The separate neural control of hand movements and contact forces

To manipulate an object, we must simultaneously control the contact forces exerted on the object and the movements of our hand. Two alternative views for manipulation have been proposed: one in which motions and contact forces are represented and controlled by separate neural processes, and one in which motions and forces are controlled jointly, by a single process. To evaluate these alternatives, we designed three tasks in which subjects maintained a specified contact force while their hand was moved by a robotic manipulandum. The prescribed contact force and hand motions were selected in each task to induce the subject to attain one of three goals: (1) exerting a regulated contact force, (2) tracking the motion of the manipulandum, and (3) attaining both force and motion goals concurrently. By comparing subjects' performances in these three tasks, we found that behavior was captured by the summed actions of two independent control systems: one applying the desired force, and the other guiding the hand along the predicted path of the manipulandum. Furthermore, the application of transcranial magnetic stimulation impulses to the posterior parietal cortex selectively disrupted the control of motion but did not affect the regulation of static contact force. Together, these findings are consistent with the view that manipulation of objects is performed by independent brain control of hand motions and interaction forces

Measurement error caused by spatial misalignment in environmental epidemiology

Copyright @ 2009 Gryparis et al - Published by Oxford University Press.In many environmental epidemiology studies, the locations and/or times of exposure measurements and health assessments do not match. In such settings, health effects analyses often use the predictions from an exposure model as a covariate in a regression model. Such exposure predictions contain some measurement error as the predicted values do not equal the true exposures. We provide a framework for spatial measurement error modeling, showing that smoothing induces a Berkson-type measurement error with nondiagonal error structure. From this viewpoint, we review the existing approaches to estimation in a linear regression health model, including direct use of the spatial predictions and exposure simulation, and explore some modified approaches, including Bayesian models and out-of-sample regression calibration, motivated by measurement error principles. We then extend this work to the generalized linear model framework for health outcomes. Based on analytical considerations and simulation results, we compare the performance of all these approaches under several spatial models for exposure. Our comparisons underscore several important points. First, exposure simulation can perform very poorly under certain realistic scenarios. Second, the relative performance of the different methods depends on the nature of the underlying exposure surface. Third, traditional measurement error concepts can help to explain the relative practical performance of the different methods. We apply the methods to data on the association between levels of particulate matter and birth weight in the greater Boston area.This research was supported by NIEHS grants ES012044 (AG, BAC), ES009825 (JS, BAC), ES007142 (CJP), and ES000002 (CJP), and EPA grant R-832416 (JS, BAC)

Distributed digital contexts and learning : personal empowerment and social transformation in marginalized populations

The role of digital media and learning has often been synonymous with the use of open education resources in formal institutional settings. Further, open and distance learning has been criticized for focusing narrowly on educational objectives, ignoring socio-political issues of access and participation by marginalized populations. This study examines the lived experiences of female migrant domestic workers (N=20) in Singapore attending Open University. Mobile and social media supplement open and distance learning resources to allow for open practices of consumption, production and sharing in distributed contexts of digital learning. Marginalized students engaged in participation and collaboration activities, with specific privacy practices due to their social positions. Digital learning led to substantive learning for personal empowerment and social transformation, with aspirational strategies often involving digital skills. The discussion reflects on identity management across formal and informal digital settings as a means of transforming societal discourses of discrimination

Effects of plant hormones and 20-hydroxyecdysone on tomato (Lycopersicum esculentum) seed germination and seedlings growth

20-hydroxyecdysone (20E) is the major phytoecdysteroid of about 6% of plants. Its role in plant physiology has not been fully elucidated. In this work we studied the effects of 20E application on somemorphological and biochemical parameters of tomato, Lycopersicum esculentum, seed during germination and seedling development (5 d). We compared the 20E effects with the action of phytohormones: gibberellic acid (GA3), naftalen acetic acid (NAA), benzyl amino purine (BAP). NAA treatment resulted in marked reduction in shoot length. GA3 treatment promoted maximal shoot elongation. BAP affected negatively shoot length only at late stages, while 20E application stimulated shoot elongation at early stages and reduced it on the fifth day; NAA inhibited root elongation all along the test period. GA3 treatment had no effect on root length, whereas BAP showed strong inhibition on root elongation. On the other hand, 20E showed a weak inhibition of root elongation on the fifth day. As compared to control and to other treatments, NAA and 20E provoked a drastic decrease in protein contents during seedling growth, whereas a high increase was observed under BAP treatment. Electrophoresis revealed that protein bands were not degraded and mobilized after NAA treatmentwhile in control or after 20E and others phytohormones applications, protein patters displayed weak band intensities and some of them were not detected. NAA, GA3 and BAP provoked a decrease inproline content during seedlings, while the effect of 20E on proline levels varied during germination and plantlet development. This work showed that 20E like phytohormones fulfil some bioactive actionsduring germination and seedlings growth in tomato

Internationalisation, cultural distance and country characteristics: a Bayesian analysis of SME's financial performance

Relying on the accounting data of a panel of 403 Italian manufacturing SMEs collected over a period of 5 years, we find results suggesting that multinationality per se does not impact on the economic performance of international small and medium sized firms. It is the characteristics of the country selected i.e. the political hazard, the financial stability and the economic performance that significantly influence SMEs financial performance. The management implication for small and medium sized firms selecting and entering new geographic markets is significant, since our results show that for SMEs it is the market selection process that really matters and not the degree of multinationality

Exploring capability and accountability outcomes of open development for the poor and marginalized: An analysis of select literature

Open development concerns the application of digitally-enabled openness to radically change human capability and governance contexts (Davies & Edwards, 2012; Smith & Reilly, 2013; Smith, Elder, & Emdon, 2011). However, what openness means, and how it contributes to development outcomes is contested (Buskens, 2013; Singh & Gurumurthy, 2013). Furthermore, the potential of open development to support positive social transformation has not yet materialized, particularly for marginalized populations (Bentley & Chib, 2016), partly because relatively little is known regarding how transformation is enacted in the field. Likewise, two promising outcomes – the expansion of human capabilities and accountability – have not been explored in detail. This research interrogates the influence of digitally-enabled openness on transformation processes and outcomes. A purposeful sample of literature was taken to evaluate outcomes and transformation processes according to our theoretical framework, which defines seven cross-cutting dimensions essential to incorporate. We argue that these dimensions explain links between structures, processes and outcomes of open development. These links are essential to understand in the area of Community Informatics as they enable researchers and practitioners to support effective use of openness by and for poor and marginalized communities to pursue their own objectives

Bayesian Methods for Analysis and Adaptive Scheduling of Exoplanet Observations

We describe work in progress by a collaboration of astronomers and statisticians developing a suite of Bayesian data analysis tools for extrasolar planet (exoplanet) detection, planetary orbit estimation, and adaptive scheduling of observations. Our work addresses analysis of stellar reflex motion data, where a planet is detected by observing the "wobble" of its host star as it responds to the gravitational tug of the orbiting planet. Newtonian mechanics specifies an analytical model for the resulting time series, but it is strongly nonlinear, yielding complex, multimodal likelihood functions; it is even more complex when multiple planets are present. The parameter spaces range in size from few-dimensional to dozens of dimensions, depending on the number of planets in the system, and the type of motion measured (line-of-sight velocity, or position on the sky). Since orbits are periodic, Bayesian generalizations of periodogram methods facilitate the analysis. This relies on the model being linearly separable, enabling partial analytical marginalization, reducing the dimension of the parameter space. Subsequent analysis uses adaptive Markov chain Monte Carlo methods and adaptive importance sampling to perform the integrals required for both inference (planet detection and orbit measurement), and information-maximizing sequential design (for adaptive scheduling of observations). We present an overview of our current techniques and highlight directions being explored by ongoing research.Comment: 29 pages, 11 figures. An abridged version is accepted for publication in Statistical Methodology for a special issue on astrostatistics, with selected (refereed) papers presented at the Astronomical Data Analysis Conference (ADA VI) held in Monastir, Tunisia, in May 2010. Update corrects equation (3

Statistical models for over-dispersion in the frequency of peaks over threshold data for a flow series.

In a peaks over threshold analysis of a series of river flows, a sufficiently high threshold is used to extract the peaks of independent flood events. This paper reviews existing, and proposes new, statistical models for both the annual counts of such events and the process of event peak times. The most common existing model for the process of event times is a homogeneous Poisson process. This model is motivated by asymptotic theory. However, empirical evidence suggests that it is not the most appropriate model, since it implies that the mean and variance of the annual counts are the same, whereas the counts appear to be overdispersed, i.e., have a larger variance than mean. This paper describes how the homogeneous Poisson process can be extended to incorporate time variation in the rate at which events occur and so help to account for overdispersion in annual counts through the use of regression and mixed models. The implications of these new models on the implied probability distribution of the annual maxima are also discussed. The models are illustrated using a historical flow series from the River Thames at Kingston