955 resultados para Causality (Physics)


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Objective This study highlights the serious consequences of ignoring reverse causality bias in studies on compensation-related factors and health outcomes and demonstrates a technique for resolving this problem of observational data. Study Design and Setting Data from an English longitudinal study on factors, including claims for compensation, associated with recovery from neck pain (whiplash) after rear-end collisions are used to demonstrate the potential for reverse causality bias. Although it is commonly believed that claiming compensation leads to worse recovery, it is also possible that poor recovery may lead to compensation claims—a point that is seldom considered and never addressed empirically. This pedagogical study compares the association between compensation claiming and recovery when reverse causality bias is ignored and when it is addressed, controlling for the same observable factors. Results When reverse causality is ignored, claimants appear to have a worse recovery than nonclaimants; however, when reverse causality bias is addressed, claiming compensation appears to have a beneficial effect on recovery, ceteris paribus. Conclusion To avert biased policy and judicial decisions that might inadvertently disadvantage people with compensable injuries, there is an urgent need for researchers to address reverse causality bias in studies on compensation-related factors and health.

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This is the first of two papers that map (dis)continuities in notions of power from Aristotle to Newton to Foucault. They trace the ways in which bio-physical conceptions of power became paraphrased in social science and deployed in educational discourse on the child and curriculum from post-Newtonian times to the present. The analyses suggest that, amid ruptures in the definition, role, location and meaning given 'power' historically in various 'physical' and 'social' cosmologies, the naming of 'power' has been dependent on 'physics', on the theorization of motion across 'Western' sciences. This first paper examines some (dis)continuities in regard to histories of motion and power from Aristotelian 'natural science' to Newtonian mechanics.

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The physical mechanism through which Ei-Nino and Southern Oscillation (ENSO) tends to produce deficient precipitation over Indian continent is investigated using both observations as well as a general circulation model. Both analysis of observations and atmospheric general circulation model (AGCM) study show that the planetary scale response associated with ENSO primarily influences the equatorial Indian Ocean region. Through this interaction it tends to favour the equatorial heat source, enhance precipitation over the equatorial Indian Ocean and indirectly cause a decrease in continental precipitation through induced subsidence. This situation is further complicated by the fact the regional tropospheric quasi biennial oscillation (QBO) has a bimodal structure over this region with large amplitude over the Indian continent. While the ENSO response has a quasi-four year periodicity and tends peak during beginning of the calendar year, the QBO mode tends to peak during northern summer. Thus, the QBO mode exerts a stronger influence on the interannual variability of the monsoon. The strength of the Indian monsoon in a given year depends on the combined effect of the ENSO and the QBO mode. Sines the two oscillations have disparate time scales, exact phase information of the two modes during northern summer is important in determining the Indian summer monsoon. The physical mechanism of the interannual variations of the Indian monsoon precipitation associated with ENSO presented here is similar to the physical process that cause intraseasonal 'active', 'break' oscillations of the monsoon.

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This is a summary of the beyond the Standard Model (including model building working group of the WHEPP-X workshop held at Chennai from January 3 to 15, 2008.

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Simultaneous recordings of spike trains from multiple single neurons are becoming commonplace. Understanding the interaction patterns among these spike trains remains a key research area. A question of interest is the evaluation of information flow between neurons through the analysis of whether one spike train exerts causal influence on another. For continuous-valued time series data, Granger causality has proven an effective method for this purpose. However, the basis for Granger causality estimation is autoregressive data modeling, which is not directly applicable to spike trains. Various filtering options distort the properties of spike trains as point processes. Here we propose a new nonparametric approach to estimate Granger causality directly from the Fourier transforms of spike train data. We validate the method on synthetic spike trains generated by model networks of neurons with known connectivity patterns and then apply it to neurons limultaneously recorded from the thalamus and the primary somatosensory cortex of a squirrel monkey undergoing tactile stimulation.

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A formula has been derived for the mean-square error in the phases of crystal reflections determined through the multiwavelength anomalous scattering method. The error is written in terms of a simple function of the positions in the complex plane of the 'centres' corresponding to the different wavelengths. For the case of three centres, the mean-square error is inversely proportional to the area of the triangle formed by them. The theoretical values are in good agreement with those obtained by earlier workers from computer simulations. The present method makes it easier to optimize the number and the actual wavelengths to be employed in the multiwavelength method. The maximum benefits of this method are expected in experiments employing synchrotron radiation or neutrons.

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This paper reports and discusses the principal findings of an Australian study exploring the decisions of high achieving Year 10 students about taking physics and chemistry courses (Lyons, 2003). The study used a ‘multiple worlds’ framework to explore the diverse background characteristics that previous quantitative research had shown were implicated in these decisions. Based on analyses of questionnaire and interview data, the study found that the students’ decisions involved the complex negotiation of a number of cultural characteristics within their school science and family worlds. Many of the students regarded junior high school science as irrelevant, uninteresting and difficult, leaving them with few intrinsic reasons for enrolling in senior science courses. The study found that decisions about taking physical science courses were associated with the resources of cultural and social capital within their families, and the degree to which these resources were congruent with the advantages of choosing these courses. The paper concludes that the low intrinsic value of school science and the erosion of its strategic value contribute to the reluctance of students to choose physical science courses in the senior school.

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We study the possibility of using W pair production and leptonic decay of one of the W's at the ILC with polarized beams as a probe of the Littlest Higgs Model. We consider cross-sections, polarization fractions of the W's, leptonic decay energy and angular distributions, and left-right polarization asymmetry as probes of the model. With parameter values allowed by present experimental constraints detectable effects on these observables at typical ILC energies of 500 GeV and 800 GeV will be present. Beam polarization is further found to enhance the sensitivity.

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Multielectrode neurophysiological recording and high-resolution neuroimaging generate multivariate data that are the basis for understanding the patterns of neural interactions. How to extract directions of information flow in brain networks from these data remains a key challenge. Research over the last few years has identified Granger causality as a statistically principled technique to furnish this capability. The estimation of Granger causality currently requires autoregressive modeling of neural data. Here, we propose a nonparametric approach based on widely used Fourier and wavelet transforms to estimate both pairwise and conditional measures of Granger causality, eliminating the need of explicit autoregressive data modeling. We demonstrate the effectiveness of this approach by applying it to synthetic data generated by network models with known connectivity and to local field potentials recorded from monkeys performing a sensorimotor task.

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In 1974, the Russian physicist Vitaly Ginzburg wrote a book entitled `Key Problems of Physics and Astrophysics' in which he presented a selection of important and challenging problems along with speculations on what the future holds. The selection had a broad range, was highly personalized, and was aimed at the general scientist, for whom it made very interesting reading