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438 papers
AI-assisted development tools enable software engineers to generate implementations at substantially higher speed and volume than in traditional workflows, yet relatively little is known about how existing guardrails evolve in response.
This work presents the first characterization study of open-source satellite software, examining its ecosystem and development practices, revealing a highly heterogeneous and task-specialized ecosystem with 66 programming languages and diverse implementation strategies.
RTL-Obliger is presented, a neuro-symbolic framework that infers implicit security obligations of register-transfer-level RTL in a functionality-preserving two-stage generation and raises mean all-pass rates.
PLCBENCH is presented, to the authors' knowledge, the first real-PLC hardware-in-the-loop (HIL) framework for characterizing this cyber-to-physical capability and its boundaries and it combines vendor-native interaction, commercial PLC execution, closed-loop reduced-order process simulation, and independent outcome verification.
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An entity-only external interface with task-conditioned relation materialization during inference with two-layer index separates global routing from local entity focus is proposed and evaluated on DeepSeek-V4-Flash and SWE-bench Verified.
Analysis of patterns of knowledge and use of medicinal plants and biomedical medicines among migrants in an urban setting contributes to understanding how medicinal plant knowledge and therapeutic practices are maintained or transformed in urban migrant contexts.
MEmilio is a modular, high-performance framework for epidemic simulation that harmonizes the specification and execution of diverse dynamic epidemiological models within a unified and harmonized architecture, and aims to lower barriers to reuse and generalize models, enable principled comparisons of implicit assumptions, and accelerate the development of novel approaches that strengthen modeling-based outbreak preparedness.
Verification and validation (V&V) campaigns for satellites commonly rely on FlatSat platforms to access critical electrical and communication interfaces before final integration. For CubeSats, an ideal platform should be compact and minimize reliance on external instrumentation. Existing solutions often rely on external instrumentation or on simple passive backplanes, whereas more integrated alternatives tend to be proprietary, closed-source, and costly. To address this gap, this article introduces an open-source FlatSat platform that combines bridge- and dock-type architectures, including a set of fully integrated features, such as embedded current and temperature sensors, hardware- and software-based fault injection, and a reconfigurable system-on-module (SoM) running a custom Linux distribution for flexibility and multimission adaptability. The platform was validated through practical, lab-based scenarios using representative CubeSat subsystems. These tests confirmed its ability to emulate missing subsystems, conduct on-orbit scenario simulations and emulations, and perform unified monitoring and logging of sensor and telemetry data without the need for external instrumentation; this establishes it as a practical and reusable solution for advanced V&V, particularly in academic settings. Design files, firmware, and software are publicly available to promote reproducibility and adaptation.
XREPOTEST is introduced, a multilingual repository-level benchmark for unit test generation spanning five underexplored languages: Rust, Go, Julia, PHP, and Ruby, and Invocation Rate is proposed to assess whether generated tests meaningfully exercise the intended functionality.
This work explores the sputtering of additively manufactured (AM) materials for use in gridded ion source applications. The first part of the paper uses 316L stainless steel as an example to demonstrate that additively manufactured material does not exhibit adverse sputtering behavior, such as higher sputter yield, compared with conventionally manufactured material. To this end, three additively manufactured 316L stainless steel samples were exposed to the beam of a KDC-40 electrostatic gridded ion source at three distinct energy levels of 400, 600, and 800 eV on each side of the sample for a duration of one hour. The samples were masked to create a distinct boundary between treated and untreated regions, identifiable using profilometry, and were biased to -18V for testing. Samples were then examined using a Bruker optical profilometer and further processed using the open-source software Gwyddion to evaluate the sputtering yield. The sputter yield varied in the range 0.2-2 atoms/ion for 400-800 eV ions and increased with ion energy. The measured sputtering yield was fairly consistent with predictions from analytical models developed in prior literature, while exhibiting some variations potentially due to added effects of increased temperature and oxide layers. The second part of the paper demonstrates feasibility of using an additively manufactured tungsten-rhenium grids in existing KDC-40 electrostatic gridded ion source.
This work attempts to design core layer in campus network employing best practices of network topology and routing protocol at the layer with a use case of core layer in a university campus network using software-defined networking (SDN) paradigm.
It is shown that the contradiction in experience with neural surrogates in derivative-free optimisation dissolves once three factors are stated, and that these, rather than the fit accuracy a training curve reports, are what delimit when a learned local model pays.
In his latest book, Professor Eugene Fitzgerald examines the forces that turn breakthroughs into value — and why innovation resists simple formulas.
MIT students designed, built, and tested a jet engine with AI copilots, assessing AI’s usefulness in developing high-performance aerospace systems.
Researchers developed an auditing technique to test generative AI models for malicious capabilities, without prompting them for illegal outputs.
A USAF cadet and a Lincoln Laboratory researcher found AI chatbots can help nontechnical service members produce viable software applications for their unique problems.
Our latest voice model has improved precision and lower latency to make voice interactions more fluid, natural and precise.
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