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At least 19 recordsLinked to original sources
PubMed2000

Correlates of simulated hill climb cycling performance.

The aim of this study was to assess the relationship between several commonly used aerobic and anaerobic cycle ergometer tests and performance during a treadmill cycling hill climb. Eight competitive cyclists (age 27+/-7 years; body mass 73.2+/-5.2 kg; height 177+/-6 cm; mean +/- s) completed six tests in random order: a lactate minimum test; a Wingate anaerobic power test; and two 6-km climbs at 6% and two 1-km climbs at 12% gradient performed on a motorized treadmill. The mean times and power outputs for the 6-km and 1-km climbs were 16:30+/-1:08 min: s and 330+/-17.8 W, and 4:19+/-0:27 min: s and 411+/-24.4 W, respectively. The best individual predictor of 6-km and 1-km performance times was the time for the corresponding climb at the other distance (r = 0.97). The next strongest predictor of both hill climb performances was the average power produced during the Wingate test divided by body mass. Stepwise regression analysis showed that the two variables contributing most to the prediction equation for both climbs were the Wingate average power per unit of body mass and maximal aerobic power divided by total mass (rider + bike), which together accounted for 92 and 96% of the variability in the 6-km and 1-km climbs. In conclusion, among competitive cyclists, the Wingate average power per unit of body mass was the best single predictor of simulated cycling hill climb performance at the distance and gradient used.

Adaptation, Physiological↗
PubMed2006

Optimal power-to-mass ratios when predicting flat and hill-climbing time-trial cycling.

The purpose of this article was to establish whether previously reported oxygen-to-mass ratios, used to predict flat and hill-climbing cycling performance, extend to similar power-to-mass ratios incorporating other, often quick and convenient measures of power output recorded in the laboratory [maximum aerobic power (W(MAP)), power output at ventilatory threshold (W(VT)) and average power output (W(AVG)) maintained during a 1 h performance test]. A proportional allometric model was used to predict the optimal power-to-mass ratios associated with cycling speeds during flat and hill-climbing cycling. The optimal models predicting flat time-trial cycling speeds were found to be (W(MAP)m(-0.48))(0.54), (W(VT)m(-0.48))(0.46) and (W(AVG)m(-0.34))(0.58) that explained 69.3, 59.1 and 96.3% of the variance in cycling speeds, respectively. Cross-validation results suggest that, in conjunction with body mass, W(MAP) can provide an accurate and independent prediction of time-trial cycling, explaining 94.6% of the variance in cycling speeds with the standard deviation about the regression line, s=0.686 km h(-1). Based on these models, there is evidence to support that previously reported VO2-to-mass ratios associated with flat cycling speed extend to other laboratory-recorded measures of power output (i.e. Wm(-0.32)). However, the power-function exponents (0.54, 0.46 and 0.58) would appear to conflict with the assumption that the cyclists' speeds should be proportional to the cube root (0.33) of power demand/expended, a finding that could be explained by other confounding variables such as bicycle geometry, tractional resistance and/or the presence of a tailwind. The models predicting 6 and 12% hill-climbing cycling speeds were found to be proportional to (W(MAP)m(-0.91))(0.66), revealing a mass exponent, 0.91, that also supports previous research.

Adult↗
PubMed2003

Use of a novel Hill-climbing genetic algorithm in protein folding simulations.

We have developed a novel Hill-climbing genetic algorithm (GA) for simulation of protein folding. The program (written in C) builds a set of Cartesian points to represent an unfolded polypeptide's backbone. The dihedral angles determining the chain's configuration are stored in an array of chromosome structures that is copied and then mutated. The fitness of the mutated chain's configuration is determined by its radius of gyration. A four-helix bundle was used to optimise simulation conditions, and the program was compared with other, larger, genetic algorithms on a variety of structures. The program ran 50% faster than other GA programs. Overall, tests on 100 non-redundant structures gave comparable results to other genetic algorithms, with the Hill-climbing program running from between 20 and 50% faster. Examples including crambin, cytochrome c, cytochrome B and hemerythrin gave good secondary structure fits with overall alpha carbon atom rms deviations of between 5 and 5.6 A with an optimised hydrophobic term in the fitness function.

Algorithms↗
PubMed2006

Effect of cycling position on oxygen uptake and preferred cadence in trained cyclists during hill climbing at various power outputs.

Numerous researchers have studied the physiological responses to seated and standing cycling, but actual field data are sparse. One open issue is the preferred cadence of trained cyclists while hill climbing. The purpose of this study, therefore, was to examine the affect of cycling position on economy and preferred cadence in trained cyclists while they climbed a moderate grade hill at various power outputs. Eight trained cyclists (25.8 +/- 7.2 years, [Formula: see text] 68.8 +/- 5.0 ml kg(-1) min(-1), peak power 407.6 +/- 69.0 W) completed a seated and standing hill climb at approximately 50, 65 and 75% of peak power output (PPO) in the order shown, although cycling position was randomized, i.e., half the cyclists stood or remained seat on their first trial at each power output. Cyclists also performed a maximal trial unrestricted by position. Heart rate, power output, and cadence were measured continuously with a power tap; ventilation [Formula: see text], BF and cadence were significantly higher with seated climbing at all intensities; there were no other physiological differences between the climbing positions. These data support the premise that trained cyclists are equally economical using high or low cadences, but may face a limit to benefits gained with increasing cadence.

Adult↗
PubMed2004

Real-coded memetic algorithms with crossover hill-climbing.

This paper presents a real-coded memetic algorithm that applies a crossover hill-climbing to solutions produced by the genetic operators. On the one hand, the memetic algorithm provides global search (reliability) by means of the promotion of high levels of population diversity. On the other, the crossover hill-climbing exploits the self-adaptive capacity of real-parameter crossover operators with the aim of producing an effective local tuning on the solutions (accuracy). An important aspect of the memetic algorithm proposed is that it adaptively assigns different local search probabilities to individuals. It was observed that the algorithm adjusts the global/local search balance according to the particularities of each problem instance. Experimental results show that, for a wide range of problems, the method we propose here consistently outperforms other real-coded memetic algorithms which appeared in the literature.

Algorithms↗
PubMed1983

Matching, maximizing, and hill-climbing.

In simple situations, animals consistently choose the better of two alternatives. On concurrent variable-interval variable-interval and variable-interval variable-ratio schedules, they approximately match aggregate choice and reinforcement ratios. The matching law attempts to explain the latter result but does not address the former. Hill-climbing rules such as momentary maximizing can account for both. We show that momentary maximizing constrains molar choice to approximate matching; that molar choice covaries with pigeons' momentary-maximizing estimate; and that the "generalized matching law" follows from almost any hill-climbing rule.

Journal Article↗
PubMedDate not supplied

A hill-climbing approach for automatic gridding of cDNA microarray images.

Image and statistical analysis are two important stages of cDNA microarrays. Of these, gridding is necessary to accurately identify the location of each spot while extracting spot intensities from the microarray images and automating this procedure permits high-throughput analysis. Due to the deficiencies of the equipment used to print the arrays, rotations, misalignments, high contamination with noise and artifacts, and the enormous amount of data generated, solving the gridding problem by means of an automatic system is not trivial. Existing techniques to solve the automatic grid segmentation problem cover only limited aspects of this challenging problem and require the user to specify the size of the spots, the number of rows and columns in the grid, and boundary conditions. In this paper, a hill-climbing automatic gridding and spot quantification technique is proposed which takes a microarray image (or a subgrid) as input and makes no assumptions about the size of the spots, rows, and columns in the grid. The proposed method is based on a hill-climbing approach that utilizes different objective functions. The method has been found to effectively detect the grids on microarray images drawn from databases from GEO and the Stanford genomic laboratories.

Algorithms↗
PubMed1983

Hill-climbing by pigeons.

Pigeons were exposed to two types of concurrent operant-reinforcement schedules in order to determine what choice rules determine behavior on these schedules. In the first set of experiments, concurrent variable-interval, variable-interval schedules, key-peck responses to either of two alternative schedules produced food reinforcement after a random time interval. The frequency of food-reinforcement availability for the two schedules was varied over different ranges for different birds. In the second series of experiments, concurrent variable-ratio, variable-interval schedules, key-peck responses to one schedule produced food reinforcement after a random time interval, whereas food reinforcement occurred for an alternative schedule only after a random number of responses. Results from both experiments showed that pigeons consistently follow a behavioral strategy in which the alternative schedule chosen at any time is the one which offers the highest momentary reinforcement probability (momentary maximizing). The quality of momentary maximizing was somewhat higher and more consistent when both alternative reinforcement schedules were time-based than when one schedule was time-based and the alternative response-count based. Previous attempts to provide evidence for the existence of momentary maximizing were shown to be based upon faulty assumptions about the behavior implied by momentary maximizing and resultant inappropriate measures of behavior.

Journal Article↗
PubMed2006

An effective structure learning method for constructing gene networks.

MOTIVATION: Bayesian network methods have shown promise in gene regulatory network reconstruction because of their capability of capturing causal relationships between genes and handling data with noises found in biological experiments. The problem of learning network structures, however, is NP hard. Consequently, heuristic methods such as hill climbing are used for structure learning. For networks of a moderate size, hill climbing methods are not computationally efficient. Furthermore, relatively low accuracy of the learned structures may be observed. The purpose of this article is to present a novel structure learning method for gene network discovery. RESULTS: In this paper, we present a novel structure learning method to reconstruct the underlying gene networks from the observational gene expression data. Unlike hill climbing approaches, the proposed method first constructs an undirected network based on mutual information between two nodes and then splits the structure into substructures. The directional orientations for the edges that connect two nodes are then obtained by optimizing a scoring function for each substructure. Our method is evaluated using two benchmark network datasets with known structures. The results show that the proposed method can identify networks that are close to the optimal structures. It outperforms hill climbing methods in terms of both computation time and predicted structure accuracy. We also apply the method to gene expression data measured during the yeast cycle and show the effectiveness of the proposed method for network reconstruction.

Algorithms↗
PubMed2004

What makes an insight problem? The roles of heuristics, goal conception, and solution recoding in knowledge-lean problems.

Four experiments investigated transformation problems with insight characteristics. In Experiment 1, performance on a version of the 6-coin problem that had a concrete and visualizable solution followed a hill-climbing heuristic. Experiment 2 demonstrated that the difficulty of a version of the problem that potentially required insight for solution stems from the same hill-climbing heuristic, which creates an implicit conceptual block. Experiment 3 confirmed that the difficulty of the potential insight solution is conceptual, not procedural. Experiment 4 demonstrated the same principles of move selection on the 6-coin problem and the 10-coin (triangle) problem. It is argued that hill-climbing heuristics provide a common framework for understanding transformation and insight problem solving. Postsolution receding may account for part of the phenomenology of insight.

Cognition↗
PubMed1995

Search strategies for applied molecular evolution.

A new approach to drug discovery is based on the generation of high diversity libraries of DNA, RNA, peptides or small molecules. Search of such libraries for useful molecules is an optimization problem on high-dimensional molecular fitness landscapes. We utilize a spin-glass-like model, the NK model, to analyze search strategies based on pooling, mutation, recombination and selective hill-climbing. Our results suggest that pooling followed by recombination and/or hill-climbing finds better candidate molecules than pooling alone on most molecular landscapes. Our results point to new experiments to assess the structure of molecular fitness landscapes and improve current models.

Drug Design↗
PubMed1996

Seated versus standing cycling in competitive road cyclists: uphill climbing and maximal oxygen uptake.

Seven competitive road cyclists (M +/- SE = 23.7 +/- 1.5 yr, 70.5 +/- 1.7 kg) participated to determine the effects of cycling body position on physiological responses during uphill cycling and maximal oxygen uptake (VO2max). There was no significant difference in VO2max between seated and standing positions on a cycle ergometer (66.4 +/- 1.6 vs. 66.4 +/- 1.7 ml . kg-1 . min-1). When the subjects rode their own bicycle on a treadmill, oxygen uptake and heart rate were significantly (p < 0.05) higher during standing when subjects bicycled at 20.0 km . h-1 (4% grade), but no difference was observed when riding at 12.3 km . h-1 (10% grade). Leg RPE was significantly (p < 0.05) lower for standing position up a 10% grade. The results suggest that the standing position is less economical during moderate hill climbing, but during steep hill climbing, it results in a decreased sensation of effort in the legs.

Adult↗
PubMed2004

MoDEL: an efficient strategy for ungapped local multiple alignment.

We introduce a method for ungapped local multiple alignment (ULMA) in a given set of amino acid or nucleotide sequences. This method explores two search spaces using a linked optimization strategy. The first search space M consists of all possible words of a given length W, defined on the residue alphabet. An evolutionary algorithm searches this space globally. The second search space P consists of all possible ULMAs in the sequence set, each ULMA being represented by a position vector defining exactly one subsequence of length W per sequence. This search space is sampled with hill-climbing processes. The search of both spaces are coupled by projecting high scoring results from the global evolutionary search of M onto P. The hill-climbing processes then refine the optimization by local search, using the relative entropy between the ULMA and background residue frequencies as an objective function. We demonstrate some advantages of our strategy by analyzing difficult natural amino acid sequences and artificial datasets. A web interface is available at

Algorithms↗
PubMed1989

Protein evolution on rugged landscapes.

We analyze a mathematical model of protein evolution in which the evolutionary process is viewed as hill-climbing on a random fitness landscape. In studying the structure of such landscapes, we note that a large number of local optima exist, and we calculate the time and number of mutational changes until a protein gets trapped at a local optimum. Such a hill-climbing process may underlie the evolution of antibody molecules by somatic hypermutation.

Biological Evolution↗
PubMed2005

Accurate prediction of kidney allograft outcome based on creatinine course in the first 6 months posttransplant.

Most attempts to predict early kidney allograft loss are based on the patient and donor characteristics at baseline. We investigated how the early posttransplant creatinine course compares to baseline information in the prediction of kidney graft failure within the first 4 years after transplantation. Two approaches to create a prediction rule for early graft failure were evaluated. First, the whole data set was analysed using a decision-tree building software. The software, rpart, builds classification or regression models; the resulting models can be represented as binary trees. In the second approach, a Hill-Climbing algorithm was applied to define cut-off values for the median creatinine level and creatinine slope in the period between day 60 and 180 after transplantation. Of the 497 patients available for analysis, 52 (10.5%) experienced an early graft loss (graft loss within the first 4 years after transplantation). From the rpart algorithm, a single decision criterion emerged: Median creatinine value on days 60 to 180 higher than 3.1 mg/dL predicts early graft failure (accuracy 95.2% but sensitivity = 42.3%). In contrast, the Hill-Climbing algorithm delivered a cut-off of 1.8 mg/dL for the median creatinine level and a cut-off of 0.3 mg/dL per month for the creatinine slope (sensitivity = 69.5% and specificity 79.0%). Prediction rules based on median and slope of creatinine levels in the first half year after transplantation allow early identification of patients who are at risk of loosing their graft early after transplantation. These patients may benefit from therapeutic measures tailored for this high-risk setting.

Creatinine↗
PubMed2004

New hybrid stochastic-deterministic technique for fast registration of dermatological images.

Digital image processing in the medical field has become very popular in recent years owing to the significant advantages it offers over conventional techniques of visual or analogue image analysis. One of the most significant aspects in medical image processing has been that of image registration, which deals with the task of registering two images taken under different conditions. Image registration is considered an important issue in the field of dermatology, as pictures of a lesion taken in different periods need to be compared and quantitatively analysed. A hybrid image registration scheme was developed and evaluated for dermatological applications. The method splits the parameter estimation problem into two, with a combination of deterministic and iterative estimation techniques. The scaling and rotation parameters are estimated using a cross-correlation of image invariant image descriptors algorithm, whereas the two translation parameters are estimated with a non-parametric similarity criterion and a hill-climbing optimisation scheme. The efficacy of the method has been validated for the registration and comparison of malignant melanoma images. Determination of rotation and scaling parameters was performed using the log-polar transformation technique, which proved to be very accurate, even when high rotation and scaling values were imposed. Deviations for the rotation parameter estimations were less than 0.5%, whereas, for the scaling factor, differences were on average less than 2.5%, with a maximum difference estimated to be 4.5%. Translation parameter estimation was performed using integer similarity measures namely the stochastic sign change, the deterministic sign change (DSC) and the window value range, the performance of which has been assessed and, in all cases, was found to be highly effective. A novel hill-climbing optimisation algorithm has been proposed and, in combination with the DSC similarity criterion, was evaluated and proved to successfully estimate translation parameters. Thus the proposed hybrid registration technique can successfully estimate problem parameters in a time-efficient manner.

Algorithms↗