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At least 307 records · Page 17Linked to original sources

PubMed1999

An EM-type Algorithm for Ordered Restriction Map Alignment.

Constructing restriction maps is one of the important steps towards the determination of DNA sequences. Recently, the single-molecule approaches to constructing restriction maps, such as Optical Mapping by D. Schwartz et al., have developed. In practice, with the single-molecule approach like Optical Mapping, the identification of the restriction sites is complicated by several error factors due to resolving power of biological experiments. The ordered restriction map alignment problem is a problem to estimate the actual restriction sites from many imprecise copies of map from single molecule. In this paper, we formulate the problem on the basis of the statistical maximum likelihood estimate, and propose a new efficient local search algorithm for this problem, by applying the Expectation-Maximization (EM) algorithm along with the concept of two-clustering. Our algorithm works well for a lot of sets of simulated data, some of which we believe more difficult than the actual cases.

Journal Article↗

PubMedDate not supplied

Effect of dose and formulation on iron tolerance in pregnancy.

BACKGROUND: The National Nutritional Anaemia Prophylaxis Programme (NNAPP) in India was launched in 1971. However, anaemia continues to be a major public health problem. Partial coverage of the population, inadequate dose of the iron supplement, defective absorption due to intestinal infestations and problems with formulation have been recognized as factors responsible for its failure. Therefore, the bioavailability of iron from different formulations containing 60 mg of elemental iron and of tablets with varying doses of elemental iron was undertaken. METHODS: One hundred and fifteen women were randomly allotted to receive different formulations and doses of iron and then undergo iron tolerance tests. They received ferrous sulphate tablets containing 60 mg, 120 mg and 180 mg of elemental iron; formulations containing 60 mg of elemental iron as pure ferrous sulphate salt, ferrous fumarate tablets, ferrous fumarate syrup, excipients added to pure ferrous sulphate salts, powdered ferrous sulphate tablets, iron tablets distributed by the NNAPP and pure ferrous salt in gelatin capsules. RESULTS: The data obtained from 32 subjects were excluded because of non-compliance, intolerance of the medication and lack of results of blood tests. Data from the remaining 83 subjects indicated that increasing the dose of elemental iron from 60 mg to 180 mg improved the bioavailability of iron, but was associated with unacceptable side-effects. Also, liquid formulations of iron had a better bioavailability, with ferrous fumarate syrup and gelatin capsules being the most superior. CONCLUSION: Providing the iron formulation with a high bioavailability should enable the NNAPP to be more successful in decreasing the prevalence of anaemia.

Anemia↗

PubMed1992

A distribution-free procedure for the statistical analysis of bioequivalence studies.

In bioequivalence assessment, the consumer risk of erroneously accepting bioequivalence is of primary concern. In order to control the consumer risk, the decision problem is formulated with bioinequivalence as hypothesis and bioequivalence as alternative. In the parametric approach, a split into two one-sided test problems and application of two-sample t-tests have been suggested. Rejection of both hypotheses at nominal alpha-level is equivalent to the inclusion of the classical (shortest) (1-2 alpha) 100%-confidence interval in the bioequivalence range. This paper demonstrates that the rejection of the two one-sided hypotheses at nominal alpha-level by means of nonparametric Mann-Whitney-Wilcoxon tests is equivalent to the inclusion of the corresponding distribution-free (1-2 alpha) 100%-confidence interval in the bioequivalence range. This distribution-free (nonparametric) approach needs weaker model assumptions and hence presents an alternative to the parametric approach.

Adult↗

PubMed1990

A distribution-free procedure for the statistical analysis of bioequivalence studies.

Adult↗

PubMed2003

Converting general nonlinear programming problems into separable programming problems with feedforward neural networks.

In this paper we present a method for converting general nonlinear programming (NLP) problems into separable programming (SP) problems by using feedforward neural networks (FNNs). The basic idea behind the method is to use two useful features of FNNs: their ability to approximate arbitrary continuous nonlinear functions with a desired degree of accuracy and their ability to express nonlinear functions in terms of parameterized compositions of functions of single variables. According to these two features, any nonseparable objective functions and/or constraints in NLP problems can be approximately expressed as separable functions with FNNs. Therefore, any NLP problems can be converted into SP problems. The proposed method has three prominent features. (a) It is more general than existing transformation techniques; (b) it can be used to formulate optimization problems as SP problems even when their precise analytic objective function and/or constraints are unknown; (c) the SP problems obtained by the proposed method may highly facilitate the selection of grid points for piecewise linear approximation of nonlinear functions. We analyze the computational complexity of the proposed method and compare it with an existing transformation approach. We also present several examples to demonstrate the method and the performance of the simplex method with the restricted basis entry rule for solving SP problems.

Neural Networks, Computer↗

PubMed2004

On the control of chaotic systems via symbolic time series analysis.

Symbolic analysis of time series is extended to systems with inputs, in order to obtain input/output symbolic models to be used for control policy design. For that, the notion of symbolic word is broadened to possibly include past input values. Then, a model is derived in the form of a controlled Markov chain, i.e., transition probabilities are conditioned on the control value. The quality of alternative models with different word length and alphabet size is assessed by means of an indicator based on Shannon entropy. A control problem is formulated, with the goal of confining the system output in a smaller domain with respect to that of the uncontrolled case. Solving this problem (by means of a suitable numerical method) yields the relevant control policy, as well as an estimate of the probability distribution of the output of the controlled system. Three examples of application (based on the analysis of time series synthetically generated by the logistic map, the Lorenz system, and an epidemiological model) are presented and used to discuss the features and limitations of the method.

Journal Article↗

PubMed1998

A fast neural-network algorithm for VLSI cell placement.

Cell placement is an important phase of current VLSI circuit design styles such as standard cell, gate array, and Field Programmable Gate Array (FPGA). Although nondeterministic algorithms such as Simulated Annealing (SA) were successful in solving this problem, they are known to be slow. In this paper, a neural network algorithm is proposed that produces solutions as good as SA in substantially less time. This algorithm is based on Mean Field Annealing (MFA) technique, which was successfully applied to various combinatorial optimization problems. A MFA formulation for the cell placement problem is derived which can easily be applied to all VLSI design styles. To demonstrate that the proposed algorithm is applicable in practice, a detailed formulation for the FPGA design style is derived, and the layouts of several benchmark circuits are generated. The performance of the proposed cell placement algorithm is evaluated in comparison with commercial automated circuit design software Xilinx Automatic Place and Route (APR) which uses SA technique. Performance evaluation is conducted using ACM/SIGDA Design Automation benchmark circuits. Experimental results indicate that the proposed MFA algorithm produces comparable results with APR. However, MFA is almost 20 times faster than APR on the average.

Journal Article↗

PubMed1988

A procedure for locating emergency-service facilities for all possible response distances.

The problem of locating emergency-service facilities involves the assignment of a set of demand points to a set of facilities. One way to formulate the problem is to minimize the number of required facilities, given that the maximum distance between the demand points and their nearest facility does not exceed some specified value. We present a procedure for determining the numbers of such facilities for all possible values of the maximum distance. Computational results are presented for a microcomputer implementation.

Decision Support Systems, Management↗

PubMed1993

Comparison of the adjoint and influence coefficient methods for solving the inverse hyperthermia problem.

An adjoint formulation is derived and used to determine the elements in the Jacobian matrix associated with the inverse problem of estimating the blood perfusion and temperature fields during hyperthermia cancer treatments. This method and a previously developed influence coefficient method for obtaining that matrix are comparatively evaluated by solving a set of numerically simulated inverse hyperthermia problems. The adjoint method has the advantage of requiring fewer solutions of the bioheat transfer equation to estimate the Jacobian than does the influence coefficient method when the number of measurement sensors is significantly smaller than the number of unknown parameters. Thus, it could be a preferable method to use in hyperthermia applications where the number of sensors is strictly limited by patient considerations. However, the adjoint method requires that CPU time intensive convolutions be numerically evaluated. Comparisons of the performance of the adjoint formulation and the influence coefficient method show that, first, there is a critical ratio of the number of measurement sensors to the number of unknown parameters at which the CPU time per iteration required to calculate the Jacobian matrix is the same for both methods. The adjoint method is faster than the influence coefficient method only when the value of the ratio is less than that critical value. For the hyperthermia problems investigated in the present study, this only occurs for cases with a very small number of measurement sensors. This presents a potential problem for clinical applications because the fewer measurement sensors used, the less information that can be gathered to correctly solve the inverse problem.(ABSTRACT TRUNCATED AT 250 WORDS)

Blood Flow Velocity↗

PubMed2005

A common formalism for the integral formulations of the forward EEG problem.

The forward electroencephalography (EEG) problem involves finding a potential V from the Poisson equation inverted Delta x (sigma inverted Delta V) f, in which f represents electrical sources in the brain, and sigma the conductivity of the head tissues. In the piecewise constant conductivity head model, this can be accomplished by the boundary element method (BEM) using a suitable integral formulation. Most previous work uses the same integral formulation, corresponding to a double-layer potential. In this paper we present a conceptual framework based on a well-known theorem (Theorem 1) that characterizes harmonic functions defined on the complement of a bounded smooth surface. This theorem says that such harmonic functions are completely defined by their values and those of their normal derivatives on this surface. It allows us to cast the previous BEM approaches in a unified setting and to develop two new approaches corresponding to different ways of exploiting the same theorem. Specifically, we first present a dual approach which involves a single-layer potential. Then, we propose a symmetric formulation, which combines single- and double-layer potentials, and which is new to the field of EEG, although it has been applied to other problems in electromagnetism. The three methods have been evaluated numerically using a spherical geometry with known analytical solution, and the symmetric formulation achieves a significantly higher accuracy than the alternative methods. Additionally, we present results with realistically shaped meshes. Beside providing a better understanding of the foundations of BEM methods, our approach appears to lead also to more efficient algorithms.

Algorithms↗

PubMed1991

Knowledge-based schedule formulation and maintenance under uncertainty.

This paper is concerned with the dual sequential problems of (1) determining an acceptable personnel schedule over a specified time period, and (2) adjusting that schedule during the course of its execution in reaction to daily changes in both demand and available personnel. The first problem is schedule formulation; the second sequential problem is schedule execution. A rule-based, hierarchical system has been developed for first modeling and then solving both the schedule formulation and the schedule execution problems as a two-phase dependent process. The system is applied to the scheduling and staffing of nurses. A double-blind evaluation was conducted, which ascertained the quality of the resultant schedules in terms of maintainability, coverage, and personal satisfaction. The evaluation indicates that for units on which personnel changes have occurred, the prototype appears to perform as well as human schedulers.

Humans↗

PubMed1999

Representing contrast detection as an eigenvalue problem.

Contrast detection can be formulated as an eigenvalue problem. One of the simplest resulting models has only two parameters. The model is space variant and employs the Hermite functions as eigenfunctions. Computing the response to a sinusoidal acuity grating yields the observer's contrast response. The model itself, however, is developed within an abstract mathematical framework which is general enough to include Fourier analysis as a special case. Consequently, the methods of Fourier analysis are generalized to those of eigenfunction expansion and the spectral theory of linear operators.

Contrast Sensitivity↗

PubMedDate not supplied

Case formulation in psychotherapy: revitalizing its usefulness as a clinical tool.

OBJECTIVE: Case formulation has been recognized to be a useful conceptual and clinical tool in psychotherapy as diagnosis itself does not focus on the underlying causes of a patient's problems. Case formulation can fill the gap between diagnosis and treatment, with the potential to provide insights into the integrative, explanatory, prescriptive, predictive, and therapist aspects of a case. Despite the acknowledgment that case formulation is a basic, necessary, and key clinical skill, it is still largely undertaught and underlearned. Some of the issues faced in the development of a case formulation include that of immediacy versus comprehensiveness, complexity versus simplicity, observation versus organization, and the need for cultural sensitivity toward each individual patient. METHODS: The authors propose five aspects of case formulation beneficial to therapists and residents in training. CONCLUSIONS: The authors argue that case formulation remains an important and indispensable integrative tool for therapists and residents in training who are involved in psychotherapeutic interventions.

Case-Control Studies↗

PubMed2005

Magnetic models on Apollonian networks.

Thermodynamic and magnetic properties of Ising models defined on the triangular Apollonian network are investigated. This and other similar networks are inspired by the problem of covering a Euclidian domain with circles of maximal radii. Maps for the thermodynamic functions in two subsequent generations of the construction of the network are obtained by formulating the problem in terms of transfer matrices. Numerical iteration of this set of maps leads to very precise values for the thermodynamic properties of the model. Different choices for the coupling constants between only nearest neighbors along the lattice are taken into account. For both ferromagnetic and antiferromagnetic constants, long-range magnetic ordering is obtained. With exception of a size-dependent effective critical behavior of the correlation length, no evidence of asymptotic criticality was detected.

Journal Article↗

PubMed2001

A probabilistic solution to the MEG inverse problem via MCMC methods: the reversible jump and parallel tempering algorithms.

We investigated the usefulness of probabilistic Markov chain Monte Carlo (MCMC) methods for solving the magnetoencephalography (MEG) inverse problem, by using an algorithm composed of the combination of two MCMC samplers: Reversible Jump (RJ) and Parallel Tempering (PT). The MEG inverse problem was formulated in a probabilistic Bayesian approach, and we describe how the RJ and PT algorithms are fitted to our application. This approach offers better resolution of the MEG inverse problem even when the number of source dipoles is unknown (RJ), and significant reduction of the probability of erroneous convergence to local modes (PT). First estimates of the accuracy and resolution of our composite algorithm are given from results of simulation studies obtained with an unknown number of sources, and with white and neuromagnetic noise. In contrast to other approaches, MCMC methods do not just give an estimation of a "single best" solution, but they provide confidence interval for the source localization, probability distribution for the number of fitted dipoles, and estimation of other almost equally likely solutions.

Algorithms↗

PubMed2006

A hybrid Newton-type method for censored survival data using double weights in linear models.

As an alternative to the Cox model, the rank-based estimating method for censored survival data has been studied extensively since it was proposed by Tsiatis [Tsiatis AA (1990) Ann Stat 18:354-372] among others. Due to the discontinuity feature of the estimating function, a significant amount of work in the literature has been focused on numerical issues. In this article, we consider the computational aspects of a family of doubly weighted rank-based estimating functions. This family is rich enough to include both estimating functions of Tsiatis (1990) for the randomly observed data and of Nan et al. [Nan B, Yu M, Kalbfleisch JD (2006) Biometrika (to appear)] for the case-cohort data as special examples. The latter belongs to the biased sampling problems. We show that the doubly weighted rank-based discontinuous estimating functions are monotone, a property established for the randomly observed data in the literature, when the generalized Gehan-type weights are used. Though the estimating problem can be formulated to a linear programming problem as that for the randomly observed data, due to its easily uncontrollable large scale even for a moderate sample size, we instead propose a Newton-type iterated method to search for an approximate solution of the (system of) discontinuous monotone estimating equation(s). Simulation results provide a good demonstration of the proposed method. We also apply our method to a real data example.

Carcinoma↗

PubMed2006

An expectation-maximization algorithm for probabilistic reconstructions of full-length isoforms from splice graphs.

Reconstructing full-length transcript isoforms from sequence fragments (such as ESTs) is a major interest and challenge for bioinformatic analysis of pre-mRNA alternative splicing. This problem has been formulated as finding traversals across the splice graph, which is a directed acyclic graph (DAG) representation of gene structure and alternative splicing. In this manuscript we introduce a probabilistic formulation of the isoform reconstruction problem, and provide an expectation-maximization (EM) algorithm for its maximum likelihood solution. Using a series of simulated data and expressed sequences from real human genes, we demonstrate that our EM algorithm can correctly handle various situations of fragmentation and coupling in the input data. Our work establishes a general probabilistic framework for splice graph-based reconstructions of full-length isoforms.

Algorithms↗

PubMed1989

Boundary conditions at the cartilage-synovial fluid interface for joint lubrication and theoretical verifications.

The objective of this study is to establish and verify the set of boundary conditions at the interface between a biphasic mixture (articular cartilage) and a Newtonian or non-Newtonian fluid (synovial fluid) such that a set of well-posed mathematical problems may be formulated to investigate joint lubrication problems. A "pseudo-no-slip" kinematic boundary condition is proposed based upon the principle that the conditions at the interface between mixtures or mixtures and fluids must reduce to those boundary conditions in single phase continuum mechanics. From this proposed kinematic boundary condition, and balances of mass, momentum and energy, the boundary conditions at the interface between a biphasic mixture and a Newtonian or non-Newtonian fluid are mathematically derived. Based upon these general results, the appropriate boundary conditions needed in modeling the cartilage-synovial fluid-cartilage lubrication problem are deduced. For two simple cases where a Newtonian viscous fluid is forced to flow (with imposed Couette or Poiseuille flow conditions) over a porous-permeable biphasic material of relatively low permeability, the well known empirical Taylor slip condition may be derived using matched asymptotic analysis of the boundary layer at the interface.

Cartilage, Articular↗