Multicommodity formulations for the prize collecting vehicle routing problem in the petrol industry

The Mobile Oil Recovery (MOR) unit is a truck designed to pump marginal oil wells in a petrol field. The MOR optimization Problem (MORP) consists in optimizing both the oil extraction and the travel costs. In this article, we describe several formulations for the MORP using a single vehicle and we propose two formulations to the case where several vehicles are used. We strengthen the proposed formulations by taking advantage of the MORP characteristics, by improving the number of subtour elimination constraints and by using cuts. Computational results are presented for instances close to the reality and optimality is proved for instances with up to 200 nodes

A polynomial-time algorithm for the discrete facility location problem with limited distances and capacity constraints

The objective in terms of the facility location problem with limited distances is to minimize the sum of distance functions from the facility to its clients, but with a limit on each of these distances, from which the corresponding function becomes constant. The problem is applicable in situations where the service provided by the facility is insensitive after given threshold distances. In this paper, we propose a polynomial-time algorithm for the discrete version of the problem with capacity constraints regarding the number of served clients. These constraints are relevant for introducing quality measures in facility location decision processes as well as for justifying the facility creation

A Lagrangian-based score for assessing the quality of pairwise constraints in semi-supervised clustering

ABSTRACT: Clustering algorithms help identify homogeneous subgroups from data. In some cases, additional information about the relationship among some subsets of the data exists. When using a semi-supervised clustering algorithm, an expert may provide additional information to constrain the solution based on that knowledge and, in doing so, guide the algorithm to a more useful and meaningful solution. Such additional information often takes the form of a cannot-link constraint (i.e., two data points cannot be part of the same cluster) or a must-link constraint (i.e., two data points must be part of the same cluster). A key challenge for users of such constraints in semi-supervised learning algorithms, however, is that the addition of inaccurate or conflicting constraints can decrease accuracy and little is known about how to detect whether expert-imposed constraints are likely incorrect. In the present work, we introduce a method to score each must-link and cannot-link pairwise constraint as likely incorrect. Using synthetic experimental examples and real data, we show that the resulting impact score can successfully identify individual constraints that should be removed or revised

Workload measurement in a communication application operated through a P300-based brain-computer interface

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Guaranteed clustering and biclustering via semidefinite programming

Identifying clusters of similar objects in data plays a significant role in a wide range of applications. As a model problem for clustering, we consider the densest k-disjoint-clique problem, whose goal is to identify the collection of k disjoint cliques of a given weighted complete graph maximizing the sum of the densities of the complete subgraphs induced by these cliques. In this paper, we establish conditions ensuring exact recovery of the densest k cliques of a given graph from the optimal solution of a particular semidefinite program. In particular, the semidefinite relaxation is exact for input graphs corresponding to data consisting of k large, distinct clusters and a smaller number of outliers. This approach also yields a semidefinite relaxation for the biclustering problem with similar recovery guarantees. Given a set of objects and a set of features exhibited by these objects, biclustering seeks to simultaneously group the objects and features according to their expression levels. This problem may be posed as partitioning the nodes of a weighted bipartite complete graph such that the sum of the densities of the resulting bipartite complete subgraphs is maximized. As in our analysis of the densest k-disjoint-clique problem, we show that the correct partition of the objects and features can be recovered from the optimal solution of a semidefinite program in the case that the given data consists of several disjoint sets of objects exhibiting similar features. Empirical evidence from numerical experiments supporting these theoretical guarantees is also provided

Move and countermove: the integrated stress response in picorna- and coronavirus-infected cells

Viruses, when entering their host cells, are met by a fierce intracellular immune defense. One prominent antiviral pathway is the integrated stress response (ISR). Upon activation of the ISR - typically though not exclusively upon detection of dsRNA - translation-initiation factor eukaryotic initiation factor 2 (eIF2) becomes phosphorylated to act as an inhibitor of guanine nucleotide-exchange factor eIF2B. Thus, with the production of ternary complex blocked, a global translational arrest ensues. Successful virus replication hinges on effective countermeasures. Here, we review ISR antagonists and antagonistic mechanisms employed by picorna- and coronaviruses. Special attention will be given to a recently discovered class of viral antagonists that inhibit the ISR by targeting eIF2B, thereby allowing unabated translation initiation even at exceedingly high levels of phosphorylated eIF2

The Interface Region Imaging Spectrograph (IRIS)

The Interface Region Imaging Spectrograph (IRIS) small explorer spacecraft provides simultaneous spectra and images of the photosphere, chromosphere, transition region, and corona with 0.33-0.4 arcsec spatial resolution, 2 s temporal resolution and 1 km/s velocity resolution over a field-of-view of up to 175 arcsec x 175 arcsec. IRIS was launched into a Sun-synchronous orbit on 27 June 2013 using a Pegasus-XL rocket and consists of a 19-cm UV telescope that feeds a slit-based dual-bandpass imaging spectrograph. IRIS obtains spectra in passbands from 1332-1358, 1389-1407 and 2783-2834 Angstrom including bright spectral lines formed in the chromosphere (Mg II h 2803 Angstrom and Mg II k 2796 Angstrom) and transition region (C II 1334/1335 Angstrom and Si IV 1394/1403 Angstrom). Slit-jaw images in four different passbands (C II 1330, Si IV 1400, Mg II k 2796 and Mg II wing 2830 Angstrom) can be taken simultaneously with spectral rasters that sample regions up to 130 arcsec x 175 arcsec at a variety of spatial samplings (from 0.33 arcsec and up). IRIS is sensitive to emission from plasma at temperatures between 5000 K and 10 MK and will advance our understanding of the flow of mass and energy through an interface region, formed by the chromosphere and transition region, between the photosphere and corona. This highly structured and dynamic region not only acts as the conduit of all mass and energy feeding into the corona and solar wind, it also requires an order of magnitude more energy to heat than the corona and solar wind combined. The IRIS investigation includes a strong numerical modeling component based on advanced radiative-MHD codes to facilitate interpretation of observations of this complex region. Approximately eight Gbytes of data (after compression) are acquired by IRIS each day and made available for unrestricted use within a few days of the observation.Comment: 53 pages, 15 figure

Structure and Rotation of the Solar Interior: Initial Results from the MDI Medium-L Program

The medium-l program of the Michelson Doppler Imager instrument on board SOHO provides continuous observations of oscillation modes of angular degree, l, from 0 to approximately 300. The data for the program are partly processed on board because only about 3% of MDI observations can be transmitted continuously to the ground. The on-board data processing, the main component of which is Gaussian-weighted binning, has been optimized to reduce the negative influence of spatial aliasing of the high-degree oscillation modes. The data processing is completed in a data analysis pipeline at the SOI Stanford Support Center to determine the mean multiplet frequencies and splitting coefficients. The initial results show that the noise in the medium-l oscillation power spectrum is substantially lower than in ground-based measurements. This enables us to detect lower amplitude modes and, thus, to extend the range of measured mode frequencies. This is important for inferring the Sun's internal structure and rotation. The MDI observations also reveal the asymmetry of oscillation spectral lines. The line asymmetries agree with the theory of mode excitation by acoustic sources localized in the upper convective boundary layer. The sound-speed profile inferred from the mean frequencies gives evidence for a sharp variation at the edge of the energy-generating core. The results also confirm the previous finding by the GONG (Gough et al., 1996) that, in a thin layer just beneath the convection zone, helium appears to be less abundant than predicted by theory. Inverting the multiplet frequency splittings from MDI, we detect significant rotational shear in this thin layer. This layer is likely to be the place where the solar dynamo operates. In order to understand how the Sun works, it is extremely important to observe the evolution of this transition layer throughout the 11-year activity cycle