoral Study Group.

BACKGROUND: A microemulsion formulation of cyclosporine, Neoral, has been developed to overcome the problems associated with the poor and variable absorption of the traditional oil-based oral formulation, Sandimmune. The present study was conducted to compare the safety and tolerability of Neoral versus Sandimmune in maintenance renal transplant recipients over 1 year, and to assess the number of dose adjustments necessary to maintain trough cyclosporine concentrations within the desired therapeutic range. METHODS. Patients on Sandimmune were randomized to be converted to Neoral (n=373) or remain on Sandimmune (n=93) for 12 months. RESULTS: The proportion of patients needing dose increases to maintain cyclosporine trough levels within the desired range was significantly higher in the Sandimmune group during the first 3 months of the study, whereas the number of patients needing dose reductions was similar in both groups throughout the study period. There were no differences between the groups in terms of changes in blood pressure, serum creatinine levels, or other laboratory parameters. No significant differences in the incidence of adverse events known to be related to cyclosporine were observed between the treatment groups. More adverse events were causally related to Neoral than to Sandimmune by the investigators. However, overall, there were no clinically relevant differences between the treatment groups in the main safety and tolerability variables. CONCLUSIONS: The results of this study in maintenance renal transplant patients suggest that the improved pharmacokinetic characteristics of the microemulsion formulation of cyclosporine, Neoral, may facilitate the clinical management of cyclosporine immunosuppression, compared with the traditional formulation, Sandimmune. Furthermore, there is no evidence that the average improved bioavailability of Neoral has a negative impact on the main safety and tolerability variables, as no significant differences in graft function, the incidence of rejections, and most adverse events were seen.

Creatinine↗
PubMed2001

Area-preserving dynamics of a long slender finger by curvature: a test case for globally conserved phase ordering.

A long and slender finger can serve as a simple "test bed" for different phase-ordering models. In this work, the globally conserved, interface-controlled dynamics of a long finger is investigated, analytically and numerically, in two dimensions. An important limit is considered when the finger dynamics is reducible to area-preserving motion by curvature. A free boundary problem for the finger shape is formulated. An asymptotic perturbation theory is developed that uses the finger aspect ratio as a small parameter. The leading-order approximation is a modification of the Mullins finger (a well-known analytic solution) whose width is allowed to slowly vary with time. This time dependence is described, in the leading order, by an exponential law with the characteristic time proportional to the (constant) finger area. The subleading terms of the asymptotic theory are also calculated. Finally, the finger dynamics is investigated numerically, employing the Ginzburg-Landau equation with a global conservation law. The theory is in very good agreement with the numerical solution.

Journal Article↗
PubMed2005

High-resolution numerical approximation of traffic flow problems with variable lanes and free-flow velocities.

This paper develops macroscopic traffic flow models for a highway section with variable lanes and free-flow velocities, that involve spatially varying flux functions. To address this complex physical property, we develop a Riemann solver that derives the exact flux values at the interface of the Riemann problem. Based on this solver, we formulate Godunov-type numerical schemes to solve the traffic flow models. Numerical examples that simulate the traffic flow around a bottleneck that arises from a drop in traffic capacity on the highway section are given to illustrate the efficiency of these schemes.

Journal Article↗
PubMed2004

Confined quantum time of arrivals.

We show that formulating the quantum time of arrival problem in a segment of the real line suggests rephrasing the quantum time of arrival problem to finding states that evolve to unitarily collapse at a given point at a definite time. For the spatially confined particle, we show that the problem admits a solution in the form of an eigenvalue problem of a compact and self-adjoint time of arrival operator derived by a quantization of the classical time of arrival, which is canonically conjugate with the Hamiltonian in a closed subspace of the Hilbert space.

Journal Article↗
PubMed2002

ARP/wARP's model-building algorithms. I. The main chain.

Algorithms underlying the automatic model-building functionality of the ARP/wARP software suite are presented. Finding the most likely set of Calpha atoms from a given set of atoms is formulated as a constrained integer programming problem. The objective function is a density-weighted score for the match between observed and expected chain conformation. Graph-search algorithms are presented that find solutions to this problem in an efficient manner.

Algorithms↗
PubMed2000

Parametric estimate of intensity inhomogeneities applied to MRI.

This paper presents a new approach to the correction of intensity inhomogeneities in magnetic resonance imaging (MRI) that significantly improves intensity-based tissue segmentation. The distortion of the image brightness values by a low-frequency bias field impedes visual inspection and segmentation. The new correction method called parametric bias field correction (PABIC) is based on a simplified model of the imaging process, a parametric model of tissue class statistics, and a polynomial model of the inhomogeneity field. We assume that the image is composed of pixels assigned to a small number of categories with a priori known statistics. Further we assume that the image is corrupted by noise and a low-frequency inhomogeneity field. The estimation of the parametric bias field is formulated as a nonlinear energy minimization problem using an evolution strategy (ES). The resulting bias field is independent of the image region configurations and thus overcomes limitations of methods based on homomorphic filtering. Furthermore, PABIC can correct bias distortions much larger than the image contrast. Input parameters are the intensity statistics of the classes and the degree of the polynomial function. The polynomial approach combines bias correction with histogram adjustment, making it well suited for normalizing the intensity histogram of datasets from serial studies. We present simulations and a quantitative validation with phantom and test images. A large number of MR image data acquired with breast, surface, and head coils, both in two dimensions and three dimensions, have been processed and demonstrate the versatility and robustness of this new bias correction scheme.

Brain↗
PubMed2005

Space-dependent color gamut mapping: a variational approach.

Gamut mapping deals with the need to adjust a color image to fit into the constrained color gamut of a given rendering medium. A typical use for this tool is the reproduction of a color image prior to its printing, such that it exploits best the given printer/medium color gamut, namely the colors the printer can produce on the given medium. Most of the classical gamut mapping methods involve a pixel-by-pixel mapping and ignore the spatial color configuration. Recently proposed spatial-dependent approaches for gamut mapping are either based on heuristic assumptions or involve a high computational cost. In this paper, we present a new variational approach for space-dependent gamut mapping. Our treatment starts with the presentation of a new measure for the problem, closely related to a recent measure proposed for Retinex. We also link our method to recent measures that attempt to couple spectral and spatial perceptual measures. It is shown that the gamut mapping problem leads to a quadratic programming formulation, guaranteed to have a unique solution if the gamut of the target device is convex. An efficient numerical solution is proposed with promising results.

Algorithms↗
PubMed2004

Dynamic ion channel activation scheduling in patch clamp on a chip.

In 2002, Fertig et al. made a remarkable invention: the first successful demonstration of a patch clamp on a chip--a planar quartz-based biological chip that contains up to several hundred ion channels. This patch-clamp chip can be used in massively parallel screens for ion channel activity, thereby providing a high-throughput screening tool for drug discovery efforts. In this paper, we propose computationally efficient dynamic stochastic scheduling algorithms for activating individual ion channels in the patch-clamp chip. By formulating the ion channel activation scheduling problem as a partially observed Markov decision process with a multiarmed bandit structure, near-optimal dynamic scheduling for activation of the individual channels is achieved to optimize the information gained from the patch-clamp chip. Numerical examples using state-of-the-art algorithms developed recently in artificial intelligence and operations research are presented to illustrate these dynamic ion channel (macromolecule) activation scheduling algorithms.

Algorithms↗
PubMed2006

Study of a fast discriminative training algorithm for pattern recognition.

Discriminative training refers to an approach to pattern recognition based on direct minimization of a cost function commensurate with the performance of the recognition system. This is in contrast to the procedure of probability distribution estimation as conventionally required in Bayes' formulation of the statistical pattern recognition problem. Currently, most discriminative training algorithms for nonlinear classifier designs are based on gradient-descent (GD) methods for cost minimization. These algorithms are easy to derive and effective in practice, but are slow in training speed and have difficulty selecting the learning rates. To address the problem, we present our study on a fast discriminative training algorithm. The algorithm initializes the parameters by the expectation-maximization (EM) algorithm, and then uses a set of closed-form formulas derived in this paper to further optimize a proposed objective of minimizing error rate. Experiments in speech applications show that the algorithm provides better recognition accuracy in a fewer iterations than the EM algorithm and a neural network trained by hundreds of GD iterations. Although some convergent properties need further research, the proposed objective and derived formulas can benefit further study of the problem.

Algorithms↗
PubMed2004

A unified quadratic-programming-based dynamical system approach to joint torque optimization of physically constrained redundant manipulators.

In this paper, for joint torque optimization of redundant manipulators subject to physical constraints, we show that velocity-level and acceleration-level redundancy-resolution schemes both can be formulated as a quadratic programming (QP) problem subject to equality and inequality/bound constraints. To solve this QP problem online, a primal-dual dynamical system solver is further presented based on linear variational inequalities. Compared to previous researches, the presented QP-solver has simple piecewise-linear dynamics, does not entail real-time matrix inversion, and could also provide joint-acceleration information for manipulator torque control in the velocity-level redundancy-resolution schemes. The proposed QP-based dynamical system approach is simulated based on the PUMA560 robot arm with efficiency and effectiveness demonstrated.

Algorithms↗
PubMed2005

Modeling of driver's collision avoidance maneuver based on controller switching model.

This paper presents a modeling strategy of human driving behavior based on the controller switching model focusing on the driver's collision avoidance maneuver. The driving data are collected by using the three-dimensional (3-D) driving simulator based on the CAVE Automatic Virtual Environment (CAVE), which provides stereoscopic immersive virtual environment. In our modeling, the control scenario of the human driver, that is, the mapping from the driver's sensory information to the operation of the driver such as acceleration, braking, and steering, is expressed by Piecewise Polynomial (PWP) model. Since the PWP model includes both continuous behaviors given by polynomials and discrete logical conditions, it can be regarded as a class of Hybrid Dynamical System (HDS). The identification problem for the PWP model is formulated as the Mixed Integer Linear Programming (MILP) by transforming the switching conditions into binary variables. From the obtained results, it is found that the driver appropriately switches the "control law" according to the sensory information. In addition, the driving characteristics of the beginner driver and the expert driver are compared and discussed. These results enable us to capture not only the physical meaning of the driving skill but the decision-making aspect (switching conditions) in the driver's collision avoidance maneuver as well.

Accidents, Traffic↗
PubMed1989

Three-dimensional kinematic modelling of the human shoulder complex--Part II: Mathematical modelling and solution via optimization.

In this paper, individual joint sinus cones associated with the sternoclavicular, claviscapular, and glenohumeral joints of the three-dimensional kinematic model introduced in Part I for the human shoulder complex are quantitatively determined. First, mathematical description of the humerus orientation with respect to torso is given in terms of eight joint variables. Since the system is a kinematically redundant one, solution for the joint variables satisfying a prescribed humerus orientation is possible only if additional requirements are imposed; and the "minimum joint motion" criterion is introduced for this purpose. Two methods, namely the Lagrange multipliers and flexible tolerance methods, are formulated and tested for the optimization problem. The statistical in-vivo data base for the circumductory motion of the upper arm is employed to determine a set of joint variables via optimization, which are then utilized to establish the sizes and orientations of the elliptical cones for the individual joint sinuses. The results are discussed and compared with those given on the basis of measurements made on cadaveric specimens.

Biomechanical Phenomena↗
PubMed1995

Learning in recurrent finite difference networks.

A recurrent learning algorithm based on a finite difference discretization of continuous equations for neural networks is derived. This algorithm has the simplicity of discrete algorithms while retaining some essential characteristics of the continuous equations. In discrete networks learning smooth oscillations is difficult if the period of oscillation is too large. The network either grossly distorts the waveforms or is unable to learn at all. We show how the finite difference formulation can explain and overcome this problem. Formulas for learning time constants and time delays in this framework are also presented.

Algorithms↗