Linear Bellman combination for control of character animation

Controllers are necessary for physically-based synthesis of character animation. However, creating controllers requires either manual tuning or expensive computer optimization. We introduce linear Bellman combination as a method for reusing existing controllers. Given a set of controllers for related tasks, this combination creates a controller that performs a new task. It naturally weights the contribution of each component controller by its relevance to the current state and goal of the system. We demonstrate that linear Bellman combination outperforms naive combination often succeeding where naive combination fails. Furthermore, this combination is provably optimal for a new task if the component controllers are also optimal for related tasks. We demonstrate the applicability of linear Bellman combination to interactive character control of stepping motions and acrobatic maneuvers.Singapore-MIT GAMBIT Game LabNational Science Foundation (U.S.) (Grant 2007043041)National Science Foundation (U.S.) (Grant CCF-0810888)Adobe SystemsPixar (Firm

Human Gene Coexpression Landscape: Confident Network Derived from Tissue Transcriptomic Profiles

This is an open-access article distributed under the terms of the Creative Commons Attribution License.[Background]: Analysis of gene expression data using genome-wide microarrays is a technique often used in genomic studies to find coexpression patterns and locate groups of co-transcribed genes. However, most studies done at global >omic> scale are not focused on human samples and when they correspond to human very often include heterogeneous datasets, mixing normal with disease-altered samples. Moreover, the technical noise present in genome-wide expression microarrays is another well reported problem that many times is not addressed with robust statistical methods, and the estimation of errors in the data is not provided. [Methodology/Principal Findings]: Human genome-wide expression data from a controlled set of normal-healthy tissues is used to build a confident human gene coexpression network avoiding both pathological and technical noise. To achieve this we describe a new method that combines several statistical and computational strategies: robust normalization and expression signal calculation; correlation coefficients obtained by parametric and non-parametric methods; random cross-validations; and estimation of the statistical accuracy and coverage of the data. All these methods provide a series of coexpression datasets where the level of error is measured and can be tuned. To define the errors, the rates of true positives are calculated by assignment to biological pathways. The results provide a confident human gene coexpression network that includes 3327 gene-nodes and 15841 coexpression-links and a comparative analysis shows good improvement over previously published datasets. Further functional analysis of a subset core network, validated by two independent methods, shows coherent biological modules that share common transcription factors. The network reveals a map of coexpression clusters organized in well defined functional constellations. Two major regions in this network correspond to genes involved in nuclear and mitochondrial metabolism and investigations on their functional assignment indicate that more than 60% are house-keeping and essential genes. The network displays new non-described gene associations and it allows the placement in a functional context of some unknown non-assigned genes based on their interactions with known gene families. [Conclusions/Significance]: The identification of stable and reliable human gene to gene coexpression networks is essential to unravel the interactions and functional correlations between human genes at an omic scale. This work contributes to this aim, and we are making available for the scientific community the validated human gene coexpression networks obtained, to allow further analyses on the network or on some specific gene associations. The data are available free online at http://bioinfow.dep.usal.es/coexpression/. © 2008 Prieto et al.Funding and grant support was provided by the Ministery of Health, Spanish Government (ISCiii-FIS, MSyC; Project reference PI061153) and by the Ministery of Education, Castilla-Leon Local Government (JCyL; Project reference CSI03A06).Peer Reviewe

The role of the user within the medical device design and development process: medical device manufacturers' perspectives

Copyright @ 2011 Money et al.Background: Academic literature and international standards bodies suggest that user involvement, via the incorporation of human factors engineering methods within the medical device design and development (MDDD) process, offer many benefits that enable the development of safer and more usable medical devices that are better suited to users' needs. However, little research has been carried out to explore medical device manufacturers' beliefs and attitudes towards user involvement within this process, or indeed what value they believe can be added by doing so.Methods: In-depth interviews with representatives from 11 medical device manufacturers are carried out. We ask them to specify who they believe the intended users of the device to be, who they consult to inform the MDDD process, what role they believe the user plays within this process, and what value (if any) they believe users add. Thematic analysis is used to analyse the fully transcribed interview data, to gain insight into medical device manufacturers' beliefs and attitudes towards user involvement within the MDDD process.Results: A number of high-level themes emerged, relating who the user is perceived to be, the methods used, the perceived value and barriers to user involvement, and the nature of user contributions. The findings reveal that despite standards agencies and academic literature offering strong support for the employment formal methods, manufacturers are still hesitant due to a range of factors including: perceived barriers to obtaining ethical approval; the speed at which such activity may be carried out; the belief that there is no need given the 'all-knowing' nature of senior health care staff and clinical champions; a belief that effective results are achievable by consulting a minimal number of champions. Furthermore, less senior health care practitioners and patients were rarely seen as being able to provide valuable input into the process.Conclusions: Medical device manufacturers often do not see the benefit of employing formal human factors engineering methods within the MDDD process. Research is required to better understand the day-to-day requirements of manufacturers within this sector. The development of new or adapted methods may be required if user involvement is to be fully realised.This study was in part funded by grant number Ref: GR/S29874/01 from the Engineering and Physical Sciences Research Council. This article is made available through the Brunel University Open Access Publishing Fund

Motif co-regulation and co-operativity are common mechanisms in transcriptional, post-transcriptional and post-translational regulation

A substantial portion of the regulatory interactions in the higher eukaryotic cell are mediated by simple sequence motifs in the regulatory segments of genes and (pre-)mRNAs, and in the intrinsically disordered regions of proteins. Although these regulatory modules are physicochemically distinct, they share an evolutionary plasticity that has facilitated a rapid growth of their use and resulted in their ubiquity in complex organisms. The ease of motif acquisition simplifies access to basal housekeeping functions, facilitates the co-regulation of multiple biomolecules allowing them to respond in a coordinated manner to changes in the cell state, and supports the integration of multiple signals for combinatorial decision-making. Consequently, motifs are indispensable for temporal, spatial, conditional and basal regulation at the transcriptional, post-transcriptional and post-translational level. In this review, we highlight that many of the key regulatory pathways of the cell are recruited by motifs and that the ease of motif acquisition has resulted in large networks of co-regulated biomolecules. We discuss how co-operativity allows simple static motifs to perform the conditional regulation that underlies decision-making in higher eukaryotic biological systems. We observe that each gene and its products have a unique set of DNA, RNA or protein motifs that encode a regulatory program to define the logical circuitry that guides the life cycle of these biomolecules, from transcription to degradation. Finally, we contrast the regulatory properties of protein motifs and the regulatory elements of DNA and (pre-)mRNAs, advocating that co-regulation, co-operativity, and motif-driven regulatory programs are common mechanisms that emerge from the use of simple, evolutionarily plastic regulatory modules

Tracking Grasping Moving Objects Using Reflex Behaviour

NRC publication: Ye

Abstract “Walk to here”: A Voice Driven Animation System

We present a novel interface for directing the actions of computer animated characters and camera movements. Our system takes spoken input in combination with mouse pointing to generate desired character animation based on motion capture data. The aim is to achieve a more natural animation interface by supporting the types of dialogue and pointing that might be used when one person is explaining a desired motion to another person. We compare our voice-driven system with a button-driven animation interface that has equivalent capabilities. An informal user study indicates that for the test scenarios, the voice-user interface (VUI) is faster than an equivalent graphical user interface (GUI). Potential applications include storyboarding for film or theatre, directing characters in video games, and scene reconstruction. 1