Tax revenue accruing from the commercialization of research findings as an indicator for economic benefits of government financed research

In this article, we propose the use of tax payments accruing from the commercialization of research findings as a measure of research benefits complementing the existing range of evaluation tools. We place this novel approach to assess the economic returns to publicly funded research in the context of previous studies and highlight its advantages. The application of our method over a long period is demonstrated with the example of saccharin, which was discovered in the context of a curiosity-driven fundamental research project. In our study, we focused on Monsanto's commercial saccharin production finding notable return

Query processing of spatial objects: Complexity versus Redundancy

The management of complex spatial objects in applications, such as geography and cartography, imposes stringent new requirements on spatial database systems, in particular on efficient query processing. As shown before, the performance of spatial query processing can be improved by decomposing complex spatial objects into simple components. Up to now, only decomposition techniques generating a linear number of very simple components, e.g. triangles or trapezoids, have been considered. In this paper, we will investigate the natural trade-off between the complexity of the components and the redundancy, i.e. the number of components, with respect to its effect on efficient query processing. In particular, we present two new decomposition methods generating a better balance between the complexity and the number of components than previously known techniques. We compare these new decomposition methods to the traditional undecomposed representation as well as to the well-known decomposition into convex polygons with respect to their performance in spatial query processing. This comparison points out that for a wide range of query selectivity the new decomposition techniques clearly outperform both the undecomposed representation and the convex decomposition method. More important than the absolute gain in performance by a factor of up to an order of magnitude is the robust performance of our new decomposition techniques over the whole range of query selectivity

Point force manipulation and activated dynamics of polymers adsorbed on structured substrates

We study the activated motion of adsorbed polymers which are driven over a structured substrate by a localized point force.Our theory applies to experiments with single polymers using, for example, tips of scanning force microscopes to drag the polymer.We consider both flexible and semiflexible polymers,and the lateral surface structure is represented by double-well or periodic potentials. The dynamics is governed by kink-like excitations for which we calculate shapes, energies, and critical point forces. Thermally activated motion proceeds by the nucleation of a kink-antikink pair at the point where the force is applied and subsequent diffusive separation of kink and antikink. In the stationary state of the driven polymer, the collective kink dynamics can be described by an one-dimensional symmetric simple exclusion process.Comment: 7 pages, 2 Figure

Effect of hydraulic parameters on sediment transport capacity in overland flow over erodible beds

Sediment transport is an important component of the soil erosion process, which depends on several hydraulic parameters like unit discharge, mean flow velocity, and slope gradient. In most of the previous studies, the impact of these hydraulic parameters on transport capacity was studied for non-erodible bed conditions. Hence, this study aimed to examine the influence of unit discharge, mean flow velocity and slope gradient on sediment transport capacity for erodible beds and also to investigate the relationship between transport capacity and composite force predictors, i.e. shear stress, stream power, unit stream power and effective stream power. In order to accomplish the objectives, experiments were carried out in a 3.0 m long and 0.5 m wide flume using four well sorted sands (0.230, 0.536, 0.719, 1.022 mm). Unit discharges ranging from 0.07 to 2.07 × 10<sup>−3</sup> m<sup>2</sup> s<sup>−1</sup> were simulated inside the flume at four slopes (5.2, 8.7, 13.2 and 17.6%) to analyze their impact on sediment transport rate. The sediment transport rate measured at the bottom end of the flume by taking water and sediment samples was considered equal to sediment transport capacity, because the selected flume length of 3.0 m was found sufficient to reach the transport capacity. The experimental result reveals that the slope gradient has a stronger impact on transport capacity than unit discharge and mean flow velocity due to the fact that the tangential component of gravity force increases with slope gradient. Our results show that unit stream power is an optimal composite force predictor for estimating transport capacity. Stream power and effective stream power can also be successfully related to the transport capacity, however the relations are strongly dependent on grain size. Shear stress showed poor performance, because part of shear stress is dissipated by bed irregularities, bed form evolution and sediment detachment. An empirical transport capacity equation was derived, which illustrates that transport capacity can be predicted from median grain size, total discharge and slope gradient

Glassy freezing of orbital dynamics in FeCr2S4 and FeSc2S4

We report on a thorough dielectric investigation of the glass-like freezing of the orbital reorientation-dynamics, recently found for the crystalline sulpho-spinels FeCr2S4 and FeSc2S4. As the orbital reorientations are coupled to a rearrangement of the surrounding ionic lattice via the Jahn-Teller effect, the freezing of the orbital moments is revealed by a relaxational behaviour of the complex dielectric permittivity. Additional conductivity (both dc and ac) and contact contributions showing up in the spectra are taken into account by an equivalent circuit description. The orbital relaxation dynamics continuously slows down over six decades in time, before at the lowest temperatures the glass transition becomes suppressed by quantum tunnelling.Comment: J. Non-Cryst. Solids, in press. 6 pages, 4 figure

Multi-Step Processing of Spatial Joins

Spatial joins are one of the most important operations for combining spatial objects of several relations. In this paper, spatial join processing is studied in detail for extended spatial objects in twodimensional data space. We present an approach for spatial join processing that is based on three steps. First, a spatial join is performed on the minimum bounding rectangles of the objects returning a set of candidates. Various approaches for accelerating this step of join processing have been examined at the last year’s conference [BKS 93a]. In this paper, we focus on the problem how to compute the answers from the set of candidates which is handled by the following two steps. First of all, sophisticated approximations are used to identify answers as well as to filter out false hits from the set of candidates. For this purpose, we investigate various types of conservative and progressive approximations. In the last step, the exact geometry of the remaining candidates has to be tested against the join predicate. The time required for computing spatial join predicates can essentially be reduced when objects are adequately organized in main memory. In our approach, objects are first decomposed into simple components which are exclusively organized by a main-memory resident spatial data structure. Overall, we present a complete approach of spatial join processing on complex spatial objects. The performance of the individual steps of our approach is evaluated with data sets from real cartographic applications. The results show that our approach reduces the total execution time of the spatial join by factors

Adaptive Path Planning for Depth Constrained Bathymetric Mapping with an Autonomous Surface Vessel

This paper describes the design, implementation and testing of a suite of algorithms to enable depth constrained autonomous bathymetric (underwater topography) mapping by an Autonomous Surface Vessel (ASV). Given a target depth and a bounding polygon, the ASV will find and follow the intersection of the bounding polygon and the depth contour as modeled online with a Gaussian Process (GP). This intersection, once mapped, will then be used as a boundary within which a path will be planned for coverage to build a map of the Bathymetry. Methods for sequential updates to GP's are described allowing online fitting, prediction and hyper-parameter optimisation on a small embedded PC. New algorithms are introduced for the partitioning of convex polygons to allow efficient path planning for coverage. These algorithms are tested both in simulation and in the field with a small twin hull differential thrust vessel built for the task.Comment: 21 pages, 9 Figures, 1 Table. Submitted to The Journal of Field Robotic

Efficient Processing of Spatial Joins Using R-Trees

Abstract: In this paper, we show that spatial joins are very suitable to be processed on a parallel hardware platform. The parallel system is equipped with a so-called shared virtual memory which is well-suited for the design and implementation of parallel spatial join algorithms. We start with an algorithm that consists of three phases: task creation, task assignment and parallel task execu-tion. In order to reduce CPU- and I/O-cost, the three phases are processed in a fashion that pre-serves spatial locality. Dynamic load balancing is achieved by splitting tasks into smaller ones and reassigning some of the smaller tasks to idle processors. In an experimental performance compar-ison, we identify the advantages and disadvantages of several variants of our algorithm. The most efficient one shows an almost optimal speed-up under the assumption that the number of disks is sufficiently large. Topics: spatial database systems, parallel database systems