Effective Stimuli for Constructing Reliable Neuron Models

The rich dynamical nature of neurons poses major conceptual and technical challenges for unraveling their nonlinear membrane properties. Traditionally, various current waveforms have been injected at the soma to probe neuron dynamics, but the rationale for selecting specific stimuli has never been rigorously justified. The present experimental and theoretical study proposes a novel framework, inspired by learning theory, for objectively selecting the stimuli that best unravel the neuron's dynamics. The efficacy of stimuli is assessed in terms of their ability to constrain the parameter space of biophysically detailed conductance-based models that faithfully replicate the neuron's dynamics as attested by their ability to generalize well to the neuron's response to novel experimental stimuli. We used this framework to evaluate a variety of stimuli in different types of cortical neurons, ages and animals. Despite their simplicity, a set of stimuli consisting of step and ramp current pulses outperforms synaptic-like noisy stimuli in revealing the dynamics of these neurons. The general framework that we propose paves a new way for defining, evaluating and standardizing effective electrical probing of neurons and will thus lay the foundation for a much deeper understanding of the electrical nature of these highly sophisticated and non-linear devices and of the neuronal networks that they compose

A Project Portfolio Management Approach to Tacklingthe Exploration/Exploitation Trade-off

Organizational ambidexterity (OA) is an essen-tial capability for surviving in dynamic business environ-ments that advocates the simultaneous engagement inexploration and exploitation. Over the last decades,knowledge on OA has substantially matured, coveringinsights into antecedents, outcomes, and moderators of OA.However, there is little prescriptive knowledge that offersguidance on how to put OA into practice and to tackle thetrade-off between exploration and exploitation. To addressthis gap, the authors adopt the design science researchparadigm and propose an economic decision model asartifact. The decision model assists organizations inselecting and scheduling exploration and exploitation pro-jects to become ambidextrous in an economically reason-able manner. As for justificatory knowledge, the decisionmodel draws from prescriptive knowledge on projectportfolio management and value-based management, andfrom descriptive knowledge related to OA to structure thefield of action. To evaluate the decision model, its designspecification is discussed against theory-backed designobjectives and with industry experts. The paper alsoinstantiates the decision model as a software prototype andapplies the prototype to a case based on real-world data

New Multi-objective Decision Support Methodology to Solve Problems of Reconfiguration in the Electric Distribution Systems

Part 13: Energy: Decision SupportInternational audienceThe distribution systems (DS) reconfiguration problem is formulated in this paper as a multi-objective mixed-integer linear programming (MILP) multi-period problem, enforcing that the obtained topology is radial in order to exploit several advantages those configurations offer. The effects of distributed generation (DG) and energy storage systems (ESS) are also investigated. To address the multi-objective problem, an improved implementation of the ε-constraint method (AUGMECON-2) is used, providing an adequate representation of the Pareto set. The objective functions considered stand for the minimization of active power losses and the minimization of switching operations. The proposed methodology is tested using a real system based on the S. Miguel Island, Azores, Portugal. The potential uses of cloud-based engineering systems, both in terms of exploiting the enhanced decentralized computational opportunities they offer and of utilizing them in order to achieve communication and coordination between several entities that are engaged in DS, are thoroughly discussed