The Aesthetics of Theory Selection and the Logics of Art

Philosophers of science discuss whether theory selection depends on aesthetic judgments or criteria, and whether these putatively aesthetic features are genuinely extra-epistemic. As examples, judgments involving criteria such as simplicity and symmetry are often cited. However, other theory selection criteria, such as fecundity, coherence, internal consistency, and fertility, more closely match those criteria used in art contexts and by scholars working in aesthetics. Paying closer attention to the way these criteria are used in art contexts allows us to understand some evaluative and developmental practices in scientific theory selection as genuinely aesthetic, enlarging the scope of the goals of science

Long-term effects of timber management on marten (Martes americana) habitat potential in an Ontario boreal forest

To evaluate the hypothesis that current forest management practices in the boreal forest are decreasing the quantity and quality of long-term marten habitat, and alternative, more suitable strategies exist, a Geographic Information System (GlS)-based simulation study was initiated to determine the habitat suitability for marten of a boreal forest under various timber management strategies. Two simulation models were used in this study. The first was the Harvest Schedule Generator (HSG), a wood-supply model created at the Petawawa National Forestry Institute (Forestry Canada). The second was a marten Habitat Suitability Index (HSI) model developed for this study. Each of the timber harvest strategies decreased the amount of long-term marten habitat. However, slight decreases in the level of spruce harvest provide significant future increases in suitable habitat. In the short term, delayed harvest of mature black spruce stands provides an improvement in marten habitat suitability. The procedures developed in this study provide valuable quantitative information which can be used to aid in forest management decision making

Topology of the European Network of Earth Observation Networks and the need for an European Network of Networks

Research programe: Ecosystems Services and Management (ESM)ConnectinGEO (Coordinating an Observation Network of Networks EnCompassing saTellite and IN-situ to fill the Gaps in European Observations" is an H2020 Coordination and Support Action with the primary goal of linking existing Earth Observation networks with science and technology (S&T) communities, the industry sector, the Group on Earth Observations (GEO), and Copernicus. The project will end in February 2017. ConnectinGEO will initiate a European Network of Earth Observation Networks (ENEON) that will encompass space-based, airborne and in-situ observations networks. ENEON will be composed of project partners representing thematic observation networks along with the GEOSS Science and Technology Stakeholder Network, GEO Communities of Practices, Copernicus services, Sentinel missions and in-situ support data representatives, representatives of the European space-based, airborne and in-situ observations networks. This communication presents the complex panorama of Earth Observations Networks in Europe. The list of networks is classified by discipline, variables, geospatial scope, etc. We also capture the membership and relations with other networks and umbrella organizations like GEO. The result is a complex interrelation between networks that can not be clearly expressed in a flat list. Technically the networks can be represented as nodes with relations between them as lines connecting the nodes in a graph. We have chosen RDF as a language and an AllegroGraph 3.3 triple store that is visualized in several ways using for example Gruff 5.7. Our final aim is to identify gaps in the EO Networks and justify the need for a more structured coordination between them

Attachment styles and clinical communication performance in trainee doctors

Objective To investigate the relationship between trainee doctors’ attachment style and their performance in qualifying clinical and communication skills assessments. Methods Participants were 190 undergraduate medical students whose performance was assessed by examiners across two areas (communication and clinical skills) during their qualifying Objective Structured Clinical Examination (OSCE). Simulated patients also rated communication skills. Participants’ attachment style was rated across two dimensions, avoidance and anxiety, with the Relationship Questionnaire (RQ). Results Lower levels of attachment avoidance and anxiety were significant predictors of higher performance in both communication and clinical skills. Conclusion Trainee doctors’ attachment styles are associated with patient communication and clinical performance. Further research is needed to investigate the impact of attachment on consultations between doctors and patients within clinical settings. Practice implication Attachment theory can inform our understanding why, for some student doctors, interacting with patients may be particularly challenging and require additional support by medical educators

How sensitive are estimates of carbon fixation in agricultural models to input data?

<p>Abstract</p> <p>Background</p> <p>Process based vegetation models are central to understand the hydrological and carbon cycle. To achieve useful results at regional to global scales, such models require various input data from a wide range of earth observations. Since the geographical extent of these datasets varies from local to global scale, data quality and validity is of major interest when they are chosen for use. It is important to assess the effect of different input datasets in terms of quality to model outputs. In this article, we reflect on both: the uncertainty in input data and the reliability of model results. For our case study analysis we selected the Marchfeld region in Austria. We used independent meteorological datasets from the Central Institute for Meteorology and Geodynamics and the European Centre for Medium-Range Weather Forecasts (ECMWF). Land cover / land use information was taken from the GLC2000 and the CORINE 2000 products.</p> <p>Results</p> <p>For our case study analysis we selected two different process based models: the Environmental Policy Integrated Climate (EPIC) and the Biosphere Energy Transfer Hydrology (BETHY/DLR) model. Both process models show a congruent pattern to changes in input data. The annual variability of NPP reaches 36% for BETHY/DLR and 39% for EPIC when changing major input datasets. However, EPIC is less sensitive to meteorological input data than BETHY/DLR. The ECMWF maximum temperatures show a systematic pattern. Temperatures above 20°C are overestimated, whereas temperatures below 20°C are underestimated, resulting in an overall underestimation of NPP in both models. Besides, BETHY/DLR is sensitive to the choice and accuracy of the land cover product.</p> <p>Discussion</p> <p>This study shows that the impact of input data uncertainty on modelling results need to be assessed: whenever the models are applied under new conditions, local data should be used for both input and result comparison.</p

How many people need to classify the same image? A method for optimizing volunteer contributions in binary geographical classifications

Involving members of the public in image classification tasks that can be tricky to automate is increasingly recognized as a way to complete large amounts of these tasks and promote citizen involvement in science. While this labor is usually provided for free, it is still limited, making it important for researchers to use volunteer contributions as efficiently as possible. Using volunteer labor efficiently becomes complicated when individual tasks are assigned to multiple volunteers to increase confidence that the correct classification has been reached. In this paper, we develop a system to decide when enough information has been accumulated to confidently declare an image to be classified and remove it from circulation. We use a Bayesian approach to estimate the posterior distribution of the mean rating in a binary image classification task. Tasks are removed from circulation when user-defined certainty thresholds are reached. We demonstrate this process using a set of over 4.5 million unique classifications by 2783 volunteers of over 190,000 images assessed for the presence/absence of cropland. If the system outlined here had been implemented in the original data collection campaign, it would have eliminated the need for 59.4% of volunteer ratings. Had this effort been applied to new tasks, it would have allowed an estimated 2.46 times as many images to have been classified with the same amount of labor, demonstrating the power of this method to make more efficient use of limited volunteer contributions. To simplify implementation of this method by other investigators, we provide cutoff value combinations for one set of confidence levels

D7.4 Strategic view for the sustainability of ENEON after the end of the project

EU Framework Program for Research and Innovation (SC5-18a-2014 - H2020)Project title: Coordinating an Observation Network of Networks EnCompassing saTellite and IN situ to fill the Gaps in European ObservationsTheme: SC5-18a-2014. Coordinating European Observation Networks to reinforce the knowledge base for climate, natural resources and raw materials.Report with options for the continuation and sustainability of ENEON after the end of the project

Economic Development and Forest Cover: Evidence from Satellite Data

We use satellite data on forest cover along national borders in order to study the determinants of deforestation differences across countries. We combine the forest cover information with data on homogeneous response units, which allow us to control for cross-country geoclimatic differences when assessing the drivers of deforestation. Income per capita appears to be the most robust determinant of differences in cross-border forest cover and our results present evidence of the existence of decreasing effects of income on forest cover as economic development progresses.(authors' abstract)Series: Department of Economics Working Paper Serie

A global-scale data set of mining areas

The area used for mineral extraction is a key indicator for understanding and mitigating the environmental impacts caused by the extractive sector. To date, worldwide data products on mineral extraction do not report the area used by mining activities. In this paper, we contribute to filling this gap by presenting a new data set of mining extents derived by visual interpretation of satellite images. We delineated mining areas within a 10 km buffer from the approximate geographical coordinates of more than six thousand active mining sites across the globe. The result is a global-scale data set consisting of 21,060 polygons that add up to 57,277 km². The polygons cover all mining above-ground features that could be identified from the satellite images, including open cuts, tailings dams, waste rock dumps, water ponds, and processing infrastructure. The data set is available for download from https://doi.org/10.1594/PANGAEA.910894 and visualization at www.fineprint.global/viewer