The application of information retrieval techniques to search tasks in software engineering is made difficult by the lexical gap between search queries, usually expressed in natural language (e.g. English), and retrieved documents, usually expressed in code (e.g. programming languages). This is often the case in bug and feature location, community question answering, or more generally the communication between technical personnel and non-technical stake holders in a software project. In this paper, we propose bridging the lexical gap by projecting natural language statements and code snippets as meaning vectors in a shared representation space. In the proposed architecture, word embeddings are first trained on API documents, tutorials, and reference documents, and then aggregated in order to estimate semantic similarities between documents. Empirical evaluations show that the learned vector space embeddings lead to improvements in a previously explored bug localization task and a newly defined task of linking API documents to computer programming questions.

The Pearl River and its tributaries drains large areas of southern China and has been the primary source of sediment to the northern continental margin of the South China Sea since its opening. In this study we use a combination of bulk sediment geochemistry, Nd and Sr isotope geochemistry, and single grain zircon U-Pb dating to understand the source of sediment in the modern drainage. We also performed zircon U-Pb dating on Eocene sedimentary rocks sampled by International Ocean Discovery Program (IODP) Expedition

This paper proposes a method for planning the three-dimensional path for low-flying unmanned aerial vehicle (UAV) in complex terrain based on interfered fluid dynamical system (IFDS) and the theory of obstacle avoidance by the flowing stream. With no requirement of solutions to fluid equations under complex boundary conditions, the proposed method is suitable for situations with complex terrain and different shapes of obstacles. Firstly, by transforming the mountains, radar and anti-aircraft fire in complex terrain into cylindrical, conical, spherical, parallelepiped obstacles and their combinations, the 3D low-flying path planning problem is turned into solving streamlines for obstacle avoidance by fluid flow. Secondly, on the basis of a unified mathematical expression of typical obstacle shapes including sphere, cylinder, cone and parallelepiped, the modulation matrix for interfered fluid dynamical system is constructed and 3D streamlines around a single obstacle are obtained. Solutions to streamlines with multiple obstacles are then derived using weighted average of the velocity field. Thirdly, extra control force method and virtual obstacle method are proposed to deal with the stagnation point and the case of obstacles' overlapping respectively. Finally, taking path length and flight height as sub-goals, genetic algorithm (GA) is used to obtain optimal 3D path under the maneuverability constraints of the UAV. Simulation results show that the environmental modeling is simple and the path is smooth and suitable for UAV. Theoretical proof is also presented to show that the proposed method has no effect on the characteristics of fluid avoiding obstacles. ª 2015 Production and hosting by Elsevier Ltd. on behalf of CSAA & BUAA.

Fan-beam tunable diode laser absorption spectroscopy (TDLAS) system was combined with onion-peeling deconvolution to reconstruct axisymmetric temperature and gas concentration distributions. The fan-beam TDLAS system consists of two tunable distributed feedback diode lasers at 7185.597 and 7444.36 cm −1 , a cylindrical lens and multiple photodiode detectors in a linear detector array. When a well-collimated laser beam penetrates through a cylindrical lens, a fan-beam laser was formed. Then, the fan-beam laser penetrates through the target region and is detected by the photodiode detectors in the detector array. After transforming the fan-beam geometry to equivalent parallel-beam geometry, axisymmetric temperature and gas concentration distributions can be reconstructed using the onion-peeling deconvolution. To obtain the reconstruction results with higher accuracy, a revised Tikhonov regularization method was adopted in the onion-peeling deconvolution. In this paper, numerical simulation and experimental verification were carried out to validate the feasibility of the proposed methods. The results show that the proposed methods can be used to on-line monitor the axisymmetric temperature and gas concentration distributions with higher accuracy and robustness in combustion diagnosis. IndexTerms-Axisymmetric temperature and gas concentration distributions, fan-beam tunable diode laser absorption spectroscopy (TDLAS), onion-peeling deconvolution, regularization method. 0018-9456Zhang Cao received the B.Sc. (Hons.) degree in automation and the M.Eng. and Ph.D. (Hons.) degrees in measurement technology and automatic devices from Tianjin University,

ACE2 and MasR expressions in the hypertensive heart and kidney are not regulated by circulating AngII levels. Ang1-7 is involved in multiple repair responses, suggesting that therapeutic strategies aimed at administering Ang1-7 hold potential for the management of cardiac remodeling.