Tootfinder

A Conceptual Introduction to Hetero-functional Graph Theory for Systems-of-Systems
Amro M. Farid, Amirreza Hosseini, John C. Little
https://arxiv.org/abs/2505.24046

A Conceptual Introduction to Hetero-functional Graph Theory for Systems-of-Systems
A defining feature of twenty first century engineering challenges is their inherent complexity, demanding the convergence of knowledge across diverse disciplines. Establishing consistent methodological foundations for engineering systems remains a challenge -- one that both systems engineering and network science have sought to address. Model-based systems engineering (MBSE) has recently emerged as a practical, interdisciplinary approach for developing complex systems from concept through imple…

Greening AI-enabled Systems with Software Engineering: A Research Agenda for Environmentally Sustainable AI Practices
Lu\'is Cruz, Jo\~ao Paulo Fernandes, Maja H. Kirkeby, Silverio Mart\'inez-Fern\'andez, June Sallou, Hina Anwar, Enrique Barba Roque, Justus Bogner, Joel Casta\~no, Fernando Castor, Aadil Chasmawala, Sim\~ao Cunha, Daniel Feitosa, Alexandra Gonz\'alez, Andreas Jedlitschka, Patricia Lago, Ana Oprescu, Pooja Rani, Jo\~ao Saraiva, Federica Sarro, Raghavendra…

Greening AI-enabled Systems with Software Engineering: A Research Agenda for Environmentally Sustainable AI Practices
The environmental impact of Artificial Intelligence (AI)-enabled systems is increasing rapidly, and software engineering plays a critical role in developing sustainable solutions. The "Greening AI with Software Engineering" CECAM-Lorentz workshop (no. 1358, 2025) funded by the Centre Européen de Calcul Atomique et Moléculaire and the Lorentz Center, provided an interdisciplinary forum for 29 participants, from practitioners to academics, to share knowledge, ideas, practices, and current resul…

Integrative, Scalable Modeling of Hydrological Systems with MBSE and HFGT
Megan Harris, Ehsanoddin Ghorbanichemazkati, Mohammad Mahdi Naderi, John C. Little, Amro M. Farid
https://arxiv.org/abs/2506.00696

Integrative, Scalable Modeling of Hydrological Systems with MBSE and HFGT
Worsening global challenges in the Anthropocene demand complex, adaptive solutions grounded in a systems-level understanding of coupled social and environmental dynamics. However, existing modeling approaches often fall short due to disciplinary silos, limited scalability, and the absence of shared ontological frameworks. Model-Based Systems Engineering (MBSE), when integrated with Hetero-functional Graph Theory (HFGT), offers a powerful methodology for modeling systems of systems while preserv…

Dissipation engineering of fermionic long-range order beyond Lindblad
Silvia Neri, Fran\c{c}ois Damanet, Andrew J. Daley, Marialuisa Chiofalo, Jorga Yago Malo
https://arxiv.org/abs/2507.00553

Dissipation engineering of fermionic long-range order beyond Lindblad
We investigate the possibility of engineering dissipatively long-range order that is robust against heating in strongly interacting fermionic systems, relevant for atoms in cavity QED. It was previously shown [Tindall et al. Phys.Rev.Lett. 123, 030603 (2019)] that it is possible to stabilize long-range order in a Hubbard model by exploiting a dissipative mechanism in the Lindblad limit, this latter being valid for spectrally unstructured baths. Here, we first show that this mechanism still hold…

Topological phase control in Mn1-xGexBi2Te4 via spin-orbit coupling and magnetic configuration engineering
A. M. Shikin, N. L. Zaitsev, A. V. Eryzhenkov, R. V. Makeev, T. P. Estyunina, D. A. Estyunin, A. V. Tarasov
https://arxiv.org/abs/2506.00511

Topological phase control in Mn1-xGexBi2Te4 via spin-orbit coupling and magnetic configuration engineering
Magnetic topological systems based on MnBi2Te4 have recently attracted significant attention due to their rich interplay between magnetism and topological electronic states. In this work, using density functional theory (DFT), we investigate topological phase transitions (TPTs) in Mn1-xGexBi2Te4 compounds with both ferromagnetic (FM) and antiferromagnetic (AFM) ordering under variations of spin-orbit coupling (SOC) strength and uniaxial strain along the c axis. We show that the emergence of a W…

Towards a unified user modeling language for engineering human centered AI systems
Aaron Conrardy, Alfredo Capozucca, Jordi Cabot
https://arxiv.org/abs/2505.24697

Towards a unified user modeling language for engineering human centered AI systems
In today's digital society, personalization has become a crucial aspect of software applications, significantly impacting user experience and engagement. A new wave of intelligent user interfaces, such as AI-based conversational agents, has the potential to enable such personalization beyond what other types of interfaces could offer in the past. Personalization requires the ability to specify a complete user profile, covering as many dimensions as possible, such as potential accessibility cons…

This https://arxiv.org/abs/2412.07818 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Real-time Chest X-Ray Distributed Decision Support for Resource-constrained Clinics
Internet of Things (IoT) based healthcare systems offer significant potential for improving the delivery of healthcare services in humanitarian engineering, providing essential healthcare services to millions of underserved people in remote areas worldwide. However, these areas have poor network infrastructure, making communications difficult for traditional IoT. This paper presents a real-time chest X-ray classification system for hospitals in remote areas using FastDDS real-time middleware, o…

Engineering Magnetization with Photons: Nanoscale Advances in the Inverse Faraday Effect for Metallic and Plasmonic Systems
Chantal Hareau, Xingyu Yang, Maria Sanz, Matthew Sheldon, Mathieu Mivelle
https://arxiv.org/abs/2506.23515

Engineering Magnetization with Photons: Nanoscale Advances in the Inverse Faraday Effect for Metallic and Plasmonic Systems
The inverse Faraday effect, the ability of light to act as a source of magnetism, is a cornerstone of modern ultrafast optics. Harnessing this effect at the nanoscale promises to transform data storage and spintronics, yet its predictive understanding remains elusive. This review synthesizes recent progress in engineering the IFE within plasmonic architectures. We bridge the theoretical foundations, from classical drift current models to quantum descriptions, with the latest experimental milest…

Enhancing Spatio-Temporal Resolution of Process-Based Life Cycle Analysis with Model-Based Systems Engineering \& Hetero-functional Graph Theory
Niraj Gohil, Nawshad Haque, Amgad Elgowainy, Amro M. Farid
https://arxiv.org/abs/2506.00230

Enhancing Spatio-Temporal Resolution of Process-Based Life Cycle Analysis with Model-Based Systems Engineering \& Hetero-functional Graph Theory
Life cycle analysis (LCA) has emerged as a vital tool for assessing the environmental impacts of products, processes, and systems throughout their entire lifecycle. It provides a systematic approach to quantifying resource consumption, emissions, and waste, enabling industries, researchers, and policymakers to identify hotspots for sustainability improvements. By providing a comprehensive assessment of systems, from raw material extraction to end-of-life disposal, LCA facilitates the developmen…

Data-Driven Multiscale Topology Optimization of Soft Functionally Graded Materials with Large Deformations
Shiguang Deng, Horacio D. Espinosa, Wei Chen
https://arxiv.org/abs/2506.23422

Data-Driven Multiscale Topology Optimization of Soft Functionally Graded Materials with Large Deformations
Functionally Graded Materials (FGMs) made of soft constituents have emerged as promising material-structure systems in potential applications across many engineering disciplines, such as soft robots, actuators, energy harvesting, and tissue engineering. Designing such systems remains challenging due to their multiscale architectures, multiple material phases, and inherent material and geometric nonlinearities. The focus of this paper is to propose a general topology optimization framework that …

Extracting Contact Forces in Cohesive Granular Ensembles
Abrar Naseer, Karen E. Daniels, Tejas G. Murthy
https://arxiv.org/abs/2507.00517 https://

Extracting Contact Forces in Cohesive Granular Ensembles
Interparticle cohesion is prevalent in stored powders, geological formations, and infrastructure engineering, yet a comprehensive understanding of the effects of its micro-mechanics on bulk properties has not been established experimentally. One challenge has been that while photoelasticy has been widely and successfully used to measure the vector contact forces within dry granular systems, where the particle-particle interactions are solely frictional and compressive in nature, it has seen lit…

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems
Tomer Slor, Dean Oren, Shira Baneth, Tom Coen, Haim Suchowski
https://arxiv.org/abs/2506.23173

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems
In the rapidly evolving field of optical engineering, precise alignment of multi-lens imaging systems is critical yet challenging, as even minor misalignments can significantly degrade performance. Traditional alignment methods rely on specialized equipment and are time-consuming processes, highlighting the need for automated and scalable solutions. We present two complementary deep learning-based inverse-design methods for diagnosing misalignments in multi-element lens systems using only optic…

Advanced System Engineering Approaches to Emerging Challenges in Planetary and Deep-Space Exploration
J. de Curt\`o, Cristina LiCalzi, Julien Tubiana Warin, Jack Gehlert, Brian Langbein, Alexandre Gamboa, Chris Sixbey, William Maguire, Santiago Fern\'andez, \'Alvaro Maestroarena, Alex Brenchley, Logan Maroclo, Philemon Mercado, Joshua DeJohn, Cesar Velez, Ethan Dahmus, Taylor Steinys, David Fritz, I. de Zarz\`a

Advanced System Engineering Approaches to Emerging Challenges in Planetary and Deep-Space Exploration
This paper presents innovative solutions to critical challenges in planetary and deep-space exploration electronics. We synthesize findings across diverse mission profiles, highlighting advances in: (1) MARTIAN positioning systems with dual-frequency transmission to achieve $\pm$1m horizontal accuracy; (2) artificial reef platforms for Titan's hydrocarbon seas utilizing specialized sensor arrays and multi-stage communication chains; (3) precision orbital rendezvous techniques demonstrating nove…

KARMA Approach supporting Development Process Reconstruction in Model-based Systems Engineering
Jiawei Li, Zan Liang, Guoxin Wang, Jinzhi Lu, Yan Yan, Shouxuan Wu, Hao Wang
https://arxiv.org/abs/2506.22037

KARMA Approach supporting Development Process Reconstruction in Model-based Systems Engineering
Model reconstruction is a method used to drive the development of complex system development processes in model-based systems engineering. Currently, during the iterative design process of a system, there is a lack of an effective method to manage changes in development requirements, such as development cycle requirements and cost requirements, and to realize the reconstruction of the system development process model. To address these issues, this paper proposes a model reconstruction method to…

Anthropic details how it built its multi-agent Claude Research system, claiming significant improvements in internal evaluations over single-agent systems (Anthropic)
https://www.anthropic.com/engineering/built-multi-agent-research-system

How we built our multi-agent research system
On the the engineering challenges and lessons learned from building Claude's Research system

Micelle Forming Linear-Dendritic Block Copolymers: A Theoretical Comparison between Random Hyperbranched and Precise Dendrimer Polymer Architectures
Marios Giannakou, Oleg V. Borisov, Friederike Schmid
https://arxiv.org/abs/2506.01765

Micelle Forming Linear-Dendritic Block Copolymers: A Theoretical Comparison between Random Hyperbranched and Precise Dendrimer Polymer Architectures
Hyperbranched block copolymers offer a simpler and more efficient synthesis route compared to more traditional dendritic systems, while still providing exceptional control over surface functionality and self-assembly. This makes them ideal candidates for engineering nanoparticles with tailored properties for applications such as drug delivery and sensing. Here we use self-consistent field calculations to compare the micelle structures formed by copolymers with a polydisperse hyperbranched (LHBC…

Insights into Ionic Diffusion in C-S-H Gel Pore from MD Simulations: Spatial Distributions, Energy Barriers, and Structural Descriptor
Weiqiang Chen, Kai Gong
https://arxiv.org/abs/2506.23089

Insights into Ionic Diffusion in C-S-H Gel Pore from MD Simulations: Spatial Distributions, Energy Barriers, and Structural Descriptor
Understanding transport behavior in nanoconfined environments is critical to many natural and engineering systems, including cementitious materials, yet its molecular-level mechanisms remain poorly understood. Here, molecular dynamics (MD) simulations were used to investigate Na+, Cl-, and water diffusion inside a 4 nm calcium-silicate-hydrate (C-S-H) pore channel over temperatures ranging from 300 K to 360 K. Spatially resolved analysis revealed strong suppression of diffusivity near the solid…

This https://arxiv.org/abs/2503.17274 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Composable Uncertainty in Symmetric Monoidal Categories for Design Problems
Applied category theory often studies symmetric monoidal categories (SMCs) whose morphisms represent open systems. These structures naturally accommodate complex wiring patterns, leveraging (co)monoidal structures for splitting and merging wires, or compact closed structures for feedback. A key example is the compact closed SMC of design problems (DP), which enables a compositional approach to co-design in engineering. However, in practice, the systems of interest may not be fully known. Recent…

Is spreadsheet syntax better than numeric indexing for cell selection?
Philip Heltweg, Dirk Riehle, Georg-Daniel Schwarz
https://arxiv.org/abs/2505.23296 h…

Is spreadsheet syntax better than numeric indexing for cell selection?
Selecting a subset of cells is a common task in data engineering, for example, to remove errors or select only specific parts of a table. Multiple approaches to express this selection exist. One option is numeric indexing, commonly found in general programming languages, where a tuple of numbers identifies the cell. Alternatively, the separate dimensions can be referred to using different enumeration schemes like "A1" for the first cell, commonly found in software such as spreadsheet systems. …

Comparative Analysis of the Code Generated by Popular Large Language Models (LLMs) for MISRA C Compliance
Malik Muhammad Umer
https://arxiv.org/abs/2506.23535

Comparative Analysis of the Code Generated by Popular Large Language Models (LLMs) for MISRA C++ Compliance
Safety-critical systems are engineered systems whose failure or malfunction could result in catastrophic consequences. The software development for safety-critical systems necessitates rigorous engineering practices and adherence to certification standards like DO-178C for avionics. DO-178C is a guidance document which requires compliance to well-defined software coding standards like MISRA C++ to enforce coding guidelines that prevent the use of ambiguous, unsafe, or undefined constructs. Larg…

Acoustic-Assisted Fabrication of Thin Shells with Spatially Distributed Imperfections
Ilyes Krida, Jacob Tang, Daniel Floryan, Tian Chen
https://arxiv.org/abs/2506.23828

Acoustic-Assisted Fabrication of Thin Shells with Spatially Distributed Imperfections
Thin-shell structures, found in biological systems such as beetle carapaces and widely used in aerospace, civil, and mechanical engineering, achieve remarkable strength-to-mass ratio given their slenderness and curved geometries. However, their load-bearing capacity is highly sensitive to geometric imperfections, which are often unavoidable during fabrication and can trigger subcritical buckling. Silicone-based hemispherical domes have served as an experimental modal system to study this phenom…

A State of the Art on Recent Progress and Emerging Challenges on Energy Transfer Between Vibrating Modes Under an External Mechanical Force With Time-Varying Frequency From 2020 to 2025
Jose Manoel Balthazar, Jorge Luis Palacios Felix, Mauricio A. Ribeiro, Angelo Marcelo Tusset, Jeferson Jose de Lima, Vinicius Piccirillo, Julijana Simonovic, Nikola D. Nevsic, Marcos Varanis, Clivaldo de Oliveira, Raphaela C. Machado, Gabriella O M Oliveira

A State of the Art on Recent Progress and Emerging Challenges on Energy Transfer Between Vibrating Modes Under an External Mechanical Force With Time-Varying Frequency From 2020 to 2025
In this paper, we discuss an example of current importance with a future perspective in engineering, in which excitation sources always have limited power, limited inertia, and their frequencies vary according to the instantaneous state of the vibrating system. Practical examples of non-ideal systems are considered. The most common phenomenon for this kind of system is discussed. The period considered is from 2020 to 2025. The specific properties of various models are also discussed. Directions…

Visualization enhances Problem Solving in Multi-Qubit Systems: An Eye-Tracking Study
Jonas Bley, Eva Rexigel, Alda Arias, Lars Krupp, Nikolas Longen, Paul Lukowicz, Stefan K\"uchemann, Jochen Kuhn, Maximilian Kiefer-Emmanouilidis, Artur Widera
https://arxiv.org/abs/2505.21508

Visualization enhances Problem Solving in Multi-Qubit Systems: An Eye-Tracking Study
Quantum Information Science (QIS) is a vast, diverse, and abstract field. In consequence, learners face many challenges. Science, Technology, Engineering, and Mathematics (STEM) education research has found that visualizations are valuable to aid learners in complex matters. The conditions under which visualizations pose benefits are largely unexplored in QIS education. In this eye-tracking study, we examine the conditions under which the visualization of multi-qubit systems in addition to the …

This https://arxiv.org/abs/2410.16295 has been replaced.
link: https://scholar.google.com/scholar?q=a

Universal Approximation of Mean-Field Models via Transformers
This paper investigates the use of transformers to approximate the mean-field dynamics of interacting particle systems exhibiting collective behavior. Such systems are fundamental in modeling phenomena across physics, biology, and engineering, including opinion formation, biological networks, and swarm robotics. The key characteristic of these systems is that the particles are indistinguishable, leading to permutation-equivariant dynamics. First, we empirically demonstrate that transformers are…

A parallel algorithm for the computation of the Jones polynomial
Kasturi Barkataki, Eleni Panagiotou
https://arxiv.org/abs/2505.23101 https://

A parallel algorithm for the computation of the Jones polynomial
Knots, links and entangled filaments appear in many physical systems of interest in biology and engineering. Classifying knots and measuring entanglement is of interest both for advancing knot theory, as well as for analyzing large data that become available through experiments or Artificial Intelligence. In this context, the efficient computation of topological invariants and other metrics of entanglement becomes an urgent issue. The computation of common measures of topological complexity, su…

This https://arxiv.org/abs/2505.09880 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Determining Absence of Unreasonable Risk: Approval Guidelines for an Automated Driving System Deployment
This paper provides an overview of how the determination of absence of unreasonable risk can be operationalized. It complements previous theoretical work published by existing developers of Automated Driving Systems (ADS) on the overall engineering practices and methodologies for readiness determination. Readiness determination is, at its core, a risk assessment process. It is aimed at evaluating the residual risk associated with a new deployment. The paper proposes methodological criteria to g…

Designer Heavy Fermions in Incommensurate $\bf{Nb_3Cl_8}$/Graphene van der Waals Heterostructures
Yuchen Gao, Wenjie Zhou, Fan Yang, Zhijie Ma, Hansheng Xu, Xinyue Huang, Kenji Watanabe, Takashi Taniguchi, Youguo Shi, Yu Ye
https://arxiv.org/abs/2506.21837

Designer Heavy Fermions in Incommensurate $\bf{Nb_3Cl_8}$/Graphene van der Waals Heterostructures
Heavy fermion systems, traditionally realized in rare-earth compounds with limited tunability, have hindered systematic exploration of correlated quantum phenomena. Here, we introduce a general strategy for engineering heavy fermions in incommensurate van der Waals heterostructures by coupling a Mott insulator (Nb$_3$Cl$_8$) with itinerant electrons (from monolayer graphene), circumventing strict lattice-matching requirements. Through magnetotransport and slave spin mean-field calculations, we …

Canonical Quantization of a Memristive Leaky Integrate-and-Fire Neuron Circuit
Dean Brand, Domenica Dibenedetto, Francesco Petruccione
https://arxiv.org/abs/2506.21363

Canonical Quantization of a Memristive Leaky Integrate-and-Fire Neuron Circuit
We present a theoretical framework for a quantized memristive Leaky Integrate-and-Fire (LIF) neuron, uniting principles from neuromorphic engineering and open quantum systems. Starting from a classical memristive LIF circuit, we apply canonical quantization techniques to derive a quantum model grounded in circuit quantum electrodynamics. Numerical simulations demonstrate key dynamical features of the quantized memristor and LIF neuron in the weak-coupling and adiabatic regime, including memory …

Disentangled representations of microscopy images
Jacopo Dapueto, Vito Paolo Pastore, Nicoletta Noceti, Francesca Odone
https://arxiv.org/abs/2506.20649 ht…

Disentangled representations of microscopy images
Microscopy image analysis is fundamental for different applications, from diagnosis to synthetic engineering and environmental monitoring. Modern acquisition systems have granted the possibility to acquire an escalating amount of images, requiring a consequent development of a large collection of deep learning-based automatic image analysis methods. Although deep neural networks have demonstrated great performance in this field, interpretability, an essential requirement for microscopy image an…

This https://arxiv.org/abs/2412.04352 has been replaced.
initial toot: https://mastoxiv.page/@a…

Emergent Weyl-like points in periodically modulated systems and Floquet engineering
We investigate a three-dimensional (3D) topological phase resembling a Weyl semimetal, modulated by a periodic potential and engineered through Floquet dynamics. This system is constructed by stacking two-dimensional Chern insulators and hosts Weyl-like points defined in the parameter space $(k_x, k_y, z)$, distinct from conventional Weyl points in momentum space $(k_x, k_y, k_z)$. The Weyl-semimetal-like phase exhibits characteristics akin to those of Weyl semimetals, including linear dispersi…

ALE-Bench: A Benchmark for Long-Horizon Objective-Driven Algorithm Engineering
Yuki Imajuku, Kohki Horie, Yoichi Iwata, Kensho Aoki, Naohiro Takahashi, Takuya Akiba
https://arxiv.org/abs/2506.09050

ALE-Bench: A Benchmark for Long-Horizon Objective-Driven Algorithm Engineering
How well do AI systems perform in algorithm engineering for hard optimization problems in domains such as package-delivery routing, crew scheduling, factory production planning, and power-grid balancing? We introduce ALE-Bench, a new benchmark for evaluating AI systems on score-based algorithmic programming contests. Drawing on real tasks from the AtCoder Heuristic Contests, ALE-Bench presents optimization problems that are computationally hard and admit no known exact solution. Unlike short-du…

Spin Polarization Control via Magnetic Field in Dissipative Bosonic Systems
Yaoyuan Fan, Shuoyu Shi, Lang Cao, Qiuxin Zhang, Dong Hu, Yu Wang, Xiaoji Zhou
https://arxiv.org/abs/2506.17962

Spin Polarization Control via Magnetic Field in Dissipative Bosonic Systems
Engineering spin polarization in dissipative bosonic systems is crucial for advancing quantum technologies, especially for applications in quantum metrology and space-based quantum simulations. This work demonstrates precise magnetic moment control in multicomponent Bose gases during evaporative cooling via tailored magnetic fields. By adjusting the magnetic field gradients, null point position, and duration, we selectively tune evaporation rates of magnetic sublevels, achieving targeted spin p…

Quantum-Accelerated Wireless Communications: Concepts, Connections, and Implications
Naoki Ishikawa, Giuseppe Thadeu Freitas de Abreu, Petar Popovski, Robert W. Heath Jr
https://arxiv.org/abs/2506.20863

Quantum-Accelerated Wireless Communications: Concepts, Connections, and Implications
Quantum computing is poised to redefine the algorithmic foundations of communication systems. While quantum superposition and entanglement enable quadratic or exponential speedups for specific problems, identifying use cases where these advantages yield engineering benefits is, however, still nontrivial. This article presents the fundamentals of quantum computing in a style familiar to the communications society, outlining the current limits of fault-tolerant quantum computing and uncovering a …

Design and performance of a Toroidal RF Volume Coil with Intrinsic Electromagnetic Interference Rejection for low-field Portable Halbach-Based MRI Systems
Jules Vliem (Electrical Engineering Department, Eindhoven University of Technology, Eindhoven, The Netherlands), Najac Chloe (C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands), Beatrice Lena (C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Le…

Design and performance of a Toroidal RF Volume Coil with Intrinsic Electromagnetic Interference Rejection for low-field Portable Halbach-Based MRI Systems
Purpose: One of the intrinsic limitations of low-field MRI is low signal-to-noise ratio (SNR), which can be further reduced by electromagnetic interference (EMI) due to the lack of a Faraday shielded room. To address this issue, we propose a novel RF coil design that is inherently less sensitive to EMI while maintaining high receive sensitivity. Methods: The proposed coil structure is based on an anapole (toroidal) design and consists of six rings, each containing four continuous wires wound ar…

ROS-related Robotic Systems Development with V-model-based Application of MeROS Metamodel
Tomasz Winiarski, Jan Kaniuka, Daniel Gie{\l}dowski, Jakub Ostrysz, Krystian Radlak, Dmytro Kushnir
https://arxiv.org/abs/2506.08706

ROS-related Robotic Systems Development with V-model-based Application of MeROS Metamodel
As robotic systems grow increasingly complex, heterogeneous, and safety-critical, the need for structured development methodologies becomes paramount. Although frameworks like the Robot Operating System (ROS) and Model-Based Systems Engineering (MBSE) offer foundational tools, they often lack integration when used together. This paper addresses that gap by aligning the widely recognized V-model development paradigm with the MeROS metamodel SysML-based modeling language tailored for ROS-based sy…

Robust space-time multiscale upscaling via multicontinuum homogenization for evolving perforated media
Wei Xie, Viet Ha Hoang, Yin Yang, Yunqing Huang
https://arxiv.org/abs/2506.21104

Robust space-time multiscale upscaling via multicontinuum homogenization for evolving perforated media
Time-evolving perforated domains arise in many engineering and geoscientific applications, including reactive transport, particle deposition, and structural degradation in porous media. Accurately capturing the macroscopic behavior of such systems poses significant computational challenges due to the dynamic fine-scale geometries. In this paper, we develop a robust and generalizable multiscale modeling framework based on multicontinuum homogenization to derive effective macroscopic equations in…

Snap-Through Thermomechanical Metamaterials for High-Performance Thermal Rectification
Qinyun Ding, Yuhao Wang, Guanqing Xiong, Wei Chen, Ying Chen, Zhaoguang Wang, Arup Neogi, Jaehyung Ju
https://arxiv.org/abs/2506.23489

Snap-Through Thermomechanical Metamaterials for High-Performance Thermal Rectification
Thermal diodes that enable directional heat transport are essential for advanced thermal management in microelectronics, energy systems, and thermal logic devices. However, existing designs based on phase-change materials, nanostructures, or interfacial engineering suffer from limited rectification performance, configurational inflexibility, and poor scalability. Here, we present a thermomechanical metamaterial-based thermal diode that combines temperature-responsive actuation with structural b…

Photonic Altermagnets: Magnetic Symmetries in Photonic Structures
Andrew Sungwook Kim, Youqiang Huang, Zhipei Sun, Q-Han Park, Hyunyong Choi
https://arxiv.org/abs/2506.23497

Photonic Altermagnets: Magnetic Symmetries in Photonic Structures
The unique physical properties of altermagnets, when transplanted to photonic systems, are anticipated to offer a new degree of freedom for engineering electromagnetic waves. Here, we show that a photonic analogue of altermagnetism can be mimicked in photonic crystals, where engineered photonic crystals can host spin space group symmetries. Our approach allows for the creation of spin-split bands and the corresponding transport properties provide an effective platform for circularly polarized l…

Engineering Resilience: An Energy-Based Approach to Sustainable Behavioural Interventions
Arpitha Srivathsa Malavalli, Karthik Sama, Janvi Chhabra, Pooja Bassin, Srinath Srinivasa
https://arxiv.org/abs/2506.16836

Engineering Resilience: An Energy-Based Approach to Sustainable Behavioural Interventions
Addressing complex societal challenges, such as improving public health, fostering honesty in workplaces, or encouraging eco-friendly behaviour requires effective nudges to influence human behaviour at scale. Intervention science seeks to design such nudges within complex societal systems. While interventions primarily aim to shift the system toward a desired state, less attention is given to the sustainability of that state, which we define in terms of resilience: the system's ability to retai…

Predicting Thermodynamics of Liquid Water from Time Series Analysis
Ma{\l}gorzata J. Zimo\'n, Fausto Martelli
https://arxiv.org/abs/2506.21821 https://…

Predicting Thermodynamics of Liquid Water from Time Series Analysis
Thermodynamics, introduced over two centuries ago, remains foundational to our understanding of physical, chemical, biological, and engineering systems. Its principles are traditionally grounded in the statistical mechanics framework, which explains macroscopic behavior from microscopic states. In this work, we propose an alternative approach that interprets thermodynamic behavior through the lenses of time series analysis, an approach commonly used in other fields, including finance, climate, …

Engineering RAG Systems for Real-World Applications: Design, Development, and Evaluation
Md Toufique Hasan, Muhammad Waseem, Kai-Kristian Kemell, Ayman Asad Khan, Mika Saari, Pekka Abrahamsson
https://arxiv.org/abs/2506.20869

Engineering RAG Systems for Real-World Applications: Design, Development, and Evaluation
Retrieval-Augmented Generation (RAG) systems are emerging as a key approach for grounding Large Language Models (LLMs) in external knowledge, addressing limitations in factual accuracy and contextual relevance. However, there is a lack of empirical studies that report on the development of RAG-based implementations grounded in real-world use cases, evaluated through general user involvement, and accompanied by systematic documentation of lessons learned. This paper presents five domain-specific…

Universal Reusability in Recommender Systems: The Case for Dataset- and Task-Independent Frameworks
Tri Kurniawan Wijaya, Xinyang Shao, Gonzalo Fiz Pontiveros, Edoardo D'Amico
https://arxiv.org/abs/2506.03391

Universal Reusability in Recommender Systems: The Case for Dataset- and Task-Independent Frameworks
Recommender systems are pivotal in delivering personalized experiences across industries, yet their adoption and scalability remain hindered by the need for extensive dataset- and task-specific configurations. Existing systems often require significant manual intervention, domain expertise, and engineering effort to adapt to new datasets or tasks, creating barriers to entry and limiting reusability. In contrast, recent advancements in large language models (LLMs) have demonstrated the transform…

STRATUS: A Multi-agent System for Autonomous Reliability Engineering of Modern Clouds
Yinfang Chen, Jiaqi Pan, Jackson Clark, Yiming Su, Noah Zheutlin, Bhavya Bhavya, Rohan Arora, Yu Deng, Saurabh Jha, Tianyin Xu
https://arxiv.org/abs/2506.02009

STRATUS: A Multi-agent System for Autonomous Reliability Engineering of Modern Clouds
In cloud-scale systems, failures are the norm. A distributed computing cluster exhibits hundreds of machine failures and thousands of disk failures; software bugs and misconfigurations are reported to be more frequent. The demand for autonomous, AI-driven reliability engineering continues to grow, as existing humanin-the-loop practices can hardly keep up with the scale of modern clouds. This paper presents STRATUS, an LLM-based multi-agent system for realizing autonomous Site Reliability Engine…

ModeliHub: A Web-based, Federated Analytics Platform for Modelica-centric, Model-based Systems Engineering
Mohamad Omar Nachawati
https://arxiv.org/abs/2506.18790

ModeliHub: A Web-based, Federated Analytics Platform for Modelica-centric, Model-based Systems Engineering
This paper introduces ModeliHub, a Web-based, federated analytics platform designed specifically for model-based systems engineering with Modelica. ModeliHub's key innovation lies in its Modelica-centric, hub-and-spoke federation architecture that provides systems engineers with a Modelica-based, unified system model of repositories containing heterogeneous engineering artifacts. From this unified system model, ModeliHub's Virtual Twin engine provides a real-time, interactive simulation environ…

Modelling of Counter-Current Gas-Liquid Annular Flow in a Vertical Annulus
Mahshid Firouzi
https://arxiv.org/abs/2506.10270 https://a…

Modelling of Counter-Current Gas-Liquid Annular Flow in a Vertical Annulus
Annular two-phase flow involving upward-moving gas and downward-flowing liquid within a vertical annular geometry is a common configuration in various engineering systems. In such systems, accurately predicting the pressure gradient is essential for understanding flow stability, equipment performance, and system design under counter-current conditions. This paper presents a general mechanistic model to predict the pressure gradient in counter-current annular flow within a vertical annular space…

Replaced article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- Energy-consistent integration of mechanical systems based on Livens principle
Philipp L. Kinon, Peter Betsch

Ordering Results between Two Extreme Order Statistics with Heterogeneous Linear Failure Rate Distributed Components
CM Revathi, Rajesh Moharana, Raju Bhakta
https://arxiv.org/abs/2506.05773

Ordering Results between Two Extreme Order Statistics with Heterogeneous Linear Failure Rate Distributed Components
Stochastic comparisons of series and parallel systems are important in many areas of engineering, operations research and reliability analysis. These comparisons allow for the evaluation of the performance and reliability of systems under different conditions, and can inform decisions related to system design, probabilities of failure, maintenance and operation. In this paper, we investigate the stochastic comparisons of the series and parallel systems under the assumption that the component li…

JAX-LaB: A High-Performance, Differentiable, Lattice Boltzmann Library for Modeling Multiphase Fluid Dynamics in Geosciences and Engineering
Piyush Pradhan, Pierre Gentine, Shaina Kelly
https://arxiv.org/abs/2506.17713

JAX-LaB: A High-Performance, Differentiable, Lattice Boltzmann Library for Modeling Multiphase Fluid Dynamics in Geosciences and Engineering
We present JAX-LaB, a differentiable, Python-based Lattice Boltzmann library for simulating multiphase and multiphysics flows in hydrologic, geologic, and engineered porous media. Built as an extension of the XLB library, JAX-LaB utilizes JAX for computations and offers a performant, hardware-agnostic implementation that integrates seamlessly with machine learning workflows and scales efficiently across CPUs, GPUs, and distributed systems. Multiphase interactions are modeled using the Shan-Chen…

Error-resilient Reversal of Quantum Chaotic Dynamics Enabled by Scramblons
Yu-Chen Li, Tian-Gang Zhou, Shengyu Zhang, Ze Wu, Liqiang Zhao, Haochuan Yin, Xiaoxue An, Hui Zhai, Pengfei Zhang, Xinhua Peng
https://arxiv.org/abs/2506.19915

Error-resilient Reversal of Quantum Chaotic Dynamics Enabled by Scramblons
The emergence of the arrow of time in quantum many-body systems stems from the inherent tendency of Hamiltonian evolution to scramble quantum information and increase entanglement. While, in principle, one might counteract this temporal directionality by engineering a perfectly inverted Hamiltonian to reverse entanglement growth, such a scenario is fundamentally unstable because even minor imperfections in the backward evolution can be exponentially amplified, a hallmark of quantum many-body ch…

Hopf-Induced Desynchronization
Seungjae Lee, Lennart J. Kuklinski, Moritz Th\"umler, Marc Timme
https://arxiv.org/abs/2506.16845 https://

Hopf-Induced Desynchronization
The emergence of synchrony essentially underlies the functionality of many systems across physics, biology and engineering. In all established synchronization phase transitions so far, a stable synchronous state is connected to a stable incoherent state: For continuous transitions, stable synchrony directly connects to stable incoherence at a critical point, whereas for discontinuous transitions, stable synchrony is connected to stable incoherence via an additional unstable branch. Here we pres…

Probing Phonon Modes in Reconstructed twisted Homo and Hetero Bilayer System
Sushil Kumar Sahu, Robin Bajaj, Syed Ummair Ali, Ajay Bhut, Roshan Jesus Mathew, Shinjan Mandal, Kenji Watanabe, Takashi Taniguchi, Manish Jain, Chandan Kumar
https://arxiv.org/abs/2506.19669

Probing Phonon Modes in Reconstructed twisted Homo and Hetero Bilayer System
Twist angle engineering in van der Waals homo and hetero-bilayers introduces profound modifications in their electronic, optical and mechanical properties due to lattice reconstruction. In these systems, the interlayer coupling and atomic rearrangement strongly depend on the twist angle, leading to the formation of periodic Moire superlattices. At small twist angles, significant lattice relaxation results in the emergence of domain structures separated by one dimensional soliton networks, influ…

This https://arxiv.org/abs/2505.18377 has been replaced.
initial toot: https://mastoxiv.page/@ar…

SP2RINT: Spatially-Decoupled Physics-Inspired Progressive Inverse Optimization for Scalable, PDE-Constrained Meta-Optical Neural Network Training
DONNs harness the physics of light propagation for efficient analog computation, with applications in AI and signal processing. Advances in nanophotonic fabrication and metasurface-based wavefront engineering have opened new pathways to realize high-capacity DONNs across various spectral regimes. Training such DONN systems to determine the metasurface structures remains challenging. Heuristic methods are fast but oversimplify metasurfaces modulation, often resulting in physically unrealizable d…

Quantum Optimization for Software Engineering: A Survey
Man Zhang, Yuechen Li, Tao Yue, Kai-Yuan Cai
https://arxiv.org/abs/2506.16878 https://

Quantum Optimization for Software Engineering: A Survey
Quantum computing, particularly in the area of quantum optimization, is steadily progressing toward practical applications, supported by an expanding range of hardware platforms and simulators. While Software Engineering (SE) optimization has a strong foundation, which is exemplified by the active Search-Based Software Engineering (SBSE) community and numerous classical optimization methods, the growing complexity of modern software systems and their engineering processes demands innovative sol…

Multivariate Long-term Profile Monitoring with Application to the KW51 Railway Bridge
Philipp Wittenberg, Alexander Mendler, Sven Knoth, Jan Gertheiss
https://arxiv.org/abs/2506.20295

Multivariate Long-term Profile Monitoring with Application to the KW51 Railway Bridge
Structural Health Monitoring (SHM) plays a pivotal role in modern civil engineering, providing critical insights into the health and integrity of infrastructure systems. This work presents a novel multivariate long-term profile monitoring approach to eliminate fluctuations in the measured response quantities, e.g., caused by environmental influences or measurement error. Our methodology addresses critical challenges in SHM and combines supervised methods with unsupervised, principal component a…

Low-EFFourth: A computational framework for generating and studying multilevel model ensembles in low-dimensional systems
Francisco de Melo Vir\'issimo
https://arxiv.org/abs/2506.03313

Low-EFFourth: A computational framework for generating and studying multilevel model ensembles in low-dimensional systems
This paper introduces Low-EFFourth (LEF4), a MATLAB-based computational framework designed for generating and studying multilevel model ensembles in continuous dynamical systems. Initially developed to address questions in climate modelling, LEF4 can also be used in other disciplines such as epidemiology, economics, and engineering, with minimal modifications to the code. The framework provides an efficient and flexible approach for investigating uncertainties arising from initial conditions, m…

A MARL-based Approach for Easing MAS Organization Engineering
Julien Soul\'e, Jean-Paul Jamont, Michel Occello, Louis-Marie Traonouez, Paul Th\'eron
https://arxiv.org/abs/2506.05437

A MARL-based Approach for Easing MAS Organization Engineering
Multi-Agent Systems (MAS) have been successfully applied in industry for their ability to address complex, distributed problems, especially in IoT-based systems. Their efficiency in achieving given objectives and meeting design requirements is strongly dependent on the MAS organization during the engineering process of an application-specific MAS. To design a MAS that can achieve given goals, available methods rely on the designer's knowledge of the deployment environment. However, high complex…

Human-in-the-loop: Real-time Preference Optimization
Wenbin Wang, Wenjie Xu, Colin N. Jones
https://arxiv.org/abs/2506.02225 https://…

Human-in-the-loop: Real-time Preference Optimization
Human-aware controllers play an important role in engineering systems for improving productivity, efficiency, and sustainability. It is essential to design such a controller that optimizes user utility while adhering to plant dynamics. While most online optimization algorithms rely on first-order or zeroth-order oracles, human feedback often appears as pairwise comparisons. In this work, we propose an online feedback optimization algorithm that leverages such preference feedback. We design a co…

Does the Forced Van der Pol Oscillator Exhibit Irregular Behavior?
Samaira Tibrewal, Soumyajit Seth
https://arxiv.org/abs/2505.22385 https://

Does the Forced Van der Pol Oscillator Exhibit Irregular Behavior?
Nonlinear oscillators are commonly encountered in a wide range of physical and engineering systems, exhibiting rich and complex dynamics. Among these, the Van der Pol oscillator is well known for its self-sustained limit cycle behavior. However, when subjected to external sinusoidal forcing, its dynamics can deviate significantly from this regular behavior. This study explores the emergence of complex dynamical regimes in the sinusoidally forced Van der Pol oscillator, focusing on identifying t…

Nonlinear Model Order Reduction of Dynamical Systems in Process Engineering: Review and Comparison
Jan C. Schulze, Alexander Mitsos
https://arxiv.org/abs/2506.12819

Nonlinear Model Order Reduction of Dynamical Systems in Process Engineering: Review and Comparison
Computationally cheap yet accurate enough dynamical models are vital for real-time capable nonlinear optimization and model-based control. When given a computationally expensive high-order prediction model, a reduction to a lower-order simplified model can enable such real-time applications. Herein, we review state-of-the-art nonlinear model order reduction methods and provide a theoretical comparison of method properties. Additionally, we discuss both general-purpose methods and tailored appro…

A cavity array microscope for parallel single-atom interfacing
Adam L. Shaw, Anna Soper, Danial Shadmany, Aishwarya Kumar, Lukas Palm, Da-Yeon Koh, Vassilios Kaxiras, Lavanya Taneja, Matt Jaffe, David I. Schuster, Jonathan Simon
https://arxiv.org/abs/2506.10919

A cavity array microscope for parallel single-atom interfacing
Neutral atom arrays and optical cavity QED systems have developed in parallel as central pillars of modern experimental quantum science. While each platform has demonstrated exceptional capabilities-such as high-fidelity quantum logic in atom arrays, and strong light-matter coupling in cavities-their combination holds promise for realizing fast and non-destructive atom measurement, building large-scale quantum networks, and engineering hybrid atom-photon Hamiltonians. However, to date, experime…

This https://arxiv.org/abs/2403.16634 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csMS_…

Symbolic and User-friendly Geometric Algebra Routines (SUGAR) for Computations in Matlab
Geometric algebra (GA) is a mathematical tool for geometric computing, providing a framework that allows a unified and compact approach to geometric relations which in other mathematical systems are typically described using different more complicated elements. This fact has led to an increasing adoption of GA in applied mathematics and engineering problems. However, the scarcity of symbolic implementations of GA and its inherent complexity, requiring a specific mathematical background, make it…

Educators' Perceptions of Large Language Models as Tutors: Comparing Human and AI Tutors in a Blind Text-only Setting
Sankalan Pal Chowdhury, Terry Jingchen Zhang, Donya Rooein, Dirk Hovy, Tanja K\"aser, Mrinmaya Sachan
https://arxiv.org/abs/2506.08702

Educators' Perceptions of Large Language Models as Tutors: Comparing Human and AI Tutors in a Blind Text-only Setting
The rapid development of Large Language Models (LLMs) opens up the possibility of using them as personal tutors. This has led to the development of several intelligent tutoring systems and learning assistants that use LLMs as back-ends with various degrees of engineering. In this study, we seek to compare human tutors with LLM tutors in terms of engagement, empathy, scaffolding, and conciseness. We ask human tutors to annotate and compare the performance of an LLM tutor with that of a human tut…

A Reference Model and Patterns for Production Event Data Enrichment
Mark van der Pas, Remco Dijkman, Alp Ak\c{c}ay, Ivo Adan, John Walker
https://arxiv.org/abs/2506.11502

A Reference Model and Patterns for Production Event Data Enrichment
With the advent of digital transformation, organisations are increasingly generating large volumes of data through the execution of various processes across disparate systems. By integrating data from these heterogeneous sources, it becomes possible to derive new insights essential for tasks such as monitoring and analysing process performance. Typically, this information is extracted during a data pre-processing or engineering phase. However, this step is often performed in an ad-hoc manner an…

Deep Learning-Based Prediction of High Explosive Induced Fluid Dynamics
Francis G. VanGessel, Mitul Pandya
https://arxiv.org/abs/2506.14710 https://…

Deep Learning-Based Prediction of High Explosive Induced Fluid Dynamics
Underwater explosions produce complex fluid phenomena relevant to diverse applications including maritime engineering, medical therapeutics, and inertial confinement fusion. These systems exhibit multiphase flows, chemical kinetics, and highly compressible dynamics that challenge traditional computational approaches. Current hydrodynamic solvers, while accurate, are computationally expensive and non-differentiable, limiting their use in design optimization and real-time applications. Here we sh…

Bridging the Silos of Digitalization and Sustainability by Twin Transition: A Multivocal Literature Review
Baran Shajari, Istvan David
https://arxiv.org/abs/2506.04267

Bridging the Silos of Digitalization and Sustainability by Twin Transition: A Multivocal Literature Review
Twin transition is the method of parallel digital and sustainability transitions in a mutually supporting way or, in common terms, "greening of and by IT and data." Twin transition reacts to the growing problem of unsustainable digitalization, particularly in the ecological sense. Ignoring this problem will eventually limit the digital adeptness of society and the problem-solving capacity of humankind. Information systems engineering must find ways to support twin transition journeys through it…

Construction of Kondo Chains by Engineering Porphyrin {\pi}-Radicals on Au(111)
Yan Zhao, Kaiyue Jiang, Peng-Yi Liu, Ruoning Li, Jie Li, Xin Li, Xinchen Fang, Anjing Zhao, Yutong Zhu, Hongxiang Xu, Ting Chen, Dong Wang, Xiaodong Zhuang, Shimin Hou, Kai Wu, Song Gao, Qing-Feng Sun, Yajie Zhang, Yongfeng Wang
https://arxiv.org/abs…

Construction of Kondo Chains by Engineering Porphyrin π-Radicals on Au(111)
Quantum manipulation of molecular radical spins provides a crucial platform for exploring emergent phenomena in many-body systems. Here, we combine surface-confined synthesis with scanning tunneling microscopy (STM) tip-induced dehydrogenation to achieve atom-precise engineering of quasi-one-dimensional porphyrin-based Kondo chains (1-7 units) on Au(111). Key design innovations leverage large-sized porphyrins to suppress intrachain antiferromagnetic coupling, while ${Zn}^{2+}$ chelation at porp…

Minimizing Structural Vibrations via Guided Flow Matching Design Optimization
Jan van Delden, Julius Schultz, Sebastian Rothe, Christian Libner, Sabine C. Langer, Timo L\"uddecke
https://arxiv.org/abs/2506.15263

Minimizing Structural Vibrations via Guided Flow Matching Design Optimization
Structural vibrations are a source of unwanted noise in engineering systems like cars, trains or airplanes. Minimizing these vibrations is crucial for improving passenger comfort. This work presents a novel design optimization approach based on guided flow matching for reducing vibrations by placing beadings (indentations) in plate-like structures. Our method integrates a generative flow matching model and a surrogate model trained to predict structural vibrations. During the generation process…

Learning event-triggered controllers for linear parameter-varying systems from data
Renjie Ma, Su Zhang, Wenjie Liu, Zhijian Hu, Peng Shi
https://arxiv.org/abs/2506.08366

Learning event-triggered controllers for linear parameter-varying systems from data
Nonlinear dynamical behaviours in engineering applications can be approximated by linear-parameter varying (LPV) representations, but obtaining precise model knowledge to develop a control algorithm is difficult in practice. In this paper, we develop the data-driven control strategies for event-triggered LPV systems with stability verifications. First, we provide the theoretical analysis of $θ$-persistence of excitation for LPV systems, which leads to the feasible data-based representations. T…

Forecasting the spatiotemporal evolution of fluid-induced microearthquakes with deep learning
Jaehong Chung, Michael Manga, Timothy Kneafsey, Tapan Mukerji, Mengsu Hu
https://arxiv.org/abs/2506.14923

Forecasting the spatiotemporal evolution of fluid-induced microearthquakes with deep learning
Microearthquakes (MEQs) generated by subsurface fluid injection record the evolving stress state and permeability of reservoirs. Forecasting their full spatiotemporal evolution is therefore critical for applications such as enhanced geothermal systems (EGS), CO$_2$ sequestration and other geo-engineering applications. We present a transformer-based deep learning model that ingests hydraulic stimulation history and prior MEQ observations to forecast four key quantities: cumulative MEQ count, cum…

A nonlocal-to-local approach to aggregation-diffusion equations
Carles Falc\'o, Ruth E. Baker, Jos\'e A. Carrillo
https://arxiv.org/abs/2505.08443 …

A nonlocal-to-local approach to aggregation-diffusion equations
Over the past decades, nonlocal models have been widely used to describe aggregation phenomena in biology, physics, engineering, and the social sciences. These are often derived as mean-field limits of attraction-repulsion agent-based models, and consist of systems of nonlocal partial differential equations. Using differential adhesion between cells as a biological case study, we introduce a novel local model of aggregation-diffusion phenomena. This system of local aggregation-diffusion equatio…

Microservices and Real-Time Processing in Retail IT: A Review of Open-Source Toolchains and Deployment Strategies
Aaditaa Vashisht (Department of Information Science,Engineering, RV College of Engineering, India), Rekha B S (Department of Information Science,Engineering, RV College of Engineering, India)
https://arxiv.org/abs/25…

Microservices and Real-Time Processing in Retail IT: A Review of Open-Source Toolchains and Deployment Strategies
With the rapid pace of digital transformation, the retail industry is increasingly depending on real-time, scalable, and resilient systems to manage financial transactions, analyze customer behavior, and streamline order processing. This literature review explores how modern event-driven and microservices-based architectures, particularly those leveraging Apache Kafka, Spring Boot, MongoDB, and Kubernetes are transforming retail and financial systems. By systematically reviewing academic public…

Large Language Models for Design Structure Matrix Optimization
Shuo Jiang, Min Xie, Jianxi Luo
https://arxiv.org/abs/2506.09749 https://

Large Language Models for Design Structure Matrix Optimization
In complex engineering systems, the interdependencies among components or development activities are often modeled and analyzed using Design Structure Matrix (DSM). Reorganizing elements within a DSM to minimize feedback loops and enhance modularity or process efficiency constitutes a challenging combinatorial optimization (CO) problem in engineering design and operations. As problem sizes increase and dependency networks become more intricate, traditional optimization methods that solely use m…

Probability of Collision with Tethered Spacecraft
Yema Paul, Emmanuel Delande, Francois Vinet, Francois Laporte, Manuel Sanjurjo-Rivo, Aldo Tonnini, Joan-Pau Sanchez
https://arxiv.org/abs/2506.04969

Probability of Collision with Tethered Spacecraft
This Engineering Note addresses the challenge of estimating the probability of collision for tethered spacecraft during close encounters with other space objects. Standard probability of collision methods, based on spherical hard-body assumptions, tend to be overly conservative when applied to long tether systems. We introduce a method that accounts for the tether's spatial extent and configuration uncertainty by maximizing the probability of collision over all physically admissible tether shap…

Is Your Automated Software Engineer Trustworthy?
Noble Saji Mathews, Meiyappan Nagappan
https://arxiv.org/abs/2506.17812 https://arxi…

Is Your Automated Software Engineer Trustworthy?
Large Language Models (LLMs) are being increasingly used in software engineering tasks, with an increased focus on bug report resolution over the past year. However, most proposed systems fail to properly handle uncertain or incorrect inputs and outputs. Existing LLM-based tools and coding agents respond to every issue and generate a patch for every case, even when the input is vague or their own output is incorrect. There are no mechanisms in place to abstain when confidence is low. This leads…

Active Digital Twins via Active Inference
Matteo Torzoni, Domenico Maisto, Andrea Manzoni, Francesco Donnarumma, Giovanni Pezzulo, Alberto Corigliano
https://arxiv.org/abs/2506.14453

Active Digital Twins via Active Inference
Digital twins are transforming engineering and applied sciences by enabling real-time monitoring, simulation, and predictive analysis of physical systems and processes. However, conventional digital twins rely primarily on passive data assimilation, which limits their adaptability in uncertain and dynamic environments. This paper introduces the active digital twin paradigm, based on active inference. Active inference is a neuroscience-inspired, Bayesian framework for probabilistic reasoning and…

This https://arxiv.org/abs/2502.06753 has been replaced.
link: https://scholar.google.com/scholar?q=a

SMRS: advocating a unified reporting standard for surrogate models in the artificial intelligence era
Surrogate models are widely used to approximate complex systems across science and engineering to reduce computational costs. Despite their widespread adoption, the field lacks standardisation across key stages of the modelling pipeline, including data sampling, model selection, evaluation, and downstream analysis. This fragmentation limits reproducibility and cross-domain utility -- a challenge further exacerbated by the rapid proliferation of AI-driven surrogate models. We argue for the urgen…

Stochastic elastohydrodynamics of adhesion and phase separation during cell-cell contact across a viscous channel
Vira Dhaliwal, Jingbang Liu, Andreas Carlson
https://arxiv.org/abs/2506.05906

Stochastic elastohydrodynamics of adhesion and phase separation during cell-cell contact across a viscous channel
Contact between fluctuating, fluid-lubricated soft surfaces is prevalent in engineering and biological systems, a process starting with adhesive contact, which can give rise to complex coarsening dynamics. One representation of such a system, which is relevant to biological membrane adhesion, is a fluctuating elastic interface covered by adhesive molecules that bind and unbind to a solid substrate across a narrow gap filled with a viscous fluid. This flow is described by the stochastic elastohy…

SemAgent: A Semantics Aware Program Repair Agent
Anvith Pabba, Alex Mathai, Anindya Chakraborty, Baishakhi Ray
https://arxiv.org/abs/2506.16650 https://

SemAgent: A Semantics Aware Program Repair Agent
Large Language Models (LLMs) have shown impressive capabilities in downstream software engineering tasks such as Automated Program Repair (APR). In particular, there has been a lot of research on repository-level issue-resolution benchmarks such as SWE-Bench. Although there has been significant progress on this topic, we notice that in the process of solving such issues, existing agentic systems tend to hyper-localize on immediately suspicious lines of code and fix them in isolation, without a …

Electrically reconfigurable extended lasing state in an organic liquid-crystal microcavity
Dmitriy Dovzhenko (School of Physics and Astronomy, University of Southampton, Southampton, United Kingdom), Luciano Siliano Ricco (Science Institute, University of Iceland, Reykjavik, Iceland), Krzysztof Sawicki (School of Physics and Astronomy, University of Southampton, Southampton, United Kingdom), Marcin Muszy\'nski (Institute of Experimental Physics, Faculty of Physics, University of Wa…

Electrically reconfigurable extended lasing state in an organic liquid-crystal microcavity
Small-footprint, low-power arrays of coupled coherent emitters with the capability of near- and far-field engineering and coherence control are highly sought after to meet modern nanophotonics evolving needs. Between existing solutions based on vertical-cavity surface-emitting lasers, phase masks in bulk traditional cavity-based systems, and lattices of exciton-polariton condensates, only the strongly light-matter coupled systems were shown to be capable of controlled on-chip interaction betwee…

This https://arxiv.org/abs/2505.02450 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCE_…

Predicting the Dynamics of Complex System via Multiscale Diffusion Autoencoder
Predicting the dynamics of complex systems is crucial for various scientific and engineering applications. The accuracy of predictions depends on the model's ability to capture the intrinsic dynamics. While existing methods capture key dynamics by encoding a low-dimensional latent space, they overlook the inherent multiscale structure of complex systems, making it difficult to accurately predict complex spatiotemporal evolution. Therefore, we propose a Multiscale Diffusion Prediction Network (M…

EPC Framework for BESS Projects
Zeenat Hameed, Chresten Tr{\ae}holt
https://arxiv.org/abs/2506.13281 https://arxiv.org/pdf/2506.13281…

EPC Framework for BESS Projects
Battery Energy Storage Systems (BESS) are critical for modern power networks, supporting grid services such as frequency regulation, peak shaving, and black start. Delivering a BESS under an Engineering, Procurement, and Construction (EPC) model requires a concise methodology that balances regulatory compliance, technical details, and schedule efficiency. This paper presents a streamlined, five step EPC framework covering feasibility assessment, permitting, procurement, construction, and commis…

An Empirical study on LLM-based Log Retrieval for Software Engineering Metadata Management
Simin Sun, Yuchuan Jin, Miroslaw Staron
https://arxiv.org/abs/2506.11659

An Empirical study on LLM-based Log Retrieval for Software Engineering Metadata Management
Developing autonomous driving systems (ADSs) involves generating and storing extensive log data from test drives, which is essential for verification, research, and simulation. However, these high-frequency logs, recorded over varying durations, pose challenges for developers attempting to locate specific driving scenarios. This difficulty arises due to the wide range of signals representing various vehicle components and driving conditions, as well as unfamiliarity of some developers' with the…

Non-invasive measurement of local stress inside soft materials with programmed shear waves
Zhaoyi Zhang, Guo-Yang Li, Yuxuan Jiang, Yang Zheng, Artur L. Gower, Michel Destrade, Yanping Cao
https://arxiv.org/abs/2506.03816

Non-invasive measurement of local stress inside soft materials with programmed shear waves
Mechanical stresses in soft materials across different length scales play a fundamental role in understanding the function of biological systems and in the use of artificial materials for engineering soft machines and biomedical devices. Yet it remains a great challenge to probe local mechanical stresses in situ in a non-invasive, non-destructive manner, in particular when the mechanical properties are unknown. To address this challenge, we propose an acoustoelastic imaging-based method to infe…

Visible Brillouin-quadratic microlaser in a high-Q thin-film lithium niobate microdisk
Xiaochao Luo, Chuntao Li, Xingzhao Huang, Jintian Lin, Renhong Gao, Yifei Yao, Yingnuo Qiu, Yixuan Yang, Lei Wang, Huakang Yu, Ya Cheng
https://arxiv.org/abs/2506.08615

Visible Brillouin-quadratic microlaser in a high-Q thin-film lithium niobate microdisk
Narrow-linewidth lasers at short/visible wavelengths are crucial for quantum and atomic applications, such as atomic clocks, quantum computing, atomic and molecular spectroscopy, and quantum sensing. However, such lasers are often only accessible in bulky tabletop systems and remain scarce in integrated photonic platform. Here, we report an on-chip visible Brillouin-quadratic microlaser in a 117-um-diameter thin-film lithium niobate (TFLN) microdisk via dispersion engineering. Enabled by the ul…

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey
Ina K. Schieferdecker
https://arxiv.org/abs/2506.14640

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey
In industry, software testing is the primary method to verify and validate the functionality, performance, security, usability, and so on, of software-based systems. Test automation has gained increasing attention in industry over the last decade, following decades of intense research into test automation and model-based testing. However, designing, developing, maintaining and evolving test automation is a considerable effort. Meanwhile, AI's breakthroughs in many engineering fields are opening…

Towards Bridging Formal Methods and Human Interpretability
Abhijit Paul, Proma Chowdhury, Kazi Sakib
https://arxiv.org/abs/2506.09759 https://

Towards Bridging Formal Methods and Human Interpretability
Labeled Transition Systems (LTS) are integral to model checking and design repair tools. System engineers frequently examine LTS designs during model checking or design repair to debug, identify inconsistencies, and validate system behavior. Despite LTS's significance, no prior research has examined human comprehension of these designs. To address this, we draw on traditional software engineering and graph theory, identifying 7 key metrics: cyclomatic complexity, state space size, average branc…

Towards a Knowledge Base of Common Sustainability Weaknesses in Green Software Development
Priyavanshi Pathania, Rohit Mehra, Vibhu Saujanya Sharma, Vikrant Kaulgud, Sanjay Podder, Adam P. Burden
https://arxiv.org/abs/2506.08812

Towards a Knowledge Base of Common Sustainability Weaknesses in Green Software Development
With the climate crisis looming, engineering sustainable software systems become crucial to optimize resource utilization, minimize environmental impact, and foster a greener, more resilient digital ecosystem. For developers, getting access to automated tools that analyze code and suggest sustainabilityrelated optimizations becomes extremely important from a learning and implementation perspective. However, there is currently a dearth of such tools due to the lack of standardized knowledge, whi…