3,910 research outputs found
Audiovestibular evolution in a patient undergoing surgical resection of a temporal bone myxoma
No full textRegulation of shear-induced nuclear translocation of the Nrf2 transcription factor in endothelial cells
Full text linkAbstract Background Vascular endothelial cells (ECs) constantly experience fluid shear stresses generated by blood flow. Laminar flow is known to produce atheroprotective effects on ECs. Nrf2 is a transcription factor that is essential for the antioxidant response element (ARE)-mediated induction of genes such as heme-oxygenase 1 (HO-1). We previously showed that fluid shear stress increases intracellular reactive oxygen species (ROS) in ECs. Moreover, oxidants are known to stimulate Nrf2. We thus examined the regulation of Nrf2 in cultured human ECs by shear stress. Results Exposure of human umbilical vein endothelial cells (HUVECs) to laminar shear stress (12 dyne/cm2) induced Nrf2 nuclear translocation, which was inhibited by a phosphatidylinositol 3-kinase (PI3K) inhibitor, a protein kinase C (PKC) inhibitor, and an antioxidant agent N-acetyl cysteine (NAC), but not by other protein kinase inhibitors. Therefore, PI3K, PKC, and ROS are involved in the signaling pathway that leads to the shear-induced nuclear translocation of Nrf2. We also found that shear stress increased the ARE-binding activity of Nrf2 and the downstream expression of HO-1. Conclusion Our data suggest that the atheroprotective effect of laminar flow is partially attributed to Nrf2 activation which results in ARE-mediated gene transcriptions, such as HO-1 expression, that are beneficial to the cardiovascular system.</p
Utilising Deep Learning Models for the Surface Registration Problem in HoloNav
No full textSurface Registration is a registration problem that handles the registration of two similar surfaces. In most research that utilises Deep Learning (DL) models to handle surface registration two theories are investigated; the first being whether surfaces sampled from the same origin can be registered together, and the second theory being whether the models can register Point Clouds with low overlapping data for utilisation in Simultaneous Localisation and Mapping (SLAM) applications. However, the surface registration to be utilised in the HoloNav Augmented Reality (AR) navigation system will utilise Point Clouds sampled from different origins with a high overlap ratio. This research, therefore, aims to determine the viability of DL methods for surface registration in HoloNav data. To determine the viability, rotation and translation errors in the match were used, with the aforementioned metrics later being evaluated manually with the utilisation of a visualiser. The results indicate that the models can generalise on the navigator data for an initial Euler angle difference of 45 degrees, but due to the difference in sampling density on the utilised point clouds can not provide accurate matches. Therefore, the utilisation of DL models can be considered to be viable if the navigator data has a sampling density similar to the pre-operative model.https://github.com/alpcicimen/holonav-dl-registration The link to the github repository containing the utilised dataset, scripts, as well as the modified DL models RPMNet and PREDATOR.CSE3000 Research ProjectComputer Science and Engineerin
The Scent of a Smell: An Extensive Comparison between Textual and Structural Smells
No full textCode smells are symptoms of poor design or implementation choices that have a negative effect on several aspects of software maintenance and evolution, such as program comprehension or change- and fault-proneness. This is why researchers have spent a lot of effort on devising methods that help developers to automatically detect them in source code. Almost all the techniques presented in literature are based on the analysis of structural properties extracted from source code, although alternative sources of information (e.g., textual analysis) for code smell detection have also been recently investigated. Nevertheless, some studies have indicated that code smells detected by existing tools based on the analysis of structural properties are generally ignored (and thus not refactored) by the developers. In this paper, we aim at understanding whether code smells detected using textual analysis are perceived and refactored by developers in the same or different way than code smells detected through structural analysis. To this aim, we set up two different experiments. We have first carried out a software repository mining study to analyze how developers act on textually or structurally detected code smells. Subsequently, we have conducted a user study with industrial developers and quality experts in order to qualitatively analyze how they perceive code smells identified using the two different sources of information. Results indicate that textually detected code smells are easier to identify and for this reason they are considered easier to refactor with respect to code smells detected using structural properties. On the other hand, the latter are often perceived as more severe, but more difficult to exactly identify and remove.Accepted Author ManuscriptSoftware Engineerin
March dl: Adding Adaptive Heuristics and a New Branching Strategy
No full textWe introduce the march dl satisability (SAT) solver, a successor of march eq. The latter was awarded state-of-the-art in two categories during the Sat 2004 competition. The focus lies on presenting those features that are new in march dl. Besides a description, each of these features is illustrated with some experimental results. By extending the pre-processor, using adaptive heuristics, and by using a new branching strategy, march dl is able to solve nearly all benchmarks faster than its predecessor. Moreover, various instances which were beyond the reach of march eq, can now be solved - relatively easily - due to these new features.Software TechnologyElectrical Engineering, Mathematics and Computer Scienc
Crash Reproduction Using Helper Objectives
No full textEvolutionary-based crash reproduction techniques aid developers in their debugging practices by generating a test case that reproduces a crash given its stack trace. In these techniques, the search process is typically guided by a single search objective called Crash Distance. Previous studies have shown that current approaches could only reproduce a limited number of crashes due to a lack of diversity in the population during the search. In this study, we address this issue by applying Multi-Objectivization using Helper-Objectives (MO-HO) on crash reproduction. In particular, we add two helper-objectives to the Crash Distance to improve the diversity of the generated test cases and consequently enhance the guidance of the search process. We assessed MO-HO against the single-objective crash reproduction. Our results show that MO-HO can reproduce two additional crashes that were not previously reproducible by the single-objective approach.Virtual/online event due to COVID-19 Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Software EngineeringSoftware Technolog
A General Formulation to Describe Empirical Rainfall Thresholds for Landslides
Full text linkAbstractIn this paper, a brief description of the Generalized FLaIR Model (GFM, De Luca and Versace, 2016) is provided, that is able to reproduce all the empirical thresholds proposed in literature, aimed to forecast landslides triggered by rainfall. In particular, this paper focuses on Antecedent Precipitation (AP) schemes. The paper demonstrates that these are particular solutions of the GFM and will exemplify this using AP schemes for NE Italy1, Seattle2 and Nicaragua - El Salvador3
Releasing Fast and Slow: An Exploratory Case Study at ING
No full textThe appeal of delivering new features faster has led many software projects to adopt rapid releases. However, it is not well understood what the effects of this practice are. This paper presents an exploratory case study of rapid releases at ING, a large banking company that develops software solutions in-house, to characterize rapid releases. Since 2011, ING has shifted to a rapid release model. This switch has resulted in a mixed environment of 611 teams releasing relatively fast and slow. We followed a mixed-methods approach in which we conducted a survey with 461 participants and corroborated their perceptions with 2 years of code quality data and 1 year of release delay data. Our research shows that: rapid releases are more commonly delayed than their non-rapid counterparts, however, rapid releases have shorter delays; rapid releases can be beneficial in terms of reviewing and user-perceived quality; rapidly released software tends to have a higher code churn, a higher test coverage and a lower average complexity; challenges in rapid releases are related to managing dependencies and certain code aspects, e.g. design debt.Software EngineeringSoftware Technolog
AATOM - An Agent-based Airport Terminal Operations Model simulator
No full textAATOM, the Agent-based Airport Terminal Operations Model simulator is open-source, agent-based at its core, and contains several calibrated presets and templates of basic airport terminal components that can readily be used. Agents in this simulator follow the AATOM architecture, an activity-based architecture for human airport agents. This allows analysis based on agent activities, such as shopping and check-in, which is of vital interest for airports. The combination of agent-based modeling and the presence of basic airport terminal components makes AATOM a unique simulator, allowing the modeler to only focus on implementation of important features of their model. The usefulness of AATOM is demonstrated by presenting case studies in the areas of airport security, gate assignment and resilience.Air Transport & OperationsEmbedded System
Dynamic Prediction of Delays in Software Projects using Delay Patterns and Bayesian Modeling
No full textModern agile software projects are subject to constant change, making it essential to re-asses overall delay risk throughout the project life cycle. Existing effort estimation models are static and not able to incorporate changes occurring during project execution. In this paper, we propose a dynamic model for continuously predicting overall delay using delay patterns and Bayesian modeling. The model incorporates the context of the project phase and learns from changes in team performance over time. We apply the approach to real-world data from 4,040 epics and 270 teams at ING. An empirical evaluation of our approach and comparison to the state-of-the-art demonstrate significant improvements in predictive accuracy. The dynamic model consistently outperforms static approaches and the state-of-the-art, even during early project phases.Software EngineeringSoftware Technolog
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