Tops-Only Domains

In this paper we consider the standard voting model with a finite set of alternatives A and n voters and address the following question : what are the characteristics of domains D that induce the property that every strategy-proof social choice function f : Dn -> A satisfying unanimity, has the tops-only property? We first impose a minimal richness condition which ensures that for every alternative a, there exists an admissible ordering where a is maximal. We identify conditions on D that are sufficient for strategy-proofness and unanimity to imply tops onlyness in the general case of n voters and in the special case, n = 2. We provide an algorithm for constructing tops-only domains from connected graphs with elements of A as nodes. We provide several applications of our results. Finally, we relax the minimal richness assumption and partially extend our results.Voting, social choice, tops-only domain

Flaw Selection Strategies for Partial-Order Planning

Several recent studies have compared the relative efficiency of alternative flaw selection strategies for partial-order causal link (POCL) planning. We review this literature, and present new experimental results that generalize the earlier work and explain some of the discrepancies in it. In particular, we describe the Least-Cost Flaw Repair (LCFR) strategy developed and analyzed by Joslin and Pollack (1994), and compare it with other strategies, including Gerevini and Schubert's (1996) ZLIFO strategy. LCFR and ZLIFO make very different, and apparently conflicting claims about the most effective way to reduce search-space size in POCL planning. We resolve this conflict, arguing that much of the benefit that Gerevini and Schubert ascribe to the LIFO component of their ZLIFO strategy is better attributed to other causes. We show that for many problems, a strategy that combines least-cost flaw selection with the delay of separable threats will be effective in reducing search-space size, and will do so without excessive computational overhead. Although such a strategy thus provides a good default, we also show that certain domain characteristics may reduce its effectiveness.Comment: See http://www.jair.org/ for an online appendix and other files accompanying this articl

Modules for Experiments in Stellar Astrophysics (MESA)

Stellar physics and evolution calculations enable a broad range of research in astrophysics. Modules for Experiments in Stellar Astrophysics (MESA) is a suite of open source libraries for a wide range of applications in computational stellar astrophysics. A newly designed 1-D stellar evolution module, MESA star, combines many of the numerical and physics modules for simulations of a wide range of stellar evolution scenarios ranging from very-low mass to massive stars, including advanced evolutionary phases. MESA star solves the fully coupled structure and composition equations simultaneously. It uses adaptive mesh refinement and sophisticated timestep controls, and supports shared memory parallelism based on OpenMP. Independently usable modules provide equation of state, opacity, nuclear reaction rates, and atmosphere boundary conditions. Each module is constructed as a separate Fortran 95 library with its own public interface. Examples include comparisons to other codes and show evolutionary tracks of very low mass stars, brown dwarfs, and gas giant planets; the complete evolution of a 1 Msun star from the pre-main sequence to a cooling white dwarf; the Solar sound speed profile; the evolution of intermediate mass stars through the thermal pulses on the He-shell burning AGB phase; the interior structure of slowly pulsating B Stars and Beta Cepheids; evolutionary tracks of massive stars from the pre-main sequence to the onset of core collapse; stars undergoing Roche lobe overflow; and accretion onto a neutron star. Instructions for downloading and installing MESA can be found on the project web site (http://mesa.sourceforge.net/).Comment: 110 pages, 39 figures; submitted to ApJS; visit the MESA website at http://mesa.sourceforge.ne

Beyond the simple Proximity Force Approximation: geometrical effects on the non-retarded Casimir interaction

We study the geometrical corrections to the simple Proximity Force Approximation for the non-retarded Casimir force. We present analytical results for the force between objects of various shapes and substrates, and between pairs of objects. We compare the results to those from more exact numerical calculations. We treat spheres, spheroids, cylinders, cubes, cones, and wings; the analytical PFA results together with the geometrical correction factors are summarized in a table.Comment: 18 pages, 19 figures, 1 tabl

Beyond the simple Proximity Force Approximation: geometrical effects on the non-retarded Casimir interaction

We study the geometrical corrections to the simple Proximity Force Approximation for the non-retarded Casimir force. We present analytical results for the force between objects of various shapes and substrates, and between pairs of objects. We compare the results to those from more exact numerical calculations. We treat spheres, spheroids, cylinders, cubes, cones, and wings; the analytical PFA results together with the geometrical correction factors are summarized in a table.Comment: 18 pages, 19 figures, 1 tabl

A hybrid algorithm for Bayesian network structure learning with application to multi-label learning

We present a novel hybrid algorithm for Bayesian network structure learning, called H2PC. It first reconstructs the skeleton of a Bayesian network and then performs a Bayesian-scoring greedy hill-climbing search to orient the edges. The algorithm is based on divide-and-conquer constraint-based subroutines to learn the local structure around a target variable. We conduct two series of experimental comparisons of H2PC against Max-Min Hill-Climbing (MMHC), which is currently the most powerful state-of-the-art algorithm for Bayesian network structure learning. First, we use eight well-known Bayesian network benchmarks with various data sizes to assess the quality of the learned structure returned by the algorithms. Our extensive experiments show that H2PC outperforms MMHC in terms of goodness of fit to new data and quality of the network structure with respect to the true dependence structure of the data. Second, we investigate H2PC's ability to solve the multi-label learning problem. We provide theoretical results to characterize and identify graphically the so-called minimal label powersets that appear as irreducible factors in the joint distribution under the faithfulness condition. The multi-label learning problem is then decomposed into a series of multi-class classification problems, where each multi-class variable encodes a label powerset. H2PC is shown to compare favorably to MMHC in terms of global classification accuracy over ten multi-label data sets covering different application domains. Overall, our experiments support the conclusions that local structural learning with H2PC in the form of local neighborhood induction is a theoretically well-motivated and empirically effective learning framework that is well suited to multi-label learning. The source code (in R) of H2PC as well as all data sets used for the empirical tests are publicly available.Comment: arXiv admin note: text overlap with arXiv:1101.5184 by other author

Disclosure rules and declared essential patents

Many standard setting organizations (SSOs) require participants to disclose patents that might be infringed by implementing a proposed standard, and commit to license their “essential” patents on terms that are fair, reasonable and non-discriminatory (FRAND). Data from SSO intellectual property disclosures have been used in academic studies to provide a window into the standard setting process, and in legal proceedings to assess the relative contribution of different parties to a standard. We describe the disclosure process, discuss the link between SSO rules and patent-holder incentives, and analyze disclosure practices using a novel dataset constructed from the disclosure archives of thirteen major SSOs. Our empirical results suggest that subtle differences in SSO policies influence which patents are disclosed, the terms of licensing commitments, and ultimately long-run citation and litigation rates for the underlying patents. Thus, while policy debates sometimes characterize SSOs as a relatively homogeneous set of institutions, our results point in the opposite direction – towards the importance of recognizing heterogeneity in SSO policies and practices

The Dutch deposit of electronic publications (DNEP) - 1995-2000

In 1993 the Internet took off with the introduction of HTML and the first browser (Mosaic1). Two years later, in 1995, the Koninklijke Bibliotheek decided to start a series of experiments and projects which would lead to a deposit system for Dutch Electronic Publications. In the same year the Koninklijke Bibliotheek made a policy decision to include electronic material into its deposit. That marked the start of the Dutch Deposit for Electronic Publications (DNEP2). Both as an operational service and at the same time as a test-bed for research into digital archiving. The Koninklijke Bibliotheek has a staff of 254.5 FTE3. The ICT-department has 15 FTE (about 6%).The ICT-department is responsible for the systems management of the operational systems, for the support of the end-users and for research and development. Apart from the R&D done in the ICTdepartment the Koninklijke Bibliotheek also has a department of library research (see the website4 of the Koninklijke Bibliotheek for more information). In the first few years a lot of experiments were done. Various hardware and software was tested and research was done on issues such as metadata, the number of electronic publications available, how to process them in the library etc. At the end of 1998 the Koninklijke Bibliotheek decided that the time was ripe to make the next step. This was the implementation of the DNEP on a large scale and as part of the normal workflow inside the library departments