802 research outputs found

    Prediction of transonic flutter for a supercritical wing by modified strip analysis and comparison with experiment

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    Use of a supercritical airfoil can adversely affect wing flutter speeds in the transonic range. As adequate theories for three dimensional unsteady transonic flow are not yet available, the modified strip analysis was used to predict the transonic flutter boundary for the supercritical wing. The steady state spanwise distributions of section lift curve slope and aerodynamic center, required as input for the flutter calculations, were obtained from pressure distributions. The calculated flutter boundary is in agreement with experiment in the subsonic range. In the transonic range, a transonic bucket is calculated which closely resembles the experimental one with regard to both shape and depth, but it occurs at about 0.04 Mach number lower than the experimental one

    The High-Resolution Structures of the Neutral and the Low pH Crystals of Aminopeptidase from \u3cem\u3eAeromonas proteolytica\u3c/em\u3e

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    The aminopeptidase from Aeromonas proteolytica (AAP) contains two zinc ions in the active site and catalyzes the degradation of peptides. Herein we report the crystal structures of AAP at 0.95-Ã… resolution at neutral pH and at 1.24-Ã… resolution at low pH. The combination of these structures allowed the precise modeling of atomic positions, the identification of the metal bridging oxygen species, and insight into the physical properties of the metal ions. On the basis of these structures, a new putative catalytic mechanism is proposed for AAP that is likely relevant to all binuclear metalloproteases

    Giant Magnetic Moments of Nitrogen Stabilized Mn Clusters and Their Relevance to Ferromagnetism in Mn Doped GaN

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    Using first principles calculations based on density functional theory, we show that the stability and magnetic properties of small Mn clusters can be fundamentally altered by the presence of nitrogen. Not only are their binding energies substantially enhanced, but also the coupling between the magnetic moments at Mn sites remains ferromagnetic irrespective of their size or shape. In addition, these nitrogen stabilized Mn clusters carry giant magnetic moments ranging from 4 Bohr magnetons in MnN to 22 Bohr magnetons in Mn_5N. It is suggested that the giant magnetic moments of Mn_xN clusters may play a key role in the ferromagnetism of Mn doped GaN which exhibit a wide range (10K - 940K) of Curie temperatures

    Subsonic aerodynamic and flutter characteristics of several wings calculated by the SOUSSA P1.1 panel method

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    The SOUSSA (steady, oscillatory, and unsteady subsonic and supersonic aerodynamics) program is the computational implementation of a general potential flow analysis (by the Green's function method) that can generate pressure distributions on complete aircraft having arbitrary shapes, motions and deformations. Some applications of the initial release version of this program to several wings in steady and oscillatory motion, including flutter are presented. The results are validated by comparisons with other calculations and experiments. Experiences in using the program as well as some recent improvements are described

    Dev2vec: Representing Domain Expertise of Developers in an Embedding Space

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    Accurate assessment of the domain expertise of developers is important for assigning the proper candidate to contribute to a project or to attend a job role. Since the potential candidate can come from a large pool, the automated assessment of this domain expertise is a desirable goal. While previous methods have had some success within a single software project, the assessment of a developer's domain expertise from contributions across multiple projects is more challenging. In this paper, we employ doc2vec to represent the domain expertise of developers as embedding vectors. These vectors are derived from different sources that contain evidence of developers' expertise, such as the description of repositories that they contributed, their issue resolving history, and API calls in their commits. We name it dev2vec and demonstrate its effectiveness in representing the technical specialization of developers. Our results indicate that encoding the expertise of developers in an embedding vector outperforms state-of-the-art methods and improves the F1-score up to 21%. Moreover, our findings suggest that ``issue resolving history'' of developers is the most informative source of information to represent the domain expertise of developers in embedding spaces.Comment: 30 pages, 5 figure

    Alloprof: a new French question-answer education dataset and its use in an information retrieval case study

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    Teachers and students are increasingly relying on online learning resources to supplement the ones provided in school. This increase in the breadth and depth of available resources is a great thing for students, but only provided they are able to find answers to their queries. Question-answering and information retrieval systems have benefited from public datasets to train and evaluate their algorithms, but most of these datasets have been in English text written by and for adults. We introduce a new public French question-answering dataset collected from Alloprof, a Quebec-based primary and high-school help website, containing 29 349 questions and their explanations in a variety of school subjects from 10 368 students, with more than half of the explanations containing links to other questions or some of the 2 596 reference pages on the website. We also present a case study of this dataset in an information retrieval task. This dataset was collected on the Alloprof public forum, with all questions verified for their appropriateness and the explanations verified both for their appropriateness and their relevance to the question. To predict relevant documents, architectures using pre-trained BERT models were fine-tuned and evaluated. This dataset will allow researchers to develop question-answering, information retrieval and other algorithms specifically for the French speaking education context. Furthermore, the range of language proficiency, images, mathematical symbols and spelling mistakes will necessitate algorithms based on a multimodal comprehension. The case study we present as a baseline shows an approach that relies on recent techniques provides an acceptable performance level, but more work is necessary before it can reliably be used and trusted in a production setting

    Scholar-activists in an expanding European food sovereignty movement

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    This article analyzes the roles, relations, and positions of scholar-activists in the European food sovereignty movement. In doing so, we document, make visible and question the political dimensions of researchers' participation in the movement. We argue that scholar-activists are part of the movement, but are distinct from the affected constituencies, put in place to ensure adequate representation of key movement actors. This is because scholar-activists lack a collective identity, have no processes to formulate collective demands, and no mechanisms for inter-researcher and researchers-movement communication. We reflect on whether and how scholar-activists could organize, and discuss possible pathways for a more cohesive and stronger researcher engagement in the movement.</p

    Teaching in groups in grade III.

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    Thesis (Ed.M.)--Boston University N.B.:Pages 28, 144 and 145 are missing from original thesis

    Effective Test Generation Using Pre-trained Large Language Models and Mutation Testing

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    One of the critical phases in software development is software testing. Testing helps with identifying potential bugs and reducing maintenance costs. The goal of automated test generation tools is to ease the development of tests by suggesting efficient bug-revealing tests. Recently, researchers have leveraged Large Language Models (LLMs) of code to generate unit tests. While the code coverage of generated tests was usually assessed, the literature has acknowledged that the coverage is weakly correlated with the efficiency of tests in bug detection. To improve over this limitation, in this paper, we introduce MuTAP for improving the effectiveness of test cases generated by LLMs in terms of revealing bugs by leveraging mutation testing. Our goal is achieved by augmenting prompts with surviving mutants, as those mutants highlight the limitations of test cases in detecting bugs. MuTAP is capable of generating effective test cases in the absence of natural language descriptions of the Program Under Test (PUTs). We employ different LLMs within MuTAP and evaluate their performance on different benchmarks. Our results show that our proposed method is able to detect up to 28% more faulty human-written code snippets. Among these, 17% remained undetected by both the current state-of-the-art fully automated test generation tool (i.e., Pynguin) and zero-shot/few-shot learning approaches on LLMs. Furthermore, MuTAP achieves a Mutation Score (MS) of 93.57% on synthetic buggy code, outperforming all other approaches in our evaluation. Our findings suggest that although LLMs can serve as a useful tool to generate test cases, they require specific post-processing steps to enhance the effectiveness of the generated test cases which may suffer from syntactic or functional errors and may be ineffective in detecting certain types of bugs and testing corner cases PUTs.Comment: 16 pages, 3 figure
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