Robust nonlinear system identification: Bayesian mixture of experts using the t-distribution

A novel variational Bayesian mixture of experts model for robust regression of bifurcating and piece-wise continuous processes is introduced. The mixture of experts model is a powerful model which probabilistically splits the input space allowing different models to operate in the separate regions. However, current methods have no fail-safe against outliers. In this paper, a robust mixture of experts model is proposed which consists of Student-t mixture models at the gates and Student-t distributed experts, trained via Bayesian inference. The Student-t distribution has heavier tails than the Gaussian distribution, and so it is more robust to outliers, noise and nonnormality in the data. Using both simulated data and real data obtained from the Z24 bridge this robust mixture of experts performs better than its Gaussian counterpart when outliers are present. In particular, it provides robustness to outliers in two forms: unbiased parameter regression models, and robustness to overfitting/complex models

Differences in EMG burst patterns during grasping dexterity tests and activities of daily living

The aim of this study was to characterize the muscle activation patterns which underlie the performance of two commonly used grasping patterns and compare the characteristics of such patterns during dexterity tests and activities of daily living. EMG of flexor digitorum and extensor digitorum were monitored from 6 healthy participants as they performed three tasks related to activities of daily living (picking up a coin, drinking from a cup, feeding with a spoon) and three dexterity tests (Variable Dexterity Test-Precision, Variable Dexterity Test-Cylinder, Purdue Pegboard Test). A ten-camera motion capture system was used to simultaneously acquire kinematics of index and middle fingers. Spatiotemporal aspects of the EMG signals were analyzed and compared to metacarpophalangeal joint angle of index and middle fingers. The work has shown that a common rehabilitation test such as the Purdue Pegboard test is a poor representation of the muscle activation patterns for activities of daily living. EMG and joint angle patterns from the Variable Dexterity Tests which has been designed to more accurately reflect a range of ADl's were consistently comparable with tasks requiring precision and cylinder grip, reaffirming the importance of object size and shape when attempting to accurately assess hand function

Some Recent Developments in SHM Based on Nonstationary Time Series Analysis

Many of the algorithms used for structural health monitoring (SHM) are based on, or motivated by, time series analysis. Quite often, detection methods are variants of approaches developed within the statistical process control (SPC) community. Many of the algorithms used represent mature theory and have a rigorous probabilistic or mathematical basis. However, one of the main issues facing SHM practitioners is that the structures of interest rarely respect the assumptions inherent in deriving algorithms. In the case of time series data, SPC-based approaches usually require the data to be stationary and, unfortunately, SHM data are often nonstationary because of benign variations in the environment of the structure of interest, or because of deliberate operational changes in the use of the structure. This nonstationarity can manifest itself as slowly varying trends on the data or in abrupt switches between regimes. Recent work in nonstationary time series methods for SHM has made considerable progress in accommodating nonstationarity and some of that work is discussed within this paper: in terms of understanding slowly varying trends, the cointegration algorithm from econometrics is presented; for understanding abrupt switches, Bayesian mixtures of experts are presented. Another issue in time series analysis is indirectly related to the assumption of linear behavior of structures and the impact of this assumption is briefly considered in terms of its effects on detection thresholds in SPC-like methods; again, progress has been made recently. Some issues still remain, and these are discussed also

Aesthetic-aerodynamic design optimization of a car grille profile while preserving brand identity

The purpose of this study is to investigate how to combine the aesthetic quality with the engineering functionality in a design project while preserving the brand identity. It is aimed to develop a framework for decision making in the design of a specific product that can be used by designers simply and efficiently. The car front grille design is presented as the case study and the aerodynamic drag minimization is chosen as the functionality criterion of the design. A specific brand is selected to study its identity and a specific product associated with this brand is chosen to implement the approach. Finally, a framework is presented in the form of a table and a utility function which can be used to optimize the grille profile of the chosen vehicle multi-objectively

Suppression of planar cell polarity signaling and migration in glioblastoma by Nrdp1-mediated Dvl polyubiquitination.

The lethality of the aggressive brain tumor glioblastoma multiforme (GBM) results in part from its strong propensity to invade surrounding normal brain tissue. Although oncogenic drivers such as epidermal growth factor receptor activation and Phosphatase and Tensin homolog inactivation are thought to promote the motility and invasiveness of GBM cells via phosphatidylinostitol 3-kinase activation, other unexplored mechanisms may also contribute to malignancy. Here we demonstrate that several components of the planar cell polarity (PCP) arm of non-canonical Wnt signaling including VANGL1, VANGL2 and FZD7 are transcriptionally upregulated in glioma and correlate with poorer patient outcome. Knockdown of the core PCP pathway component VANGL1 suppresses the motility of GBM cell lines, pointing to an important mechanistic role for this pathway in glioblastoma malignancy. We further observe that restoration of Nrdp1, a RING finger type E3 ubiquitin ligase whose suppression in GBM also correlates with poor prognosis, reduces GBM cell migration and invasiveness by suppressing PCP signaling. Our observations indicate that Nrdp1 physically interacts with the Vangl1 and Vangl2 proteins to mediate the K63-linked polyubiquitination of the Dishevelled, Egl-10 and Pleckstrin (DEP) domain of the Wnt pathway protein Dishevelled (Dvl). Ubiquitination hinders Dvl binding to phosphatidic acid, an interaction necessary for efficient Dvl recruitment to the plasma membrane upon Wnt stimulation of Fzd receptor and for the propagation of downstream signals. We conclude that the PCP pathway contributes significantly to the motility and hence the invasiveness of GBM cells, and that Nrdp1 acts as a negative regulator of PCP signaling by inhibiting Dvl through a novel polyubiquitination mechanism. We propose that the upregulation of core PCP components, together with the loss of the key negative regulator Nrdp1, act coordinately to promote GBM invasiveness and malignancy

Towards environmentally sustainable human behaviour: targeting non-conscious and conscious processes for effective and acceptable policies.

Meeting climate change targets to limit global warming to 2°C requires rapid and large reductions in demand for products that most contribute to greenhouse gas (GHG) emissions. These include production of bulk materials (e.g. steel and cement), energy supply (e.g. fossil fuels) and animal source foods (particularly ruminants and their products). Effective strategies to meet these targets require transformative changes in supply as well as demand, involving changes in economic, political and legal systems at local, national and international levels, building on evidence from many disciplines. This paper outlines contributions from behavioural science in reducing demand. Grounded in dual-process models of human behaviour (involving non-conscious and conscious processes) this paper considers first why interventions aimed at changing population values towards the environment are usually insufficient or unnecessary for reducing demand although they may be important in increasing public acceptability of policies that could reduce demand. It then outlines two sets of evidence from behavioural science towards effective systems-based strategies, to identify interventions likely to be effective at: (i) reducing demand for products that contribute most to GHG emissions, mainly targeting non-conscious processes and (ii) increasing public acceptability for policy changes to enable these interventions, targeting conscious processes.This article is part of the themed issue 'Material demand reduction'