Search

The electron antinuetrino flux limits are presented for the brightest gamma-ray burst (GRB) of all time, GRB221009A, over a range of 1.8-200 MeV using the Kamioka Liquid Scintillator Anti Neutrino Detector (KamLAND). Using a variety of time windows to search for electron antineutrinos coincident with the GRB, we set an upper limit on the flux under the assumption of various neutrino source spectra. No excess was observed in any time windows ranging from seconds to days around the event trigger time. The limits are compared to the results presented by IceCube., Comment: 8 pages, 3 figures, 1 table

There is growing concern about maintainers self-sabotaging their work in order to take political or economic stances, a practice referred to as "protestware". Our objective is to understand the discourse around discussions on such an attack, how it is received by the community, and whether developers respond to the attack in a timely manner. We study two notable protestware cases i.e., colors.js and es5-ext. Results indicate that protestware discussions are spread more quickly on the GitHub platform, while security vulnerabilities are faster on social media. By establishing a taxonomy of protestware discussions, we identify posts that express stances and provide technical mitigation instructions. We applied a thematic analysis to 684 protestware related posts to identify five major themes during the discussions: i. disseminate and response, ii. stance, iii. reputation, iv. communicative styles, v. rights and ethics. This work sheds light on the nuanced landscape of protestware discussions, offering insights for both researchers and developers into maintaining a healthy balance between the political or social actions of developers and the collective well-being of the open-source community.

Understanding the nature of grain boundaries is a prerequisite for fabricating high-performance superconducting bulks and wires. For iron-based superconductors [e.g. Ba(Fe,Co)$_2$As$_2$, Fe(Se,Te), and NdFeAs(O,F)], the dependence of the critical current density $J_\mathrm{c}$ on misorientation angle ($\theta_\mathrm{GB}$) has been explored on [001]-tilt grain boundaries, but no data for other types of orientations have been reported. Here, we report on the structural and transport properties of Fe(Se,Te) grown on CeO$_2$-buffered symmetric [010]-tilt roof-type SrTiO$_3$ bicrystal substrates by pulsed laser deposition. X-ray diffraction and transmission electron microscopy revealed that $\theta_\mathrm{GB}$ of Fe(Se,Te) was smaller whereas $\theta_\mathrm{GB}$ of CeO$_2$ was larger than that of the substrate. The difference in $\theta_\mathrm{GB}$ between the CeO$_2$ buffer layer and the substrate is getting larger with increasing $\theta_\mathrm{GB}$. For $\theta_\mathrm{GB}\geq24^\circ$ of the substrates, $\theta_\mathrm{GB}$ of Fe(Se,Te) was zero, whereas $\theta_\mathrm{GB}$ of CeO$_2$ was continuously increasing. The inclined growth of CeO$_2$ can be explained by the geometrical coherency model. The $c$-axis growth of Fe(Se,Te) for $\theta_\mathrm{GB}\geq24^\circ$ of the substrates is due to the domain matching epitaxy on (221) planes of CeO$_2$. Electrical transport measurements confirmed no reduction of inter-grain $J_\mathrm{c}$ for $\theta_\mathrm{GB}\leq9^\circ$, indicative of strong coupling between the grains., Comment: 6 figures, with Supplementary Information

We propose and demonstrate a static quantum dot on a potential hilltop to generate and analyze ballistic hot electrons along a quantum Hall edge channel well above the chemical potential. High energy resolution associated with discrete energy levels is attractive for studying hot-electron dynamics. Particularly, the energy distribution function of hot electrons weakly coupled to cold electrons is investigated to reveal spectral diffusion with energy relaxation. The analysis allows us to estimate the maximum energy exchange per scattering, which is an important parameter to describe interacting electrons in the edge channel., Comment: 10 pages, 9 figures

We present a search for neutrinoless double-beta ($0\nu\beta\beta$) decay of $^{136}$Xe using the full KamLAND-Zen 800 dataset with 745 kg of enriched xenon, corresponding to an exposure of $2.097$ ton yr of $^{136}$Xe. This updated search benefits from a more than twofold increase in exposure, recovery of photo-sensor gain, and reduced background from muon-induced spallation of xenon. Combining with the search in the previous KamLAND-Zen phase, we obtain a lower limit for the $0\nu\beta\beta$ decay half-life of $T_{1/2}^{0\nu} > 3.8 \times 10^{26}$ yr at 90% C.L., a factor of 1.7 improvement over the previous limit. The corresponding upper limits on the effective Majorana neutrino mass are in the range 28-122 meV using phenomenological nuclear matrix element calculations., Comment: arXiv admin note: text overlap with arXiv:2203.02139

Preceding a core-collapse supernova, various processes produce an increasing amount of neutrinos of all flavors characterized by mounting energies from the interior of massive stars. Among them, the electron antineutrinos are potentially detectable by terrestrial neutrino experiments such as KamLAND and Super-Kamiokande via inverse beta decay interactions. Once these pre-supernova neutrinos are observed, an early warning of the upcoming core-collapse supernova can be provided. In light of this, KamLAND and Super-Kamiokande, both located in the Kamioka mine in Japan, have been monitoring pre-supernova neutrinos since 2015 and 2021, respectively. Recently, we performed a joint study between KamLAND and Super-Kamiokande on pre-supernova neutrino detection. A pre-supernova alert system combining the KamLAND detector and the Super-Kamiokande detector was developed and put into operation, which can provide a supernova alert to the astrophysics community. Fully leveraging the complementary properties of these two detectors, the combined alert is expected to resolve a pre-supernova neutrino signal from a 15 M$_{\odot}$ star within 510 pc of the Earth, at a significance level corresponding to a false alarm rate of no more than 1 per century. For a Betelgeuse-like model with optimistic parameters, it can provide early warnings up to 12 hours in advance., Comment: Resubmitted to ApJ. 22 pages, 16 figures, for more information about the combined pre-supernova alert system, see https://www.lowbg.org/presnalarm/

The GitHub platform has fueled the creation of truly global software, enabling contributions from developers across various geographical regions of the world. As software becomes more entwined with global politics and social regulations, it becomes similarly subject to government sanctions. In 2019, GitHub restricted access to certain services for users in specific locations but rolled back these restrictions for some communities (e.g., the Iranian community) in 2021. We conducted a large-scale empirical study, collecting approximately 156 thousand user profiles and their 41 million activity points from 2008 to 2022, to understand the response of developers. Our results indicate that many of these targeted developers were able to navigate through the sanctions. Furthermore, once these sanctions were lifted, these developers opted to return to GitHub instead of withdrawing their contributions to the platform. The study indicates that platforms like GitHub play key roles in sustaining global contributions to Open Source Software.

While there is no replacement for the learned expertise, devotion, and social benefits of a guide dog, there are cases in which a robot navigation assistant could be helpful for individuals with blindness or low vision (BLV). This study investigated the potential for an industrial agile robot to perform guided navigation tasks. We developed two interface prototypes that allowed for spatial information between a human-robot pair: a voice-based app and a flexible, responsive handle. The participants (n=21) completed simple navigation tasks and a post-study survey about the prototype functionality and their trust in the robot. All participants successfully completed the navigation tasks and demonstrated the interface prototypes were able to pass spatial information between the human and the robot. Future work will include expanding the voice-based app to allow the robot to communicate obstacles to the handler and adding haptic signals to the handle design., Comment: This is an extended version of the late-breaking report presented as "Rayna Hata and Stacy A. Doore. Assistive Agile Robot for Non-visual Navigation. IEEE International Conference on Intelligent Robots and Systems, Detroit, MI. October 1-5, 2023"

GitHub's Copilot for Pull Requests (PRs) is a promising service aiming to automate various developer tasks related to PRs, such as generating summaries of changes or providing complete walkthroughs with links to the relevant code. As this innovative technology gains traction in the Open Source Software (OSS) community, it is crucial to examine its early adoption and its impact on the development process. Additionally, it offers a unique opportunity to observe how developers respond when they disagree with the generated content. In our study, we employ a mixed-methods approach, blending quantitative analysis with qualitative insights, to examine 18,256 PRs in which parts of the descriptions were crafted by generative AI. Our findings indicate that: (1) Copilot for PRs, though in its infancy, is seeing a marked uptick in adoption. (2) PRs enhanced by Copilot for PRs require less review time and have a higher likelihood of being merged. (3) Developers using Copilot for PRs often complement the automated descriptions with their manual input. These results offer valuable insights into the growing integration of generative AI in software development.

The existence of cosmic dark matter and neutrino properties are long-standing problems in cosmology and particle physics. These problems have been investigated by using radiation detectors. We will discuss the application of inorganic crystal scintillators to studies on dark matter and neutrino properties. A large volume and high-purity inorganic crystal is a promising detector for investigating dark matter and neutrino.

Self-Admitted Technical Debt (SATD) annotates development decisions that intentionally exchange long-term software artifact quality for short-term goals. Recent work explores the existence of SATD clones (duplicate or near duplicate SATD comments) in source code. Cloning of SATD in build systems (e.g., CMake and Maven) may propagate suboptimal design choices, threatening qualities of the build system that stakeholders rely upon (e.g., maintainability, reliability, repeatability). Hence, we conduct a large-scale study on 50,608 SATD comments extracted from Autotools, CMake, Maven, and Ant build systems to investigate the prevalence of SATD clones and to characterize their incidences. We observe that: (i) prior work suggests that 41-65% of SATD comments in source code are clones, but in our studied build system context, the rates range from 62% to 95%, suggesting that SATD clones are a more prevalent phenomenon in build systems than in source code; (ii) statements surrounding SATD clones are highly similar, with 76% of occurrences having similarity scores greater than 0.8; (iii) a quarter of SATD clones are introduced by the author of the original SATD statements; and (iv) among the most commonly cloned SATD comments, external factors (e.g., platform and tool configuration) are the most frequent locations, limitations in tools and libraries are the most frequent causes, and developers often copy SATD comments that describe issues to be fixed later. Our work presents the first step toward systematically understanding SATD clones in build systems and opens up avenues for future work, such as distinguishing different SATD clone behavior, as well as designing an automated recommendation system for repaying SATD effectively based on resolved clones.

Maintainers are now self-sabotaging their work in order to take political or economic stances, a practice referred to as "protestware". In this poster, we present our approach to understand how the discourse about such an attack went viral, how it is received by the community, and whether developers respond to the attack in a timely manner. We study two notable protestware cases, i.e., Colors.js and es5-ext, comparing with discussions of a typical security vulnerability as a baseline, i.e., Ua-parser, and perform a thematic analysis of more than two thousand protest-related posts to extract the different narratives when discussing protestware.

GitHub Sponsors was launched in 2019, enabling donations to open-source software developers to provide financial support, as per GitHub's slogan: "Invest in the projects you depend on". However, a 2022 study on GitHub Sponsors found that only two-fifths of developers who were seeking sponsorship received a donation. The study found that, other than internal actions (such as offering perks to sponsors), developers had advertised their GitHub Sponsors profiles on social media, such as Twitter (also known as X). Therefore, in this work, we investigate the impact of tweets that contain links to GitHub Sponsors profiles on sponsorship, as well as their reception on Twitter/X. We further characterize these tweets to understand their context and find that (1) such tweets have the impact of increasing the number of sponsors acquired, (2) compared to other donation platforms such as Open Collective and Patreon, GitHub Sponsors has significantly fewer interactions but is more visible on Twitter/X, and (3) developers tend to contribute more to open-source software during the week of posting such tweets. Our findings are the first step toward investigating the impact of social media on obtaining funding to sustain open-source software.

To meet the demands for more adaptable and expedient approaches to augment both research and manufacturing, we report an autonomous system using real-time in-situ characterization and an autonomous, decision-making processer based on an active learning algorithm. This system was applied to a plastic film forming system to highlight its efficiency and accuracy in determining the process conditions for specified target film dimensions, importantly, without any human intervention. Application of this system towards nine distinct film dimensions demonstrated the system ability to quickly determine the appropriate and stable process conditions (average 11 characterization-adjustment iterations, 19 minutes) and the ability to avoid traps, such as repetitive over-correction. Furthermore, comparison of the achieved film dimensions to the target values showed a high accuracy (R2 = 0.87, 0.90) for film width and thickness, respectively. In addition, the use of an active learning algorithm afforded our system to proceed optimization with zero initial training data, which was unavailable due to the complex relationships between the control factors (material supply rate, applied force, material viscosity) within the plastic forming process. As our system is intrinsically general and can be applied to any most material processes, these results have significant implications in accelerating both research and industrial processes., Comment: 18pages, 7figures

Solving complex visual tasks such as "Who invented the musical instrument on the right?" involves a composition of skills: understanding space, recognizing instruments, and also retrieving prior knowledge. Recent work shows promise by decomposing such tasks using a large language model (LLM) into an executable program that invokes specialized vision models. However, generated programs are error-prone: they omit necessary steps, include spurious ones, and are unable to recover when the specialized models give incorrect outputs. Moreover, they require loading multiple models, incurring high latency and computation costs. We propose Visual Program Distillation (VPD), an instruction tuning framework that produces a vision-language model (VLM) capable of solving complex visual tasks with a single forward pass. VPD distills the reasoning ability of LLMs by using them to sample multiple candidate programs, which are then executed and verified to identify a correct one. It translates each correct program into a language description of the reasoning steps, which are then distilled into a VLM. Extensive experiments show that VPD improves the VLM's ability to count, understand spatial relations, and reason compositionally. Our VPD-trained PaLI-X outperforms all prior VLMs, achieving state-of-the-art performance across complex vision tasks, including MMBench, OK-VQA, A-OKVQA, TallyQA, POPE, and Hateful Memes. An evaluation with human annotators also confirms that VPD improves model response factuality and consistency. Finally, experiments on content moderation demonstrate that VPD is also helpful for adaptation to real-world applications with limited data., Comment: CVPR 2024 Oral