How to Complete an Interactive Configuration Process?

When configuring customizable software, it is useful to provide interactive tool-support that ensures that the configuration does not breach given constraints. But, when is a configuration complete and how can the tool help the user to complete it? We formalize this problem and relate it to concepts from non-monotonic reasoning well researched in Artificial Intelligence. The results are interesting for both practitioners and theoreticians. Practitioners will find a technique facilitating an interactive configuration process and experiments supporting feasibility of the approach. Theoreticians will find links between well-known formal concepts and a concrete practical application.Comment: to appear in SOFSEM 201

On stationary points of nonexpansive set-valued mappings

In this paper we deal with stationary points (also known as endpoints) of nonexpansive set-valued mappings and show that the existence of such points under certain conditions follows as a consequence of the existence of approximate stationary sequences. In particular we provide abstract extensions of well-known fixed point theorems.Dirección General de Enseñanza SuperiorJunta de Andalucí

The Logic of Uncertainty and Executive Discretion in Decision Making: The Dallas-Fort Worth Metroplex Ebola Response

This paper addresses an important question: what can a highly complex public health situation such as the Dallas-Fort Worth Ebola outbreak tell us about the use of discretion by executive level public administrators? The public administration literature is rich with evidence of street-level bureaucratic discretion, but has not explored executive level discretion decision making. The authors argue that in highly complex situations of uncertainty, such as in the case of the Dallas-Fort Worth regional Ebola emergency response, the executive use of discretion translates to decisions under the conditions of uncertainty. This article theorizes a logic of uncertainty when two important assumptions exist; the situation is absent a plan to guide decision making, and the decision makers lack any previous precedent with the situation. Results indicate that when survey respondents departed from their emergency management plan, and planned as the event folded, they were more likely to use executive discretion decision making

Hybrid Algorithms Based on Integer Programming for the Search of Prioritized Test Data in Software Product Lines

In Software Product Lines (SPLs) it is not possible, in general, to test all products of the family. The number of products denoted by a SPL is very high due to the combinatorial explosion of features. For this reason, some coverage criteria have been proposed which try to test at least all feature interactions without the necessity to test all products, e.g., all pairs of features (pairwise coverage). In addition, it is desirable to first test products composed by a set of priority features. This problem is known as the Prioritized Pairwise Test Data Generation Problem. In this work we propose two hybrid algorithms using Integer Programming (IP) to generate a prioritized test suite. The first one is based on an integer linear formulation and the second one is based on a integer quadratic (nonlinear) formulation. We compare these techniques with two state-of-the-art algorithms, the Parallel Prioritized Genetic Solver (PPGS) and a greedy algorithm called prioritized-ICPL. Our study reveals that our hybrid nonlinear approach is clearly the best in both, solution quality and computation time. Moreover, the nonlinear variant (the fastest one) is 27 and 42 times faster than PPGS in the two groups of instances analyzed in this work.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Partially funded by the Spanish Ministry of Economy and Competitiveness and FEDER under contract TIN2014-57341-R, the University of Málaga, Andalucía Tech and the Spanish Network TIN2015-71841-REDT (SEBASENet)

A Robust Initialization Scheme for a Lateral Trajectory Optimization Problem with Time of Arrival Windows

We present a robust initialization scheme that estimates parameter values for the numerical solution of a two-point boundary value problem. The two-point boundary value problem formulation stems from the optimization of a cost functional subject to the dynamics of a simplified lateral aircraft model and other constraints. Leveraging regular perturbation methods, initial parameter estimates are analytically determined and used to initialize a gradient descent optimization routine which is shown to rapidly converge over a range of initial aircraft positions and heading angles. Additionally, the velocity of the aircraft is optimized to ensure the trajectory of the aircraft terminates within a desired region in both time and space

Electron Wave Function in Armchair Graphene Nanoribbons

By using analytical solution of a tight-binding model for armchair nanoribbons, it is confirmed that the solution represents the standing wave formed by intervalley scattering and that pseudospin is invariant under the scattering. The phase space of armchair nanoribbon which includes a single Dirac singularity is specified. By examining the effects of boundary perturbations on the wave function, we suggest that the existance of a strong boundary potential is inconsistent with the observation in a recent scanning tunneling microscopy. Some of the possible electron-density superstructure patterns near a step armchair edge located on top of graphite are presented. It is demonstrated that a selection rule for the G band in Raman spectroscopy can be most easily reproduced with the analytical solution.Comment: 7 pages, 4 figure

Translational development of difluoromethylornithine (DFMO) for the treatment of neuroblastoma

Neuroblastoma is a childhood tumor in which MYC oncogenes are commonly activated to drive tumor progression. Survival for children with high-risk neuroblastoma remains poor despite treatment that incorporates high-dose chemotherapy, stem cell support, surgery, radiation therapy and immunotherapy. More effective and less toxic treatments are sought and one approach under clinical development involves re-purposing the anti-protozoan drug difluoromethylornithine (DFMO; Eflornithine) as a neuroblastoma therapeutic. DFMO is an irreversible inhibitor of ornithine decarboxylase (Odc), a MYC target gene, bona fide oncogene, and the rate-limiting enzyme in polyamine synthesis. DFMO is approved for the treatment of Trypanosoma brucei gambiense encephalitis (“African sleeping sickness”) since polyamines are essential for the proliferation of these protozoa. However, polyamines are also critical for mammalian cell proliferation and the finding that MYC coordinately regulates all aspects of polyamine metabolism suggests polyamines may be required to support cancer promotion by MYC. Pre-emptive blockade of polyamine synthesis is sufficient to block tumor initiation in an otherwise fully penetrant transgenic mouse model of neuroblastoma driven by MYCN, underscoring the necessity of polyamines in this process. Moreover, polyamine depletion regimens exert potent anti-tumor activity in pre-clinical models of established neuroblastoma as well, in combination with numerous chemotherapeutic agents and even in tumors with unfavorable genetic features such as MYCN, ALK or TP53 mutation. This has led to the testing of DFMO in clinical trials for children with neuroblastoma. Current trial designs include testing lower dose DFMO alone (2,000 mg/m2/day) starting at the completion of standard therapy, or higher doses combined with chemotherapy (up to 9,000 mg/m2/day) for patients with relapsed disease that has progressed. In this review we will discuss important considerations for the future design of DFMO-based clinical trials for neuroblastoma, focusing on the need to better define the principal mechanisms of anti-tumor activity for polyamine depletion regimens. Putative DFMO activities that are both cancer cell intrinsic (targeting the principal oncogenic driver, MYC) and cancer cell extrinsic (altering the tumor microenvironment to support anti-tumor immunity) will be discussed. Understanding the mechanisms of DFMO activity are critical in determining how it might be best leveraged in upcoming clinical trials. This mechanistic approach also provides a platform by which iterative pre-clinical testing using translational tumor models may complement our clinical approaches

Isolation and characterization of feline dental pulp stem cells

Objectives The aim of this study was to isolate feline dental pulp stem cells (fDPSCs) and characterize their clonogenic and proliferative abilities, as well as their multipotency, immunophenotype and cytogenetic stability. Methods Dental pulp was isolated by explant culture from two cats <1 year old at post mortem. Their clonogenicity was characterized using a colony-forming unit fibroblast assay, and their proliferative ability was quantified with a doubling time assay in passages 2, 4 and 6 (P2, P4 and P6, respectively). Multipotency was characterized with an in vitro trilineage differentiation assay in P2, and cells were immunophenotyped in P4 by flow cytometry. Chromosomic stability was evaluated by cytogenetic analysis in P2, P4 and P6. Results The fDPSCs displayed spindle and epithelial-like morphologies. Isolated cells showed a marked clonogenic capacity and doubling time was maintained from P2 to P6. Trilineage differentiation was obtained in one sample, while the other showed osteogenic and chondrogenic differentiation. Immunophenotypic analysis showed fDPSCs were CD45−, CD90+ and CD44+. Structural and numerical cytogenetic aberrations were observed in P2–P4. Conclusions and relevance In this study, fDPSCs from two cats were isolated by explant culture and immunophenotyped. Cells displayed clonogenic and proliferative ability, and multipotency in vitro, and signs of chromosomic instability were observed. Although a larger study is needed to confirm these results, this is the first report of fDPSC isolation and in vitro characterization

Capturing variability in Model Based Systems Engineering

International audienceAutomotive model-based systems engineering needs to be dapted to the industry specific needs, in particular by implementing appropriate means of representing and operating with variability. We rely on existing modeling techniques as an opportunity to provide a description of variability adapted to a systems en- gineering model. However, we also need to take into account requirements related to backwards compatibility with current practices, given the industry experience in mass customization. We propose to adopt the product line paradigm in model-based systems engineering by extending the orthogonal variability model, and adapting it to our specific needs. This brings us to an expression closer to a description of constraints, related to both orthogonal variability, and to SysML system models. We introduce our approach through a discussion on the different aspects that need to be covered for expressing variability in systems engineering. We explore these aspects by observing an automotive case study, and relate them to a list of contextual requirements for variability management