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Physics Preprint PDF DOI

Local probing of superconductivity at oxide interfaces with atomic force microscopy

Dilek Yildiz, Sungmin Kim, Dengyu Yang, Muqing Yu, Kyoungjun Lee, Ruiqi Sun, En-Min Shih, Steven R. Blankenship, Patrick Irvin, Franz J. Giessibl, Chang-Beom Eom, Jeremy Levy, Joseph A. Stroscio · 2026

Superconductivity in strontium titanate has remained enigmatic for more than 50 years. The LaAlO$_3$/SrTiO$_3$ (LAO/STO) heterointerface enables systematic dimensional confinement, from a two-dimensio…

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Physics Preprint PDF DOI

Linear Dependence of Electron-Decay Maximum Energy on the Mass Number A Along Isotopic Chains For Z<47

Tolga Yarman, Nimet Zaim, Alexander Kholmetskii, Ozan Yarman, Faruk Aga Yarman · 2026

We investigate the systematics of the maximum Electron-decay energy E as a function of the mass number A along isotopic chains with a fixed proton number across Z<47. By making use of the available cu…

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Computer Science Preprint PDF DOI

AI Inference as Relocatable Electricity Demand: A Latency-Constrained Energy-Geography Framework

Xubin Luo, Yang Cheng · 2026

AI inference is becoming a persistent and geographically distributed source of electricity demand. Unlike many traditional electrical loads, inference workloads can sometimes be executed away from the…

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Computer Science Preprint PDF DOI

NetSatBench: A Distributed LEO Constellation Emulator with an SRv6 Case Study

Andrea Detti, Shahram Dadras, Giuseppe Tropea · 2026

NetSatBench is a distributed emulation platform for evaluating communication protocols and application workloads over large-scale LEO satellite systems. Satellites, gateways, and user terminals are im…

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AI & Data Science Preprint PDF DOI

Post-Optimization Adaptive Rank Allocation for LoRA

Vishnuprasadh Kumaravelu, Sunil Gupta, P. K. Srijith · 2026

Exponential growth in the scale of modern foundation models has led to the widespread adoption of Low-Rank Adaptation (LoRA) as a parameter-efficient fine-tuning technique. However, standard LoRA impl…

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AI & Data Science Preprint PDF DOI

A generalised pre-training strategy for deep learning networks in semantic segmentation of remotely sensed images

Yuan Fang, Yuanzhi Cai, Jagannath Aryal, Qinfeng Zhu, Hong Huang, Cheng Zhang, Lei Fan · 2026

In the segmentation of remotely sensed images, deep learning models are typically pre-trained using large image databases like ImageNet before fine-tuned on domain-specific datasets. However, the perf…

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Computer Science Preprint PDF DOI

Line Segment Clipping using Quadrilateral Concavity and Convexity

Bimal Kumar Ray · 2026

This paper proposes an algorithm for clipping line segment against an axis-aligned rectangular window. The conventional algorithms for line segment clipping treat the clipping boundary and/or the line…

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Computer Science Preprint PDF DOI

Multi-Connectivity for UAVs: A Measurement Study of Integrating Cellular, Aerial Mesh, and LEO Satellite Links

Aygun Baltaci, Irshad A. Meer, Mustafa Ozger, Cicek Cavdar, Dominic Schupke · 2026

Future uncrewed aerial vehicle (UAV) systems increasingly combine heterogeneous communication technologies, such as low-latency aerial mesh, terrestrial cellular, and satellite links, to improve robus…

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AI & Data Science Preprint PDF DOI

Green Physics-Informed Machine Learning Models For Structural Health Monitoring

Daisy R Bradley, Elizabeth J Cross · 2026

Machine learning continues to emerge as an important tool to be utilised within structural engineering and structural health monitoring, due to its ability to accurately and quickly perform both regre…

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AI & Data Science Preprint PDF DOI

HATS: An Open data set Integrating Human Perception Applied to the Evaluation of Automatic Speech Recognition Metrics

Thibault Baneras Roux, Jane Wottawa, Mickael Rouvier, Teva Merlin, Richard Dufour · 2026

Conventionally, Automatic Speech Recognition (ASR) systems are evaluated on their ability to correctly recognize each word contained in a speech signal. In this context, the word error rate (WER) metr…

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AI & Data Science Preprint PDF DOI

Toward Scalable SDN for LEO Mega-Constellations: A Graph Learning Approach

Sivaram Krishnan, Bassel Al Homssi, Zhouyou Gu, Jihong Park, Sung-Min Oh, Jinho Choi · 2026

Terrestrial network limitations drive the integration of non-terrestrial networks (NTNs), notably mega-constellations comprising thousands of low Earth orbit (LEO) satellites. While these satellites a…

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AI & Data Science Preprint PDF DOI

Leading Across the Spectrum of Human-AI Relationships: A Conceptual Framework for Increasingly Heterogeneous Teams

Alejandro R. Jadad · 2026

What shapes a consequential decision when human and artificial intelligence work on it together? The answer is becoming harder to see. A decision may look human-led after AI has set the frame, or appe…

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Computer Science Preprint PDF DOI

New Diameter Approximations via Distance Oracle Techniques

Yael Kirkpatrick, Liam Roditty, Richard Qi, Virginia Vassilevska Williams · 2026

Computing the diameter of a graph is a problem of great interest both in general algorithms research and specifically within fine-grained complexity, where it is a cornerstone hard problem. Recent wor…

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AI & Data Science Preprint PDF DOI

End-to-end autonomous scientific discovery on a real optical platform

Shuxing Yang, Fujia Chen, Rui Zhao, Junyao Wu, Yize Wang, Haiyao Luo, Ning Han, Qiaolu Chen, Yuze Hu, Wenhao Li, Mingzhu Li, Hongsheng Chen, Yihao Yang · 2026

Scientific research has long been human-led, driving new knowledge and transformative technologies through the continual revision of questions, methods and claims as evidence accumulates. Although lar…

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Physics Preprint PDF DOI

SPYGLASS. VII-B. Tracing the Fragments of Massive Star Formation Using Low-Mass Associations

Ronan Kerr, Adam L. Kraus, Jonathan C. Tan, Julio Chaname, Facundo Perez Paolino, Joshua S. Speagle, Juan P. Farias, Jose G. Fernandez-Trincado, Keith Hawkins · 2026

New observations from the Gaia spacecraft have traced an emerging demographic of low-mass associations disconnected from larger associations or GMCs. The first of these associations were recently char…

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Engineering Preprint PDF DOI

Bi-Level Optimization for Contact and Motion Planning in Rope-Assisted Legged Robots

Ruben Malacarne, Ioannis Tsikelis, Enrico Mingo Hoffman, Michele Focchi · 2026

This paper presents a planning pipeline framework for locomotion in rope-assisted robots climbing vertical surfaces. The proposed framework is formulated as a bi-level optimization scheme that address…

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AI & Data Science Preprint PDF DOI

HalluCiteChecker: A Lightweight Toolkit for Hallucinated Citation Detection and Verification in the Era of AI Scientists

Yusuke Sakai, Hidetaka Kamigaito, Taro Watanabe · 2026

We introduce HalluCiteChecker, a toolkit for detecting and verifying hallucinated citations in scientific papers. While AI assistant technologies have transformed the academic writing process, includi…

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Mathematics Preprint PDF DOI

On the monotonicity of affine quermassintegrals

Shibing Chen, Yuanyuan Li, Xianduo Wang · 2026

Lutwak's affine quermassintegral theory is a foundational component of modern affine Brunn--Minkowski theory. Developed in the 1980s, it provides affine analogues of the classical quermassintegrals an…

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AI & Data Science Preprint PDF DOI

Virtual-reality based patient-specific simulation of spine surgical procedures: A fast, highly automated and high-fidelity system for surgical education and planning

Raj Kumar Ranabhat, Tayler D Ross, Tony Jiao, Jeremie Larouche, Joel Finkelstein, Michael Hardisty · 2026

Surgical training involves didactic teaching, mentor-led learning, surgical skills laboratories, and direct exposure to surgery; however, increasing clinical pressures have limited operating room (OR)…

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AI & Data Science Preprint PDF DOI

AirZoo: A Unified Large-Scale Dataset for Grounding Aerial Geometric 3D Vision

Xiaoya Cheng, Rouwan Wu, Xinyi Liu, Zeyu Cui, Yan Liu, Na Zhao, Yu Liu, Maojun Zhang, Shen Yan · 2026

Despite the rapid progress in data-driven 3D vision, aerial geometric 3D vision remains a formidable challenge due to the severe scarcity of large-scale, high-fidelity training data. Existing benchmar…

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