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PubMed1999

Simultaneous Optimization of Feeding Rate and Operation Parameters for Fed-Batch Fermentation Processes.

An efficient method is introduced for simultaneously determining optimal polices of feeding rate and operation parameters for a fermentation process. Such an optimization problem is converted into the finite dimensional optimization problem using the control parametrization technique. The hybrid differential evolution is introduced to solve the converted problem. The optimal production rate obtained by the simultaneous optimization approach could be significantly improved with comparison to a simplified optimization problem, which is considered the optimal feed control only, as observed from the simulation results.

Journal Article↗

PubMed2003

Life cycle optimization of automobile replacement: model and application.

Although recent progress in automotive technology has reduced exhaust emissions per mile for new cars, the continuing use of inefficient, higher-polluting old cars as well as increasing vehicle miles driven are undermining the benefits of this progress. As a way to address the "inefficient old vehicle" contribution to this problem, a novel life cycle optimization (LCO) model is introduced and applied to the automobile replacement policy question. The LCO model determines optimal vehicle lifetimes, accounting for technology improvements of new models while considering deteriorating efficiencies of existing models. Life cycle inventories for different vehicle models that represent materials production, manufacturing, use, maintenance, and end-of-life environmental burdens are required as inputs to the LCO model. As a demonstration, the LCO model was applied to mid-sized passenger car models between 1985 and 2020. An optimization was conducted to minimize cumulative carbon monoxide (CO), non-methane hydrocarbon (NMHC), oxides of nitrogen (NOx), carbon dioxide (CO2), and energy use over the time horizon (1985-2020). For CO, NMHC, and NOx pollutants with 12000 mi of annual mileage, automobile lifetimes ranging from 3 to 6 yr are optimal for the 1980s and early 1990s model years while the optimal lifetimes are expected to be 7-14 yr for model year 2000s and beyond. On the other hand, a lifetime of 18 yr minimizes cumulative energy and CO2 based on driving 12000 miles annually. Optimal lifetimes are inversely correlated to annual vehicle mileage, especially for CO, NMHC, and NOx emissions. On the basis of the optimization results, policies improving durability of emission controls, retiring high-emitting vehicles, and improving fuel economies are discussed.

Air Pollution↗

PubMed2001

Impact of pharmacokinetic-pharmacodynamic model linearization on the accuracy of population information matrix and optimal design.

Influence of experimental design on hyperparameter estimates precision when performing a population pharmacokinetic-pharmacodynamic (PK-PD) analysis has been shown by several studies and various approaches have been proposed for optimizing or evaluating such designs. Some of these methods rely on the optimization of a suitable scalar function of the population information matrix. Unfortunately for the nonlinear models encountered in pharmacokinetics or pharmacodynamics the latter is particularly difficult to evaluate. Under some assumptions and after a linearization of the PK-PD model a closed form of this matrix can be obtained which considerably simplifies its calculation but leads to an approximation. The aim of this paper is to evaluate the quality of the latter and its potential impact, when comparing or optimizing population designs and to relate it to Bates and Watts curvature measures. Two models commonly used in PK-PD were considered and nominal hyperparameter values when chosen for each one. Several population designs were studied and the associated population information matrix was computed for each using the approximate procedure and also using a reference method. Design optimizations were calculated under constraints for each model from the reference and approximate population information matrix. Nonlinearity curvatures were also computed for every model and design. The impact of model linearization when calculating the population information matrix was then examined in terms of lower bound accuracies on the hyperparameter estimates, design criterion variation, as well as D-optimal population designs, these results being related to nonlinearity curvature measures. Our results emphasize the influence of the parameter effects curvature when deriving the lower bounds of the hyperparameter estimates precision for a given design from the approximate population information matrix especially for hyperparameters quantifying the PK-PD interindividual variability. No discrepancies were detected between the population D-optimal designs obtained from the approximate and reference matrix despite some minor differences in criterion variation with respect to the design. More pronounced differences were, however, observed when comparing the amplitudes of criterion variation which can lead to errors when calculating design efficiencies. From a practical point of view, a strategy easily applicable by the pharmacokineticist for avoiding such problems in the context of population design optimization or comparison is then proposed.

Humans↗

PubMed1998

Identification of the optimal parameters for recording cortical evoked potentials to human oesophageal electrical stimulation.

Cortical evoked potentials in response to stimulation of the oesophagus may prove to be a powerful technique for assessing the oesophageal afferent pathway in health and disease. However, in order to maximize the potential of this technique it is essential that the optimal parameters for recording oesophageal CEP are established. The aim was to determine the optimal parameters required to record reproducible CEP. CEP were recorded from the vertex in eight subjects (age range 23-44 years). Electrical stimulation was performed 5 cm above the lower oesophageal sphincter using a bipolar ring electrode at 0.2 Hz. Protocol 1: to determine the stimulation intensity which generates the largest amplitude and shortest latency, two runs of 50 stimuli were applied at increasing intensities. Protocol 2: to determine the number of stimuli for optimal signal to noise ratio, 10 runs of 50 stimuli were recorded. Individual runs were averaged. Protocol 3: to determine the optimal inter-run interval, CEP evoked by 200 stimuli were averaged using randomly chosen inter-run intervals. Protocol 4: CEP reproducibility using parameters determined from Protocols 1-3 was assessed in three subjects on three separate occasions. The results were as follows: Protocol 1; P1 latency was shortest and P1-N1 amplitude largest at an intensity of 75% above threshold. Protocol 2; optimal signal-to-noise was achieved by averaging four runs of 50 stimuli. Protocol 3; the optimal interstudy interval was 10 min. Protocol 4; highly reproducible CEP were obtained in all individuals. Using these optimal parameters, it is possible to obtain highly reproducible oesophageal CEP to ES which can now be used for clinical study.

Adult↗

PubMed1988

Epidemiology of infantile hydrocephalus in Sweden. Reduced optimality in prepartum, partum and postpartum conditions. A case-control study.

The optimality concept developed by Prechtl was adopted to investigate a population-based series of infantile hydrocephalus (IH). The results were compared with those from a control series of newborns. The case series comprised 128 IH children born at term and 50 born preterm, and the control series 269 and 176, respectively. Cases with a prenatal cause of IH, as compared with those with a perinatal cause and controls, had significantly increased risk of IH by reduced optimality in the prepartum period. Peaks in the flow of non-optimal items in the prenatal group were repeated abortions or perinatal death in previous pregnancies, maternal disorder and twin birth. The profile of reduced optimality in term IH cases of undefined cause was similar to that of term cases with a prenatal cause. All IH cases had significantly increased reduced optimality in the postpartum period compared with controls. The increase was massive in cases where IH was of perinatal cause, with peaks in items of acidosis, apnea, respiratory treatment, infection and cerebral irritation. Reduced optimality in partum conditions did not discriminate between IH of pre- and perinatal cause. Reduced optimality in the prepartum, partum and postpartum periods in IH children, as compared with those with cerebral palsy syndromes, was nearly identical to that of hemiplegic, and significantly lower than that of diplegic and dyskinetic, cerebral palsy.

Female↗

PubMed2004

An adaptive immune optimization algorithm for energy minimization problems.

Based on the immune theory of biology, a novel evolutionary algorithm, adaptive immune optimization algorithm (AIOA), is proposed. In AIOA, density regulation and immune selection is adopted to control the individual diversity and the convergence adaptively. By an application of the algorithm to the optimization of test functions, it is shown that the algorithm is a highly efficient optimization method compared with other stochastic optimization methods. The algorithm was also applied to the optimization of Lennard-Jones clusters, and the results show that the method can find the optimal structure of N</=80 with a very high efficiency. The proposed algorithm may be a good tool for fast global optimization in chemical or biological molecular simulations.

Journal Article↗

PubMed2004

Parallel iterative reaction path optimization in ab initio quantum mechanical/molecular mechanical modeling of enzyme reactions.

The determination of reaction paths for enzyme systems remains a great challenge for current computational methods. In this paper we present an efficient method for the determination of minimum energy reaction paths with the ab initio quantum mechanical/molecular mechanical approach. Our method is based on an adaptation of the path optimization procedure by Ayala and Schlegel for small molecules in gas phase, the iterative quantum mechanical/molecular mechanical (QM/MM) optimization method developed earlier in our laboratory and the introduction of a new metric defining the distance between different structures in the configuration space. In this method we represent the reaction path by a discrete set of structures. For each structure we partition the atoms into a core set that usually includes the QM subsystem and an environment set that usually includes the MM subsystem. These two sets are optimized iteratively: the core set is optimized to approximate the reaction path while the environment set is optimized to the corresponding energy minimum. In the optimization of the core set of atoms for the reaction path, we introduce a new metric to define the distances between the points on the reaction path, which excludes the soft degrees of freedom from the environment set and includes extra weights on coordinates describing chemical changes. Because the reaction path is represented by discrete structures and the optimization for each can be performed individually with very limited coupling, our method can be executed in a natural and efficient parallelization, with each processor handling one of the structures. We demonstrate the applicability and efficiency of our method by testing it on two systems previously studied by our group, triosephosphate isomerase and 4-oxalocrotonate tautomerase. In both cases the minimum energy paths for both enzymes agree with the previously reported paths.

Algorithms↗

PubMed2006

Density-functional geometry optimization of the 150,000-atom photosystem-I trimer.

We present a linear-scaling method based on the use of density-functional theory (DFT) for the system-wide optimization of x-ray structural coordinates and apply it to optimize the 150,000 atoms of the photosystem-I (PS-I) trimer. The method is based on repetitive applications of a multilevel ONIOM procedure using the PW916-31G(d) DFT calculations for the high level and PM3 for the lower level; this method treats all atoms in the structure equivalently, a structure in which the majority of the atoms can be considered as part of some internal "active site." To obtain a realistic single structure, some changes to the original protein model were necessary but these are kept to a minimum in order that the optimized structure most closely resembles the original x-ray one. Optimization has profound effects on the perceived electronic properties of the cofactors, with, e.g., optimization lowering the internal energy of the chlorophylls by on average 53 kcal mol(-1) and eliminates the enormous 115 kcal mol(-1) energy spread depicted by the original x-ray heavy-atom coordinates. A highly precise structure for PS-I results that is suitable for analysis of device function. Significant qualitative features of the structure are also improved such as correction of an error in the stereochemistry of one of the chlorophylls in the "special pair" of the reaction center, as well as the replacement of a water molecule with a metal cation in a critical region on the C3 axis. The method also reveals other unusual features of the structure, leading both to suggestions concerning device functionality and possible mutations between gene sequencing and x-ray structure determination. The optimization scheme is thus shown to augment the molecular modeling schemes that are currently used to add medium-resolution structural information to the raw scattering data in order to obtain atomically resolved structures. System-wide optimization is now a feasible process and its use within protein x-ray data refinement should be considered.

Binding Sites↗

PubMed2006

Optimal work-rest cycles for an isometric intermittent gripping task as a function of force, posture and grip span.

The aim of this study was to investigate the maximum acceptable contraction frequencies (i.e. work-rest cycles) for an isometric-intermittent handgrip task as a function of grip span, applied force and shoulder posture using psychophysical and physiological approaches. Twelve healthy males served as subjects. The three grip spans investigated were the optimal, 2 cm narrower than the optimal, and 2 cm wider than the optimal. The grip force levels studied were 15% and 30% of maximum voluntary grip force and the two shoulder postures were 25 degrees flexion and 30 degrees abduction. The psychophysical results indicate that subjects work faster with the narrower grip span at 15% of maximum voluntary grip force level in comparison to working with the optimal and the wider spans. However, when the task required 30% of maximum grip force level, the subjects worked faster with the optimal grip span. These findings were supported by the results of electromyography, heart rate, blood pressure and perceived discomfort. The study suggests that grip span of a tool is an important factor to be considered in predicting optimal work-rest cycles for hand grip tasks, and the optimum setting of grip span of the hand-tool depends on the required task force level. That is, the optimality is relative rather than absolute. In addition, it appears that weaker subjects can work at a higher rate than stronger ones at the same relative force level.

Adult↗

PubMed2004

Evaluation of parallel decomposition methods for biomechanical optimizations.

As the complexity of musculoskeletal models continues to increase, so will the computational demands of biomechanical optimizations. For this reason, parallel biomechanical optimizations are becoming more common. Most implementations parallelize the optimizer. In this study, an alternate approach is investigated that parallelizes the analysis function (i.e., a kinematic or dynamic simulation) called repeatedly by the optimizer to calculate the cost function and constraints. To evaluate this approach, a system identification problem involving a kinematic ankle joint model was solved using a gradient-based optimizer and three parallel decomposition methods: gradient calculation decomposition, analysis function decomposition, or both methods combined. For a given number of processors, analysis function decomposition exhibited the best performance despite the highest communication and synchronization overhead, while gradient calculation decomposition demonstrated the worst performance due to the fact that the necessary line searches were not performed in parallel. These findings suggest that the method of parallelization most commonly used for biomechanical optimizations may not be the most efficient, depending on the optimization algorithm used. In many applications, the best computational strategy may be to focus on parallelizing the analysis function.

Algorithms↗

PubMed1997

Optimizing the movement of a single absorber for 1D non-uniform dose delivery by (fast) simulated annealing.

A new simplified technique for 1D non-uniform dose delivery using a single dynamic absorber, driven by a computer system, has been recently proposed together with a simple analytic algorithm. This technique uses an optimized 'stepped' absorber's speed profile and the generated fluence profile is an approximation of the desired radiation beam. In the case of non-uniform beam profiles with multiple maxima/minima, the original proposed 'stepping algorithm' has some limitations and produces a too rough approximation of the desired profiles. In order to increase the agreement between desired and generated profiles, more sophisticated optimization schemes are required. In this paper we have applied a variant of simulated annealing (SA) as a statistical optimization algorithm to further investigate the possibilities and the limits of the single-absorber technique in the field of 1D intensity modulation. In the current application the cost function used is the mean square root of the percentage differences between desired and generated profiles, the absorber's resting times have been chosen as optimization variables and at each iteration just one variable is randomly changed, adding an incremental 'grain'. A Cauchy generating function is used, different cooling schedules are evaluated; constraints related to our apparatus are introduced and starting annealing parameters are set after some initial optimization tests. The method is tested in reproducing theoretical non-uniform beams, by comparing desired modulated fluence profiles with calculated fluence profiles obtainable with the single absorber after the derivation of optimized speed profiles by the proposed SA approach. The results of these simulations show that the application of the SA method optimizes the single absorber's performance and that clinically important modulated beams useful for conformal radiotherapy can be accurately reproduced.

Algorithms↗

PubMed2000

Hardware-sensitive optimization for intensity modulated radiotherapy.

The multileaf collimator (MLC) hardware constraints are usually neglected in the process of intensity-modulated beam optimization. Consequently, it is not always possible to deliver planned beam modulation using dynamic MLC. Beam optimization is significantly diminished if the results must be approximated due to limitations imposed by the delivery device. To overcome this problem, an inverse beam optimization method which incorporates the hardware constraints has been developed. The hardware constraints, including the leaf velocity, the dose rate and the minimum required gap between opposing and adjacent leaves, were considered. An iterative search for feasible modulation was conducted alternately in the dosimetric space and the MLC position-time space. The optimization algorithm was designed for a unidirectional leaf trajectory and a constant dose rate. A scheme to reduce tongue-and-groove underdosage during optimization was also implemented. Comparisons were made between the solutions produced by this method and conventional optimization disregarding the hardware restrictions. The beam profiles generated by the conventional method were modified to satisfy the hardware specifications. The results indicate that inclusion of MLC constraints during optimization can improve the degree of conformity that is deliverable.

Algorithms↗

PubMed2002

Re-optimization in adaptive radiotherapy.

In routine clinical practice, radiotherapy treatment planning is performed based on the patient CT images obtained during the patient setup procedure. However, the actual delivered dose to the patient might be different from the planned dose because of various reasons such as patient motion. Under such situations, it is desirable to modify the original treatment plan in order to partially remedy the dose delivery errors in the subsequent dose delivery process. Such modification can be implemented by modifying the original treatment plan using re-optimization. In this work, issues such as the re-optimization dose prescription, optimization constraints in re-optimization, re-optimization in multiple fractionation schemes and re-optimization procedure with generalized dose-based objective functions were investigated and corresponding mathematical schemes proposed. The derived results were applied to a clinical case study in which it was shown that the proposed re-optimization method is able to remedy the cold spots in tumour while delivering low dose to normal structures. Thus the potential effectiveness of the method was demonstrated.

Algorithms↗

PubMedDate not supplied

Performance of threading scoring functions designed using new optimization method.

We present a new procedure for optimization of a threading scoring function. A scoring function is usually formulated in terms of the structural environment states that describe the protein fold model. We propose a method for the optimal selection of those structural environment states that naturally follows from the probabilistic description of the threading problem and is done prior to threading experiments. We demonstrate the selection of the optimal structural environment states for the solvent exposure of the amino acid position, and present the results of threading experiments performed using scoring functions designed with and without the optimization of the structural environment states. These results confirm that the optimal scoring function predicts the sequence-to-structure alignments most accurately. Threading experiments performed with 15 optimally designed scoring functions show that the correlation coefficient between the information content of the amino acid distribution that determines the scoring function and the accuracy of the optimal sequence-to-structure alignment is 0.94.

Amino Acid Sequence↗

PubMed2004

DNA/MVA vaccine for HIV type 1: effects of codon-optimization and the expression of aggregates or virus-like particles on the immunogenicity of the DNA prime.

Recently, a vaccine consisting of DNA priming followed by boosting with modified vaccinia Ankara (MVA) has provided long-term protection of rhesus macaques against a virulent challenge with a chimera of simian and human immunodeficiency viruses. Here, we report studies on the development of the DNA component for a DNA/MVA HIV vaccine for humans. Specifically, we assess the ability of a codon-optimized Gag-expressing DNA and two noncodon-optimized Gag-Pol-Env-expressing DNAs to prime the MVA booster dose. The codon-optimized DNA expressed virus-like particles (VLPs), whereas one of the noncodon-optimized DNAs expressed VLPs and the other expressed aggregates of HIV proteins. The MVA boost expressed Gag-Pol and Env and produced VLPs. Immunogenicity studies in macaques used one intramuscular prime with 600 microg of DNA and two intramuscular boosts with 1 x 10(8) pfu of MVA at weeks 8 and 30. The codon-optimized and noncodon-optimized DNAs proved similar in their ability to prime anti-Gag T cell responses. The aggregate and VLP-expressing Gag-Pol-Env DNAs also showed no significant differences in their ability to prime anti-Env Ab responses. The second MVA booster dose did not increase the peak CD4 and CD8 T cell responses, but increased anti-Env Ab titers by 40- to 90-fold. MVA-only immunizations elicited 10-100 times lower frequencies of T cells and 2-4 lower titers of anti-Env Ab than the Gag-Pol-Env DNA/MVA immunizations. Based on the breadth of the T cell response and a trend toward higher titers of anti-Env Ab, we are moving forward with human trials of the noncodon-optimized VLP-expressing DNA.

AIDS Vaccines↗

PubMed2006

Optimal sum-of-pairs multiple sequence alignment using incremental Carrillo and Lipman bounds.

Alignment of sequences is an important routine in various areas of science, notably molecular biology. Multiple sequence alignment is a computationally hard optimization problem which involves the consideration of different possible alignments in order to find an optimal one, given a measure of goodness of alignments. Dynamic programming algorithms are generally well suited for the search of optimal alignments, but are constrained by unwieldy space requirements for large numbers of sequences. Carrillo and Lipman devised a method that helps to reduce the search space for an optimal alignment under a sum-of-pairs measure using bounds on the scores of its pairwise projections. In this paper, we generalize Carrillo and Lipman bounds and demonstrate a novel approach for finding optimal sum-of-pairs multiple alignments that allows incremental pruning of the optimal alignment search space. This approach can result in a drastic pruning of the final search space polytope (where we search for the optimal alignment) when compared to Carrillo and Lipman's approach and hence allows many runs that are not feasible with the original method.

Algorithms↗

PubMed2026

Theseus: fast and optimal affine-gap sequence-to-graph alignment.

MOTIVATION: Sequence-to-graph alignment is a central problem in bioinformatics, with applications in multiple sequence alignment (MSA) and pangenome analysis, among others. However, current algorithms for optimal affine-gap alignment impose high memory and computational requirements, limiting their scalability to aligning long sequences to complex graphs. Practical solutions partially address this problem using heuristic strategies that ultimately trade off optimality for speed. RESULTS: This work presents Theseus, a novel, fast, and optimal affine-gap sequence-to-graph alignment algorithm. Theseus leverages similarities between genomic sequences to accelerate the alignment computation and reduces the overall memory requirements without compromising optimality. To that end, Theseus processes only a subset of the dynamic programming cells, using a sparse-data strategy that enables efficient sequence-to-graph alignment. Moreover, our algorithm supports optimal affine-gap alignment on arbitrary directed graphs, including those with cycles. We evaluate Theseus on two key problems: MSA and pangenome read mapping. For MSA, we compare it against SPOA, abPOA, and POASTA. Theseus is 1.6× to 17.6× faster than POASTA, and 7.3× faster, on average, than SPOA, both optimal aligners. Compared with abPOA, Theseus ensures optimality and scales to the largest problems. For pangenome read mapping, we benchmark Theseus against the alignment stage of the mapping tool vg map, along with the alignment kernels of SPOA, abPOA, and POASTA. Theseus outperforms the other methods, showing a 1.9× to 16.9× speedup on short reads. Moreover, Theseus is 1.5× to 36.3× faster than vg when aligning against synthetic cyclic graphs. AVAILABILITY AND IMPLEMENTATION: Theseus code and documentation are publicly available at https://github.com/albertjimenezbl/theseus-lib.

Algorithms↗

PubMed2005

Optimal design and efficiency of two-phase case-control studies with error-prone and error-free exposure measures.

This paper addresses optimal design and efficiency of two-phase (2P) case-control studies in which the first phase uses an error-prone exposure measure, Z, while the second phase measures true, dichotomous exposure, X, in a subset of subjects. Optimal design of a separate second phase, to be added to a preexisting study, is also investigated. Differential misclassification is assumed throughout. Results are also applicable to 2P cohort studies with error-prone and error-free measures of disease status but error-free exposure measures. While software based on the mean score method of Reilly and Pepe (1995, Biometrika 82, 299--314) can find optimal designs given pilot data, the lack of simple formulae makes it difficult to generalize about efficiency compared to one-phase (1P) studies based on X alone. Here, formulae for the optimal ratios of cases to controls and first- to second-phase sizes, and the optimal second-phase stratified sampling fractions, given a fixed budget, are given. The maximum efficiency of 2P designs compared to a 1P design is deduced and is shown to be bounded from above by a function of the sensitivities and specificities of Z. The efficiency of 'balanced' separate second-phase designs (Breslow and Cain, 1988, Biometrika 75, 11--20)-in which equal numbers of subjects are chosen from each first-phase strata-compared to optimal design is deduced, enabling situations where balanced designs are nearly optimal to be identified.

Blotting, Western↗