2,499 research outputs found
A study on choice and reaction time
SUMMARY:
Every day we have to make choices, to solve small and big life problems, and we behave accordingly. The experience becomes crucial and determinant in sport situation. The research intends to propose an analysis, at a first level, of the main factors involved in choice and action. The direction and the conditions proposed by the study could be a framework for future research and for further developments in sport.
Selection among options, choice, focal action and the time of reaction are the centre of the investigation. The main parameters are choice and reaction time. Choice describes the process of weighting and picking the more suitable alternative. Reaction time is the time of preparation and execution, the time during selection, choice, and the performing of the focal action, which ends at the recording of the data.
Reaction time period and choice events were analysed separately. Choice, in particular, was related to a positive prediction, that is to a correct answer. Among the variables involved in the experimental situation, choice, reward, delay and cues were chosen. The main aim was to find the change in reaction time, when a correct response could be predicted.
A special Reaction Time Device was built up, tailored on the specific needs of the experiments. The period between a visual “go” signal and a target touching by an arm, the focal action, was the time of reaction. The feedback given by the Device informed the subject on the correct or not correct choice. A basic protocol was defined, and the experimental plan, built up by 4 steps, related to specific aims, was fixed.
The first step had an introductory role. It tested simple and choice conditions. Random sequences and random delays were presented. Choice reaction time was examined when dominant, non-dominant and either arm were performing. The final evaluations allow detecting correct and incorrect answer factors, and the effect of different delays, as first reference of these components. The data register no difference in reaction time between dominant and non dominant arm performed during choice.
The second step involved reward factor. The aim was to compare reaction time without and with a possibility of reward. The results showed that at those conditions, no significant reaction time difference was registered.
The third step examined the delay factor and tested the reaction time when a variable or a fixed foreperiod was presented, before the “go” signal. It was concluded that there is no significant difference in time of reaction between a constant and a changeable delay.
The contractions of the subject’s focal and postural adjustment representative muscles were simultaneously recorded during the tests through EMG, to check the preparation phase and, eventually, a possible change in muscle contractions during the selection of the alternatives. The results confirmed that choice is a high level process and that, at least at those conditions, muscles are involved only at the last, final stage, after selection.
The former 3-step experiments had the role of premise to test the weight of some relevant variables. The centre of decision-making process is guessing, is anticipating the event. It implies the presence of clues, which can be identified, recognised and can lead the person to predict the next answer. This was the main motive of the fourth step. Three of the four sequences had a pattern, made up by 3 numbers, presented 4 times in the same sequence. The reaction time results included very short and very long values, far from the normal distribution. They were transformed in Log (- 350), to get coefficients suitable to be processed through parametric tests.
The numbers suggested that after the first experiences of the pattern, some subjects, having the feedback at each trial, identified and recognised the regularity and tended to be more correct at the last presentation. Some of them took a longer time to come to a choice, some were quicker. Two among 3 patterns were detected easier. In one of the 3 special sequences, the percentage of pattern correct answers was 48%, beyond the probability limit. It means that nearly half of the answers were positive and nearly half of the people guessed the pattern.
There was a clear difference in percentage of correct answers between the random sequence, which remained within the probability percentage, 33%, and 2 of the 3 sequences. In addition the percentage of patterned correct answer was higher than the total percentage of positive responses, inside the same sequence. Nevertheless in statistical terms the p values were not significant.
The 2 factors tested during the investigation, reaction time and choice, showed that, at the specific conditions of the experiments, there is no clear reciprocal correspondence. Unlike the studies in the field, correct answers were not directly related to lower reaction times, as expected, in patterned trials. Sometimes the subjects took more time to make their choice.
Short and long reactions, within the same subject and among quick and slow volunteers, balanced the data. The results were not significant, nevertheless the differences were evident and in the right direction.
The conclusion was that in a choice situation, when guessing was encouraged by cues to get correct response, the number of patterned correct trials tended to increase, in particular at the last repetition of the pattern.
The analysis on reaction time could not confirm the expected relationship between pattern correct trials, a sign of guessed cue, and a decreasing time of reaction
PIntron: a Fast Method for Gene Structure Prediction via Maximal Pairings of a Pattern and a Text
Current computational methods for exon-intron structure prediction from a
cluster of transcript (EST, mRNA) data do not exhibit the time and space
efficiency necessary to process large clusters of over than 20,000 ESTs and
genes longer than 1Mb. Guaranteeing both accuracy and efficiency seems to be a
computational goal quite far to be achieved, since accuracy is strictly related
to exploiting the inherent redundancy of information present in a large
cluster. We propose a fast method for the problem that combines two ideas: a
novel algorithm of proved small time complexity for computing spliced
alignments of a transcript against a genome, and an efficient algorithm that
exploits the inherent redundancy of information in a cluster of transcripts to
select, among all possible factorizations of EST sequences, those allowing to
infer splice site junctions that are highly confirmed by the input data. The
EST alignment procedure is based on the construction of maximal embeddings that
are sequences obtained from paths of a graph structure, called Embedding Graph,
whose vertices are the maximal pairings of a genomic sequence T and an EST P.
The procedure runs in time linear in the size of P, T and of the output.
PIntron, the software tool implementing our methodology, is able to process in
a few seconds some critical genes that are not manageable by other gene
structure prediction tools. At the same time, PIntron exhibits high accuracy
(sensitivity and specificity) when compared with ENCODE data. Detailed
experimental data, additional results and PIntron software are available at
http://www.algolab.eu/PIntron
Pure Parsimony Xor Haplotyping
The haplotype resolution from xor-genotype data has been recently formulated
as a new model for genetic studies. The xor-genotype data is a cheaply
obtainable type of data distinguishing heterozygous from homozygous sites
without identifying the homozygous alleles. In this paper we propose a
formulation based on a well-known model used in haplotype inference: pure
parsimony. We exhibit exact solutions of the problem by providing polynomial
time algorithms for some restricted cases and a fixed-parameter algorithm for
the general case. These results are based on some interesting combinatorial
properties of a graph representation of the solutions. Furthermore, we show
that the problem has a polynomial time k-approximation, where k is the maximum
number of xor-genotypes containing a given SNP. Finally, we propose a heuristic
and produce an experimental analysis showing that it scales to real-world large
instances taken from the HapMap project
ASPIC: a novel method to predict the exon-intron structure of a gene that is optimally compatible to a set of transcript sequences
BACKGROUND: Currently available methods to predict splice sites are mainly based on the independent and progressive alignment of transcript data (mostly ESTs) to the genomic sequence. Apart from often being computationally expensive, this approach is vulnerable to several problems – hence the need to develop novel strategies. RESULTS: We propose a method, based on a novel multiple genome-EST alignment algorithm, for the detection of splice sites. To avoid limitations of splice sites prediction (mainly, over-predictions) due to independent single EST alignments to the genomic sequence our approach performs a multiple alignment of transcript data to the genomic sequence based on the combined analysis of all available data. We recast the problem of predicting constitutive and alternative splicing as an optimization problem, where the optimal multiple transcript alignment minimizes the number of exons and hence of splice site observations. We have implemented a splice site predictor based on this algorithm in the software tool ASPIC (Alternative Splicing PredICtion). It is distinguished from other methods based on BLAST-like tools by the incorporation of entirely new ad hoc procedures for accurate and computationally efficient transcript alignment and adopts dynamic programming for the refinement of intron boundaries. ASPIC also provides the minimal set of non-mergeable transcript isoforms compatible with the detected splicing events. The ASPIC web resource is dynamically interconnected with the Ensembl and Unigene databases and also implements an upload facility. CONCLUSION: Extensive bench marking shows that ASPIC outperforms other existing methods in the detection of novel splicing isoforms and in the minimization of over-predictions. ASPIC also requires a lower computation time for processing a single gene and an EST cluster. The ASPIC web resource is available at
Rapid Fabrication of Fe and Pd Thin Films as SERS-Active Substrates via Dynamic Hydrogen Bubble Template Method
Fe and Pd thin film samples have been fabricated in a rapid fashion utilizing the versatile technique of dynamic hydrogen bubble template (DHBT) method via potentiostatic electrodeposition over a copper substrate. The morphology of the samples is dendritic, with the composition being directly proportional to the deposition time. All the samples have been tested as SERS substrates for the detection of Rhodamine 6G (R6G) dye. The samples perform very well, with the best performance shown by the Pd samples. The lowest detectable R6G concentration was found to be 10(−6) M (479 μgL(−1)) by one of the Pd samples with the deposition time of 180 s. The highest enhancement of signals noticed in this sample can be attributed to its morphology, which is more nanostructured compared to other samples, which is extremely conducive to the phenomenon of localized surface plasmon resonance (LSPR). Overall, these samples are cheaper, easy to prepare with a rapid fabrication method, and show appreciable SERS performance
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