A Quadruple Diffusion Convolutional Recurrent Network for Human Motion Prediction

Recurrent neural network (RNN) has become popular for human motion prediction thanks to its ability to capture temporal dependencies. However, it has limited capacity in modeling the complex spatial relationship in the human skeletal structure. In this work, we present a novel diffusion convolutional recurrent predictor for spatial and temporal movement forecasting, with multi-step random walks traversing bidirectionally along an adaptive graph to model interdependency among body joints. In the temporal domain, existing methods rely on a single forward predictor with the produced motion deflecting to the drift route, which leads to error accumulations over time. We propose to supplement the forward predictor with a forward discriminator to alleviate such motion drift in the long term under adversarial training. The solution is further enhanced by a backward predictor and a backward discriminator to effectively reduce the error, such that the system can also look into the past to improve the prediction at early frames. The two-way spatial diffusion convolutions and two-way temporal predictors together form a quadruple network. Furthermore, we train our framework by modeling the velocity from observed motion dynamics instead of static poses to predict future movements that effectively reduces the discontinuity problem at early prediction. Our method outperforms the state of the arts on both 3D and 2D datasets, including the Human3.6M, CMU Motion Capture and Penn Action datasets. The results also show that our method correctly predicts both high-dynamic and low-dynamic moving trends with less motion drift

A Two-stream Convolutional Network for Musculoskeletal and Neurological Disorders Prediction

Musculoskeletal and neurological disorders are the most common causes of walking problems among older people, and they often lead to diminished quality of life. Analyzing walking motion data manually requires trained professionals and the evaluations may not always be objective. To facilitate early diagnosis, recent deep learning-based methods have shown promising results for automated analysis, which can discover patterns that have not been found in traditional machine learning methods. We observe that existing work mostly applies deep learning on individual joint features such as the time series of joint positions. Due to the challenge of discovering inter-joint features such as the distance between feet (i.e. the stride width) from generally smaller-scale medical datasets, these methods usually perform sub-optimally. As a result, we propose a solution that explicitly takes both individual joint features and inter-joint features as input, relieving the system from the need of discovering more complicated features from small data. Due to the distinctive nature of the two types of features, we introduce a two-stream framework, with one stream learning from the time series of joint position and the other from the time series of relative joint displacement. We further develop a mid-layer fusion module to combine the discovered patterns in these two streams for diagnosis, which results in a complementary representation of the data for better prediction performance. We validate our system with a benchmark dataset of 3D skeleton motion that involves 45 patients with musculoskeletal and neurological disorders, and achieve a prediction accuracy of 95.56%, outperforming state-of-the-art methods

Punctuated equilibria and 1/f noise in a biological coevolution model with individual-based dynamics

We present a study by linear stability analysis and large-scale Monte Carlo simulations of a simple model of biological coevolution. Selection is provided through a reproduction probability that contains quenched, random interspecies interactions, while genetic variation is provided through a low mutation rate. Both selection and mutation act on individual organisms. Consistent with some current theories of macroevolutionary dynamics, the model displays intermittent, statistically self-similar behavior with punctuated equilibria. The probability density for the lifetimes of ecological communities is well approximated by a power law with exponent near -2, and the corresponding power spectral densities show 1/f noise (flicker noise) over several decades. The long-lived communities (quasi-steady states) consist of a relatively small number of mutualistically interacting species, and they are surrounded by a ``protection zone'' of closely related genotypes that have a very low probability of invading the resident community. The extent of the protection zone affects the stability of the community in a way analogous to the height of the free-energy barrier surrounding a metastable state in a physical system. Measures of biological diversity are on average stationary with no discernible trends, even over our very long simulation runs of approximately 3.4x10^7 generations.Comment: 20 pages RevTex. Minor revisions consistent with published versio

Reaction rate for two--neutron capture by 4^4He

Recent investigations suggest that the neutrino--heated hot bubble between the nascent neutron star and the overlying stellar mantle of a type--II supernova may be the site of the r--process. In the preceding $\alpha$--process building up the elements to $A \approx 100$, the $^4$He(2n,$\gamma$)$^6$He-- and $^6$He($\alpha$,n)$^9$Be--reactions bridging the instability gap at $A=5$ and $A=8$ could be of relevance. We suggest a mechanism for $^4$He(2n,$\gamma$)$^6$He and calculate the reaction rate within the $\alpha$+n+n approach. The value obtained is about a factor 1.6 smaller than the one obtained recently in the simpler direct--capture model, but is at least three order of magnitude enhanced compared to the previously adopted value. Our calculation confirms the result of the direct--capture calculation that under representative conditions in the $\alpha$--process the reaction path proceeding through $^6$He is negligible compared to $^4$He($\alpha$n,$\gamma$)$^9$Be.Comment: 13 pages, 4 postscript figures, to appear in "Zeitschrift f. Physik A", changed internet address and filename, the uuencoded postscript file including the figures is available at ftp://is1.kph.tuwien.ac.at/pub/ohu/twoneutron.u

The Impact of New EUV Diagnostics on CME-Related Kinematics

We present the application of novel diagnostics to the spectroscopic observation of a Coronal Mass Ejection (CME) on disk by the Extreme Ultraviolet Imaging Spectrometer (EIS) on the Hinode spacecraft. We apply a recently developed line profile asymmetry analysis to the spectroscopic observation of NOAA AR 10930 on 14-15 December 2006 to three raster observations before and during the eruption of a 1000km/s CME. We see the impact that the observer's line-of-sight and magnetic field geometry have on the diagnostics used. Further, and more importantly, we identify the on-disk signature of a high-speed outflow behind the CME in the dimming region arising as a result of the eruption. Supported by recent coronal observations of the STEREO spacecraft, we speculate about the momentum flux resulting from this outflow as a secondary momentum source to the CME. The results presented highlight the importance of spectroscopic measurements in relation to CME kinematics, and the need for full-disk synoptic spectroscopic observations of the coronal and chromospheric plasmas to capture the signature of such explosive energy release as a way of providing better constraints of CME propagation times to L1, or any other point of interest in the heliosphere.Comment: Accepted to appear in Solar Physics Topical Issue titled "Remote Sensing of the Inner Heliosphere". Manuscript has 14 pages, 5 color figures. Movies supporting the figures can be found in http://download.hao.ucar.edu/pub/mscott/papers/Weathe

Modeling the Longitudinal Asymmetry in Sunspot Emergence -- the Role of the Wilson Depression

The distributions of sunspot longitude at first appearance and at disappearance display an east-west asymmetry that results from a reduction in visibility as one moves from disk centre to the limb. To first order, this is explicable in terms of simple geometrical foreshortening. However, the centre-to-limb visibility variation is much larger than that predicted by foreshortening. Sunspot visibility is also known to be affected by the Wilson effect: the apparent dish shape of the sunspot photosphere caused by the temperature-dependent variation of the geometrical position of the tau=1 layer. In this article we investigate the role of the Wilson effect on the sunspot appearance distributions, deducing a mean depth for the umbral tau=1 layer of 500 to 1500 km. This is based on the comparison of observations of sunspot longitude distribution and Monte Carlo simulations of sunspot appearance using different models for spot growth rate, growth time and depth of Wilson depression.Comment: 18 pages, 10 figures, in press (Solar Physics

The dependence of the EIT wave velocity on the magnetic field strength

"EIT waves" are a wavelike phenomenon propagating in the corona, which were initially observed in the extreme ultraviolet (EUV) wavelength by the EUV Imaging Telescope (EIT). Their nature is still elusive, with the debate between fast-mode wave model and non-wave model. In order to distinguish between these models, we investigate the relation between the EIT wave velocity and the local magnetic field in the corona. It is found that the two parameters show significant negative correlation in most of the EIT wave fronts, {\it i.e.}, EIT wave propagates more slowly in the regions of stronger magnetic field. Such a result poses a big challenge to the fast-mode wave model, which would predict a strong positive correlation between the two parameters. However, it is demonstrated that such a result can be explained by the fieldline stretching model, \emph{i.e.,} that "EIT waves" are apparently-propagating brightenings, which are generated by successive stretching of closed magnetic field lines pushed by the erupting flux rope during coronal mass ejections (CMEs).Comment: 11 pages, 8 figures, accepted for publication in Solar Phy

A multilevel neo-institutional analysis of infection prevention and control in English hospitals: coerced safety culture change?

Despite committed policy, regulative and professional efforts on healthcare safety, little is known about how such macro-interventions permeate organisations and shape culture over time. Informed by neo-institutional theory, we examined how inter-organisational influences shaped safety practices and inter-subjective meanings following efforts for coerced culture change. We traced macro-influences from 2000 to 2015 in infection prevention and control (IPC). Safety perceptions and meanings were inductively analysed from 130 in-depth qualitative interviews with senior- and middle-level managers from 30 English hospitals. A total of 869 institutional interventions were identified; 69% had a regulative component. In this context of forced implementation of safety practices, staff experienced inherent tensions concerning the scope of safety, their ability to be open and prioritisation of external mandates over local need. These tensions stemmed from conflicts among three co-existing institutional logics prevalent in the NHS. In response to requests for change, staff flexibly drew from a repertoire of cognitive, material and symbolic resources within and outside their organisations. They crafted 'strategies of action', guided by a situated assessment of first-hand practice experiences complementing collective evaluations of interventions such as 'pragmatic', 'sensible' and also 'legitimate'. Macro-institutional forces exerted influence either directly on individuals or indirectly by enriching the organisational cultural repertoire

Photospheric and Subphotospheric Dynamics of Emerging Magnetic Flux

Magnetic fields emerging from the Sun's interior carry information about physical processes of magnetic field generation and transport in the convection zone. Soon after appearance on the solar surface the magnetic flux gets concentrated in sunspot regions and causes numerous active phenomena on the Sun. This paper discusses some properties of the emerging magnetic flux observed on the solar surface and in the interior. A statistical analysis of variations of the tilt angle of bipolar magnetic regions during the emergence shows that the systematic tilt with respect to the equator (the Joy's law) is most likely established below the surface. However, no evidence of the dependence of the tilt angle on the amount of emerging magnetic flux, predicted by the rising magnetic flux rope theories, is found. Analysis of surface plasma flows in a large emerging active region reveals strong localized upflows and downflows at the initial phase of emergence but finds no evidence for large-scale flows indicating future appearance a large-scale magnetic structure. Local helioseismology provides important tools for mapping perturbations of the wave speed and mass flows below the surface. Initial results from SOHO/MDI and GONG reveal strong diverging flows during the flux emergence, and also localized converging flows around stable sunspots. The wave speed images obtained during the process of formation of a large active region, NOAA 10488, indicate that the magnetic flux gets concentrated in strong field structures just below the surface. Further studies of magnetic flux emergence require systematic helioseismic observations from the ground and space, and realistic MHD simulations of the subsurface dynamics.Comment: 21 pages, 15 figures, to appear in Space Science Review