Tootfinder

This https://arxiv.org/abs/2309.03917 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Gluon Generalized TMDs and Wigner Distributions in boost invariant longitudinal space
We present the gluon generalized TMDs for non-zero skewness and Wigner distributions in the boost invariant longitudinal space. The boost-invariant longitudinal space is defined as $σ=\frac{1}{2}b^-Δ^+$ and is conjugate to the skewness variable $ξ$. We use the dressed quark model, where a high-energetic quark is dressed by a gluon. This two-particle system has the advantage of addressing both the gluon and the quark sectors. The different contributions in Wigner distributions coming from dif…

Implementing local-explainability in Gradient Boosting Trees: Feature Contribution
\'Angel Delgado-Panadero, Beatriz Hern\'andez-Lorca, Mar\'ia Teresa Garc\'ia-Ord\'as, Jos\'e Alberto Ben\'itez-Andrades
https://arxiv.org/abs/2402.09197

Implementing local-explainability in Gradient Boosting Trees: Feature Contribution
Gradient Boost Decision Trees (GBDT) is a powerful additive model based on tree ensembles. Its nature makes GBDT a black-box model even though there are multiple explainable artificial intelligence (XAI) models obtaining information by reinterpreting the model globally and locally. Each tree of the ensemble is a transparent model itself but the final outcome is the result of a sum of these trees and it is not easy to clarify. In this paper, a feature contribution method for GBDT is developed.…

Topologies of maximally extended non-Hausdorff Misner Space
N. E. Rieger
https://arxiv.org/abs/2402.09312 https://arxiv.org/pdf/2402.…

Topologies of maximally extended non-Hausdorff Misner Space
Misner (1967) space is a portion of 2-dimensional Minkowski spacetime, identified under a boost $\mathcal B$. It is well known that the maximal analytic extension of Misner space that is Hausdorff consists of one half of Minkowski spacetime, identified under $\mathcal B$; and Hawking and Ellis (1973) have shown that the maximal analytic extension that is non-Hausdorff is equal to the full Minkowski spacetime with the point $Q$ at the origin removed, identifed under $\mathcal B$. In this paper I…

This https://arxiv.org/abs/2311.15817 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Chiral hydrodynamics of expanding systems
We obtain equations of motion for the boost-invariant expansion of a system of chiral particles. Our analysis is based on the Boltzmann equation for left- and right-handed massless particles in the relaxation time approximation. We assume Bjorken symmetry, but allow for parity breaking. We generalize the relaxation time approximation to take into account the so-called side-jump effect, but we show that the ensuing correction happens to vanish for Bjorken symmetry. After expressing the conserved…

Magic-Boost: Boost 3D Generation with Mutli-View Conditioned Diffusion
Fan Yang, Jianfeng Zhang, Yichun Shi, Bowen Chen, Chenxu Zhang, Huichao Zhang, Xiaofeng Yang, Jiashi Feng, Guosheng Lin
https://arxiv.org/abs/2404.06429

Magic-Boost: Boost 3D Generation with Mutli-View Conditioned Diffusion
Benefiting from the rapid development of 2D diffusion models, 3D content creation has made significant progress recently. One promising solution involves the fine-tuning of pre-trained 2D diffusion models to harness their capacity for producing multi-view images, which are then lifted into accurate 3D models via methods like fast-NeRFs or large reconstruction models. However, as inconsistency still exists and limited generated resolution, the generation results of such methods still lack intric…

This https://arxiv.org/abs/2311.09575 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_nuc…

Exact solution of Boltzmann equation in a longitudinal expanding system
Analytical solutions to the microscopic Boltzmann equation are useful in testing the applicability and accuracy of macroscopic hydrodynamic theory. In this work, we present exact solutions of the relativistic Boltzmann equation, based on a new family of exact solutions of the relativistic ideal hydrodynamic equations [Phys. Rev. C 105, L021902].. To the best of our knowledge, this is the first exact solution that allows longitudinal expansion with broken boost invariance.

This https://arxiv.org/abs/2403.18937 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

Analyticity and the Unruh effect: a study of local modular flow
The Unruh effect can be formulated as the statement that the Minkowski vacuum in a Rindler wedge has a boost as its modular flow. In recent years, other examples of states with geometrically local modular flow have played important roles in understanding energy and entropy in quantum field theory and quantum gravity. Here I initiate a general study of the settings in which geometric modular flow can arise, showing (i) that any geometric modular flow must be a conformal symmetry of the backgroun…

This https://arxiv.org/abs/2403.04603 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Next-to-eikonal corrections to dijet production in Deep Inelastic Scattering in the dilute limit of the Color Glass Condensate
We analyze the effects of next-to-eikonal corrections on dijet production in Deep Inelastic Scattering off nuclear targets in the framework of the Color Glass Condensate. They require the knowledge of correlators of fields in the target beyond those computed in the standard McLerran-Venugopalan model, specifically those between transverse and boost-enhanced components, and of the recoil of the fields. We neglect the latter, while for the former we develop a linear model valid for large nuclei. …

Boosting keyword spotting through on-device learnable user speech characteristics
Cristian Cioflan, Lukas Cavigelli, Luca Benini
https://arxiv.org/abs/2403.07802

Boosting keyword spotting through on-device learnable user speech characteristics
Keyword spotting systems for always-on TinyML-constrained applications require on-site tuning to boost the accuracy of offline trained classifiers when deployed in unseen inference conditions. Adapting to the speech peculiarities of target users requires many in-domain samples, often unavailable in real-world scenarios. Furthermore, current on-device learning techniques rely on computationally intensive and memory-hungry backbone update schemes, unfit for always-on, battery-powered devices. In …

Novelty Heuristics, Multi-Queue Search, and Portfolios for Numeric Planning
Dillon Z. Chen, Sylvie Thi\'ebaux
https://arxiv.org/abs/2404.05235 https://…

Novelty Heuristics, Multi-Queue Search, and Portfolios for Numeric Planning
Heuristic search is a powerful approach for solving planning problems and numeric planning is no exception. In this paper, we boost the performance of heuristic search for numeric planning with various powerful techniques orthogonal to improving heuristic informedness: numeric novelty heuristics, the Manhattan distance heuristic, and exploring the use of multi-queue search and portfolios for combining heuristics.

This https://arxiv.org/abs/2403.03229 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qbi…

Embracing Uncertainty Flexibility: Harnessing a Supervised Tree Kernel to Empower Ensemble Modelling for 2D Echocardiography-Based Prediction of Right Ventricular Volume
The right ventricular (RV) function deterioration strongly predicts clinical outcomes in numerous circumstances. To boost the clinical deployment of ensemble regression methods that quantify RV volumes using tabular data from the widely available two-dimensional echocardiography (2DE), we propose to complement the volume predictions with uncertainty scores. To this end, we employ an instance-based method which uses the learned tree structure to identify the nearest training samples to a target …

Encoder-Quantization-Motion-based Video Quality Metrics
Yixu Chen, Zaixi Shang, Hai Wei, Yongjun Wu, Sriram Sethuraman
https://arxiv.org/abs/2404.06620 htt…

Encoder-Quantization-Motion-based Video Quality Metrics
In an adaptive bitrate streaming application, the efficiency of video compression and the encoded video quality depend on both the video codec and the quality metric used to perform encoding optimization. The development of such a quality metric need large scale subjective datasets. In this work we merge several datasets into one to support the creation of a metric tailored for video compression and scaling. We proposed a set of HEVC lightweight features to boost performance of the metrics. Our…

This https://arxiv.org/abs/2403.18937 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

Analyticity and the Unruh effect: a study of local modular flow
The Unruh effect can be formulated as the statement that the Minkowski vacuum in a Rindler wedge has a boost as its modular flow. In recent years, other examples of states with geometrically local modular flow have played important roles in understanding energy and entropy in quantum field theory and quantum gravity. Here I initiate a general study of the settings in which geometric modular flow can arise, showing (i) that any geometric modular flow must be a conformal symmetry of the backgroun…

@… just curious, why does your Fediverse news bot only boost those that oppose Threads? You seem to post good and straight forward facts, yet your bot seems to only boost those with opposing opinions and statements that are sometimes false...😬

Boosted Imaginary Time Evolution of Matrix Product States
Benjamin C. B. Symons, Dilhan Manawadu, David Galvin, Stefano Mensa
https://arxiv.org/abs/2405.04959

Boosted Imaginary Time Evolution of Matrix Product States
In this work, we consider the imaginary time evolution of matrix product states. We present a novel quantum-inspired classical method that, when combined with time evolving block decimation (TEBD), is able to potentially speed-up the convergence to a ground state compared to TEBD alone. Our method, referred to as boosted imaginary time evolution, relies on the use of reflections to boost to lower energy states. Interleaving TEBD steps with boosts reduces the total number of TEBD steps and poten…

SoPhAr: Solar Phased-Arrays to boost the range of electric, hydrogen and SAF airliners in a solar world
Christian Claudel
https://arxiv.org/abs/2404.04779 …

SoPhAr: Solar Phased-Arrays to boost the range of electric, hydrogen and SAF airliners in a solar world
In late 2022, ICAO member states adopted a long-term global aspirational goal (LTAG) to achieve net zero carbon emissions from international aviation by 2050. To date however, no economically scalable solution to the aviation decarbonization problem has been proposed. Despite considerable research on potential alternative fuels including e-fuels, Sustainable Aviation Fuel (SAF), Hydrogen or Ammonia, and extensive research on purely electric propulsion, low-carbon propulsion methods are unable t…

Fundamental Limits of Optical Fiber MIMO Channels With Finite Blocklength
Xin Zhang, Dongfang Xu, Shenghui Song, M\'erouane Debbah
https://arxiv.org/abs/2404.04477

Fundamental Limits of Optical Fiber MIMO Channels With Finite Blocklength
The multiple-input and multiple-output (MIMO) technique is regarded as a promising approach to boost the throughput and reliability of optical fiber communications. However, the fundamental limits of optical fiber MIMO systems with finite block-length (FBL) are not available in the literature. This paper studies the fundamental limits of optical fiber multicore/multimode systems in the FBL regime when the coding rate is a perturbation within $\mathcal{O}(\frac{1}{\sqrt{ML}})$ of the capacity, w…

Collaborative Cybersecurity Using Blockchain: A Survey
Lo\"ic Miller, Marc-Oliver Pahl
https://arxiv.org/abs/2403.04410 https://…

Collaborative Cybersecurity Using Blockchain: A Survey
Collaborative cybersecurity relies on organizations sharing information to boost security, but trust management is a key concern. Decentralized solutions like distributed ledgers, particularly blockchain, are crucial for eliminating single points of failure. However, the existing literature on blockchain-based collaborative cybersecurity is limited, lacking comprehensive insights. This paper addresses this gap by surveying blockchain's role in collaborative cybersecurity from 2016 to 2023. It e…

This https://arxiv.org/abs/2209.01793 has been replaced.
link: https://scholar.google.com/scholar?q=a

An Enhanced ADMM-based Interior Point Method for Linear and Conic Optimization
The ADMM-based interior point (ABIP, Lin et al. 2021) method is a hybrid algorithm that effectively combines interior point method (IPM) and first-order methods to achieve a performance boost in large-scale linear optimization. Different from traditional IPM that relies on computationally intensive Newton steps, the ABIP method applies the alternating direction method of multipliers (ADMM) to approximately solve the barrier penalized problem. However, similar to other first-order methods, this …

The AI Review Lottery: Widespread AI-Assisted Peer Reviews Boost Paper Scores and Acceptance Rates
Giuseppe Russo Latona, Manoel Horta Ribeiro, Tim R. Davidson, Veniamin Veselovsky, Robert West
https://arxiv.org/abs/2405.02150

The AI Review Lottery: Widespread AI-Assisted Peer Reviews Boost Paper Scores and Acceptance Rates
Journals and conferences worry that peer reviews assisted by artificial intelligence (AI), in particular, large language models (LLMs), may negatively influence the validity and fairness of the peer-review system, a cornerstone of modern science. In this work, we address this concern with a quasi-experimental study of the prevalence and impact of AI-assisted peer reviews in the context of the 2024 International Conference on Learning Representations (ICLR), a large and prestigious machine-learn…

Audio-Visual Generalized Zero-Shot Learning using Pre-Trained Large Multi-Modal Models
David Kurzend\"orfer, Otniel-Bogdan Mercea, A. Sophia Koepke, Zeynep Akata
https://arxiv.org/abs/2404.06309

Audio-Visual Generalized Zero-Shot Learning using Pre-Trained Large Multi-Modal Models
Audio-visual zero-shot learning methods commonly build on features extracted from pre-trained models, e.g. video or audio classification models. However, existing benchmarks predate the popularization of large multi-modal models, such as CLIP and CLAP. In this work, we explore such large pre-trained models to obtain features, i.e. CLIP for visual features, and CLAP for audio features. Furthermore, the CLIP and CLAP text encoders provide class label embeddings which are combined to boost the per…

This https://arxiv.org/abs/2204.08769 has been replaced.
link: https://scholar.google.com/scholar?q=a

Bodyless Block Propagation: TPS Fully Scalable Blockchain with Pre-Validation
Despite numerous prior attempts to boost transaction per second (TPS) of blockchain system, most of them were at a price of degraded decentralization and security. In this paper, we propose a bodyless block propagation (BBP) scheme for which the blockbody is not validated and transmitted during the block propagation process, to increase TPS without compromising security. Rather, the nodes in the blockchain network anticipate the transactions and their ordering in the next upcoming block so that…

Can a Funny Chatbot Make a Difference? Infusing Humor into Conversational Agent for Behavioral Intervention
Xin Sun, Isabelle Teljeur, Zhuying Li, Jos A. Bosch
https://arxiv.org/abs/2403.00365

Can a Funny Chatbot Make a Difference? Infusing Humor into Conversational Agent for Behavioral Intervention
Regular physical activity is crucial for reducing the risk of non-communicable disease (NCD). With NCDs on the rise globally, there is an urgent need for effective health interventions, with chatbots emerging as a viable and cost-effective option because of limited healthcare accessibility. Although health professionals often utilize behavior change techniques (BCTs) to boost physical activity levels and enhance client engagement and motivation by affiliative humor, the efficacy of humor in cha…

#GitHub is under attack.
“The flow of the campaign is simple:
1. Cloning existing repos (for example: TwitterFollowBot, WhatsappBOT, discord-boost-tool, Twitch-Follow-Bot, and hundreds more)
2. Infecting them with malware loaders
3. Uploading them back to GitHub with identical names
4. Automatically forking each thousands of times
5. Covertly promoting them across the …

GitHub besieged by millions of malicious repositories in ongoing attack
GitHub keeps removing malware-laced repositories, but thousands remain.

This https://arxiv.org/abs/2403.16516 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

Visually Guided Generative Text-Layout Pre-training for Document Intelligence
Prior study shows that pre-training techniques can boost the performance of visual document understanding (VDU), which typically requires models to gain abilities to perceive and reason both document texts and layouts (e.g., locations of texts and table-cells). To this end, we propose visually guided generative text-layout pre-training, named ViTLP. Given a document image, the model optimizes hierarchical language and layout modeling objectives to generate the interleaved text and layout sequen…

This https://arxiv.org/abs/2401.14217 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

The explicit form of the unitary representation of the Poincaré group for vector-valued wave functions (massive and massless), with applications to photon's localization and position operators
We geometrically derive the explicit form of the Unitary representation of the Poincare group and use it to apply speed-of-light boosts to simple polarization basis to end up with Hawton-Baylis photon position operator with commuting components. We give explicit formulas for other photon boost eigenmodes. We investigate the underlying affine connections on the light cone in momentum space and find that while Pryce connection is metric semi-symmetric, the flat Hawton-Baylis connection is not sem…

Tuning transduction from hidden observables to optimize information harvesting
Giorgio Nicoletti, Daniel Maria Busiello
https://arxiv.org/abs/2403.04709 ht…

Tuning transduction from hidden observables to optimize information harvesting
Biological and living organisms sense and process information from their surroundings, typically having access only to a subset of external observables for a limited amount of time. In this work, we uncover how biological systems can exploit these accessible degrees of freedom (DOFs) to transduce information from the inaccessible ones with a limited energy budget. We find that optimal transduction strategies may boost information harvesting over the ideal case in which all DOFs are known, even …

@… @… The bot did not boost this post because it came from a bot. We might want to relax that rule. 🤔

This https://arxiv.org/abs/2309.03871 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

Horizon phase spaces in general relativity
We derive a prescription for the phase space of general relativity on two intersecting null surfaces. The boundary symmetry group is the semidirect product of the group of arbitrary diffeomorphisms of each null boundary which coincide at the corner, with a group of reparameterizations of the null generators. The phase space can be extended by acting with half-sided boosts that generate Weyl shocks along the initial data surfaces, and it then includes the relative boost angle between the null su…

Machine Learning Assisted Adjustment Boosts Inferential Efficiency of Randomized Controlled Trials
Han Yu, Alan D. Hutson
https://arxiv.org/abs/2403.03058 …

Machine Learning Assisted Adjustment Boosts Inferential Efficiency of Randomized Controlled Trials
In this work, we proposed a novel inferential procedure assisted by machine learning based adjustment for randomized control trials. The method was developed under the Rosenbaum's framework of exact tests in randomized experiments with covariate adjustments. Through extensive simulation experiments, we showed the proposed method can robustly control the type I error and can boost the inference efficiency for a randomized controlled trial (RCT). This advantage was further demonstrated in a real …

Coherent feedback for quantum expander in gravitational wave observatories
Niels B\"ottner, Joe Bentley, Roman Schnabel, Mikhail Korobko
https://arxiv.org/abs/2403.03758

Coherent feedback for quantum expander in gravitational wave observatories
The observation of gravitational waves from binary neutron star mergers offers insights into properties of extreme nuclear matter. However, their high-frequency signals in the kHz range are often masked by quantum noise of the laser light used. Here, we propose the "quantum expander with coherent feedback", a new detector design that features an additional optical cavity in the detector output and an internal squeeze operation. This approach allows to boost the sensitivity at high frequencies, …

The Design and Implementation of a High-Performance Log-Structured RAID System for ZNS SSDs
Jinhong Li, Qiuping Wang, Shujie Han, Patrick P. C. Lee
https://arxiv.org/abs/2402.17963

The Design and Implementation of a High-Performance Log-Structured RAID System for ZNS SSDs
Zoned Namespace (ZNS) defines a new abstraction for host software to flexibly manage storage in flash-based SSDs as append-only zones. It also provides a Zone Append primitive to further boost the write performance of ZNS SSDs by exploiting intra-zone parallelism. However, making Zone Append effective for reliable and scalable storage, in the form of a RAID array of multiple ZNS SSDs, is non-trivial since Zone Append offloads address management to ZNS SSDs and requires hosts to dedicatedly mana…

A Conceptual Design of In-Game Real and Virtual Currency Tracker
Dennis Barzanoff, Amna Asif
https://arxiv.org/abs/2404.03951 https://

A Conceptual Design of In-Game Real and Virtual Currency Tracker
The gaming industry is earning huge revenues from incorporating virtual currencies into the game design experience. Even if it is a useful approach for the game industry to boost up their earnings, the unidirectional and bidirectional in-game virtual currencies can invoke inadequate gaming behaviors and additions among players. The market lacks gaming and customer protection regulations to avoid the financial, behavioral, and psychological exploitation of users. Therefore, it is needed to devel…

A 97% Peak Efficiency Single-Inductor-Multiple-Output DC-DC Converter with a Shared Bootstrap Gate Driver
Mohammadreza Zeinali
https://arxiv.org/abs/2404.04751

A 97% Peak Efficiency Single-Inductor-Multiple-Output DC-DC Converter with a Shared Bootstrap Gate Driver
This paper describes a SIMO DC-DC converter capable of generating all the required voltages (buck and boost) utilizing n-type transistors for the output switches. The design incorporates only one shared bootstrap capacitor and a single pad to connect the top plate of the off-chip bootstrap capacitor to the on-chip drivers. By utilizing one off-chip bootstrap capacitor and sharing it between the multiple outputs, this work presents a low cost and low area solution for implementing a SIMO DC-DC c…

This https://arxiv.org/abs/2308.08453 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDS_…

Tightest Admissible Shortest Path
The shortest path problem in graphs is fundamental to AI. Nearly all variants of the problem and relevant algorithms that solve them ignore edge-weight computation time and its common relation to weight uncertainty. This implies that taking these factors into consideration can potentially lead to a performance boost in relevant applications. Recently, a generalized framework for weighted directed graphs was suggested, where edge-weight can be computed (estimated) multiple times, at increasing a…

Balanced Data Placement for GEMV Acceleration with Processing-In-Memory
Mohamed Assem Ibrahim, Mahzabeen Islam, Shaizeen Aga
https://arxiv.org/abs/2403.20297

Balanced Data Placement for GEMV Acceleration with Processing-In-Memory
With unprecedented demand for generative AI (GenAI) inference, acceleration of primitives that dominate GenAI such as general matrix-vector multiplication (GEMV) is receiving considerable attention. A challenge with GEMVs is the high memory bandwidth this primitive demands. Multiple memory vendors have proposed commercially viable processing-in-memory (PIM) prototypes that attain bandwidth boost over processor via augmenting memory banks with compute capabilities and broadcasting same command t…

A new pairwise boost quantum number from celestial states
Francesco Alessio, Michele Arzano
https://arxiv.org/abs/2403.03760 https://…

A new pairwise boost quantum number from celestial states
Infrared effects in the scattering of particles in gravity and electrodynamics entail an exchange of relativistic angular momentum between pairs of particles and the gauge field. Due to this exchange particles can carry an asymptotically non-vanishing "pairwise" boost-like angular momentum proportional to the product of their couplings to the field. At the quantum level this asymptotic angular momentum suggests the existence of a new quantum number carried by multi-particle states. We argue tha…

This https://arxiv.org/abs/2309.05285 has been replaced.
initial toot: https://mastoxiv.page/@a…

Effects of strain-tunable valleys on charge transport in bismuth
The manipulation of the valley degree of freedom can boost the technological development of novel functional devices based on valleytronics. The current mainstream platform for valleytronics is to produce a monolayer with inversion asymmetry, in which the strain-band engineering through the substrates can serve to improve the performance of valley-based devices. However, pinpointing the effective role of strain is inevitable for the precise design of the desired valley structure. Here, we demon…

Optical absorption signatures of superconductors driven by Van Hove singularities
Hyeok-Jun Yang, Yi-Ting Hsu
https://arxiv.org/abs/2404.04329 https://

Optical absorption signatures of superconductors driven by Van Hove singularities
Due to the diverging density of states (DOS), Van Hove singularities (VHS) near the Fermi level are known to boost the susceptibility to a wide variety of electronic instabilities, including superconductivity. We theoretically show that the number of VHS in the normal state can be qualitatively inferred from the optical absorption spectra Re $σ_{ii}(ω)$ in the superconducting state. The key feature is the absorption peak at frequency $ω=2Δ$ from the optical transition across the superconduc…

Accessing the speed of sound in relativistic ultracentral nucleus-nucleus collisions using the mean transverse momentum
Fernando G. Gardim, Andre V. Giannini, Jean-Yves Ollitrault
https://arxiv.org/abs/2403.06052

Accessing the speed of sound in relativistic ultracentral nucleus-nucleus collisions using the mean transverse momentum
It has been argued that the speed of sound of the strong interaction at high temperature can be measured using the variation of the mean transverse momentum with the particle multiplicity in ultracentral heavy-ion collisions. We test this correspondence by running hydrodynamic simulations at zero impact parameter with several equations of state, at several colliding energies from 0.2 TeV to 15 TeV per nucleon pair. The correspondence is found to be precise and robust for a smooth, boost-invaria…

This https://arxiv.org/abs/2208.07814 has been replaced.
link: https://scholar.google.com/scholar?q=a

Does Lorentz-symmetric design boost network performance in jet physics?
In the deep learning era, improving the neural network performance in jet physics is a rewarding task as it directly contributes to more accurate physics measurements at the LHC. Recent research has proposed various network designs in consideration of the full Lorentz symmetry, but its benefit is still not systematically asserted, given that there remain many successful networks without taking it into account. We conduct a detailed study on the Lorentz-symmetric design. We propose two generaliz…

This https://arxiv.org/abs/2312.14510 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csGT_…

Strategic Bidding Wars in On-chain Auctions
The Ethereum block-building process has changed significantly since the emergence of Proposer-Builder Separation. Validators access blocks through a marketplace, where block builders bid for the right to construct the block and earn MEV (Maximal Extractable Value) rewards in an on-chain competition, known as the MEV-boost auction. While more than 90% of blocks are currently built via MEV-Boost, trade-offs between builders' strategic behaviors and auction design remain poorly understood. In this…

This https://arxiv.org/abs/2402.11768 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Targeted Parallelization of Conflict-Based Search for Multi-Robot Path Planning
Multi-Robot Path Planning (MRPP) on graphs, equivalently known as Multi-Agent Path Finding (MAPF), is a well-established NP-hard problem with critically important applications. As serial computation in (near)-optimally solving MRPP approaches the computation efficiency limit, parallelization offers a promising route to push the limit further, especially in handling hard or large MRPP instances. In this study, we initiated a \emph{targeted} parallelization effort to boost the performance of conf…

This https://arxiv.org/abs/2401.04296 has been replaced.
initial toot: https://mastoxiv.page/@a…

Effect of Longitudinal Fluctuations of $3$D Weizsäcker-Williams Field on Pressure Isotropization of Glasma
We investigate the effects of boost invariance breaking on the isotropization of pressure in the glasma, using the $3+1$D glasma simulation. The breaking is attributed to spatial fluctuations of the classical color charge density along the collision axis. We present numerical results for pressure and energy density at mid-rapidity and across a wider rapidity region. It is found that, despite varying longitudinal correlation lengths, the behaviors of the pressure isotropizations are qualitativel…

An Effective Networks Intrusion Detection Approach Based on Hybrid Harris Hawks and Multi-Layer Perceptron
Moutaz Alazab, Ruba Abu Khurma, Pedro A. Castillo, Bilal Abu-Salih, Alejandro Martin, David Camacho
https://arxiv.org/abs/2402.14037 https://arxiv.org/pdf/2402.14037
arXiv:2402.14037v1 Announce Type: new
Abstract: This paper proposes an Intrusion Detection System (IDS) employing the Harris Hawks Optimization algorithm (HHO) to optimize Multilayer Perceptron learning by optimizing bias and weight parameters. HHO-MLP aims to select optimal parameters in its learning process to minimize intrusion detection errors in networks. HHO-MLP has been implemented using EvoloPy NN framework, an open-source Python tool specialized for training MLPs using evolutionary algorithms. For purposes of comparing the HHO model against other evolutionary methodologies currently available, specificity and sensitivity measures, accuracy measures, and mse and rmse measures have been calculated using KDD datasets. Experiments have demonstrated the HHO MLP method is effective at identifying malicious patterns. HHO-MLP has been tested against evolutionary algorithms like Butterfly Optimization Algorithm (BOA), Grasshopper Optimization Algorithms (GOA), and Black Widow Optimizations (BOW), with validation by Random Forest (RF), XG-Boost. HHO-MLP showed superior performance by attaining top scores with accuracy rate of 93.17%, sensitivity level of 89.25%, and specificity percentage of 95.41%.

Beneath the Surface: Revealing Deep-Tissue Blood Flow in Human Subjects with Massively Parallelized Diffuse Correlation Spectroscopy
Lucas Kreiss, Melissa Wu, Michael Wayne, Shiqi Xu, Paul McKee, Derrick Dwamena, Kanghyun Kim, Kyung Chul Lee, Wenhui Liu, Aarin Ulku, Mark Harfouche, Xi Yang, Clare Cook, Amey Chaware, Seung Ah Lee, Erin Buckley, Claudio Bruschini, Edoardo Charbon, Scott Huettel, Roarke Horstmeyer

Beneath the Surface: Revealing Deep-Tissue Blood Flow in Human Subjects with Massively Parallelized Diffuse Correlation Spectroscopy
Diffuse Correlation Spectroscopy (DCS) allows the label-free investigation of microvascular dynamics deep within living tissue. However, common implementations of DCS are currently limited to measurement depths of $\sim 1-1.5cm$, which can limit the accuracy of cerebral hemodynamics measurement. Here we present massively parallelized DCS (pDCS) using novel single photon avalanche detector (SPAD) arrays with up to 500x500 individual channels. The new SPAD array technology can boost the signal-to…

This https://arxiv.org/abs/2208.06620 has been replaced.
link: https://scholar.google.com/scholar?q=a

Opinion Market Model: Stemming Far-Right Opinion Spread using Positive Interventions
Online extremism has severe societal consequences, including normalizing hate speech, user radicalization, and increased social divisions. Various mitigation strategies have been explored to address these consequences. One such strategy uses positive interventions: controlled signals that add attention to the opinion ecosystem to boost certain opinions. To evaluate the effectiveness of positive interventions, we introduce the Opinion Market Model (OMM), a two-tier online opinion ecosystem model…

Small Language Models Need Strong Verifiers to Self-Correct Reasoning
Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran, Jaekyeom Kim, Moontae Lee, Honglak Lee, Lu Wang
https://arxiv.org/abs/2404.17140

Small Language Models Need Strong Verifiers to Self-Correct Reasoning
Self-correction has emerged as a promising solution to boost the reasoning performance of large language models (LLMs), where LLMs refine their solutions using self-generated critiques that pinpoint the errors. This work explores whether smaller-size (<= 13B) language models (LMs) have the ability of self-correction on reasoning tasks with minimal inputs from stronger LMs. We propose a novel pipeline that prompts smaller LMs to collect self-correction data that supports the training of self-ref…

Constrained Decoding for Secure Code Generation
Yanjun Fu, Ethan Baker, Yizheng Chen
https://arxiv.org/abs/2405.00218 https://arxiv.o…

Constrained Decoding for Secure Code Generation
Code Large Language Models (Code LLMs) have been increasingly used by developers to boost productivity, but they often generate vulnerable code. Thus, there is an urgent need to ensure that code generated by Code LLMs is correct and secure. Previous research has primarily focused on generating secure code, overlooking the fact that secure code also needs to be correct. This oversight can lead to a false sense of security. Currently, the community lacks a method to measure actual progress in thi…

Limits on Early Matter Domination from the Isotropic Gamma-Ray Background
Himanish Ganjoo, M. Sten Delos
https://arxiv.org/abs/2403.18893 https://

Limits on Early Matter Domination from the Isotropic Gamma-Ray Background
In cosmologies with hidden sector dark matter, the lightest hidden sector species can come to dominate the energy budget of the universe and cause an early matter-dominated era (EMDE). EMDEs amplify the matter power spectrum on small scales, leading to dense, early-forming microhalos which massively boost the dark matter annihilation signal. We use the Fermi-LAT measurement of the isotropic gamma-ray background to place limits on the parameter space of hidden sector models with EMDEs. We calcul…

@… @… the bot should already boost #dotnetmaui tagged post (if they are not replies).
So far the bot did not become a vict…

Does Financial Literacy Impact Investment Participation and Retirement Planning in Japan?
Yi Jiang, Shohei Shimizu
https://arxiv.org/abs/2405.01078 https:/…

Does Financial Literacy Impact Investment Participation and Retirement Planning in Japan?
By employing causal discovery method, the Fast Causal Inference (FCI) model to analyze data from the 2022 "Financial Literacy Survey," we explore the causal relationships between financial literacy and financial activities, specifically investment participation and retirement planning. Our findings indicate that increasing financial literacy may not directly boost engagement in financial investments or retirement planning in Japan, which underscores the necessity for alternative strategies to m…

Linear-Time Graph Neural Networks for Scalable Recommendations
Jiahao Zhang, Rui Xue, Wenqi Fan, Xin Xu, Qing Li, Jian Pei, Xiaorui Liu
https://arxiv.org/abs/2402.13973

Linear-Time Graph Neural Networks for Scalable Recommendations
In an era of information explosion, recommender systems are vital tools to deliver personalized recommendations for users. The key of recommender systems is to forecast users' future behaviors based on previous user-item interactions. Due to their strong expressive power of capturing high-order connectivities in user-item interaction data, recent years have witnessed a rising interest in leveraging Graph Neural Networks (GNNs) to boost the prediction performance of recommender systems. Nonethel…

ReZero: Boosting MCTS-based Algorithms by Just-in-Time and Speedy Reanalyze
Chunyu Xuan, Yazhe Niu, Yuan Pu, Shuai Hu, Jing Yang
https://arxiv.org/abs/2404.16364

ReZero: Boosting MCTS-based Algorithms by Just-in-Time and Speedy Reanalyze
MCTS-based algorithms, such as MuZero and its derivatives, have achieved widespread success in various decision-making domains. These algorithms employ the reanalyze process to enhance sample efficiency, albeit at the expense of significant wall-clock time consumption. To address this issue, we propose a general approach named ReZero to boost MCTS-based algorithms. Specifically, we propose a new scheme that simplifies data collecting and reanalyzing, which significantly reduces the search cost …

Thermodynamic constraints on polar active matter hydrodynamics
Andrea Amoretti, Daniel K. Brattan, Luca Martinoia
https://arxiv.org/abs/2405.02283 https://…

Thermodynamic constraints on polar active matter hydrodynamics
In this letter we use the thermodynamics of a passive fluid to constrain transport in the corresponding active fluid which is subsequently described by the Toner-Tu equations. Acknowledging that the system fundamentally breaks boost symmetry we compel what were previously entirely phenomenological parameters in the Toner-Tu model to satisfy precise relationships among themselves. Consequently, we determine exact scalings for the transport coefficients under dynamical renormalisation group flow …

The Sine-Gordon QFT in de Sitter spacetime
Daniela Cadamuro, Markus B. Fr\"ob, Carolina Moreira Ferrera
https://arxiv.org/abs/2404.12324 https://

The Sine-Gordon QFT in de Sitter spacetime
We consider the massless Sine-Gordon model in de Sitter spacetime, in the regime $β^2 < 4 π$ and using the framework of perturbative algebraic quantum field theory. We show that a Fock space representation exists for the free massless field, but that the natural one-parameter family of vacuum-like states breaks the de Sitter boost symmetries. We prove convergence of the perturbative series for the S matrix in this representation, and construct the interacting Haag-Kastler net of local algebra…

Longitudinal Mammogram Risk Prediction
Batuhan K. Karaman, Katerina Dodelzon, Gozde B. Akar, Mert R. Sabuncu
https://arxiv.org/abs/2404.19083 https://arxiv.org/pdf/2404.19083
arXiv:2404.19083v1 Announce Type: new
Abstract: Breast cancer is one of the leading causes of mortality among women worldwide. Early detection and risk assessment play a crucial role in improving survival rates. Therefore, annual or biennial mammograms are often recommended for screening in high-risk groups. Mammograms are typically interpreted by expert radiologists based on the Breast Imaging Reporting and Data System (BI-RADS), which provides a uniform way to describe findings and categorizes them to indicate the level of concern for breast cancer. Recently, machine learning (ML) and computational approaches have been developed to automate and improve the interpretation of mammograms. However, both BI-RADS and the ML-based methods focus on the analysis of data from the present and sometimes the most recent prior visit. While it is clear that temporal changes in image features of the longitudinal scans should carry value for quantifying breast cancer risk, no prior work has conducted a systematic study of this. In this paper, we extend a state-of-the-art ML model to ingest an arbitrary number of longitudinal mammograms and predict future breast cancer risk. On a large-scale dataset, we demonstrate that our model, LoMaR, achieves state-of-the-art performance when presented with only the present mammogram. Furthermore, we use LoMaR to characterize the predictive value of prior visits. Our results show that longer histories (e.g., up to four prior annual mammograms) can significantly boost the accuracy of predicting future breast cancer risk, particularly beyond the short-term. Our code and model weights are available at https://github.com/batuhankmkaraman/LoMaR.

A TDM-based Analog Front-End for Ear-EEG Recording with 83-G$\Omega$ Input Impedance, 384-mV DC Tolerance and 0.47-$\mu$Vrms Input-Referred Noise
Huiyong Zheng
https://arxiv.org/abs/2402.17538

A TDM-based Analog Front-End for Ear-EEG Recording with 83-G$Ω$ Input Impedance, 384-mV DC Tolerance and 0.47-$μ$Vrms Input-Referred Noise
This paper presents the design of a time-division multiplexed capacitively-coupled chopper analog front end with a novel impedance boost loop (IBL) and a novel DC servo loop (DSL). The proposed IBL boosts the input impedance of the analog front end to up to several tens of G$Ω$. It firstly utilizes an external IBL to prevent the total input impedance from degradation caused by parasitic capacitance from the ESD pad and external interconnections, and secondly relies on an internal IBL to compen…

This https://arxiv.org/abs/2401.13562 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Exploiting separation-dependent coherence to boost optical resolution
The problem of resolving point-like light sources not only serves as a benchmark for optical resolution but also holds various practical applications ranging from microscopy to astronomy. In this research, we aim to resolve two thermal sources sharing arbitrary mutual coherence using the spatial mode demultiplexing technique. Our analytical study includes scenarios where the coherence and the emission rate depend on the separation between the sources, and is not limited to the faint sources lim…

Balanced Data Placement for GEMV Acceleration with Processing-In-Memory
Mohamed Assem Ibrahim, Mahzabeen Islam, Shaizeen Aga
https://arxiv.org/abs/2403.20297

Balanced Data Placement for GEMV Acceleration with Processing-In-Memory
With unprecedented demand for generative AI (GenAI) inference, acceleration of primitives that dominate GenAI such as general matrix-vector multiplication (GEMV) is receiving considerable attention. A challenge with GEMVs is the high memory bandwidth this primitive demands. Multiple memory vendors have proposed commercially viable processing-in-memory (PIM) prototypes that attain bandwidth boost over processor via augmenting memory banks with compute capabilities and broadcasting same command t…

Optical absorption signatures of superconductors driven by Van Hove singularities
Hyeok-Jun Yang, Yi-Ting Hsu
https://arxiv.org/abs/2404.04329 https://

Optical absorption signatures of superconductors driven by Van Hove singularities
Due to the diverging density of states (DOS), Van Hove singularities (VHS) near the Fermi level are known to boost the susceptibility to a wide variety of electronic instabilities, including superconductivity. We theoretically show that the number of VHS in the normal state can be qualitatively inferred from the optical absorption spectra Re $σ_{ii}(ω)$ in the superconducting state. The key feature is the absorption peak at frequency $ω=2Δ$ from the optical transition across the superconduc…

From parcels to people: development of a spatially explicit risk indicator to monitor residential pesticide exposure in agricultural areas
Francesco GalimbertiEuropean Commission, Joint Research Centre, Stephanie BoppEuropean Commission, Joint Research Centre, Alessandro CarlettiEuropean Commission, Joint Research Centre, Rui CatarinoEuropean Commission, Joint Research Centre, Martin ClaverieEuropean Commission, Joint Research Centre, Pietro FlorioEuropean Commission, Joint Research Ce…

From parcels to people: development of a spatially explicit risk indicator to monitor residential pesticide exposure in agricultural areas
The increase in global pesticide use has mirrored the rising demand for food over the last decades, resulting in a boost in crop yields. However, concerns about the impact of pesticides on biodiversity, ecosystems, and human health, especially for populations residing close to cultivated areas, are growing. This study investigates how exposure and possible risks to residents can be estimated at high spatial granularity based on plant protection product data. The complexities of such analysis we…

Quasi-parton distributions in massive QED2: Towards quantum computation
Sebastian Grieninger, Kazuki Ikeda, Ismail Zahed
https://arxiv.org/abs/2404.05112 h…

Quasi-parton distributions in massive QED2: Towards quantum computation
We analyze the quasi-parton distributions of the lightest $η'$ meson in massive two-dimensional Quantum electrodynamics (QED2) by performing a digital quantum simulation on a classical computer (exact diagonalization). The Hamiltonian and boost operators are mapped onto spin qubits in a spatial lattice with open boundary conditions. The lowest excited state in the exact diagonalization is shown to interpolate continuously between an anomalous $η'$ state at strong coupling,and a non-anomalous …

This https://arxiv.org/abs/2307.00743 has been replaced.
link: https://scholar.google.com/scholar?q=a

Joint Power Allocation and Beamforming for Active IRS-aided Directional Modulation Network
To boost the secrecy rate (SR) of the conventional directional modulation (DM) network and overcome the double fading effect of the cascaded channels of passive intelligent reflecting surface (IRS), a novel active IRS-assisted DM system with a power adjusting strategy between transmitter and active IRS is proposed in this paper. Then, a joint optimization of maximizing the SR is cast by alternately optimizing the power allocation (PA) factors, transmit beamforming, receive beamforming, and refl…

Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice
Tanner Fiez, Houssam Nassif, Arick Chen, Sergio Gamez, Lalit Jain
https://arxiv.org/abs/2402.10870

Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice
Adaptive experimental design (AED) methods are increasingly being used in industry as a tool to boost testing throughput or reduce experimentation cost relative to traditional A/B/N testing methods. However, the behavior and guarantees of such methods are not well-understood beyond idealized stationary settings. This paper shares lessons learned regarding the challenges of naively using AED systems in industrial settings where non-stationarity is prevalent, while also providing perspectives on …

From Compton Scattering of photons on targets to Inverse Compton Scattering of electron and photon beams
Luca Serafini, Vittoria Petrillo
https://arxiv.org/abs/2405.00343

From Compton Scattering of photons on targets to Inverse Compton Scattering of electron and photon beams
We revisit the kinematics of Compton Scattering (electron-photon interactions producing electrons and photons in the exit channel) covering the full range of energy/momenta distribution between the two colliding particles, with a dedicated view to statistical properties of secondary beams that are generated in beam-beam collisions. Starting from the Thomson inverse scattering, where electrons do not recoil and photons are back-scattered to higher energies by a Lorentz boost effect (factor $4γ^…

Speeding Up Path Planning via Reinforcement Learning in MCTS for Automated Parking
Xinlong Zheng, Xiaozhou Zhang, Donghao Xu
https://arxiv.org/abs/2403.17234

Speeding Up Path Planning via Reinforcement Learning in MCTS for Automated Parking
In this paper, we address a method that integrates reinforcement learning into the Monte Carlo tree search to boost online path planning under fully observable environments for automated parking tasks. Sampling-based planning methods under high-dimensional space can be computationally expensive and time-consuming. State evaluation methods are useful by leveraging the prior knowledge into the search steps, making the process faster in a real-time system. Given the fact that automated parking tas…

Generalized boost transformations in finite volumes and application to Hamiltonian methods
Yan Li, Jia-Jun Wu, T. -S. H. Lee, R. D. Young
https://arxiv.org/abs/2404.16702

Generalized boost transformations in finite volumes and application to Hamiltonian methods
The investigation of hadron interactions within lattice QCD has been facilitated by the well-known quantisation condition, linking scattering phase shifts to finite-volume energies. Additionally, the ability to utilise systems at finite total boosts has been pivotal in smoothly charting the energy-dependent behaviour of these phase shifts. The existing implementations of the quantization condition at finite boosts rely on momentum transformations between rest and moving frames, defined directly…

An Effective Networks Intrusion Detection Approach Based on Hybrid Harris Hawks and Multi-Layer Perceptron
Moutaz Alazab, Ruba Abu Khurma, Pedro A. Castillo, Bilal Abu-Salih, Alejandro Martin, David Camacho
https://arxiv.org/abs/2402.14037 https://arxiv.org/pdf/2402.14037
arXiv:2402.14037v1 Announce Type: new
Abstract: This paper proposes an Intrusion Detection System (IDS) employing the Harris Hawks Optimization algorithm (HHO) to optimize Multilayer Perceptron learning by optimizing bias and weight parameters. HHO-MLP aims to select optimal parameters in its learning process to minimize intrusion detection errors in networks. HHO-MLP has been implemented using EvoloPy NN framework, an open-source Python tool specialized for training MLPs using evolutionary algorithms. For purposes of comparing the HHO model against other evolutionary methodologies currently available, specificity and sensitivity measures, accuracy measures, and mse and rmse measures have been calculated using KDD datasets. Experiments have demonstrated the HHO MLP method is effective at identifying malicious patterns. HHO-MLP has been tested against evolutionary algorithms like Butterfly Optimization Algorithm (BOA), Grasshopper Optimization Algorithms (GOA), and Black Widow Optimizations (BOW), with validation by Random Forest (RF), XG-Boost. HHO-MLP showed superior performance by attaining top scores with accuracy rate of 93.17%, sensitivity level of 89.25%, and specificity percentage of 95.41%.

Stability-Oriented Prediction Horizons Design of Generalized Predictive Control for DC/DC Boost Converter
Yuan Li, Subham Sahoo, Sergio Vazquez, Yichao Zhang, Tomislav Dragicevic, Frede Blaabjerg
https://arxiv.org/abs/2404.16391

Stability-Oriented Prediction Horizons Design of Generalized Predictive Control for DC/DC Boost Converter
This paper introduces a novel approach in designing prediction horizons on a generalized predictive control for a DC/DC boost converter. This method involves constructing a closed-loop system model and assessing the impact of different prediction horizons on system stability. In contrast to conventional design approaches that often rely on empirical prediction horizon selection or incorporate non-linear observers, the proposed method establishes a rigorous boundary for the prediction horizon to…

This https://arxiv.org/abs/2305.19115 has been replaced.
link: https://scholar.google.com/scholar?q=a

High-Gain Disturbance Observer for Robust Trajectory Tracking of Quadrotors
This paper presents a simple method to boost the robustness of quadrotors in trajectory tracking. The presented method features a high-gain disturbance observer (HGDO) that provides disturbance estimates in real-time. The estimates are then used in a trajectory control law to compensate for disturbance effects. We present theoretical convergence results showing that the proposed HGDO can quickly converge to an adjustable neighborhood of actual disturbance values. We will then integrate the dist…

Embracing Uncertainty Flexibility: Harnessing a Supervised Tree Kernel to Empower Ensemble Modelling for 2D Echocardiography-Based Prediction of Right Ventricular Volume
Tuan A. Bohoran, Polydoros N. Kampaktsis, Laura McLaughlin, Jay Leb, Gerry P. McCann, Archontis Giannakidis
https://arxiv.org/abs/2403.03229

Embracing Uncertainty Flexibility: Harnessing a Supervised Tree Kernel to Empower Ensemble Modelling for 2D Echocardiography-Based Prediction of Right Ventricular Volume
The right ventricular (RV) function deterioration strongly predicts clinical outcomes in numerous circumstances. To boost the clinical deployment of ensemble regression methods that quantify RV volumes using tabular data from the widely available two-dimensional echocardiography (2DE), we propose to complement the volume predictions with uncertainty scores. To this end, we employ an instance-based method which uses the learned tree structure to identify the nearest training samples to a target …

This https://arxiv.org/abs/2404.07982 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

Language Imbalance Can Boost Cross-lingual Generalisation
Multilinguality is crucial for extending recent advancements in language modelling to diverse linguistic communities. To maintain high performance while representing multiple languages, multilingual models ideally align representations, allowing what is learned in one language to generalise to others. Prior research has emphasised the importance of parallel data and shared vocabulary elements as key factors for such alignment. In this study, we investigate an unintuitive novel driver of cross-l…

This https://arxiv.org/abs/2307.00921 has been replaced.
initial toot: https://mastoxiv.page/@a…

Influence of the Anderson transition on thermoelectric energy conversion in disordered electronic systems
So far, the efficiency of thermoelectric energy conversion remains low compared to traditional technologies, such as coal or nuclear. This low efficiency can be explained by connecting the thermoelastic properties of the electronic working fluid to its transport properties. Such connection also shows that operating close to electronic phase transitions can be an efficient way to boost the thermoelectric energy conversion. In this paper, we analyze thermoelectric efficiency close to the metal-in…

This https://arxiv.org/abs/2312.10832 has been replaced.
link: https://scholar.google.com/scholar?q=a

Moving frame theory of zero-bias photocurrent on the surface of topological insulators
Motivated by observations of zero-biased photocurrent on the surface of topological insulators, we show that the in-plane effective magnetic field $\tilde B$ implements a moving frame transformation on the topological insulators' helical surface states. As a result, photo-excited electrons on the surface undergo a Galilean boost proportional to the effective in-plane magnetic field $\tilde B$. The boost velocity is transversely proportional to $\tilde B$. This explains why the experimentally ob…

Large language models can help boost food production, but be mindful of their risks
Djavan De Clercq, Elias Nehring, Harry Mayne, Adam Mahdi
https://arxiv.org/abs/2403.15475

Large language models can help boost food production, but be mindful of their risks
Coverage of ChatGPT-style large language models (LLMs) in the media has focused on their eye-catching achievements, including solving advanced mathematical problems and reaching expert proficiency in medical examinations. But the gradual adoption of LLMs in agriculture, an industry which touches every human life, has received much less public scrutiny. In this short perspective, we examine risks and opportunities related to more widespread adoption of language models in food production systems.…

This https://arxiv.org/abs/2310.11765 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_nuc…

Causal hydrodynamic fluctuations in a one-dimensional expanding system
We derive equations of motion of hydrodynamic fluctuations performing perturbative expansion of the energy-momentum conservation equations around the boost invariant solution in one-dimensional expanding system. In the course of derivation, we do not assume any specific forms of constitutive equations for shear stress tensor $π^{μν}$ and bulk pressure $Π$. Therefore, the framework enables us to employ any constitutive equations beyond the Navier-Stokes theory which satisfy the causality. Em…

This https://arxiv.org/abs/2401.13562 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Exploiting separation-dependent coherence to boost optical resolution
The problem of resolving point-like light sources not only serves as a benchmark for optical resolution but also holds various practical applications ranging from microscopy to astronomy. In this research, we aim to resolve two thermal sources sharing arbitrary mutual coherence using the spatial mode demultiplexing technique. Our analytical study includes scenarios where the coherence and the emission rate depend on the separation between the sources, and is not limited to the faint sources lim…

This https://arxiv.org/abs/2308.10594 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

Carrollian fluids and spontaneous breaking of boost symmetry
In the hydrodynamic regime, field theories typically have their boost symmetry spontaneously broken due to the presence of a thermal rest frame although the associated Goldstone field does not acquire independent dynamics. We show that this is not the case for Carrollian field theories where the boost Goldstone field plays a central role. This allows us to give a first-principles derivation of the equilibrium currents and dissipative effects of Carrollian fluids. We also demonstrate that the li…

This https://arxiv.org/abs/2403.09852 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

Exploring Self-Gravitating Cylindrical Structures in Modified Gravity: Insights from Scalar-Vector-Tensor Theory
We investigate static cylindrical solutions within an extended theory of modified gravity. By incorporating various coupling functions through a straightforward boost symmetry approach, we establish the equations of motion in a self-consistent manner and subsequently determine the linear scalar field profile. Utilizing analytical methods, we solve the system of equations for the metric functions and the $U(1)$ gauge field, revealing their dependence on Bessel's functions. To comprehend gravito-…

Nonlinear Voltage Regulation of an Auxiliary Energy Storage of a Multiport Interconnection
Felipe Morales, Rafael Cisneros, Romeo Ortega, Antonio Sanchez-Squella
https://arxiv.org/abs/2403.19901

Nonlinear Voltage Regulation of an Auxiliary Energy Storage of a Multiport Interconnection
In this article, we propose a nonlinear voltage control to ensure power exchange in a multiport interconnected system, which consists of a bidirectional DC-DC converter and generating-storing devices. The converter topology under consideration is two-stage, composed of an interconnection of a buck with a boost converter. The motivation for this work is the explosive increase in the use of DC-DC converters due to the massification of renewable energies, electric vehicles powertrains, and energy …

Targeted Parallelization of Conflict-Based Search for Multi-Robot Path Planning
Teng Guo, Jingjin Yu
https://arxiv.org/abs/2402.11768 https://

Targeted Parallelization of Conflict-Based Search for Multi-Robot Path Planning
Multi-Robot Path Planning (MRPP) on graphs, equivalently known as Multi-Agent Path Finding (MAPF), is a well-established NP-hard problem with critically important applications. As serial computation in (near)-optimally solving MRPP approaches the computation efficiency limit, parallelization offers a promising route to push the limit further, especially in handling hard or large MRPP instances. In this study, we initiated a \emph{targeted} parallelization effort to boost the performance of conf…

This https://arxiv.org/abs/2212.04991 has been replaced.
link: https://scholar.google.com/scholar?q=a

Dynamically enhancing qubit-photon interactions with anti-squeezing
The interaction strength of an oscillator to a qubit grows with the oscillator's vacuum field fluctuations. The well known degenerate parametric oscillator has revived interest in the regime of strongly detuned squeezing, where its eigenstates are squeezed Fock states. Owing to these amplified field fluctuations, it was recently proposed that squeezing this oscillator would dynamically boost qubit-photon interactions. In a superconducting circuit experiment, we observe a two-fold increase in th…

From parcels to people: development of a spatially explicit risk indicator to monitor residential pesticide exposure in agricultural areas
Francesco GalimbertiEuropean Commission, Joint Research Centre, Stephanie BoppEuropean Commission, Joint Research Centre, Alessandro CarlettiEuropean Commission, Joint Research Centre, Rui CatarinoEuropean Commission, Joint Research Centre, Martin ClaverieEuropean Commission, Joint Research Centre, Pietro FlorioEuropean Commission, Joint Research Ce…

From parcels to people: development of a spatially explicit risk indicator to monitor residential pesticide exposure in agricultural areas
The increase in global pesticide use has mirrored the rising demand for food over the last decades, resulting in a boost in crop yields. However, concerns about the impact of pesticides on biodiversity, ecosystems, and human health, especially for populations residing close to cultivated areas, are growing. This study investigates how exposure and possible risks to residents can be estimated at high spatial granularity based on plant protection product data. The complexities of such analysis we…

Ironies of Generative AI: Understanding and mitigating productivity loss in human-AI interactions
Auste Simkute, Lev Tankelevitch, Viktor Kewenig, Ava Elizabeth Scott, Abigail Sellen, Sean Rintel
https://arxiv.org/abs/2402.11364

Ironies of Generative AI: Understanding and mitigating productivity loss in human-AI interactions
Generative AI (GenAI) systems offer opportunities to increase user productivity in many tasks, such as programming and writing. However, while they boost productivity in some studies, many others show that users are working ineffectively with GenAI systems and losing productivity. Despite the apparent novelty of these usability challenges, these 'ironies of automation' have been observed for over three decades in Human Factors research on the introduction of automation in domains such as aviati…

Hadron momentum spectra from analytical solutions of relativistic hydrodynamics
Mahammad Sabir Ali, Deeptak Biswas, Amaresh Jaiswal, Sushant K. Singh
https://arxiv.org/abs/2403.00624

Hadron momentum spectra from analytical solutions of relativistic hydrodynamics
We present analytical solution of relativistic hydrodynamics for a system having cylindrical symmetry with boost-invariant longitudinal expansion and Hubble-like transverse expansion. We also consider analytical solution for Hubble-like spherically expanding system. For these two cases, we calculate analytical expression for transverse momentum spectra of hadrons, at constant temperature freeze-out hypersurface using Cooper-Frye prescription. We compare our results for transverse momentum spect…

This https://arxiv.org/abs/2310.11765 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_nuc…

Causal hydrodynamic fluctuations in a one-dimensional expanding system
We derive equations of motion of hydrodynamic fluctuations performing perturbative expansion of the energy-momentum conservation equations around the boost invariant solution in one-dimensional expanding system. In the course of derivation, we do not assume any specific forms of constitutive equations for shear stress tensor $π^{μν}$ and bulk pressure $Π$. Therefore, the framework enables us to employ any constitutive equations beyond the Navier-Stokes theory which satisfy the causality. Em…

Sleep-Like Unsupervised Replay Improves Performance when Data are Limited or Unbalanced
Anthony Bazhenov, Pahan Dewasurendra, Giri Krishnan, Jean Erik Delanois
https://arxiv.org/abs/2402.10956

Sleep-Like Unsupervised Replay Improves Performance when Data are Limited or Unbalanced
The performance of artificial neural networks (ANNs) degrades when training data are limited or imbalanced. In contrast, the human brain can learn quickly from just a few examples. Here, we investigated the role of sleep in improving the performance of ANNs trained with limited data on the MNIST and Fashion MNIST datasets. Sleep was implemented as an unsupervised phase with local Hebbian type learning rules. We found a significant boost in accuracy after the sleep phase for models trained with …

ContextVis: Envision Contextual Learning and Interaction with Generative Models
Bo Shui, Chufan Shi, Yujiu Yang, Xiaomei Nie
https://arxiv.org/abs/2403.12768

ContextVis: Envision Contextual Learning and Interaction with Generative Models
ContextVis introduces a workflow by integrating generative models to create contextual learning materials. It aims to boost knowledge acquisition through the creation of resources with contextual cues. A case study on vocabulary learning demonstrates the effectiveness of generative models in developing educational resources that enrich language understanding and aid memory retention. The system combines an easy-to-use Dashboard for educators with an interactive Playground for learners, establis…

Performance, Knowledge Acquisition and Satisfaction in Self-selected Groups: Evidence from a Classroom Field Experiment
Julius D\"uker, Alexander Rieber
https://arxiv.org/abs/2403.12694

Performance, Knowledge Acquisition and Satisfaction in Self-selected Groups: Evidence from a Classroom Field Experiment
We investigate how to efficiently set up work groups to boost group productivity, individual satisfaction, and learning. Therefore, we conduct a natural field experiment in a compulsory undergraduate course and study differences between self-selected and randomly assigned groups. We find that self-selected groups perform significantly worse on group assignments. Yet, students in self-selected groups learn more and are more satisfied than those in randomly assigned groups. The effect of allowing…

Exploring Self-Gravitating Cylindrical Structures in Modified Gravity: Insights from Scalar-Vector-Tensor Theory
Davood Momeni, Phongpichit Channuie, Mudhhair Al-Ajmi
https://arxiv.org/abs/2403.09852

Exploring Self-Gravitating Cylindrical Structures in Modified Gravity: Insights from Scalar-Vector-Tensor Theory
We investigate static cylindrical solutions within an extended theory of modified gravity. By incorporating various coupling functions through a straightforward boost symmetry approach, we establish the equations of motion in a self-consistent manner and subsequently determine the linear scalar field profile. Utilizing analytical methods, we solve the system of equations for the metric functions and the $U(1)$ gauge field, revealing their dependence on Bessel's functions. To comprehend gravito-…

This https://arxiv.org/abs/2403.03968 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Beneath the Surface: Revealing Deep-Tissue Blood Flow in Human Subjects with Massively Parallelized Diffuse Correlation Spectroscopy
Diffuse Correlation Spectroscopy (DCS) allows the label-free investigation of microvascular dynamics deep within living tissue. However, common implementations of DCS are currently limited to measurement depths of $\sim 1-1.5cm$, which can limit the accuracy of cerebral hemodynamics measurement. Here we present massively parallelized DCS (pDCS) using novel single photon avalanche detector (SPAD) arrays with up to 500x500 individual channels. The new SPAD array technology can boost the signal-to…

The Influence of Extended Reality and Virtual Characters' Embodiment Levels on User Experience in Well-Being Activities
Tanja Koji\'c, Maurizio Vergari, Marco Podratz, Sebastian M\"oller, Jan-Niklas Voigt-Antons
https://arxiv.org/abs/2403.09879

The Influence of Extended Reality and Virtual Characters' Embodiment Levels on User Experience in Well-Being Activities
Millions of people have seen their daily habits transform, reducing physical activity and leading to mental health issues. This study explores how virtual characters impact motivation for well-being. Three prototypes with cartoon, robotic, and human-like avatars were tested by 22 participants. Results show that animated virtual avatars, especially with extended reality, boost motivation, enhance comprehension of activities, and heighten presence. Multiple output modalities, like audio and text,…

This https://arxiv.org/abs/2402.00095 has been replaced.
link: https://scholar.google.com/scholar?q=a

New Rotating Black Hole Solutions With Imperfect Fluid Energy-Momentum Tensor In $f(R)$ Gravity
We find a new class of exact solutions for rotating black holes in $f(R)$ gravity in presence of imperfect fluid. We find that the exact solutions are holographically dual to a hidden conformal field theory. Moreover we consider another class of exact solutions for rotating black holes in $f(R)$ gravity, which is obtained through a Lorentz boost transformation on a static spherical symmetry solutions in $f(R)$ gravity. We also find that the boosted exact solutions are holographically dual to a …

Being Heterogeneous Is Advantageous: Extreme Brownian Non-Gaussian Searches
Vittoria Sposini, Sankaran Nampoothiri, Aleksei Chechkin, Enzo Orlandini, Flavio Seno, Fulvio Baldovin
https://arxiv.org/abs/2403.10143

Being Heterogeneous Is Advantageous: Extreme Brownian Non-Gaussian Searches
Redundancy in biology may be explained by the need to optimize extreme searching processes, where one or few among many particles are requested to reach the target like in human fertilization. We show that non-Gaussian rare fluctuations in Brownian diffusion dominates such searches, introducing drastic corrections to the known Gaussian behavior. Our demonstration entails different physical systems and pinpoints the relevance of diversity within redundancy to boost fast targeting. We sketch an e…

A Unified Toll Lane Framework for Autonomous and High-Occupancy Vehicles in Interactive Mixed Autonomy
Ruolin Li, Philip N. Brown, Roberto Horowitz
https://arxiv.org/abs/2403.14011

A Unified Toll Lane Framework for Autonomous and High-Occupancy Vehicles in Interactive Mixed Autonomy
In this study, we introduce a toll lane framework that optimizes the mixed flow of autonomous and high-occupancy vehicles on freeways, where human-driven and autonomous vehicles of varying commuter occupancy share a segment. Autonomous vehicles, with their ability to maintain shorter headways, boost traffic throughput. Our framework designates a toll lane for autonomous vehicles with high occupancy to use free of charge, while others pay a toll. We explore the lane choice equilibria when all ve…

Exploring Self-Gravitating Cylindrical Structures in Modified Gravity: Insights from Scalar-Vector-Tensor Theory
Davood Momeni, Phongpichit Channuie, Mudhhair Al-Ajmi
https://arxiv.org/abs/2403.09852

Exploring Self-Gravitating Cylindrical Structures in Modified Gravity: Insights from Scalar-Vector-Tensor Theory
We investigate static cylindrical solutions within an extended theory of modified gravity. By incorporating various coupling functions through a straightforward boost symmetry approach, we establish the equations of motion in a self-consistent manner and subsequently determine the linear scalar field profile. Utilizing analytical methods, we solve the system of equations for the metric functions and the $U(1)$ gauge field, revealing their dependence on Bessel's functions. To comprehend gravito-…

Energy-dependent Boosted Dark Matter from Diffuse Supernova Neutrino Background
Anirban Das, Tim Herbermann, Manibrata Sen, Volodymyr Takhistov
https://arxiv.org/abs/2403.15367

Energy-dependent Boosted Dark Matter from Diffuse Supernova Neutrino Background
Diffuse neutrinos from past supernovae in the Universe present us with a unique opportunity to test dark matter (DM) interactions. These neutrinos can scatter and boost the DM particles in the Milky Way halo to relativistic energies allowing us to detect them in terrestrial laboratories. Focusing on generic models of DM-neutrino and electron interactions, mediated by a vector or a scalar boson, we implement energy-dependent scattering cross-sections and perform detailed numerical analysis of DM…

Being Heterogeneous Is Advantageous: Extreme Brownian Non-Gaussian Searches
Vittoria Sposini, Sankaran Nampoothiri, Aleksei Chechkin, Enzo Orlandini, Flavio Seno, Fulvio Baldovin
https://arxiv.org/abs/2403.10143

Being Heterogeneous Is Advantageous: Extreme Brownian Non-Gaussian Searches
Redundancy in biology may be explained by the need to optimize extreme searching processes, where one or few among many particles are requested to reach the target like in human fertilization. We show that non-Gaussian rare fluctuations in Brownian diffusion dominates such searches, introducing drastic corrections to the known Gaussian behavior. Our demonstration entails different physical systems and pinpoints the relevance of diversity within redundancy to boost fast targeting. We sketch an e…

Being Heterogeneous Is Advantageous: Extreme Brownian Non-Gaussian Searches
Vittoria Sposini, Sankaran Nampoothiri, Aleksei Chechkin, Enzo Orlandini, Flavio Seno, Fulvio Baldovin
https://arxiv.org/abs/2403.10143

Being Heterogeneous Is Advantageous: Extreme Brownian Non-Gaussian Searches
Redundancy in biology may be explained by the need to optimize extreme searching processes, where one or few among many particles are requested to reach the target like in human fertilization. We show that non-Gaussian rare fluctuations in Brownian diffusion dominates such searches, introducing drastic corrections to the known Gaussian behavior. Our demonstration entails different physical systems and pinpoints the relevance of diversity within redundancy to boost fast targeting. We sketch an e…