3,034 research outputs found
New Experimental Limits on Macroscopic Forces Below 100 Microns
Results of an experimental search for new macroscopic forces with Yukawa
range between 5 and 500 microns are presented. The experiment uses 1 kHz
mechanical oscillators as test masses with a stiff conducting shield between
them to suppress backgrounds. No signal is observed above the instrumental
thermal noise after 22 hours of integration time. These results provide the
strongest limits to date between 10 and 100 microns, improve on previous limits
by as much as three orders of magnitude, and rule out half of the remaining
parameter space for predictions of string-inspired models with low-energy
supersymmetry breaking. New forces of four times gravitational strength or
greater are excluded at the 95% confidence level for interaction ranges between
200 and 500 microns.Comment: 25 Pages, 7 Figures: Minor Correction
New mobilities across the lifecourse: A framework for analysing demographically-linked drivers of migration
Date of acceptance: 17/02/2015Taking the life course as the central concern, the authors set out a conceptual framework and define some key research questions for a programme of research that explores how the linked lives of mobile people are situated in time–space within the economic, social, and cultural structures of contemporary society. Drawing on methodologically innovative techniques, these perspectives can offer new insights into the changing nature and meanings of migration across the life course.Publisher PDFPeer reviewe
Testing for Network and Spatial Autocorrelation
Testing for dependence has been a well-established component of spatial
statistical analyses for decades. In particular, several popular test
statistics have desirable properties for testing for the presence of spatial
autocorrelation in continuous variables. In this paper we propose two
contributions to the literature on tests for autocorrelation. First, we propose
a new test for autocorrelation in categorical variables. While some methods
currently exist for assessing spatial autocorrelation in categorical variables,
the most popular method is unwieldy, somewhat ad hoc, and fails to provide
grounds for a single omnibus test. Second, we discuss the importance of testing
for autocorrelation in data sampled from the nodes of a network, motivated by
social network applications. We demonstrate that our proposed statistic for
categorical variables can both be used in the spatial and network setting
Comparison of Population-Based Association Study Methods Correcting for Population Stratification
Population stratification can cause spurious associations in population–based association studies. Several statistical methods have been proposed to reduce the impact of population stratification on population–based association studies. We simulated a set of stratified populations based on the real haplotype data from the HapMap ENCODE project, and compared the relative power, type I error rates, accuracy and positive prediction value of four prevailing population–based association study methods: traditional case-control tests, structured association (SA), genomic control (GC) and principal components analysis (PCA) under various population stratification levels. Additionally, we evaluated the effects of sample sizes and frequencies of disease susceptible allele on the performance of the four analytical methods in the presence of population stratification. We found that the performance of PCA was very stable under various scenarios. Our comparison results suggest that SA and PCA have comparable performance, if sufficient ancestral informative markers are used in SA analysis. GC appeared to be strongly conservative in significantly stratified populations. It may be better to apply GC in the stratified populations with low stratification level. Our study intends to provide a practical guideline for researchers to select proper study methods and make appropriate inference of the results in population-based association studies
Constraints on Non-Newtonian Gravity from Recent Casimir Force Measurements
Corrections to Newton's gravitational law inspired by extra dimensional
physics and by the exchange of light and massless elementary particles between
the atoms of two macrobodies are considered. These corrections can be described
by the potentials of Yukawa-type and by the power-type potentials with
different powers. The strongest up to date constraints on the corrections to
Newton's gravitational law are reviewed following from the E\"{o}tvos- and
Cavendish-type experiments and from the measurements of the Casimir and van der
Waals force. We show that the recent measurements of the Casimir force gave the
possibility to strengthen the previously known constraints on the constants of
hypothetical interactions up to several thousand times in a wide interaction
range. Further strengthening is expected in near future that makes Casimir
force measurements a prospective test for the predictions of fundamental
physical theories.Comment: 20 pages, crckbked.cls is used, to be published in: Proceedings of
the 18th Course of the School on Cosmology and Gravitation: The Gravitational
Constant. Generalized Gravitational Theories and Experiments (30 April- 10
May 2003, Erice). Ed. by G. T. Gillies, V. N. Melnikov and V. de Sabbata,
20pp. (Kluwer, in print, 2003
Complexity without chaos: Plasticity within random recurrent networks generates robust timing and motor control
It is widely accepted that the complex dynamics characteristic of recurrent
neural circuits contributes in a fundamental manner to brain function. Progress
has been slow in understanding and exploiting the computational power of
recurrent dynamics for two main reasons: nonlinear recurrent networks often
exhibit chaotic behavior and most known learning rules do not work in robust
fashion in recurrent networks. Here we address both these problems by
demonstrating how random recurrent networks (RRN) that initially exhibit
chaotic dynamics can be tuned through a supervised learning rule to generate
locally stable neural patterns of activity that are both complex and robust to
noise. The outcome is a novel neural network regime that exhibits both
transiently stable and chaotic trajectories. We further show that the recurrent
learning rule dramatically increases the ability of RRNs to generate complex
spatiotemporal motor patterns, and accounts for recent experimental data
showing a decrease in neural variability in response to stimulus onset
\u201cGive, but Give until It Hurts\u201d: The Modulatory Role of Trait Emotional Intelligence on the Motivation to Help
Two studies investigated the effect of trait Emotional Intelligence (trait EI) on people\u2019s moti- vation to help. In Study 1, we developed a new computer-based paradigm that tested partic- ipants\u2019 motivation to help by measuring their performance on a task in which they could gain a hypothetical amount of money to help children in need. Crucially, we manipulated partici- pants\u2019 perceived efficacy by informing them that they had been either able to save the chil- dren (positive feedback) or unable to save the children (negative feedback). We measured trait EI using the Trait Emotional Intelligence Questionnaire\u2013Short Form (TEIQue-SF) and assessed participants\u2019 affective reactions during the experiment using the PANAS-X. Results showed that high and low trait EI participants performed differently after the presen- tation of feedback on their ineffectiveness in helping others in need. Both groups showed increasing negative affective states during the experiment when the feedback was negative; however, high trait EI participants better managed their affective reactions, modulating the impact of their emotions on performance and maintaining a high level of motivation to help. In Study 2, we used a similar computerized task and tested a control situation to explore the effect of trait EI on participants\u2019 behavior when facing failure or success in a scenario unre- lated to helping others in need. No effect of feedback emerged on participants\u2019 emotional states in the second study. Taken together our results show that trait EI influences the impact of success and failure on behavior only in affect-rich situation like those in which people are asked to help others in need
Extensive Copy-Number Variation of Young Genes across Stickleback Populations
MM received funding from the Max Planck innovation funds for this project. PGDF was supported by a Marie Curie European Reintegration Grant (proposal nr 270891). CE was supported by German Science Foundation grants (DFG, EI 841/4-1 and EI 841/6-1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
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