Decoupling functional mechanisms of adaptive encoding

In a natural setting, adaptive mechanisms constantly modulate the encoding properties of sensory neurons in response to changes in the external environment. Recent experiments have revealed that adaptation affects both the spatiotemporal integration properties and baseline membrane potential of sensory neurons. However, the precise functional role of adaptation remains an open question, due in part to contradictory experimental results. Here, we develop a framework to characterize adaptive encoding, including a cascade model with a time-varying receptive field (reflecting spatiotemporal integration properties) and offset (reflecting baseline membrane potential), and a recursive technique for tracking changes in the model parameters during a single stimulus/response trial. Simulated and experimental responses from retinal neurons are used to track adaptive changes in receptive field structure and offset during nonstationary stimulation. Due to the nonlinear nature of spiking neurons, the parameters of the receptive field and offset must be estimated simultaneously, or changes in the offset (or even in the statistical distribution of the stimulus) can mask, confound, or create the illusion of adaptive changes in the receptive field. Our analysis suggests that these confounding effects may be at the root of the inconsistency in the literature and shows that seemingly conflicting experimental results can be reconciled within our framework.     

Social Mental Shaping: Modelling the Impact of Sociality on the Mental States of Autonomous Agents

This paper presents a framework that captures how the social nature of agents that are situated in a multi-agent environment impacts upon their individual mental states. Roles and social relationships provide an abstraction upon which we develop the notion of social mental shaping . This allows us to extend the standard Belief-Desire-Intention model to account for how common social phenomena (e.g. cooperation, collaborative problem-solving and negotiation) can be integrated into a unified theoretical perspective that reflects a fully explicated model of the autonomous agent's mental state.     

The Gaia Methodology for Agent-Oriented Analysis and Design

This article presents Gaia: a methodology for agent-oriented analysis and design. The Gaia methodology is both general, in that it is applicable to a wide range of multi-agent systems, and comprehensive, in that it deals with both the macro-level (societal) and the micro-level (agent) aspects of systems. Gaia is founded on the view of a multi-agent system as a computational organisation consisting of various interacting roles. We illustrate Gaia through a case study (an agent-based business process management system).     

Modeling Distributed Knowledge Processes in Next Generation Multidisciplinary Alliances*

Current research on distributed knowledge processes suggests a critical conflict between knowledge processes in groups and the technologies built to support them. The conflict centers on observations that authentic and efficient knowledge creation and sharing is deeply embedded in an interpersonal face to face context, but that technologies to support distributed knowledge processes rely on the assumption that knowledge can be made mobile outside these specific contexts. This conflict is of growing national importance as work patterns change from same site to separate site collaboration, and millions of government and industrial dollars are invested in establishing academic-industry alliances and building infrastructures to support distributed collaboration and knowledge. In this paper we describe our multi-method approach for studying the tension between embedded and mobile knowledge in a project funded by the National Science Foundation's program on Knowledge and Distributed Intelligence. This project examines knowledge processes and technology in distributed, multidisciplinary scientific teams in the National Computational Science Alliance (Alliance), a prototypical next generation enterprise. First we review evidence for the tension between embedded and mobile knowledge in several research literatures. Then we present our three-factor conceptualization that considers how the interrelationships among characteristics of the knowledge shared, group context, and communications technology contribute to the tension between embedded and mobile knowledge. Based on this conceptualization we suggest that this dichotomy does not fully explain distributed multidisciplinary knowledge processes. Therefore we propose some alternate models of how knowledge is shared. We briefly introduce the setting in which we are studying distributed knowledge processes and finally, we describe the data collection methods and the current status of the project.     

Effects of quasi-periodic training signals on acoustic echo canceller performance

Filtered white noise is the training signal typically used to test the performance of echo cancellers. However, a system optimized for operation with such training signals may perform poorly when trained instead with voiced speech. This performance difference is a consequence of the quasi-periodic nature of voiced speech. In this paper, we explore the effects of quasi-periodic training signals on echo-canceller performance. In particular, we show that unlike filtered white noise, quasi-periodic training signals can actually limit the asymptotic echo-return loss of echo cancellers. In addition, we examine the ability of several existing techniques to improve performance when quasi-periodic signals are used to train echo cancellers.     

Parallel algorithms for routing in nonblocking networks

We construct nonblocking networks that are efficient not only as regards their cost and delay, but also as regards the time and space required to control them. In this paper we present the first simultaneous weakly optimal solutions for the explicit construction of nonblocking networks, the design of algorithms and data-structures. Weakly optimal is in the sense that all measures of complexity (size and depth of the network, time for the algorithm, space for the data-structure, and number of processor-time product) are within one or more logarithmic factors of their smallest possible values. In fact, we construct a scheme in which networks withn inputs andn outputs have sizeO(n(logn)²) and depthO(logn), and we present deterministic and randomized on-line parallel algorithms to establish and abolish routes dynamically in these networks. In particular, the deterministic algorithm usesO((logn)⁵) steps to process any number of transactions in parallel (with one processor per transaction), maintaining a data structure that useO(n(logn)²) words.     

Anion-Modulated Chemical Doping of Organic Hole Conductor Boosts Efficiency and Stability of Perovskite Solar Cells

Chemical doping of organic semiconductors enables significant progress in improving their optoelectronic performance. However, the correlation between doping counter ions and charge-transport mechanism has not been yet well-understood. In this study, it is discovered that the anion-dependent degree of delocalization (DOD) of lithium-based dopants significantly determines the doping kinetics as well as the conductivity of organic hole transport layer (HTL), leading to large variation in solar cell efficiency and device stability. Specifically, the incorporation of bis(pentafluoroethanesulfonyl) imide (PFSI⁻) as the anion with a high DOD results in one order of magnitude higher film conductivity and thus an elevated power conversion efficiency (PCE) exceeding 22.1%, much higher than the state-of-the-art lithium bis(trifluoromethane)sulfonimide (LiTFSI) (21.1%) and lithium hexafluorophosphate (LiPF₆) (20.0%). Moreover, the dopant LiPF₆ with a smaller DOD produces higher doping yield of HTL accompanied by stronger light-induced PCE fluctuation. Structural analysis reveals anion-modulated ion exchange kinetics determine the hole-transport mechanism and device photostability. To mitigate these detrimental effects, a versatile strategy of Li⁺ solvation is developed to modulate the anion dissociation, enabling simultaneous improvement of device efficiency and stability. This study elucidates an intriguing and generally applicable doping mechanism, and envisages a bright future to further developing efficient and stable organic electronics.     

Stepping over obstacles of different heights and varied shoe traction alter the kinetic strategies of the leading limb

This study aims to investigate the effects of shoe traction and obstacle height on friction during walking to better understand the mechanisms required to avoid slippage following obstacle clearance. Ten male subjects walked at a self-selected pace during eight different conditions: four obstacle heights (0%, 10%, 20% and 40% of limb length) while wearing two different pairs of shoes (low and high traction). Frictional forces were calculated from the ground reaction forces following obstacle clearance, which were sampled with a Kistler platform at 960 Hz. All frictional peaks increased with increases in obstacle height. Low traction shoes yielded smaller peaks than high traction shoes. The transition from braking to propulsion occurred sooner due to altered control strategies with increased obstacle height. Collectively, these results provided insights into kinetic strategies of leading limb when confronted with low traction and high obstacle environments. This study provides valuable information into the adaptations used to reduce the potential of slips/falls when confronted with environments characterised by low shoe-floor friction and obstacles. It also provides the necessary foundation to explore the combined effects of shoe traction and obstacle clearance in elderly people, more sensitive to slippage.     

Solving nonlinear polynomial systems in the barycentric Bernstein basis

We present a method for solving arbitrary systems of N nonlinear polynomials in n variables over an n-dimensional simplicial domain based on polynomial representation in the barycentric Bernstein basis and subdivision. The roots are approximated to arbitrary precision by iteratively constructing a series of smaller bounding simplices. We use geometric subdivision to isolate multiple roots within a simplex. An algorithm implementing this method in rounded interval arithmetic is described and analyzed. We find that when the total order of polynomials is close to the maximum order of each variable, an iteration of this solver algorithm is asymptotically more efficient than the corresponding step in a similar algorithm which relies on polynomial representation in the tensor product Bernstein basis. We also discuss various implementation issues and identify topics for further study.     

Improving user assessment of error implications in digital elevation models

A digital representation of a terrain surface is an approximation of reality and is inherently prone to some degree of error and uncertainty. Research in uncertainty analysis has produced a vast range of methods for investigating error and its propagation. However, the complex and varied methods proposed by researchers and academics create ambiguity for the dataset user. In this study, existing methods are combined and simplified to present a prototype tool to enable any digital elevation model (DEM) user to access and apply uncertainty analysis. The effect of correlated gridded DEM error is investigated, using stochastic conditional simulation to generate multiple equally likely representations of an actual terrain surface. Propagation of data uncertainty to the slope derivative, and the impact on a landslide susceptibility model are assessed. Two frameworks are developed to examine the probable and possible uncertainties in classifying the landslide hazard: probabilistic and fuzzy. The entire procedure is automated using publicly available software and user requirements are minimised. A case study example shows the resultant code can be used to quantify, visualise and demonstrate the propagation of error in a DEM. As a tool for uncertainty analysis the method can improve user assessment of error and its implications.