An exploratory case study of Olympiad students’ attitudes towards and passion for science

Much is known about high school students’ attitudes towards science but there is almost no research on what passion for science might look like and how it might be manifested. This exploratory case study took advantage of a unique group of highly gifted science students participating in the Australian Science Olympiad (n=69) to explore their attitudes towards school science and science as presented in the Olympiad summer camp. In particular the role the summer camp might play in igniting the students’ passion for science was a focus of the research. Data were collected through a two tiered survey of students’ attitudes towards school science, an evaluative survey of the Olympiad summer camp and in-depth interviews with six participants. Findings indicated that Olympiad students generally had positive attitudes towards school science with most selecting science as one of their favourite subjects. However, an underlying ambivalence about school science was noted in the data. In contrast, the Olympiad summer camp transformed students’ positive attitudes into passion for science. Seven themes emerged from the data providing a foundation for a model of what academic passion for science looks like

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

Achieving Deep Cuts in the Carbon Intensity of U.S. Automobile Transportation by 2050: Complementary Roles for Electricity and Biofuels

Passenger cars in the United States (U.S.) rely primarily on petroleum-derived fuels and contribute the majority of U.S. transportation-related greenhouse gas (GHG) emissions. Electricity and biofuels are two promising alternatives for reducing both the carbon intensity of automotive transportation and U.S. reliance on imported oil. However, as standalone solutions, the biofuels option is limited by land availability and the electricity option is limited by market adoption rates and technical challenges. This paper explores potential GHG emissions reductions attainable in the United States through 2050 with a county-level scenario analysis that combines ambitious plug-in hybrid electric vehicle (PHEV) adoption rates with scale-up of cellulosic ethanol production. With PHEVs achieving a 58% share of the passenger car fleet by 2050, phasing out most corn ethanol and limiting cellulosic ethanol feedstocks to sustainably produced crop residues and dedicated crops, we project that the United States could supply the liquid fuels needed for the automobile fleet with an average blend of 80% ethanol (by volume) and 20% gasoline. If electricity for PHEV charging could be supplied by a combination of renewables and natural-gas combined-cycle power plants, the carbon intensity of automotive transport would be 79 g CO2e per vehicle-kilometer traveled, a 71% reduction relative to 2013