90,396 research outputs found

    Overcoming timescale and finite-size limitations to compute nucleation rates from small scale Well Tempered Metadynamics simulations

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    Condensation of a liquid droplet from a supersaturated vapour phase is initiated by a prototypical nucleation event. As such it is challenging to compute its rate from atomistic molecular dynamics simulations. In fact at realistic supersaturation conditions condensation occurs on time scales that far exceed what can be reached with conventional molecular dynamics methods. Another known problem in this context is the distortion of the free energy profile associated to nucleation due to the small, finite size of typical simulation boxes. In this work the problem of time scale is addressed with a recently developed enhanced sampling method while contextually correcting for finite size effects. We demonstrate our approach by studying the condensation of argon, and showing that characteristic nucleation times of the order of magnitude of hours can be reliably calculated, approaching realistic supersaturation conditions, thus bridging the gap between what standard molecular dynamics simulations can do and real physical systems.Comment: 9 pages, 7 figures, additional figures and data provided as supplementary information. Submitted to the Journal of Chemical Physisc

    Visual literacy for libraries: A practical, standards-based guide

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    When we step back and think about how to situate visual literacy into a library context, the word critical keeps coming up: critical thinking, critical viewing, critical using, critical making, and the list goes on. To understand our approach, start with your own practice, add images, and see where it takes you. Do you encourage students to think critically as they research? How can you extend this experience to images? Do you embrace critical information literacy? Can you bring visual content to enrich that experience? Do you teach students to critically evaluate sources? How can you expand that practice to images? You’ll see a lot of questions in this book, because our approach is inquiry- driven. This is not to say that we don’t cover the basics of image content. Curious about color? Covered. Not sure where to find great images? We’ll show you. Wondering what makes a good presentation? We talk about that too. But what we really want you to get out of this book is a new understanding of how images fit into our critical (there it is again) practice as librarians and how we can advance student learning with our own visual literacy. This book grounds visual literacy in your everyday practice—connecting it to what you know and do as a librarian who engages in reflective practice. Heidi Jacobs put it well when she argued that, for information literacy pedagogy, “one of the best ways for us to encourage students to be engaged learners is for us to become engaged learners, delve deeply into our own problem posing, and embody the kind of engagement we want to see in our students” (Jacobs 2008). We extend this viewpoint to visual literacy pedagogy and provide many opportunities for you to embody the kind of visual literacy that you want to develop in your learners

    The Black Death and the Future of the Plague

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    This essay summarizes what we know about the spread of Yersinia pestis today, assesses the potential risks of tomorrow, and suggests avenues for future collaboration among scientists and humanists. Plague is both a re-emerging infectious disease and a developed biological weapon, and it can be found in enzootic foci on every inhabited continent except Australia. Studies of the Black Death and successive epidemics can help us to prepare for and mitigate future outbreaks (and other pandemics) because analysis of medieval plagues provides a crucial context for modern scientific discoveries and theories. These studies prevent us from stopping at easy answers, and they force us to acknowledge that there is still much that we do not understand

    Acting Together to Lift up Philanthropy: WINGS Guidance on How to Build a Supportive Ecosystem

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    The guide shows how a philanthropy support ecosystem can be built. It uses a suite of tools and approaches that can be adapted by people in different countries to build the system that they want, by mapping relationships between organisations and sorting out who does what in order to lift up philanthropy. It is designed to allow for creativity and invention. The goal is to inspire the field by suggesting ways in which its work can be enhanced, rather than providing hard and fast rules. Although specific steps are suggested, these do not imply a rigid process that needs to be followed. Action depends on the context and the particular needs of the philanthropic sector

    Lives at the Border: Abandonment and Survival at the frontier of Lampedusa

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    Lampedusa is primarily portrayed as a European border which has been subjected to intense surveillance and securitisation. On the other hand, it is also the stage for various humanitarian interventions. Apart from being a spectacularized frontier, this dissertation shows how life in Lampedusa unfolds, through stories of cooperation and mutuality between the migrants, locals and migration workers in the context of acute abandonment. By describing their tendency to struggle for a sense of wellbeing, the thesis argues against a simplistic notion of bare life, based on a reductive imagery of the migrant, and it provides the ethnographic and theoretical instruments to critically engage with philosophical reflections by means of anthropology. Based on an eleven-month period of ethnographic fieldwork in Lampedusa, the dissertation explores the triangulated intersection of lives that is at play among migration workers, locals, and migrants. It examines their daily encounters, and it gives an insight into the hardship of the locals’ lives, their feelings towards migrants and the role of profit. Lampedusa can be defined as being simultaneously a borderland space, state of emergency, and realm of the absurd, where its multiple subjects, albeit in various forms, struggle to attain a balance between what they ought to do and what they can and cannot do. In transient conditions of indifference and acceptance, uncertainty and endurance, migrants, migration workers, and locals negotiate a resolution to what at times appears to be an irresolvable existential conundrum. Hence, this thesis explores humanness vis-a-vis self-interest and mutual sharing in borderlands, at geographical, historical, legal, social, and ethical boundaries

    Madura Coastal Potential as Ethnomathscience-Based Learning Content in Primary Schools

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    Utilization of the local cultural context in learning is one form of effort to optimize learning outcomes. Cultural context can be related to the content of lessons in schools such as mathematics (ethnomathematics) and science (ethnoscience). Ethnomathematics and ethnoscience, or what is later called ethnomathscience, is an approach to learning mathematics, physics, chemistry, and biology related to culture. Incorporating the potential of coastal tourism which is studied from an ethnomathscience point of view is very important in learning in order to prepare and shape the character of students who are always superior and ready to face the challenges of the times, but do not forget their ancestral heritage and are able to preserve both nature and culture. This study uses a mixed method that focuses on collecting, analyzing, and mixing qualitative and quantitative data in a single study. This research was conducted on the Madura Coast, especially in Pamekasan Regency. The research subjects were Pamekasan coastal communities, teachers, and students of Tanjung 3 Pamekasan Elementary School. The results of the study show that the Madura coast has the potential to be used as content in elementary school learning. Both teachers and students already understand the potential of the coast so that it can become the basis for contextual learning that promotes the culture of the local community. Mathematics and science content in elementary schools can be integrated with coastal culture

    A review of basic research tools without the confusing philosophy

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    One consequence of novice researchers studying methodology textbooks is confusion: philosophical terminology is complicated and sometimes poorly defined. Another consequence is that inexperienced researchers divide themselves into epistemological cliques, which can inhibit inter-disciplinary discussions. This is a particular problem in subjects, such as Information Science, that bridge disciplines. This article attempts to address these issues by seeking ground common to researchers, regardless of their philosophical standpoint. It identifies several ‘tools of the mind’ which are expanded on and discussed. By becoming familiar with these tools, inexperienced researchers can gain practical insights that create context for philosophical terms they later encounter. ‘Tools of the mind’ discussed are captured in the following questions: 1. What should I research? 2. How do I go about researching it? 3. What assumptions have earlier researchers made? 4. What assumptions can I make without being challenged? 5. How can I indicate what it is that I am studying to researchers who wish to build on my work? 6. What can usefully be compared to the phenomenon I am researching? 7. When circumstances change, what new research opportunities arise? 8. How do I tell my research story so that it will be reliably transmitted

    Programming by Demonstration on Riemannian Manifolds

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    This thesis presents a Riemannian approach to Programming by Demonstration (PbD). It generalizes an existing PbD method from Euclidean manifolds to Riemannian manifolds. In this abstract, we review the objectives, methods and contributions of the presented approach. OBJECTIVES PbD aims at providing a user-friendly method for skill transfer between human and robot. It enables a user to teach a robot new tasks using few demonstrations. In order to surpass simple record-and-replay, methods for PbD need to \u2018understand\u2019 what to imitate; they need to extract the functional goals of a task from the demonstration data. This is typically achieved through the application of statisticalmethods. The variety of data encountered in robotics is large. Typical manipulation tasks involve position, orientation, stiffness, force and torque data. These data are not solely Euclidean. Instead, they originate from a variety of manifolds, curved spaces that are only locally Euclidean. Elementary operations, such as summation, are not defined on manifolds. Consequently, standard statistical methods are not well suited to analyze demonstration data that originate fromnon-Euclidean manifolds. In order to effectively extract what-to-imitate, methods for PbD should take into account the underlying geometry of the demonstration manifold; they should be geometry-aware. Successful task execution does not solely depend on the control of individual task variables. By controlling variables individually, a task might fail when one is perturbed and the others do not respond. Task execution also relies on couplings among task variables. These couplings describe functional relations which are often called synergies. In order to understand what-to-imitate, PbDmethods should be able to extract and encode synergies; they should be synergetic. In unstructured environments, it is unlikely that tasks are found in the same scenario twice. The circumstances under which a task is executed\u2014the task context\u2014are more likely to differ each time it is executed. Task context does not only vary during task execution, it also varies while learning and recognizing tasks. To be effective, a robot should be able to learn, recognize and synthesize skills in a variety of familiar and unfamiliar contexts; this can be achieved when its skill representation is context-adaptive. THE RIEMANNIAN APPROACH In this thesis, we present a skill representation that is geometry-aware, synergetic and context-adaptive. The presented method is probabilistic; it assumes that demonstrations are samples from an unknown probability distribution. This distribution is approximated using a Riemannian GaussianMixtureModel (GMM). Instead of using the \u2018standard\u2019 Euclidean Gaussian, we rely on the Riemannian Gaussian\u2014 a distribution akin the Gaussian, but defined on a Riemannian manifold. A Riev mannian manifold is a manifold\u2014a curved space which is locally Euclidean\u2014that provides a notion of distance. This notion is essential for statistical methods as such methods rely on a distance measure. Examples of Riemannian manifolds in robotics are: the Euclidean spacewhich is used for spatial data, forces or torques; the spherical manifolds, which can be used for orientation data defined as unit quaternions; and Symmetric Positive Definite (SPD) manifolds, which can be used to represent stiffness and manipulability. The Riemannian Gaussian is intrinsically geometry-aware. Its definition is based on the geometry of the manifold, and therefore takes into account the manifold curvature. In robotics, the manifold structure is often known beforehand. In the case of PbD, it follows from the structure of the demonstration data. Like the Gaussian distribution, the Riemannian Gaussian is defined by a mean and covariance. The covariance describes the variance and correlation among the state variables. These can be interpreted as local functional couplings among state variables: synergies. This makes the Riemannian Gaussian synergetic. Furthermore, information encoded in multiple Riemannian Gaussians can be fused using the Riemannian product of Gaussians. This feature allows us to construct a probabilistic context-adaptive task representation. CONTRIBUTIONS In particular, this thesis presents a generalization of existing methods of PbD, namely GMM-GMR and TP-GMM. This generalization involves the definition ofMaximum Likelihood Estimate (MLE), Gaussian conditioning and Gaussian product for the Riemannian Gaussian, and the definition of ExpectationMaximization (EM) and GaussianMixture Regression (GMR) for the Riemannian GMM. In this generalization, we contributed by proposing to use parallel transport for Gaussian conditioning. Furthermore, we presented a unified approach to solve the aforementioned operations using aGauss-Newton algorithm. We demonstrated how synergies, encoded in a Riemannian Gaussian, can be transformed into synergetic control policies using standard methods for LinearQuadratic Regulator (LQR). This is achieved by formulating the LQR problem in a (Euclidean) tangent space of the Riemannian manifold. Finally, we demonstrated how the contextadaptive Task-Parameterized Gaussian Mixture Model (TP-GMM) can be used for context inference\u2014the ability to extract context from demonstration data of known tasks. Our approach is the first attempt of context inference in the light of TP-GMM. Although effective, we showed that it requires further improvements in terms of speed and reliability. The efficacy of the Riemannian approach is demonstrated in a variety of scenarios. In shared control, the Riemannian Gaussian is used to represent control intentions of a human operator and an assistive system. Doing so, the properties of the Gaussian can be employed to mix their control intentions. This yields shared-control systems that continuously re-evaluate and assign control authority based on input confidence. The context-adaptive TP-GMMis demonstrated in a Pick & Place task with changing pick and place locations, a box-taping task with changing box sizes, and a trajectory tracking task typically found in industr

    The implementation of General Practitioner Maternity Unit closure proposals in hospitals

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    This dissertation examines the 'implementation gap' and reports evidence on progress in implementing closure of health services at micro-implementation level. Specifically, the research develops an historically bound, processual and contextual account of the development and fate of permanent closures of General Practitioner Maternity Units (GPMU) in four neighbouring Oxford DHAs. The major objectives of this study are to illustrate and analyse the process by which the 'implementation gap' is closed and to identify. some of the potentially important factors which help to explain the pace and rate of change differential across health districts. The key questions, guiding the research include: What affects the pace of implementation? Why do districts fail or succeed in implementing change? What affects the 'implementability' of the GPMU closure proposals? To make further progress towards an understanding of implementation, this research adopts a new, eclectic, and integrative approach: the Contextualist Approach. One major theme underlying most of the results and ideas presented here, is that the outcome of implementation can be explained by the interplay between the content, the context and the process of implementation itself. The research is essentially qualitative. The data collection process comprises three main activities: documentary search, in-depth interviews, and ethnographic material. The strategy of data presentation and analysis was to develop a descriptive framework for organising the data (Yin, 1989). A set of three interacting groups of factors is found to affect implementability and rate and pace of change at micro-implementation level - the nature of the locale, leadership, and the quality of the proposal itself. Although other authors have studied health service policy, this research is unique in offering an extensive treatment of the changing policy context under investigation. It is also the first to investigate partial, as opposed to total, closure of hospitals within the context of the NHS, with particular emphasis on the GPMU
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