837 research outputs found

    The KB paradigm and its application to interactive configuration

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    The knowledge base paradigm aims to express domain knowledge in a rich formal language, and to use this domain knowledge as a knowledge base to solve various problems and tasks that arise in the domain by applying multiple forms of inference. As such, the paradigm applies a strict separation of concerns between information and problem solving. In this paper, we analyze the principles and feasibility of the knowledge base paradigm in the context of an important class of applications: interactive configuration problems. In interactive configuration problems, a configuration of interrelated objects under constraints is searched, where the system assists the user in reaching an intended configuration. It is widely recognized in industry that good software solutions for these problems are very difficult to develop. We investigate such problems from the perspective of the KB paradigm. We show that multiple functionalities in this domain can be achieved by applying different forms of logical inferences on a formal specification of the configuration domain. We report on a proof of concept of this approach in a real-life application with a banking company. To appear in Theory and Practice of Logic Programming (TPLP).Comment: To appear in Theory and Practice of Logic Programming (TPLP

    Efficient Experimental and Data-Centered Workflow for Microstructure-Based Fatigue Data – Towards a Data Basis for Predictive AI Models

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    Background Early fatigue mechanisms for various materials are yet to be unveiled for the (very) high-cycle fatigue (VHCF) regime. This can be ascribed to a lack of available data capturing initial fatigue damage evolution, which continues to adversely affect data scientists and computational modeling experts attempting to derive microstructural dependencies from small sample size data and incomplete feature representations. Objective The aim of this work is to address this lack and to drive the digital transformation of materials such that future virtual component design can be rendered more reliable and more efficient. Achieving this relies on fatigue models that comprehensively capture all relevant dependencies. Methods To this end, this work proposes a combined experimental and data post-processing workflow to establish multimodal fatigue crack initiation and propagation data sets efficiently. It evolves around fatigue testing of mesoscale specimens to increase damage detection sensitivity, data fusion through multimodal registration to address data heterogeneity, and image-based data-driven damage localization. Results A workflow with a high degree of automation is established, that links large distortion-corrected microstructure data with damage localization and evolution kinetics. The workflow enables cycling up to the VHCF regime in comparatively short time spans, while maintaining unprecedented time resolution of damage evolution. Resulting data sets capture the interaction of damage with microstructural features and hold the potential to unravel a mechanistic understanding. Conclusions The proposed workflow lays the foundation for future data mining and data-driven modeling of microstructural fatigue by providing statistically meaningful data sets extendable to a wide range of materials

    Exploiting the Enumeration of All Feature Model Configurations

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    .Feature models are widely used to encode the configurations of a software product line in terms of mandatory, optional and exclusive features as well as propositional constraints over the features. Numerous computationally expensive procedures have been developed to model check, test, configure, debug, or compute relevant information of feature models. In this paper we explore the possible improvement of relying on the enumeration of all configurations when performing automated analysis operations. We tackle the challenge of how to scale the existing enumeration techniques by relying on distributed computing. We show that the use of distributed computing techniques might offer practical solutions to previously unsolvable problems and opens new perspectives for the automated analysis of software product lines.Junta de Andalucía P12-TIC-1867Ministerio de Economía y Competitividad TIN2015- 70560-

    Global Inverse Consistency for Interactive Constraint Satisfaction

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    International audienceSome applications require the interactive resolution of a constraint problem by a human user. In such cases, it is highly desirable that the person who interactively solves the problem is not given the choice to select values that do not lead to solutions. We call this property global inverse consistency. Existing systems simulate this either by maintaining arc consistency after each assignment performed by the user or by compiling offline the problem as a multi-valued decision diagram. In this paper, we define several questions related to global inverse consistency and analyse their complexity. Despite their theoretical intractability, we propose several algorithms for enforcing global inverse consistency and we show that the best version is efficient enough to be used in an interactive setting on several configuration and design problems. We finally extend our contribution to the inverse consistency of tuples

    Continuously-variable survival exponent for random walks with movable partial reflectors

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    We study a one-dimensional lattice random walk with an absorbing boundary at the origin and a movable partial reflector. On encountering the reflector, at site x, the walker is reflected (with probability r) to x-1 and the reflector is simultaneously pushed to x+1. Iteration of the transition matrix, and asymptotic analysis of the probability generating function show that the critical exponent delta governing the survival probability varies continuously between 1/2 and 1 as r varies between 0 and 1. Our study suggests a mechanism for nonuniversal kinetic critical behavior, observed in models with an infinite number of absorbing configurations.Comment: 5 pages, 3 figure

    Effects of dipotassium-trioxohydroxytetrafluorotriborate, K2[B3O3F4OH], on cell viability and gene expression of common human cancer drug targets in a melanoma cell line.

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    Recently it was found that dipotassium-trioxohydroxytetrafluorotriborate, K2(B3O3F4OH), is a potent and highly specific inhibitor of precancerous cell processes. We conducted gene expression profiling of human melanoma cells before and after treatment with two concentrations (0.1 and 1 mM) of this boron inorganic derivative in order to assess its effects on deregulation of genes associated with tumor pathways. Parallel trypan blue exclusion assay was performed to assess the cytotoxicity effects of this chemical. Treatment with K2(B3O3F4OH) induced a significant decrease of cell viability in melanoma cellline at both tested concentrations. Furthermore, these treatments caused deregulation of more than 30 genes known as common anti-tumor drug targets. IGF-1 and hTERT were found to be significantly downregulated and this result may imply potential use of K2(B3O3F4OH) as an inhibitor or human telomerase and insulin-like growth factor 1, both of which are associated with various tumor pathways

    Anomalous f-electron Hall Effect in the Heavy-Fermion System CeTIn5_{5} (T = Co, Ir, or Rh)

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    The in-plane Hall coefficient RH(T)R_{H}(T) of CeRhIn5_{5}, CeIrIn5_{5}, and CeCoIn5_{5} and their respective non-magnetic lanthanum analogs are reported in fields to 90 kOe and at temperatures from 2 K to 325 K. RH(T)R_{H}(T) is negative, field-independent, and dominated by skew-scattering above \sim 50 K in the Ce compounds. RH(H0)R_{H}(H \to 0) becomes increasingly negative below 50 K and varies with temperature in a manner that is inconsistent with skew scattering. Field-dependent measurements show that the low-T anomaly is strongly suppressed when the applied field is increased to 90 kOe. Measurements on LaRhIn5_{5}, LaIrIn5_{5}, and LaCoIn5_{5} indicate that the same anomalous temperature dependence is present in the Hall coefficient of these non-magnetic analogs, albeit with a reduced amplitude and no field dependence. Hall angle (θH\theta_{H}) measurements find that the ratio ρxx/ρxy=cot(θH)\rho_{xx}/\rho_{xy}=\cot(\theta_{H}) varies as T2T^{2} below 20 K for all three Ce-115 compounds. The Hall angle of the La-115 compounds follow this T-dependence as well. These data suggest that the electronic-structure contribution dominates the Hall effect in the 115 compounds, with ff-electron and Kondo interactions acting to magnify the influence of the underlying complex band structure. This is in stark contrast to the situation in most 4f4f and 5f5f heavy-fermion compounds where the normal carrier contribution to the Hall effect provides only a small, T-independent background to RH.R_{H}.Comment: 23 pages and 8 figure

    Artificial Intelligence in Radiation Therapy

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    Artificial intelligence (AI) has great potential to transform the clinical workflow of radiotherapy. Since the introduction of deep neural networks, many AI-based methods have been proposed to address challenges in different aspects of radiotherapy. Commercial vendors have started to release AI-based tools that can be readily integrated to the established clinical workflow. To show the recent progress in AI-aided radiotherapy, we have reviewed AI-based studies in five major aspects of radiotherapy including image reconstruction, image registration, image segmentation, image synthesis, and automatic treatment planning. In each section, we summarized and categorized the recently published methods, followed by a discussion of the challenges, concerns, and future development. Given the rapid development of AI-aided radiotherapy, the efficiency and effectiveness of radiotherapy in the future could be substantially improved through intelligent automation of various aspects of radiotherapy

    Large Anomalous Hall effect in a silicon-based magnetic semiconductor

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    Magnetic semiconductors are attracting high interest because of their potential use for spintronics, a new technology which merges electronics and manipulation of conduction electron spins. (GaMn)As and (GaMn)N have recently emerged as the most popular materials for this new technology. While Curie temperatures are rising towards room temperature, these materials can only be fabricated in thin film form, are heavily defective, and are not obviously compatible with Si. We show here that it is productive to consider transition metal monosilicides as potential alternatives. In particular, we report the discovery that the bulk metallic magnets derived from doping the narrow gap insulator FeSi with Co share the very high anomalous Hall conductance of (GaMn)As, while displaying Curie temperatures as high as 53 K. Our work opens up a new arena for spintronics, involving a bulk material based only on transition metals and Si, and which we have proven to display a variety of large magnetic field effects on easily measured electrical properties.Comment: 19 pages with 5 figure

    Bilateral infraorbital nerve blocks decrease postoperative pain but do not reduce time to discharge following outpatient nasal surgery

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    While infraorbital nerve blocks have demonstrated analgesic benefits for pediatric nasal and facial plastic surgery, no studies to date have explored the effect of this regional anesthetic technique on adult postoperative recovery. We designed this study to test the hypothesis that infraorbital nerve blocks combined with a standardized general anesthetic decrease the duration of recovery following outpatient nasal surgery. At a tertiary care university hospital, healthy adult subjects scheduled for outpatient nasal surgery were randomly assigned to receive bilateral infraorbital injections with either 0.5% bupivacaine (Group IOB) or normal saline (Group NS) using an intraoral technique immediately following induction of general anesthesia. All subjects underwent a standardized general anesthetic regimen and were transported to the recovery room following tracheal extubation. The primary outcome was the duration of recovery (minutes) from recovery room admission until actual discharge to home. Secondary outcomes included average and worst pain scores, nausea and vomiting, and supplemental opioid requirements. Forty patients were enrolled. A statistically significant difference in mean [SD] recovery room duration was not observed between Groups IOB and NS (131 [61] min vs 133 [58] min, respectively; P = 0.77). Subjects in Group IOB did experience a reduction in average pain on a 0–100 mm scale (mean [95% confidence interval]) compared to Group NS (−11 [−21 to 0], P = 0.047), but no other comparison of secondary outcomes was statistically significant. When added to a standardized general anesthetic, bilateral IOB do not decrease actual time to discharge following outpatient nasal surgery despite a beneficial effect on postoperative pain
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