The spiral spin state in a zigzag spin chain system

We considered a spin chain with nearest neighbor and next nearest neighbor exchange interactions, anisotropic exchange interaction and Dzyaloshinskii-Moriya interaction. The conditions of the spiral spin state as the ground state were analyzed. Our method was to build the connection between the spiral state and the fully polarized state with a unitary transformation. Under this transformation, anisotropic exchange interaction and Dzyaloshinskii-Moriya interaction can be transformed to each other. Then we used positive semi-definite matrix theorem to identify the region of fully polarized state as the ground state for the transformed Hamiltonian, and it is the region of spiral spin state as the ground state of the original Hamiltonian. We also found that the effect of Dzyaloshinskii-Moriya interaction is important. Its strength is related to the pitch angle of spiral spins. Our method can be applied to coupled spin chains and two dimensional triangular lattice systems. The result can be compared with experiment data.Comment: 12 pages, 9 figure

Classifying document types to enhance search and recommendations in digital libraries

In this paper, we address the problem of classifying documents available from the global network of (open access) repositories according to their type. We show that the metadata provided by repositories enabling us to distinguish research papers, thesis and slides are missing in over 60% of cases. While these metadata describing document types are useful in a variety of scenarios ranging from research analytics to improving search and recommender (SR) systems, this problem has not yet been sufficiently addressed in the context of the repositories infrastructure. We have developed a new approach for classifying document types using supervised machine learning based exclusively on text specific features. We achieve 0.96 F1-score using the random forest and Adaboost classifiers, which are the best performing models on our data. By analysing the SR system logs of the CORE [1] digital library aggregator, we show that users are an order of magnitude more likely to click on research papers and thesis than on slides. This suggests that using document types as a feature for ranking/filtering SR results in digital libraries has the potential to improve user experience.Comment: 12 pages, 21st International Conference on Theory and Practise of Digital Libraries (TPDL), 2017, Thessaloniki, Greec

Statistical framework for video decoding complexity modeling and prediction

Video decoding complexity modeling and prediction is an increasingly important issue for efficient resource utilization in a variety of applications, including task scheduling, receiver-driven complexity shaping, and adaptive dynamic voltage scaling. In this paper we present a novel view of this problem based on a statistical framework perspective. We explore the statistical structure (clustering) of the execution time required by each video decoder module (entropy decoding, motion compensation, etc.) in conjunction with complexity features that are easily extractable at encoding time (representing the properties of each module's input source data). For this purpose, we employ Gaussian mixture models (GMMs) and an expectation-maximization algorithm to estimate the joint execution-time - feature probability density function (PDF). A training set of typical video sequences is used for this purpose in an offline estimation process. The obtained GMM representation is used in conjunction with the complexity features of new video sequences to predict the execution time required for the decoding of these sequences. Several prediction approaches are discussed and compared. The potential mismatch between the training set and new video content is addressed by adaptive online joint-PDF re-estimation. An experimental comparison is performed to evaluate the different approaches and compare the proposed prediction scheme with related resource prediction schemes from the literature. The usefulness of the proposed complexity-prediction approaches is demonstrated in an application of rate-distortion-complexity optimized decoding

Catchment-scale non-linear groundwater-surface water interactions in densely drained lowland catchments

Freely discharging lowland catchments are characterized by a strongly seasonal contracting and expanding system of discharging streams and ditches. Due to this rapidly changing active channel network, discharge and solute transport cannot be modeled by a single characteristic travel path, travel time distribution, unit hydrograph, or linear reservoir. We propose a systematic spatial averaging approach to derive catchment-scale storage and discharge from point-scale water balances. The effects of spatial heterogeneity in soil properties, vegetation, and drainage network are lumped and described by a relation between groundwater storage and the spatial probability distribution of groundwater depths with measurable parameters. The model describes how, in lowland catchments, the catchment-scale flux from groundwater to surface water via various flow routes is affected by a changing active channel network, the unsaturated zone and surface ponding. We used observations of groundwater levels and catchment discharge of a 6.6 km2 Dutch watershed in combination with a high-resolution spatially distributed hydrological model to test the model approach. Good results were obtained when modeling hourly discharges for a period of eight years. The validity of the underlying assumptions still needs to be tested under different conditions and for catchments of various sizes. Nevertheless, at this stage the model can already improve monitoring efficiency of groundwater-surface water interaction

Case Study Sanwich Terns - a probabilistic analysis of the ecological effects of dreding

Every year, large amounts of sand are extracted from the North Sea to meet the demands for construction activities. Potential ecological effects of these sand mining activities have to be examined and reported in so called Environmental Impact Assessments (EIA’s). In the Netherlands, the potential impacts of sand mining activities on tern populations often form an important topic in these EIA’s. Sand mining causes an increase in silt concentrations. This increase will influence the turbidity of the water, which may affect populations of visual hunting birds, such as terns

Why current-carrying magnetic flux tubes gobble up plasma and become thin as a result

It is shown that if a current-carrying magnetic flux tube is bulged at its axial midpoint z=0 and constricted at its axial endpoints z=+h,-h, then plasma will be accelerated from z=+h,-h towards z=0 resulting in a situation similar to two water jets pointed at each other. The ingested plasma convects embedded, frozen-in toroidal magnetic flux from z=+h,-h to z=0. The counter-directed flows collide and stagnate at z=0 and in so doing (i) convert their translational kinetic energy into heat, (ii) increase the plasma density at z~0, and (iii) increase the embedded toroidal flux density at z~0. The increase in toroidal flux density at z~0 increases the toroidal field Bphi and hence increases the magnetic pinch force at z~0 and so causes a reduction of the flux tube radius at z~0. Thus, the flux tube develops an axially uniform cross-section, a decreased volume, an increased density, and an increased temperature. This model is proposed as a likely hypothesis for the long-standing mystery of why solar coronal loops are observed to be axially uniform, hot, and bright.Comment: to appear in Physics of Plasmas 24 pages, 5 figure

Going against the flow: A critical analysis of virtual water trade in the context of India's National River Linking Programme

Virtual water trade has been promoted as a tool to address national and regional water scarcity. In the context of international (food) trade, this concept has been applied with a view to optimize the flow of commodities considering the water endowments of nations. The concept states that water-rich countries should produce and export water intensive commodities (which indirectly carry embedded water needed for producing them) to water-scarce countries, thereby enabling the water-scarce countries to divert their precious water resources to alternative, higher productivity uses.\ud While progress has been made on quantifying virtual water flows between countries, there exists little information on virtual water trade within large countries like India. This report quantifies and critically analyzes inter-state virtual water flows in India in the context of a large inter-basin transfer plan of the Government of India.\ud Our analysis shows that the existing pattern of inter-state virtual water trade is exacerbating scarcities in already water scarce states and that rather than being dictated by water endowments, virtual water flows are influenced by other factors such as "per capita gross cropped area" and "access to secured markets". We therefore argue that in order to have a comprehensive understanding of virtual water trade, non-water factors of production need to be taken into consideration