Tootfinder

Bending Mechanics of Biomimetic Scale Plates
Pranta Rahman Sarkar, Hossein Ebrahimi, Md Shahjahan Hossain, Ranajay Ghosh
https://arxiv.org/abs/2403.08026 h…

Bending Mechanics of Biomimetic Scale Plates
We develop the fundamentals of nonlinear and anisotropic bending behavior of biomimetic scale plates using a combination of analytical modeling, finite element (FE) computations, and motivational experiments. The analytical architecture-property relationships are derived for both synclastic and anticlastic curvatures. The results show that, as the scales engage, both synclastic and anticlastic deformations show non-linear scale contact kinematics and cross-curvature sensitivity of moments resul…

Software in the natural world: A computational approach to emergence in complex multi-level systems
Fernando E. Rosas, Bernhard C. Geiger, Andrea I Luppi, Anil K. Seth, Daniel Polani, Michael Gastpar, Pedro A. M. Mediano
https://arxiv.org/abs/2402.09090

Software in the natural world: A computational approach to emergence in complex multi-level systems
Understanding the functional architecture of complex systems is crucial to illuminate their inner workings and enable effective methods for their prediction and control. Recent advances have introduced tools to characterise emergent macroscopic levels; however, while these approaches are successful in identifying when emergence takes place, they are limited in the extent they can determine how it does. Here we address this limitation by developing a computational approach to emergence, which ch…

Free-Floating Planets, Survivor Planets, Captured Planets and Binary Planets from Stellar Flybys
Fangyuan Yu, Dong Lai
https://arxiv.org/abs/2403.07224 htt…

Free-Floating Planets, Survivor Planets, Captured Planets and Binary Planets from Stellar Flybys
In star clusters, close stellar encounters can strongly impact the architecture of a planetary system or even destroy it. We present a systematic study on the effects of stellar flybys on two-planet systems. When such a system (with a modest initial planet semi-major axis ratio, $a_1/a_2=0.6-0.8$) experiences stellar flybys, one or both planets can be ejected, forming free-floating planets (FFPs), captured planets (CPs) around the flyby star, and free-floating binary planets (BPs); the remainin…

Bending Mechanics of Biomimetic Scale Plates
Pranta Rahman Sarkar, Hossein Ebrahimi, Md Shahjahan Hossain, Ranajay Ghosh
https://arxiv.org/abs/2403.08026 h…

Bending Mechanics of Biomimetic Scale Plates
We develop the fundamentals of nonlinear and anisotropic bending behavior of biomimetic scale plates using a combination of analytical modeling, finite element (FE) computations, and motivational experiments. The analytical architecture-property relationships are derived for both synclastic and anticlastic curvatures. The results show that, as the scales engage, both synclastic and anticlastic deformations show non-linear scale contact kinematics and cross-curvature sensitivity of moments resul…

Digital models and sensory substitution devices: An inclusive communication of architecture through sound https://link.springer.com/chapter/10.1007/978-3-031-57575-4_40

Digital Models and Sensory Substitution Devices: An Inclusive Communication of Architecture Through Sound
The singular nature of architecture, compared to other types of artistic experience, admits the spatial component as the main reference for understanding an object. While scientific advances in the production of digital models have allowed for more and more...

1-bit Quantized On-chip Hybrid Diffraction Neural Network Enabled by Authentic All-optical Fully-connected Architecture
Yu Shao, Haiqi Gao, Yipeng Chen, Yujie liu, Junren Wen, Haidong He, Yuchuan Shao, Yueguang Zhang, Weidong Shen, Chenying Yang
https://arxiv.org/abs/2404.07443

1-bit Quantized On-chip Hybrid Diffraction Neural Network Enabled by Authentic All-optical Fully-connected Architecture
Optical Diffraction Neural Networks (DNNs), a subset of Optical Neural Networks (ONNs), show promise in mirroring the prowess of electronic networks. This study introduces the Hybrid Diffraction Neural Network (HDNN), a novel architecture that incorporates matrix multiplication into DNNs, synergizing the benefits of conventional ONNs with those of DNNs to surmount the modulation limitations inherent in optical diffraction neural networks. Utilizing a singular phase modulation layer and an ampli…

Stability AI releases a preview of Stable Diffusion 3.0, its next flagship text-to-image model, aiming to offer improved image quality and better performance (Sean Michael Kerner/VentureBeat)
https://venturebeat.com/ai/stable-dif…

Stable Diffusion 3.0 debuts new diffusion transformation architecture to reinvent text-to-image gen AI
The new Stable Diffusion 3.0 model aims to provide improved image quality and better performance in generating images from multi-subject prompts.

Learning Traveling Solitary Waves Using Separable Gaussian Neural Networks
Siyuan Xing, Efstathios G. Charalampidis
https://arxiv.org/abs/2403.04883 https:…

Learning Traveling Solitary Waves Using Separable Gaussian Neural Networks
In this paper, we apply a machine-learning approach to learn traveling solitary waves across various families of partial differential equations (PDEs). Our approach integrates a novel interpretable neural network (NN) architecture, called Separable Gaussian Neural Networks (SGNN) into the framework of Physics-Informed Neural Networks (PINNs). Unlike the traditional PINNs that treat spatial and temporal data as independent inputs, the present method leverages wave characteristics to transform da…

Yodel: A Layer 3.5 Name-Based Multicast Network Architecture For The Future Internet
Morteza Moghaddassian, Alberto Leon-Garcia
https://arxiv.org/abs/2403.00207

Yodel: A Layer 3.5 Name-Based Multicast Network Architecture For The Future Internet
Multicasting refers to the ability of transmitting data to multiple recipients without data sources needing to provide more than one copy of the data to the network. The network takes responsibility to route and deliver a copy of each data to every intended recipient. Multicasting has the potential to improve the network efficiency and performance (e.g., throughput and latency) through transferring fewer bits in communicating the same data to multiple recipients compared with unicast transmissi…

An AppSec Engineer with 3 years of experience and expertise in secure code reviews and automated code scanning tools is seeking guidance to learn cloud security. The engineer seeks advice on whether to first learn about cloud architecture before delving into security. https://reddit.com/r/cybersecurity/comments/1bs67uv/

Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling
Yair Schiff, Chia-Hsiang Kao, Aaron Gokaslan, Tri Dao, Albert Gu, Volodymyr Kuleshov
https://arxiv.org/abs/2403.03234

Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling
Large-scale sequence modeling has sparked rapid advances that now extend into biology and genomics. However, modeling genomic sequences introduces challenges such as the need to model long-range token interactions, the effects of upstream and downstream regions of the genome, and the reverse complementarity (RC) of DNA. Here, we propose an architecture motivated by these challenges that builds off the long-range Mamba block, and extends it to a BiMamba component that supports bi-directionality,…

#Requiescat For #GeraldCinamon. http://geraldcinamon.com/biography/

This https://arxiv.org/abs/2402.01831 has been replaced.
link: https://scholar.google.com/scholar?q=a

Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and Dialogue Abilities
Augmenting large language models (LLMs) to understand audio -- including non-speech sounds and non-verbal speech -- is critically important for diverse real-world applications of LLMs. In this paper, we propose Audio Flamingo, a novel audio language model with 1) strong audio understanding abilities, 2) the ability to quickly adapt to unseen tasks via in-context learning and retrieval, and 3) strong multi-turn dialogue abilities. We introduce a series of training techniques, architecture design…

This https://arxiv.org/abs/2311.14018 has been replaced.
initial toot: https://mastoxiv.page/@a…

Fabrication and extreme micromechanics of additive metal microarchitectures
The mechanical performance of metallic metamaterials with 3-dimensional solid frames is typically a combination of the geometrical effect ("architecture") and the characteristic size effects of the base material ("microstructure"). In this study, for the first time, the temperature- and rate-dependent mechanical response of copper microlattices has been investigated. The microlattices were fabricated via a localized electrodeposition in liquid (LEL) process which enables high-precision additive…

Unraveling the Molecular Magic: AI Insights on the Formation of Extraordinarily Stretchable Hydrogels
Shahriar Hojjati Emmami, Ali Pilehvar Meibody, Lobat Tayebi, Mohammadamin Tavakoli, Pierre Baldi
https://arxiv.org/abs/2403.05129

Unraveling the Molecular Magic: AI Insights on the Formation of Extraordinarily Stretchable Hydrogels
The deliberate manipulation of ammonium persulfate, methylenebisacrylamide, dimethyleacrylamide, and polyethylene oxide concentrations resulted in the development of a hydrogel with an exceptional stretchability, capable of extending up to 260 times its original length. This study aims to elucidate the molecular architecture underlying this unique phenomenon by exploring potential reaction mechanisms, facilitated by an artificial intelligence prediction system. Artificial intelligence predictor…

A$^3$PIM: An Automated, Analytic and Accurate Processing-in-Memory Offloader
Qingcai Jiang, Shaojie Tan, Junshi Chen, Hong An
https://arxiv.org/abs/2402.18592

A$^3$PIM: An Automated, Analytic and Accurate Processing-in-Memory Offloader
The performance gap between memory and processor has grown rapidly. Consequently, the energy and wall-clock time costs associated with moving data between the CPU and main memory predominate the overall computational cost. The Processing-in-Memory (PIM) paradigm emerges as a promising architecture that mitigates the need for extensive data movements by strategically positioning computing units proximate to the memory. Despite the abundant efforts devoted to building a robust and highly-availabl…

Pseudorandom Permutations from Random Reversible Circuits
William He, Ryan O'Donnell
https://arxiv.org/abs/2404.14648 https://arx…

Pseudorandom Permutations from Random Reversible Circuits
We study pseudorandomness properties of permutations on $\{0,1\}^n$ computed by random circuits made from reversible $3$-bit gates (permutations on $\{0,1\}^3$). Our main result is that a random circuit of depth $n \cdot \tilde{O}(k^2)$, with each layer consisting of $\approx n/3$ random gates in a fixed nearest-neighbor architecture, yields almost $k$-wise independent permutations. The main technical component is showing that the Markov chain on $k$-tuples of $n$-bit strings induced by a singl…

Network architecture search of X-ray based scientific applications
Adarsha Balaji, Ramyad Hadidi, Gregory Kollmer, Mohammed E. Fouda, Prasanna Balaprakash
https://arxiv.org/abs/2404.10689

Network architecture search of X-ray based scientific applications
X-ray and electron diffraction-based microscopy use bragg peak detection and ptychography to perform 3-D imaging at an atomic resolution. Typically, these techniques are implemented using computationally complex tasks such as a Psuedo-Voigt function or solving a complex inverse problem. Recently, the use of deep neural networks has improved the existing state-of-the-art approaches. However, the design and development of the neural network models depends on time and labor intensive tuning of the…

Protein binding affinity prediction under multiple substitutions applying eGNNs on Residue and Atomic graphs combined with Language model information: eGRAL
Arturo Fiorellini-Bernardis, Sebastien Boyer, Christoph Brunken, Bakary Diallo, Karim Beguir, Nicolas Lopez-Carranza, Oliver Bent
https://arxiv.org/abs/2405.02374

Protein binding affinity prediction under multiple substitutions applying eGNNs on Residue and Atomic graphs combined with Language model information: eGRAL
Protein-protein interactions (PPIs) play a crucial role in numerous biological processes. Developing methods that predict binding affinity changes under substitution mutations is fundamental for modelling and re-engineering biological systems. Deep learning is increasingly recognized as a powerful tool capable of bridging the gap between in-silico predictions and in-vitro observations. With this contribution, we propose eGRAL, a novel SE(3) equivariant graph neural network (eGNN) architecture d…

This https://arxiv.org/abs/2310.03299 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Dynamical Architectures of S-type Transiting Planets in Binaries I: Target Selection using Hipparcos and Gaia proper motion anomalies
The effect of stellar multiplicity on planetary architecture and orbital dynamics provides an important context for exoplanet demographics. We present a volume-limited catalog up to 300 pc of 66 stars hosting planets and planet candidates from Kepler, K2 and TESS with significant Hipparcos-Gaia proper motion anomalies, which indicate the presence of companions. We assess the reliability of each transiting planet candidate using ground-based follow-up observations, and find that the TESS Objects…

This https://arxiv.org/abs/2302.08347 has been replaced.
initial toot: https://mastoxiv.page/@arX…

The autoregressive neural network architecture of the Boltzmann distribution of pairwise interacting spins systems
Generative Autoregressive Neural Networks (ARNNs) have recently demonstrated exceptional results in image and language generation tasks, contributing to the growing popularity of generative models in both scientific and commercial applications. This work presents an exact mapping of the Boltzmann distribution of binary pairwise interacting systems into autoregressive form. The resulting ARNN architecture has weights and biases of its first layer corresponding to the Hamiltonian's couplings and …

This https://arxiv.org/abs/2403.09539 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

Logits of API-Protected LLMs Leak Proprietary Information
The commercialization of large language models (LLMs) has led to the common practice of high-level API-only access to proprietary models. In this work, we show that even with a conservative assumption about the model architecture, it is possible to learn a surprisingly large amount of non-public information about an API-protected LLM from a relatively small number of API queries (e.g., costing under $1,000 for OpenAI's gpt-3.5-turbo). Our findings are centered on one key observation: most moder…

Semantic Information Theory in a feedback-control Kuramoto Model
Damian R Sowinski, Adam Frank, Gourab Ghoshal
https://arxiv.org/abs/2404.02221 https://

Semantic Information Theory in a feedback-control Kuramoto Model
Semantic Information Theory (SIT) offers a new approach to evaluating the information architecture of complex systems. In this study we describe the steps required to {\it operationalize} SIT via its application to dynamical problems. Our road map has four steps: (1) separating the dynamical system into agent-environment sub-systems; (2) choosing an appropriate coarse graining and quantifying correlations; (3) identifying a measure of viability; (4) implementing a scrambling protocol and measur…

Enhancing Aeroacoustic Wind Tunnel Studies through Massive Channel Upscaling with MEMS Microphones
Daniel Ernst, Armin Goudarzi, Reinhard Geisler, Florian Philipp, Thomas Ahlefeldt, Carsten Spehr
https://arxiv.org/abs/2405.03322

Enhancing Aeroacoustic Wind Tunnel Studies through Massive Channel Upscaling with MEMS Microphones
This paper presents a large 6~m x 3~m aperture 7200 MEMS microphone array. The array is designed so that sub-arrays with optimized point spread functions can be used for beamforming and thus, enable the research of source directivity in wind tunnel facilities. The total array consists of modular 800 microphone panels, each consisting of four unique PCB board designs. This modular architecture allows for the time-synchronized measurement of an arbitrary number of panels and thus, aperture size a…

This https://arxiv.org/abs/2310.03299 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Dynamical Architectures of S-type Transiting Planets in Binaries I: Target Selection using Hipparcos and Gaia proper motion anomalies
The effect of stellar multiplicity on planetary architecture and orbital dynamics provides an important context for exoplanet demographics. We present a volume-limited catalog up to 300 pc of 66 stars hosting planets and planet candidates from Kepler, K2 and TESS with significant Hipparcos-Gaia proper motion anomalies, which indicate the presence of companions. We assess the reliability of each transiting planet candidate using ground-based follow-up observations, and find that the TESS Objects…

This https://arxiv.org/abs/2311.14018 has been replaced.
initial toot: https://mastoxiv.page/@a…

Fabrication and extreme micromechanics of additive metal microarchitectures
The mechanical performance of metallic metamaterials with 3-dimensional solid frames is typically a combination of the geometrical effect ("architecture") and the characteristic size effects of the base material ("microstructure"). In this study, for the first time, the temperature- and rate-dependent mechanical response of copper microlattices has been investigated. The microlattices were fabricated via a localized electrodeposition in liquid (LEL) process which enables high-precision additive…

This https://arxiv.org/abs/2403.09539 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

Logits of API-Protected LLMs Leak Proprietary Information
The commercialization of large language models (LLMs) has led to the common practice of high-level API-only access to proprietary models. In this work, we show that even with a conservative assumption about the model architecture, it is possible to learn a surprisingly large amount of non-public information about an API-protected LLM from a relatively small number of API queries (e.g., costing under $1,000 for OpenAI's gpt-3.5-turbo). Our findings are centered on one key observation: most moder…

This https://arxiv.org/abs/2403.15869 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_nli…

Evolution beats random chance: Performance-dependent network evolution for enhanced computational capacity
The quest to understand structure-function relationships in networks across scientific disciplines has intensified. However, the optimal network architecture remains elusive, particularly for complex information processing. Therefore, we investigate how optimal and specific network structures form to efficiently solve distinct tasks using a novel framework of performance-dependent network evolution, leveraging reservoir computing principles. Our study demonstrates that task-specific minimal net…

Hybrid modes in multilayer/antenna architecture set sideband-selective molecular Raman scattering
Giuseppina Simone
https://arxiv.org/abs/2404.14731 https:…

Hybrid modes in multilayer/antenna architecture set sideband-selective molecular Raman scattering
In the realm of healthcare, label-free sensing is a vital component for various applications. Micro-photonic technology presents a promising avenue to pursue pivotal goals. With the use of this technology, healthcare professionals and researchers can harness the power of label-free sensing to develop effective diagnostic and therapeutic tools. The integration of label-free sensing and micro-photonic technology can lead to revolutionary advancements in the healthcare industry. Here, a hybrid mul…

This https://arxiv.org/abs/2402.05226 has been replaced.
link: https://scholar.google.com/scholar?q=a

A Comprehensive Analysis of Secondary Coexistence in a Real-World CBRS Deployment
The Federal Communications Commission (FCC) in the U.S. has made the Citizens Broadband Radio Service (CBRS) band (3.55 - 3.7 GHz) available for commercial wireless usage under a shared approach using a three-tier hierarchical architecture, where the federal incumbent is the highest priority Tier 1 user, Priority Access License (PAL) holders, who have paid for licenses, are Tier 2 users and Tier 3 users operate under General Authorized Access (GAA), without license fees or protection from highe…

This https://arxiv.org/abs/2402.05226 has been replaced.
link: https://scholar.google.com/scholar?q=a

A Comprehensive Analysis of Secondary Coexistence in a Real-World CBRS Deployment
The Federal Communications Commission (FCC) in the U.S. has made the Citizens Broadband Radio Service (CBRS) band (3.55 - 3.7 GHz) available for commercial wireless usage under a shared approach using a three-tier hierarchical architecture, where the federal incumbent is the highest priority Tier 1 user, Priority Access License (PAL) holders, who have paid for licenses, are Tier 2 users and Tier 3 users operate under General Authorized Access (GAA), without license fees or protection from highe…

Measuring bipartite spin correlations of lattice-trapped dipolar atoms
Youssef Aziz Alaoui, Sean R. Muleady, Edwin Chaparro, Youssef Trifa, Ana Maria Rey, Tommaso Roscilde, Bruno Laburthe-Tolra, Laurent Vernac
https://arxiv.org/abs/2404.10531

Measuring bipartite spin correlations of lattice-trapped dipolar atoms
We demonstrate a bipartition technique using a super-lattice architecture to access correlations between alternating planes of a mesoscopic array of spin-3 chromium atoms trapped in a 3D optical lattice. Using this method, we observe that out-of-equilibrium dynamics driven by long-range dipolar interactions lead to spin anti-correlations between the two spatially separated subsystems. Our bipartite measurements reveal a subtle interplay between the anisotropy of the 3D dipolar interactions and …

Evolution beats random chance: Performance-dependent network evolution for enhanced computational capacity
Manish Yadav, Sudeshna Sinha, Merten Stender
https://arxiv.org/abs/2403.15869

Evolution beats random chance: Performance-dependent network evolution for enhanced computational capacity
The quest to understand structure-function relationships in networks across scientific disciplines has intensified. However, the optimal network architecture remains elusive, particularly for complex information processing. Therefore, we investigate how optimal and specific network structures form to efficiently solve distinct tasks using a novel framework of performance-dependent network evolution, leveraging reservoir computing principles. Our study demonstrates that task-specific minimal net…

This https://arxiv.org/abs/2404.02221 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_nli…

Semantic Information Theory in a feedback-control Kuramoto Model
Semantic Information Theory (SIT) offers a new approach to evaluating the information architecture of complex systems. In this study we describe the steps required to {\it operationalize} SIT via its application to dynamical problems. Our road map has four steps: (1) separating the dynamical system into agent-environment sub-systems; (2) choosing an appropriate coarse graining and quantifying correlations; (3) identifying a measure of viability; (4) implementing a scrambling protocol and measur…

The Architecture of Sponge Choanocyte Chambers Maximizes Mechanical Pumping Efficiency
Takumi Ogawa, Shuji Koyama, Toshihiro Omori, Kenji Kikuchi, Helene de Maleprade, Raymond E. Goldstein, Takuji Ishikawa
https://arxiv.org/abs/2402.14364

The Architecture of Sponge Choanocyte Chambers Maximizes Mechanical Pumping Efficiency
Sponges, the basalmost members of the animal kingdom, exhibit a range of complex architectures in which microfluidic channels connect multitudes of spherical chambers lined with choanocytes, flagellated filter-feeding cells. Choanocyte chambers can possess scores or even hundreds of such cells, which drive complex flows entering through porous walls and exiting into the sponge channels. One of the mysteries of the choanocyte chamber is its spherical shape, as it seems inappropriate for inducing…

A deep classifier of chaos and order in Hamiltonian systems of two degrees of freedom
Ippocratis D. Saltas, Georgios Lukes-Gerakopoulos
https://arxiv.org/abs/2402.12359

A deep classifier of chaos and order in Hamiltonian systems of two degrees of freedom
Chaos is an intriguing phenomenon that can be found in an immense variate of systems. Its detection and discrimination from its counterpart order poses an interesting challenge. To address it, we present a deep classifier capable of classifying chaos from order in the discretised dynamics of Hamiltonian systems of two degrees of freedom, through the machinery of Poincaré maps. Our deep network is based predominantly on a convolutional architecture, and generalises with good accuracy on unseen …

Measuring bipartite spin correlations of lattice-trapped dipolar atoms
Youssef Aziz Alaoui, Sean R. Muleady, Edwin Chaparro, Youssef Trifa, Ana Maria Rey, Tommaso Roscilde, Bruno Laburthe-Tolra, Laurent Vernac
https://arxiv.org/abs/2404.10531

Measuring bipartite spin correlations of lattice-trapped dipolar atoms
We demonstrate a bipartition technique using a super-lattice architecture to access correlations between alternating planes of a mesoscopic array of spin-3 chromium atoms trapped in a 3D optical lattice. Using this method, we observe that out-of-equilibrium dynamics driven by long-range dipolar interactions lead to spin anti-correlations between the two spatially separated subsystems. Our bipartite measurements reveal a subtle interplay between the anisotropy of the 3D dipolar interactions and …

What-if Analysis Framework for Digital Twins in 6G Wireless Network Management
Elif Ak, Berk Canberk, Vishal Sharma, Octavia A. Dobre, Trung Q. Duong
https://arxiv.org/abs/2404.11394

What-if Analysis Framework for Digital Twins in 6G Wireless Network Management
This study explores implementing a digital twin network (DTN) for efficient 6G wireless network management, aligning with the fault, configuration, accounting, performance, and security (FCAPS) model. The DTN architecture comprises the Physical Twin Layer, implemented using NS-3, and the Service Layer, featuring machine learning and reinforcement learning for optimizing carrier sensitivity threshold and transmit power control in wireless networks. We introduce a robust "What-if Analysis" module…