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Results for “Programming, Linear”

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PubMed1986

Limits to the relationship among recombination, disequilibrium and epistasis in two-locus models.

I determine limits to the equilibrium relationship among epistasis, recombination and disequilibrium in two-locus, two-allele models using linear programming techniques. I show that when allele frequencies are one-half at each locus, the symmetric model is the fitness pattern that generates the most disequilibrium for the smallest level of epistasis. When allele frequencies deviate from one-half much larger levels of epistasis are required to generate similar levels of disequilibrium. I determine the level of epistasis required to generate observed significant levels of disequilibrium in natural populations. The overall implication is that disequilibrium will be large at equilibrium only between strongly interacting, closely linked loci.

Alleles↗

PubMed1999

Improving the efficiency of artificial selection: more selection pressure with less inbreeding.

The use of population genetic variability in present-day selection schemes can be improved to reduce inbreeding rate and inbreeding depression without impairing genetic progress. We performed an experiment with Drosophila melanogaster to test mate selection, an optimizing method that uses linear programming to maximize the selection differential applied while at the same time respecting a restriction on the increase in inbreeding expected in the next generation. Previous studies about mate selection used computer simulation on simple additive genetic models, and no experiment with a real character in a real population had been carried out. After six selection generations, the optimized lines showed an increase in cumulated phenotypic selection differential of 10.76%, and at the same time, a reduction of 19.91 and 60.47% in inbreeding coefficient mean and variance, respectively. The increased selection pressure would bring greater selection response, and in fact, the observed change in the selected trait was on average 31.03% greater in the optimized lines. These improvements in the selection scheme were not made at the expense of the long-term expectations of genetic variability in the population, as these expectations were very similar for both mate selection and conventionally selected lines in our experiment.

Animals↗

PubMed1981

Disequilibrium, selection, and recombination: limits in two-locus, two-allele models.

All possible combinations of equilibria and fitnesses in two-locus, two-allele, deterministic, discrete-generation selection models are enumerated. This knowledge is used to obtain limits (which can be calculated to arbitrary precision) to the relationships among disequilibrium, selection and recombination for fixed values of allele frequencies. In all cases, the inequality magnitude of rD less than s/10 holds, where r is recombination and D is disequilibrium, and all selection coefficients lie between 1 - s and 1 + s times that of the double heterozygote. Linear programming techniques are used to observed nonzero values of D reported in the literature. One conclusion is that the failure to observe nonzero values of D is not surprising.

Alleles↗

PubMedDate not supplied

The efficiency of Scottish acute hospitals: an application of data envelopment analysis.

Measurement of the efficiency of health services would aid the promotion of a better allocation of health care resources. Economic analysis suggests a number of ways of defining and measuring efficiency. However, this rarely informs measures used in health service management. This paper looks at the potential for the use in the United Kingdom's National Health Service of the linear programming based method of data envelopment analysis (DEA). DEA is applied to data from 75 UK acute hospitals. The results demonstrate the capacity of DEA to produce a user-friendly array of results, based on sound theoretical underpinnings. These range from the measurement of relative efficiencies to quantified suggestions as to how hospitals may improve efficiency, by examining both their own efficiency and that of comparable units. Information is provided both about individual hospitals and the sample as a whole. DEA is also able to distinguish between hospitals demonstrating differing returns to scale. Our findings suggest that, although still very much under development, DEA is usable and, given the weakness of current means of measuring efficiency in the National Health Service, that DEA has a strong claim for further consideration.

Data Interpretation, Statistical↗

PubMed1981

Amino acid requirements of growing mice: arginine, lysine, tryptophan and phenylalanine.

Linear programmed diets designed to maximize the use of proteins and to minimize the use of free (1-) amino acids, and containing five dietary levels of each amino acid under test, were fed to weanling crossbred Carworth Farms No. 1 x Swiss mice in 14-day growth trials. Arginine dietary levels were 0.1, 0.2, 0.3, 0.4 and 0.7%; lysine: 0.2, 0.3, 0.4, 0.5 and 1.0%; tryptophan: 0.03, 0.07, 0.10, 0.13 and 0.17%; and phenylalanine: 0.10, 0.25, 0.40, 0.55 and 0.89%. Growth, feed consumption and regression-adjusted growth rates indicated the following minimum requirements: arginine less than 0.1% and probably zero, lysine 0.4%, tryptophan 0.1% and phenylalanine 0.4%. The AIN '76 reference diet was included in each amino acid test and resulted in superior growth and feed utilization. It was postulated that the greater content of free amino acids in our diets may have affected the efficiency of feed utilization adversely.

Amino Acids, Essential↗

PubMed1982

Nutritional value of feather-meal protein for chicks.

Ileal absorption of nitrogen was determined for feather meal (FM) samples, using magnesium ferrite as a marker. Diets containing 15% FM were balanced by linear programming, using two nitrogen absorption values for FM: 55%, as found, or 85%, an average value for standard feeds. When nitrogen absorption of FM was calculated as 55%, the growth of chicks from one to three weeks of age was similar to that of the control chicks. Depression of growth occurred when the diet composition was calculated using 85% nitrogen absorption for FM. The official method of pepsin digestibility in vitro, using 0.2% pepsin, did not reflect the nutritive value of FM protein. Results similar to those of nitrogen absorption in vivo were obtained with 0.002% pepsin. The total cystine content of FM and the rate of its liberation by pancreatin may also seve as an indication of the nutritive value of FM protein.

Amino Acids↗

PubMed1978

A simple method for the computation of first neighbour frequencies of DNAs from CD spectra.

A procedure for the computation of the first neighbour frequencies of DNA's is presented. This procedure is based on the first neighbour approximation of Gray and Tinoco. We show that the knowledge of all the ten elementary CD signals attached to the ten double stranded first neighbour configurations is not necessary. One can obtain the ten frequencies of an unknown DNA with the use of eight elementary CD signals corresponding to eight linearly independent polymer sequences. These signals can be extracted very simply from any eight or more CD spectra of double stranded DNA's of known frequencies. The ten frequencies of a DNA are obtained by least square fit of its CD spectrum with these elementary signals. One advantage of this procedure is that it does not necessitate linear programming, it can be used with CD data digitalized using a large number of wavelengths, thus permitting an accurate resolution of the CD spectra. Under favorable case, the ten frequencies of a DNA (not used as input data) can be determined with an average absolute error < 2%. We have also observed that certain satellite DNA's, those of Drosophila virilis and Callinectes sapidus have CD spectra compatible with those of DNA's of quasi random sequence; these satellite DNA's should adopt also the B-form in solution.

Animals↗

PubMed2002

Sampling error can significantly affect measured hospital financial performance of surgeons and resulting operating room time allocations.

UNLABELLED: Hospitals with limited operating room (OR) hours, those with intensive care unit or ward beds that are always full, or those that have no incremental revenue for many patients need to choose which surgeons get the resources. Although such decisions are based on internal financial reports, whether the reports are statistically valid is not known. Random error may affect surgeons' measured financial performance and, thus, what cases the anesthesiologists get to do and which patients get to receive care. We tested whether one fiscal year of surgeon-specific financial data is sufficient for accurate financial accounting. We obtained accounting data for all outpatient or same-day-admit surgery cases during one fiscal year at an academic medical center. Linear programming was used to find the mix of surgeons' OR time allocations that would maximize the contribution margin or minimize variable costs. Confidence intervals were calculated on these end points by using Fieller's theorem and Monte-Carlo simulation. The 95% confidence intervals for increases in contribution margins or reductions in variable costs were 4.3% to 10.8% and 6.0% to 8.9%, respectively. As many as 22% of surgeons would have had OR time reduced because of sampling error. We recommend that physicians ask for and OR managers get confidence intervals of end points of financial analyses when making decisions based on them. IMPLICATIONS: The common approach of using one fiscal year of perioperative accounting data can be insufficient to prevent random error from influencing important management decisions. When accounting data are used for hospital and operating room management decision making, confidence intervals should be calculated for the key financial variables (e.g., variable cost per hour of operating room time).

Costs and Cost Analysis↗

PubMed1989

Evaluating managerial efficiency of Veterans Administration medical centers using Data Envelopment Analysis.

This study applied the methodology of Data Envelopment Analysis (DEA) to the set of VA medical centers to evaluate their relative managerial efficiencies. Each VAMC was viewed as a producer of multiple outputs and a consumer of multiple inputs. DEA uses linear programming to identify resources that were underutilized and services that were inefficiently produced. Managerial strategies based on the dual variables were constructed to indicate the manner in which inefficient VAMCs may be made efficient. The analysis showed that relative inefficiency existed in about one third of the VAMCs nationwide. Elimination of this inefficiency would save the VA over $300 million annually on personnel, equipment, drugs, and supplies, without reducing the level of services provided. A subsequent analysis of co-variance revealed that VAMCs affiliated with a university were generally less efficient than those without such an affiliation. A similar finding was obtained for larger VAMCs relative to smaller medical centers. In neither case, however, should these results be construed to imply that VAMCs should terminate their university affiliations or that VAMCs should be made smaller since factors other than relative efficiency are clearly as or more important in such decisions.

Cost Control↗

PubMedDate not supplied

Equilibrium analysis for the forces in the human spinal column and its musculature.

The equations of equilibrium are set up for the thoracic and lumbar spine and involve body weight, external load, muscle forces, and intervertebral reactions. These equations are solved using a linear programming technique that minimizes the total force in the system. The solution gives numeric values for the muscle forces and intervertebral reactions. The results for a subject in progressive forward flexion and in lateral bend are presented. Also examined are the effects of three different orthotic devices on the muscle forces of a patient with a scoliotic spine.

Biomechanical Phenomena↗

PubMed2003

From individual control to majority rule: extending transactional models of reproductive skew in animal societies.

Transactional concession models of social evolution explain the reproductive skew within groups by assuming that a dominant individual completely controls the allocation of reproduction to other group members. The models predict when the dominant will benefit from donating parcels of reproduction to other members in return for peaceful cooperation. Using linear programming methods, we present a 'majority-rules' model in which the summed actions of all society members, each with equal power, completely determine the reproductive share of any single member. The majority-rules model predicts that, despite the diffusion of power, a 'virtual dominant' (a dominant lacking special behavioural power) will emerge and that the reproductive skew will be exactly that predicted if the virtual dominant were to control completely the group's reproductive partitioning. The virtual dominant is the individual to which group members have the maximum average genetic relatedness. This result greatly broadens the applicability of transactional models of reproductive skew to social groups of any size, such as large-colony eusocial insects, and explains why queens in such colonies can achieve reproductive domination without any behavioural enforcement. Moreover, the majority-rules model unifies transactional-skew theory with models of worker policing and even generates a new theory for the cooperation among somatic cells in a multicellular organism.

Animals↗

PubMed2004

Genome-scale in silico models of E. coli have multiple equivalent phenotypic states: assessment of correlated reaction subsets that comprise network states.

The constraint-based analysis of genome-scale metabolic and regulatory networks has been successful in predicting phenotypes and useful for analyzing high-throughput data sets. Within this modeling framework, linear optimization has been used to study genome-scale metabolic models, resulting in the enumeration of single optimal solutions describing the best use of the network to support growth. Here mixed-integer linear programming was used to calculate and study a subset of the alternate optimal solutions for a genome-scale metabolic model of Escherichia coli (iJR904) under a wide variety of environmental conditions. Analysis of the calculated sets of optimal solutions found that: (1) only a small subset of reactions in the network have variable fluxes across optima; (2) sets of reactions that are always used together in optimal solutions, correlated reaction sets, showed moderate agreement with the currently known transcriptional regulatory structure in E. coli and available expression data, and (3) reactions that are used under certain environmental conditions can provide clues about network regulatory needs. In addition, calculation of suboptimal flux distributions, using flux variability analysis, identified reactions which are used under significantly more environmental conditions suboptimally than optimally. Together these results demonstrate the utilization of reactions in genome-scale models under a variety of different growth conditions.

Aerobiosis↗

PubMed2005

Generalized directed loop method for quantum Monte Carlo simulations.

Efficient quantum Monte Carlo update schemes called directed loops have recently been proposed, which improve the efficiency of simulations of quantum lattice models. We propose to generalize the detailed balance equations at the local level during the loop construction by accounting for the matrix elements of the operators associated with open world-line segments. Using linear programming techniques to solve the generalized equations, we look for optimal construction schemes for directed loops. This also allows for an extension of the directed loop scheme to general lattice models, such as high-spin or bosonic models. The resulting algorithms are bounce free in larger regions of parameter space than the original directed loop algorithm. The generalized directed loop method is applied to the magnetization process of spin chains in order to compare its efficiency to that of previous directed loop schemes. In contrast to general expectations, we find that minimizing bounces alone does not always lead to more efficient algorithms in terms of autocorrelations of physical observables, because of the nonuniqueness of the bounce-free solutions. We therefore propose different general strategies to further minimize autocorrelations, which can be used as supplementary requirements in any directed loop scheme. We show by calculating autocorrelation times for different observables that such strategies indeed lead to improved efficiency; however, we find that the optimal strategy depends not only on the model parameters but also on the observable of interest.

Journal Article↗

PubMed2001

Quick X-ray absorption spectroscopy for determining metal speciation in environmental samples.

We present a method for determining the chemical speciation of metals in environmental particles based on Quick-X-ray Absorption Spectroscopy. The approach can be applied to either the extended or the near edge fine structure, and consists in the decomposition of the XAS spectrum of an unknown sample on a reference set of standards' spectra using quadratic linear programming. The analysis accounts for the statistical experimental errors generated during the acquisition of X-ray absorption data, and leads to error estimates on the various fractions determined via a Monte Carlo procedure. An application example is presented for the speciation of inorganic Zn in a contaminated sediment sample.

Geologic Sediments↗

PubMed2005

A pivoting algorithm for metabolic networks in the presence of thermodynamic constraints.

A linear programming algorithm is presented to constructively compute thermodynamically feasible fluxes and change in chemical potentials of reactions for a metabolic network. It is based on physical laws of mass conservation and the second law of thermodynamics that all chemical reactions should satisfy. As a demonstration, the algorithm has been applied to the core metabolic pathway of E. coli.

Algorithms↗

PubMed2005

A fuzzy-based approach to remove clock skew and reset from one-way delay measurement.

One-way delay (OWD) traces are important measurements for analyzing end-to-end performance on the Internet. It is still a great challenge to provide a scalable solution for large-scale OWD measurement. Because the clocks at end systems are usually not synchronized, the OWD measurements are often inaccurate. For the more challenging case with clock resets to some reference times during the measurement, the OWD measurements are more inaccurate. Furthermore, the measurement data often exhibit considerable network-induced noise when the network is heavily loaded. All the existing OWD measurement techniques, such as linear programming and convex-hull approach (CHA), try to solve this problem by deterministic mathematics model. However, they often fail to distinguish clock resets from temporary Internet congestion. Based on the fuzzy-clustering analysis, this paper proposes a new algorithm to estimate and remove the clock skews and resets from measurement results. This algorithm has been implemented as a tool called fuzzy-based OWD corrector (FOC). The paper then presents OWD measurements of several Internet paths using FOC. Numerical experiments demonstrate that FOC is more accurate and robust than the existing techniques. FOCs computation complexity O(N) is similar to that of CHA and its computing time is much less than that of convex-hull technique.

Algorithms↗

PubMed2006

Blind estimation of channel parameters and source components for EEG signals: a sparse factorization approach.

In this paper, we use a two-stage sparse factorization approach for blindly estimating the channel parameters and then estimating source components for electroencephalogram (EEG) signals. EEG signals are assumed to be linear mixtures of source components, artifacts, etc. Therefore, a raw EEG data matrix can be factored into the product of two matrices, one of which represents the mixing matrix and the other the source component matrix. Furthermore, the components are sparse in the time-frequency domain, i.e., the factorization is a sparse factorization in the time frequency domain. It is a challenging task to estimate the mixing matrix. Our extensive analysis and computational results, which were based on many sets of EEG data, not only provide firm evidences supporting the above assumption, but also prompt us to propose a new algorithm for estimating the mixing matrix. After the mixing matrix is estimated, the source components are estimated in the time frequency domain using a linear programming method. In an example of the potential applications of our approach, we analyzed the EEG data that was obtained from a modified Sternberg memory experiment. Two almost uncorrelated components obtained by applying the sparse factorization method were selected for phase synchronization analysis. Several interesting findings were obtained, especially that memory-related synchronization and desynchronization appear in the alpha band, and that the strength of alpha band synchronization is related to memory performance.

Adult↗

PubMed2006

Function approximation using generalized adalines.

This paper proposes neural organization of generalized adalines (gadalines) for data driven function approximation. By generalizing the threshold function of adalines, we achieve the K-state transfer function of gadalines which responds a unitary vector of K binary values to the projection of a predictor on a receptive field. A generative component that uses the K-state activation of a gadaline to trigger K posterior independent normal variables is employed to emulate stochastic predictor-oriented target generation. The fitness of a generative component to a set of paired data mathematically translates to a mixed integer and linear programming. Since consisting of continuous and discrete variables, the mathematical framework is resolved by a hybrid of the mean field annealing and gradient descent methods. Following the leave-one-out learning strategy, the obtained learning method is extended for optimizing multiple generative components. The learning result leads to parameters of a deterministic gadaline network for function approximation. Numerical simulations further test the proposed learning method with paired data oriented from a variety of target functions. The result shows that the proposed learning method outperforms the MLP and RBF learning methods for data driven function approximation.

Algorithms↗