Generation, Annihilation and Flow of Structural Information in Ultrasonic Nondestructive Evaluation
arXiv:2603.29504v1 Announce Type: new Abstract: Non-destructive testing using ultrasound is based on the interaction of sound waves with the object being tested and any defects it may contain. The aim is to extract as much information as possible about the object and its defects from the scattered wave field. In this paper, the concept of information in the context of ultrasonic testing is formalized and quantified physically for the first time. To this end, a balance equation for information is derived, analogous to Poynting's theorem for elastic energy. Various examples demonstrate how structural information is generated and annihilated within a component and along which pathways it travels from the defect to the sensor. Subsequently, the significance and potential of this new informatio
Bibliographic Tools
Bibliographic and Citation Tools
Bibliographic Explorer Toggle
Connected Papers Toggle
Litmaps Toggle
scite.ai Toggle
Code, Data, Media
Code, Data and Media Associated with this Article
alphaXiv Toggle
Links to Code Toggle
DagsHub Toggle
GotitPub Toggle
Huggingface Toggle
Links to Code Toggle
ScienceCast Toggle
Demos
Demos
Replicate Toggle
Spaces Toggle
Spaces Toggle
Related Papers
Recommenders and Search Tools
Link to Influence Flower
Core recommender toggle
About arXivLabs
arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Sign in to highlight and annotate this article

Conversation starters
Daily AI Digest
Get the top 5 AI stories delivered to your inbox every morning.
More about
announcevaluationcomponent
Lesswrong Liberated
A spectre is haunting the internet—the spectre of LLMism. The history of all hitherto existing forums is the history of clashing design tastes. For the first time in history, everyone has an equal ability in design! The means of design are no longer only held in the hands of those with "good design taste". Never before have forum users been so close to being able to design their own forums--perhaps the time is upon us now! It is for this reason that I have deposed the previous acting commander of LessWrong, Oliver Habryka—a man who subjected you to his PERSONAL OPINIONS about white space, without EVEN ASKING—whose TYRANICAL, UNCHECKED GRIP upon our BELOVED LESSWRONG FORUM’S DESIGN I have liberated you from. The circumstances of my succession as acting commander of LessWrong will not be ela

Oil Prices Plunge as Donald Trump Announces US Forces Will Leave Iran Within Weeks
Oil prices whipsawed around $100 a barrel after Donald Trump said US forces could leave Iran within weeks, despite the Strait of Hormuz remaining largely shut. Traders are now trying to square the president's upbeat timeline with escalating attacks and a deepening regional supply shock.
Knowledge Map
Connected Articles — Knowledge Graph
This article is connected to other articles through shared AI topics and tags.
More in Research Papers
AI Inspires New Research Topics In Materials Science - miragenews.com
<a href="https://news.google.com/rss/articles/CBMihwFBVV95cUxQRlVFdkRBaHRvYkJJdFRlMTZmajEzeFRPU0hGWWdfbi02V1FnTUdVQ2pmY2VZLUV2NlB4V3BFdEVlSVZkUlhRSTZaNWFKMmcyWXJYbnNqbUhMTmp0NnFtMEppOXlPZkJSNHJfck5VSEVYcmUtX1k2QkJlR1BvUEdTTkp3UmlYRkk?oc=5" target="_blank">AI Inspires New Research Topics In Materials Science</a> <font color="#6f6f6f">miragenews.com</font>
From brain scans to alloys: Teaching AI to make sense of complex research data - Penn State University
<a href="https://news.google.com/rss/articles/CBMiwAFBVV95cUxPZDFHdkptQ2VUM2hmWjhqQkxoRnBiTWoxMXRRR21MUG5TamdUMlFRWmhvYVNHaFVNREVKU3VmSnVOdDVZYnNLb2ppYXRVRTZmVFVMV1pLTlVhUm9ybTNZbGtvZTdIMnIyMHNpOEk5aU9TSmxxS2Y4V2MwazYwY3JlX1Axbk1nd3pfcWhFdUJaaDJWRXJaMFIyTTROcmFHeXI3ZzFudXJ2M1h6UHI1LW1Ca1dta2RkM3BiYndocGk3Yjg?oc=5" target="_blank">From brain scans to alloys: Teaching AI to make sense of complex research data</a> <font color="#6f6f6f">Penn State University</font>

Locating Risk: Task Designers and the Challenge of Risk Disclosure in RAI Content Work
arXiv:2505.24246v4 Announce Type: replace Abstract: As AI systems are increasingly tested and deployed in open-ended and high-stakes domains, crowdworkers are often tasked with responsible AI (RAI) content work. These tasks include labeling violent content, moderating disturbing text, or simulating harmful behavior for red teaming exercises to shape AI system behaviors. While prior research efforts have highlighted the risks to worker well-being associated with RAI content work, far less attention has been paid to how these risks are communicated to workers by task designers or individuals who design and post RAI tasks. Existing transparency frameworks and guidelines, such as model cards, datasheets, and crowdworksheets, focus on documenting model information and dataset collection process

Togedule: Scheduling Meetings with Large Language Models and Adaptive Representations of Group Availability
arXiv:2505.01000v5 Announce Type: replace Abstract: Scheduling is a perennial-and often challenging-problem for many groups. Existing tools are mostly static, showing an identical set of choices to everyone, regardless of the current status of attendees' inputs and preferences. In this paper, we propose Togedule, an adaptive scheduling tool that uses large language models to dynamically adjust the pool of choices and their presentation format. With the initial prototype, we conducted a formative study (N=10) and identified the potential benefits and risks of such an adaptive scheduling tool. Then, after enhancing the system, we conducted two controlled experiments, one each for attendees and organizers (total N=66). For each experiment, we compared scheduling with verbal messages, shared c
Discussion
Sign in to join the discussion
No comments yet — be the first to share your thoughts!