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The hydrodynamics of droplets is significant in wide-ranging applications involving immiscible fluids and emulsions in food and pharmaceutical. The control and manipulation of droplets are primarily a function of flow governing and…

Fluid Dynamics · Physics 2022-01-19 Akepogu Venkateshwarlu , Ram Prakash Bharti

Diffusive molecular communications (DiMC) have recently gained attention as a candidate for nano- to micro- and macro-scale communications due to its simplicity and energy efficiency. As signal propagation is solely enabled by Brownian…

Information Theory · Computer Science 2021-01-11 Mustafa Can Gursoy , Masoumeh Nasiri-Kenari , Urbashi Mitra

Modular architectures are a promising route toward scalable superconducting quantum processors, but finite fabrication yield and the lack of high quality temporary interconnects impose fundamental limitations on system size. Here, we…

We demonstrate conditional entanglement swapping, i.e. teleportation of entanglement, between time-bin qubits at the telecommunication wavelength of 1536.4 nm with high fidelity of 87\%. Our system is deployable, utilizing modular,…

Here, we trap and control the position of droplets to study their dynamics using hydrodynamic forces alone without an external field. The hydrodynamic trap is adapted from a previously implemented Stokes trap by incorporating a…

Fluid Dynamics · Physics 2020-11-13 Shweta Narayan , Davis B. Moravec , Andrew J. Dallas , Cari S. Dutcher

We present a tunable, non-equilibrium oil-in-oil emulsion that serves as a model system for investigating the transition from controlled droplet deformation to multiscale flows reminiscent of turbulence. By utilizing a miscible mixture of…

Soft Condensed Matter · Physics 2026-04-22 Majid Bahraminasr , Anand Yethiraj

Molecular communication (MC) enables information transfer using particles inspired by biological systems. Volatile Organic Compounds (VOCs) are one of the most abundant and diverse classes of signaling molecules used by living or non-living…

Signal Processing · Electrical Eng. & Systems 2026-04-10 Bitop Maitra , Ozgur B. Akan

Computational fluid dynamics (CFD) provides high-fidelity simulations of fluid flows but remains computationally expensive for many-query applications. In recent years deep learning (DL) has been used to construct data-driven fluid-dynamic…

Machine Learning · Computer Science 2026-04-13 David Ramos , Lucas Lacasa , Fermín Gutiérrez , Eusebio Valero , Gonzalo Rubio

This paper considers the problem of reliable communication over discrete-time channels whose impulse responses have length $L$ and exactly $S\leq L$ non-zero coefficients, and whose support and coefficients remain fixed over blocks of $N>L$…

Information Theory · Computer Science 2011-06-29 Arun Pachai Kannu , Philip Schniter

Deploying pretrained visual models in real-world environments often suffers from significant performance degradation due to the diversity of testing scenarios. Continuous adaptation of learning models on edge devices via unlabeled data…

Neural and Evolutionary Computing · Computer Science 2026-05-08 Jianming Lv , Chengjun Wang , Depin Liang , Qianli Ma , Wei Chen , Xueqi Cheng

Today, pipeline networks serve as critical infrastructure for transporting materials such as water, gas, and oil. Modern technologies such as the Internet of Things (IoT), sensor nodes, and inspection robots enable efficient pipeline…

Signal Processing · Electrical Eng. & Systems 2025-10-30 Muneer M. Al-Zubi , Mohamed-Slim Alouini

In this paper, we consider a multi-hop molecular communication network consisting of one nanotransmitter, one nanoreceiver, and multiple nanotransceivers acting as relays. We consider three different relaying schemes to improve the range of…

Information Theory · Computer Science 2016-11-17 Arman Ahmadzadeh , Adam Noel , Robert Schober

Flow matching has recently emerged as a principled framework for learning continuous-time transport maps, enabling efficient ODE-based sampling without relying on stochastic diffusion processes. While generative modeling has shown promise…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Zhi Chen , Runze Hu , Le Zhang

Solvent shifting is a process in which a non-solvent is added to a solvent/solute mixture and extracts the solvent. The solvent and the non-solvent are miscible. Because of solution supersaturation a portion of the solute transforms to…

Fluid Dynamics · Physics 2014-09-30 Ramin Hajian , Steffen Hardt

Test-time adaptation enables models to adapt to evolving domains. However, balancing the tradeoff between preserving knowledge and adapting to domain shifts remains challenging for model adaptation methods, since adapting to domain shifts…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Gabriel Tjio , Jie Zhang , Xulei Yang , Yun Xing , Nhat Chung , Xiaofeng Cao , Ivor W. Tsang , Chee Keong Kwoh , Qing Guo

Cells control fluid flows with a spatial and temporal precision that far exceeds the capabilities of current microfluidic technologies. Cells achieve this superior spatio-temporal control by harnessing dynamic networks of cytoskeleton and…

Soft Condensed Matter · Physics 2025-05-26 Fan Yang , Shichen Liu , Heun Jin Lee , Rob Phillips , Matt Thomson

We present an experimental investigation of the agglomeration of microbubbles into a 2D microfoam and its flow in a rectangular microchannel. Using a flow-focusing method, we produce the foam in situ on a microfluidic chip for a large range…

Fluid Dynamics · Physics 2009-11-11 Jan-Paul Raven , Philippe Marmottant , François Graner

Interfacial fluctuations in a two-phase binary fluid mixture reveal signatures of underlying physical processes that occur within each phase and on a range of spatial and temporal scales. In this study, we investigate a model binary fluid…

Fluid Dynamics · Physics 2026-03-04 Samuel Z Khiangte , Triparna Sanyal , Sumantra Sarkar , Nairita Pal

M-ary On-Off Frequency-Shift-Keying (OOFSK) is a digital modulation format in which M-ary FSK signaling is overlaid on On/Off keying. This paper investigates the potential of this modulation format in the context of wideband fading…

Information Theory · Computer Science 2007-07-13 Mustafa Cenk Gursoy , Sergio Verdu , H. Vincent Poor

We introduce a dynamics-level approach to watermarking generative models. Rather than embedding signals into model weights or outputs, we embed the watermark directly into the learned continuous dynamics -- the velocity field of a flow…

Machine Learning · Computer Science 2026-05-18 Shuchan Wang