221 research outputs found

    Dielectric response of soft mode in ferroelectric SrTiO3

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    We report far-infrared dielectric properties of powder form ferroelectric SrTiO3. Terahertz time-domain spectroscopy (THz-TDS) measurement reveals that the low-frequency dielectric response of SrTiO3 is a consequence of the lowest transverse optical (TO) soft mode TO1 at 2.70 THz (90.0 1/cm), which is directly verified by Raman spectroscopy. This result provides a better understanding of the relation of low-frequency dielectric function with the optical phonon soft mode for ferroelectric materials. Combining THz-TDS with Raman spectra, the overall low-frequency optical phonon response of SrTiO3 is presented in an extended spectral range from 6.7 1/cm to 1000.0 1/cm.Comment: 14 pages; 4 figure

    Software Architecture in Practice: Challenges and Opportunities

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    Software architecture has been an active research field for nearly four decades, in which previous studies make significant progress such as creating methods and techniques and building tools to support software architecture practice. Despite past efforts, we have little understanding of how practitioners perform software architecture related activities, and what challenges they face. Through interviews with 32 practitioners from 21 organizations across three continents, we identified challenges that practitioners face in software architecture practice during software development and maintenance. We reported on common software architecture activities at software requirements, design, construction and testing, and maintenance stages, as well as corresponding challenges. Our study uncovers that most of these challenges center around management, documentation, tooling and process, and collects recommendations to address these challenges.Comment: Preprint of Full Research Paper, the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE '23

    A Closer Look at the Security Risks in the Rust Ecosystem

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    Rust is an emerging programming language designed for the development of systems software. To facilitate the reuse of Rust code, crates.io, as a central package registry of the Rust ecosystem, hosts thousands of third-party Rust packages. The openness of crates.io enables the growth of the Rust ecosystem but comes with security risks by severe security advisories. Although Rust guarantees a software program to be safe via programming language features and strict compile-time checking, the unsafe keyword in Rust allows developers to bypass compiler safety checks for certain regions of code. Prior studies empirically investigate the memory safety and concurrency bugs in the Rust ecosystem, as well as the usage of unsafe keywords in practice. Nonetheless, the literature lacks a systematic investigation of the security risks in the Rust ecosystem. In this paper, we perform a comprehensive investigation into the security risks present in the Rust ecosystem, asking ``what are the characteristics of the vulnerabilities, what are the characteristics of the vulnerable packages, and how are the vulnerabilities fixed in practice?''. To facilitate the study, we first compile a dataset of 433 vulnerabilities, 300 vulnerable code repositories, and 218 vulnerability fix commits in the Rust ecosystem, spanning over 7 years. With the dataset, we characterize the types, life spans, and evolution of the disclosed vulnerabilities. We then characterize the popularity, categorization, and vulnerability density of the vulnerable Rust packages, as well as their versions and code regions affected by the disclosed vulnerabilities. Finally, we characterize the complexity of vulnerability fixes and localities of corresponding code changes, and inspect how practitioners fix vulnerabilities in Rust packages with various localities.Comment: preprint of accepted TOSEM pape

    Along-strike variation in slab geometry at the southern Mariana subduction zone revealed by seismicity through ocean bottom seismic experiments

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    Author Posting. © The Authors, 2019. This article is posted here by permission of The Royal Astronomical Society for personal use, not for redistribution. The definitive version was published in Geophysical Journal International 218(3), (2019): 2122-2135, doi: 10.1093/gji/ggz272.We have conducted the first passive Ocean Bottom Seismograph (OBS) experiment near the Challenger Deep at the southernmost Mariana subduction zone by deploying and recovering an array of 6 broad-band OBSs during December 2016–June 2017. The obtained passive-source seismic records provide the first-ever near-field seismic observations in the southernmost Mariana subduction zone. We first correct clock errors of the OBS recordings based on both teleseismic waveforms and ambient noise cross-correlation. We then perform matched filter earthquake detection using 53 template events in the catalogue of the US Geological Survey and find >7000 local earthquakes during the 6-month OBS deployment period. Results of the two independent approaches show that the maximum clock drifting was ∼2 s on one instrument (OBS PA01), while the rest of OBS waveforms had negligible time drifting. After timing correction, we locate the detected earthquakes using a newly refined local velocity model that was derived from a companion active source experiment in the same region. In total, 2004 earthquakes are located with relatively high resolution. Furthermore, we calibrate the magnitudes of the detected earthquakes by measuring the relative amplitudes to their nearest relocated templates on all OBSs and acquire a high-resolution local earthquake catalogue. The magnitudes of earthquakes in our new catalogue range from 1.1 to 5.6. The earthquakes span over the Southwest Mariana rift, the megathrust interface, forearc and outer-rise regions. While most earthquakes are shallow, depths of the slab earthquakes increase from ∼100 to ∼240 km from west to east towards Guam. We also delineate the subducting interface from seismicity distribution and find an increasing trend in dip angles from west to east. The observed along-strike variation in slab dip angles and its downdip extents provide new constraints on geodynamic processes of the southernmost Mariana subduction zone.We express our appreciation to the science parties and crew members of the R/V Shiyan 3 for deployment and collection of the OBS instruments during the Mariana expeditions. This study is supported by the Hong Kong Research Grant Council Grants (No. 14313816), Faculty of Science at CUHK, Chinese Academy of Sciences (No. Y4SL021001, QYZDY-SSW-DQC005, 133244KYSB20180029), the National Natural Science Foundation of China (No. 41890813, 91628301, 41676042, U1701641, 41576041, 91858207 and U1606401), the National Key R&D Program of China (2018YFC0309800 and 2018YFC0310100). Generic Mapping Tools (Wessel & Smith 1991) and PSSAC (developed by Prof Lupei Zhu) are used for data analysis and figure preparation in this study. Constructive comments from Dr Lidong Bie and two anonymous reviewers are helpful in improving the manuscript

    Bug characteristics in blockchain systems: A large-scale empirical study

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    Practical and effective sandboxing for Linux containers

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    How practitioners perceive coding proficiency

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    How does machine learning change software development practices?

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    Autoencoding a Soft Touch to Learn Grasping from On-land to Underwater

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    Robots play a critical role as the physical agent of human operators in exploring the ocean. However, it remains challenging to grasp objects reliably while fully submerging under a highly pressurized aquatic environment with little visible light, mainly due to the fluidic interference on the tactile mechanics between the finger and object surfaces. This study investigates the transferability of grasping knowledge from on-land to underwater via a vision-based soft robotic finger that learns 6D forces and torques (FT) using a Supervised Variational Autoencoder (SVAE). A high-framerate camera captures the whole-body deformations while a soft robotic finger interacts with physical objects on-land and underwater. Results show that the trained SVAE model learned a series of latent representations of the soft mechanics transferrable from land to water, presenting a superior adaptation to the changing environments against commercial FT sensors. Soft, delicate, and reactive grasping enabled by tactile intelligence enhances the gripper's underwater interaction with improved reliability and robustness at a much-reduced cost, paving the path for learning-based intelligent grasping to support fundamental scientific discoveries in environmental and ocean research.Comment: 17 pages, 5 figures, 1 table, submitted to Advanced Intelligent Systems for revie
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