U-Pb isotopic results for single shocked and polycrystalline zircons record 550-65.5-Ma ages for a K-T target site and 2700-1850-Ma ages for the Sudbury impact event

The refractory mineral zircon develops distinct morphological features during shock metamorphism and retains these features under conditions that would anneal them in other minerals. In addition, weakly shocked zircon grains give primary ages for the impact site, while highly reconstituted (polycrystalline) single grains give ages that approach the age of the impact event. Data for a series of originally coeval grains will define a mixing line that gives both of these ages providing that no subsequent geological disturbances have overprinted the isotopic systematics. In this study, we have shown that the three zircon grain types described by Bohor, from both K-T distal ejecta (Fireball layer, Raton Basin, Colorado) and the Onaping Formation, represent a progressive increase in impact-related morphological change that coincides with a progressive increase in isotopic resetting in zircons from the ejecta and basement rocks. Unshocked grains are least affected by isotopic resetting while polycrystalline grains are most affected. U-Pb isotopic results for 12 of 14 single zircon grains from the Fireball layer plot on or close to a line recording a primary age of 550 +/- 10 Ma and a secondary age of 65.5 +/- 3 Ma. Data for the least and most shocked grains plot closest to the primary and secondary ages respectively. The two other grains each give ages between 300 and 350 Ma. This implies that the target ejecta was dominated by 550-Ma rocks and that the recrystallization features of the zircon were superimposed during the impact event at 65.5 Ma. A predominant age of 550 Ma for zircons from the Fireball layer provides an excellent opportunity to identify the impact site and to test the hypothesis that multiple impacts occurred at this time. A volcanic origin for the Fireball layer is ruled out by shock-related morphological changes in zircon and the fact that the least shocked grains are old. Basement Levack gneisses north of the Sudbury structure have a primary age of 2711 Ma. Data for three single zircons from this rock, which record a progressive increase in shock features, are displaced 24, 36, and 45 percent along a Pb-loss line toward the 1850 +/- 1 Ma minimum age for the impact as defined by the age of the norite. Southeast of the structure three shocked grains from the Murray granite record a primary age of 2468 Ma and are displaced 24, 41, and 56 percent toward the 1853 +/- 4 Ma even as defined by coexisting titanite

Statistical Mechanics of Nonlinear On-line Learning for Ensemble Teachers

We analyze the generalization performance of a student in a model composed of nonlinear perceptrons: a true teacher, ensemble teachers, and the student. We calculate the generalization error of the student analytically or numerically using statistical mechanics in the framework of on-line learning. We treat two well-known learning rules: Hebbian learning and perceptron learning. As a result, it is proven that the nonlinear model shows qualitatively different behaviors from the linear model. Moreover, it is clarified that Hebbian learning and perceptron learning show qualitatively different behaviors from each other. In Hebbian learning, we can analytically obtain the solutions. In this case, the generalization error monotonically decreases. The steady value of the generalization error is independent of the learning rate. The larger the number of teachers is and the more variety the ensemble teachers have, the smaller the generalization error is. In perceptron learning, we have to numerically obtain the solutions. In this case, the dynamical behaviors of the generalization error are non-monotonic. The smaller the learning rate is, the larger the number of teachers is; and the more variety the ensemble teachers have, the smaller the minimum value of the generalization error is.Comment: 13 pages, 9 figure

Statistical Mechanics of Time Domain Ensemble Learning

Conventional ensemble learning combines students in the space domain. On the other hand, in this paper we combine students in the time domain and call it time domain ensemble learning. In this paper, we analyze the generalization performance of time domain ensemble learning in the framework of online learning using a statistical mechanical method. We treat a model in which both the teacher and the student are linear perceptrons with noises. Time domain ensemble learning is twice as effective as conventional space domain ensemble learning.Comment: 10 pages, 10 figure

Communal resources in open source software development

Introduction: Virtual communities play an important role in innovation. The paper focuses on the particular form of collective action in virtual communities underlying as Open Source software development projects. Method: Building on resource mobilization theory and private-collective innovation, we propose a theory of collective action in innovative virtual communities. We identify three communal resources (reputation, control over technology and learning opportunities) that appear as a byproduct while developing open source software. Analysis:Constructs are derived from exiting literature. Empirical data from Freenet, an open source software project for peer-to-peer software, illustrates both the levels of involvement and the communal resources. Results & conclusions: Communal resources are able to solve the collective action dilemma for virtual communities. We show that they increase in value for individuals along with their involvement in the community

Virtual Forest Bathing Programming as Experienced by Disabled Adults with Mobility Impairments and/or Low Energy: A Qualitative Study

Background: Although access to nature is demonstrated to benefit health and wellbeing, adults with mobility impairments and/or low energy often face barriers in accessing nature environments and nature-based programs. This study aimed to examine the experiences and impacts of virtual forest bathing by capturing the perspectives of disabled adults with mobility impairments and/or low energy. Methods: A total of 26 adults with mobility impairments provided written and spoken qualitative feedback during and following virtual forest bathing programs and 23 participants provided feedback at a one month follow-up. Virtual programs were presented online, using an accessible format, 2D videos, and images of nature accompanied by guidance led by a certified forest bathing guide and mindfulness teacher. The programs involved disabled facilitators and participants, which created a social environment of peer support. Results: Qualitative thematic analysis revealed 10 themes comprising intervention themes (virtual delivery and soothing facilitation); process themes (nature connection, relaxation, embodiment, and memories with complex emotions); and outcome themes (happiness, agency, metaphor making, and belonging). Conclusions: Virtual forest bathing may offer an effective adjunct to improve wellbeing and provide peer support for disabled adults with mobility impairments and/or low energy

Statistical Mechanics of Linear and Nonlinear Time-Domain Ensemble Learning

Conventional ensemble learning combines students in the space domain. In this paper, however, we combine students in the time domain and call it time-domain ensemble learning. We analyze, compare, and discuss the generalization performances regarding time-domain ensemble learning of both a linear model and a nonlinear model. Analyzing in the framework of online learning using a statistical mechanical method, we show the qualitatively different behaviors between the two models. In a linear model, the dynamical behaviors of the generalization error are monotonic. We analytically show that time-domain ensemble learning is twice as effective as conventional ensemble learning. Furthermore, the generalization error of a nonlinear model features nonmonotonic dynamical behaviors when the learning rate is small. We numerically show that the generalization performance can be improved remarkably by using this phenomenon and the divergence of students in the time domain.Comment: 11 pages, 7 figure

Carrots and Rainbows: Motivation and Social Practice in Open Source Software Development

Open source software (OSS) is a social and economic phenomenon that raises fundamental questions about the motivations of contributors to information systems development. Some developers are unpaid volunteers who seek to solve their own technical problems, while others create OSS as part of their employment contract. For the past 10 years, a substantial amount of academic work has theorized about and empirically examined developer motivations. We review this work and suggest considering motivation in terms of the values of the social practice in which developers participate. Based on the social philosophy of Alasdair MacIntyre, we construct a theoretical framework that expands our assumptions about individual motivation to include the idea of a long-term, value-informed quest beyond short-term rewards. This motivation-practice framework depicts how the social practice and its supporting institutions mediate between individual motivation and outcome. The framework contains three theoretical conjectures that seek to explain how collectively elaborated standards of excellence prompt developers to produce high-quality software, change institutions, and sustain OSS development. From the framework, we derive six concrete propositions and suggest a new research agenda on motivation in OSS

Under the radar: Industry entry by user entrepreneurs

We inductively develop a model of the commercialization process for new products or services user entrepreneurs undertake when entering an industry while drawing on proprietary technology developed in another industry. Extending the growing field of user entrepreneurship, we identify a two-phase approach to industry entry by user entrepreneurs who start "under the radar" of incumbent firms, gain experience, attract a first potential customer base, and then, in a second phase, engage in commercialization. During this process, a community of fellow users is of major importance for the entrepreneur, serving as a knowledge pool for skills development and experimentation with different commercialization paths. We study a nascent group of firms founded by users of video games who became entrepreneurs on entering the animation industry by producing Machinima, a new film genre characterized by shooting film in video games. We explain how user entrepreneurs gain access to complementary assets (video games) for their new use (shooting film), how they deal with intellectual property issues when using other firms' assets, and how user entrepreneurs combine domain knowledge about film production with their experience in video games and the art of Machinima. Our propositions hold implications for management and policy