Tootfinder

Amazon rolls out a generative AI feature that creates a product page, including a description and images, using information from a seller's external website (Emilia David/The Verge)
https://www.theverge.com/2024/3/13/24099685/amazon-generative…

Amazon will let sellers paste a link so AI can make a product page
Amazon will begin rolling out the new AI tool that lets sellers paste a link to generate product pages to US users soon.

New in Kitten¹: Markdown fragments
You can now write your Markdown in separate .fragment.md files and `import()` them as if they were JavaScript modules, just like you can with HTML and CSS fragments.
And while they don’t support props, they do support slots (including named slots, which you can use as poor man’s props.)
Enjoy!
:kitten: 💕
¹

app
A web development kit that’s small, purrs, and loves you.

Ok I installed it and checked their about page. Same version is listed 🤷🏼

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Page Transitions API just got a shout out at I/O. Props to @… for all his hard work on this spec

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AI-powered Fraud Detection in Decentralized Finance: A Project Life Cycle Perspective
In recent years, blockchain technology has introduced decentralized finance (DeFi) as an alternative to traditional financial systems. DeFi aims to create a transparent and efficient financial ecosystem using smart contracts and emerging decentralized applications. However, the growing popularity of DeFi has made it a target for fraudulent activities, resulting in losses of billions of dollars due to various types of frauds. To address these issues, researchers have explored the potential of ar…

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Tightly Bounded Polynomials via Flexible Discretizations for Dynamic Optimization Problems
Polynomials are widely used to represent the trajectories of states and/or inputs. It has been shown that a polynomial can be bounded by its coefficients, when expressed in the Bernstein basis. However, in general, the bounds provided by the Bernstein coefficients are not tight. We propose a method for obtaining numerical solutions to dynamic optimization problems, where a flexible discretization is used to achieve tight polynomial bounds. The proposed method is used to solve a constrained cart…

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Magnetic activity of red giants: correlation between the amplitude of solar-like oscillations and chromospheric indicators
Previous studies have found that red giants (RGs) in close binary systems undergoing spin-orbit resonance exhibit an enhanced level of magnetic activity with respect to single RGs rotating at the same rate, from measurements of photometric variability $S'_{ph}$ and chromospheric emission S-index $S_{Ca_{II}}$. Here, we consider a sample of 4465 RGs observed by the NASA Kepler mission to measure additional activity indicators that probe different heights in the chromosphere: the near-ultraviolet…

[2024-03-14 Thu (UTC), 2 new articles found for cs.PL Programming Languages]

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The what field?

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Primal-Dual iLQR
We introduce a new algorithm for solving unconstrained discrete-time optimal control problems. Our method follows a direct multiple shooting approach, and consists of applying the SQP method together with an $\ell_2$ augmented Lagrangian primal-dual merit function. We use the LQR algorithm to efficiently solve the primal-dual SQP problem. As our algorithm is a specialization of NPSQP (Gill et al. 1992), it inherits its generic properties, including global convergence, fast local convergence, an…

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Outflows Driven from a Magnetic Pseudodisk
Outflows play a pivotal role in star formation as one of its most visible markers and a means of transporting mass, momentum, and angular momentum from the infalling gas into the surrounding molecular cloud. Their wide reach (at least thousands of au) is a contrast to typical disk sizes ($\sim 10-100$ au). We employ high-resolution three-dimensional nested-grid nonideal magnetohydrodynamic (MHD) simulations to study outflow properties in the Class 0 phase. We find that no disk wind is driven fr…

[2024-05-14 Tue (UTC), 6 new articles found for math.GR Group Theory]

[2024-05-14 Tue (UTC), 1 new article found for math.AT Algebraic Topology]

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A globalization of L-BFGS for nonconvex unconstrained optimization
We present a modified limited memory BFGS (L-BFGS) method that converges globally and linearly for nonconvex objective functions. Its distinguishing feature is that it turns into L-BFGS if its iterates cluster at a point near which the objective is strongly convex with Lipschitz gradients, thereby inheriting the outstanding effectiveness of the classical method. These strong convergence guarantees are enabled by a novel form of cautious updating, where it is decided anew in each iteration which…

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Full L- and M-band high resolution spectroscopy of the S CrA binary disks with VLT-CRIRES+
The Cryogenic IR echelle Spectrometer (CRIRES) instrument at the Very Large Telescope (VLT) was in operation from 2006 to 2014. Great strides in characterizing the inner regions of protoplanetary disks were made using CRIRES observations in the L- and M-band at this time. The upgraded instrument, CRIRES+, became available in 2021 and covers a larger wavelength range simultaneously. Here we present new CRIRES+ Science Verification data of the binary system S Coronae Australis (S CrA). We aim to …

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Average Cost Optimality of Partially Observed MDPS: Contraction of Non-linear Filters, Optimal Solutions and Approximations
The average cost optimality is known to be a challenging problem for partially observable stochastic control, with few results available beyond the finite state, action, and measurement setup, for which somewhat restrictive conditions are available. In this paper, we present explicit and easily testable conditions for the existence of solutions to the average cost optimality equation where the state space is compact. In particular, we present a new contraction based analysis, which is new to th…

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A Universal Trust-Region Method for Convex and Nonconvex Optimization
This paper presents a universal trust-region method simultaneously incorporating quadratic regularization and the ball constraint. We introduce a novel mechanism to set the parameters in the proposed method that unifies the analysis for convex and nonconvex optimization. Our method exhibits an iteration complexity of $\tilde O(ε^{-3/2})$ to find an approximate second-order stationary point for nonconvex optimization. Meanwhile, the analysis reveals that the universal method attains an $O(ε^{-…

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Cardinality and Representation of Stone Relation Algebras
Previous work has axiomatised the cardinality operation in relation algebras, which counts the number of edges of an unweighted graph. We generalise the cardinality axioms to Stone relation algebras, which model weighted graphs, and study the relationships between various axioms for cardinality. This results in simpler cardinality axioms also for relation algebras. We give sufficient conditions for the representability of Stone relation algebras and for Stone relation algebras to be relation al…

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The Exponential Stabilization of a Heat and Piezoelectric Beam Interaction with Static or Hybrid Feedback Controllers
This study investigates a strongly-coupled system of partial differential equations (PDE) governing heat transfer in a copper rod, longitudinal vibrations, and total charge accumulation at electrodes within a magnetizable piezoelectric beam. Conducted within the transmission line framework, the analysis reveals profound interactions between traveling electromagnetic and mechanical waves in magnetizable piezoelectric beams, despite disparities in their velocities. Findings suggest that in the op…

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Is Interpretable Machine Learning Effective at Feature Selection for Neural Learning-to-Rank?
Lijun Lyu, Nirmal Roy, Harrie Oosterhuis, Avishek Anand
https://arxiv.org/abs/2405.07782

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Distributed Gradient Tracking Methods with Guarantees for Computing a Solution to Stochastic MPECs
We consider a class of hierarchical multi-agent optimization problems over networks where agents seek to compute an approximate solution to a single-stage stochastic mathematical program with equilibrium constraints (MPEC). MPECs subsume several important problem classes including Stackelberg games, bilevel programs, and traffic equilibrium problems, to name a few. Our goal in this work is to provably resolve stochastic MPECs in distributed regimes where the agents only have access to their loc…

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[2024-05-14 Tue (UTC), 10 new articles found for cs.IR Information Retrieval]

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Shape Optimization of hemolysis for shear thinning flows in moving domains
We consider the $3$D problem of shape optimization of blood flows in moving domains. Such a geometry is adopted to take into account the modeling of rotating systems and blood pumps for instance. The blood flow is described by generalized Navier-Stokes equations, in the particular case of shear-thinning flows. For a sequence of converging moving domains, we show that a sequence of associated solutions to blood equations converges to a solution of the problem written on the limit moving domain. …

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Real-Time Bidding Strategy of Energy Storage in an Energy Market with Carbon Emission Allocation Based on Aumann-Shapley Prices
Energy storage (ES) can help decarbonize power systems by transferring green renewable energy across time. How to unlock the potential of ES in cutting carbon emissions by appropriate market incentives has become a crucial, albeit challenging, problem. This paper fills the research gap by proposing a novel electricity market with carbon emission allocation and then investigating the real-time bidding strategy of ES in the proposed market. First, a carbon emission allocation mechanism based on A…

Comprehensive Analysis of Access Control Models in Edge Computing: Challenges, Solutions, and Future Directions
Tao Xue, Ying Zhang, Haibin Zhang
https://arxiv.org/abs/2405.07685 …

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Adaptive observer and control of spatiotemporal delayed neural fields
An adaptive observer is proposed to estimate the synaptic distribution between neurons asymptotically from the measurement of a part of the neuronal activity and a delayed neural field evolution model. The convergence of the observer is proved under a persistency of excitation condition. Then, the observer is used to derive a feedback law ensuring asymptotic stabilization of the neural fields. Finally, the feedback law is modified to ensure simultaneously practical stabilization of the neural f…

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Randomized Kaczmarz in Adversarial Distributed Setting
Developing large-scale distributed methods that are robust to the presence of adversarial or corrupted workers is an important part of making such methods practical for real-world problems. In this paper, we propose an iterative approach that is adversary-tolerant for convex optimization problems. By leveraging simple statistics, our method ensures convergence and is capable of adapting to adversarial distributions. Additionally, the efficiency of the proposed methods for solving convex problem…

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Subgame-perfect equilibrium strategies for time-inconsistent recursive stochastic control problems
We study time-inconsistent recursive stochastic control problems, i.e., for which the Bellman principle of optimality does not hold. For this class of problems classical optimal controls may fail to exist, or to be relevant in practice, and dynamic programming is not easily applicable. Therefore, the notion of optimality is defined through a game-theoretic framework by means of subgame perfect equilibrium: we interpret our preference changes which, realistically, are inconsistent over time, as …

Early phase simultaneous multi-band observations of Type II supernova SN 2024ggi with Mephisto
Xinlei Chen, Brajesh Kumar, Xinzhong Er, Helong Guo, Yuan-Pei Yang, Weikang Lin, Yuan Fang, Guowang Du, Chenxu Liu, Jiewei Zhao, Tianyu Zhang, Yuxi Bao, Xingzhu Zou, Yu Pan, Yu Wang, Xufeng Zhu, Kaushik Chatterjee, Xiangkun Liu, Dezi Liu, Edoardo P. Lagioia, Geeta Rangwal, Shiyan Zhong, Jinghua Zhang, Jianhui Lian, Yongzhi Cai, Yangwei Zhang, Xiaowei Liu

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Relativistic Binary Precession: Impact on Eccentric Binary Accretion and Multi-Messenger Astronomy
Stanislav DeLaurentiis, Zoltan Haiman, John Ryan Westernacher-Schneider, Luke Major Krauth, Jordy Davelaar, Jonathan Zrake, Andrew MacFadyen
https://arxiv.org/abs/2405.07897

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Prospects for detection of the pair-echo emission from TeV gamma-ray bursts
D. Miceli, P. Da Vela, E. Prandini
https://arxiv.org/abs/2405.07831 https://

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Long term variability of Cygnus X-1. VIII. A spectral-timing look at low energies with NICER
Ole K\"onig, Guglielmo Mastroserio, Thomas Dauser, Mariano M\'endez, Jingyi Wang, Javier A. Garc\'ia, James F. Steiner, Katja Pottschmidt, Ralf Ballhausen, Riley M. Connors, Federico Garc\'ia, Victoria Grinberg, David Horn, Adam Ingram, Erin Kara, Timothy R. Kallman, Matteo Lucchini, Edward Nathan, Michael A. Nowak, Philipp Thalhammer, Michiel van der Klis, J\"orn Wilms

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The Red Supergiant Progenitor of Type II Supernova 2024ggi
Danfeng Xiang, Jun Mo, Xiaofeng Wang, Lingzhi Wang, Jujia Zhang, Han Lin, Liyang Chen, Cuiying Song, Liang-Duan Liu, Zhenyu Wang, Gaici Li
https://arxiv.org/abs/2405.07699

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High-energy neutrinos from late-time jets of gamma-ray bursts with cocoon photons
Riki Matsui, Shigeo S Kimura, Hamid Hamidani
https://arxiv.org/abs/2405.07695

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Discovery of Very-high-energy Gamma-ray Emissions from the Low Luminosity AGN NGC 4278 by LHAASO
Zhen Cao, F. Aharonian, Q. An, Axikegu, Y. X. Bai, Y. W. Bao, D. Bastieri, X. J. Bi, Y. J. Bi, J. T. Cai, Q. Cao, W. Y. Cao, Zhe Cao, J. Chang, J. F. Chang, A. M. Chen, E. S. Chen, Liang Chen, Lin Chen, Long Chen, M. J. Chen, M. L. Chen, Q. H. Chen, S. H. Chen, S. Z. Chen, T. L. Chen, Y. Chen, N. Cheng, Y. D. Cheng, M. Y. Cui, S. W. Cui, X. H. Cui, Y. D. Cui, B. Z. Dai, H. L. Dai, Z. G. Da…

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Tidal disruption event AT2020ocn: early-time X-ray flares caused by a possible disc alignment process
Z. Cao, P. G. Jonker, D. R. Pasham, S. Wen, N. C. Stone, A. I. Zabludoff
https://arxiv.org/abs/2405.07642

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Discovery of a shock-compressed magnetic field in the north-western rim of the young supernova remnant RX J1713.7-3946 with X-ray polarimetry
Riccardo Ferrazzoli, Dmitry Prokhorov, Niccol\`o Bucciantini, Patrick Slane, Jacco Vink, Martina Cardillo, Yi-Jung Yang, Stefano Silvestri, Ping Zhou, Enrico Costa, Nicola Omodei, C. -Y. Ng, Paolo Soffitta, Martin C. Weisskopf, Luca Baldini, Alessandro Di Marco, Victor Doroshenko, Jeremy Heyl, Philip Kaaret, Dawoon E. Kim, Fr\'ed\'eric Ma…

A systematic study of the ultra-fast outflow responses to luminosity variations in active galactic nuclei
Yerong Xu, Ciro Pinto, Daniele Rogantini, Didier Barret, Stefano Bianchi, Matteo Guainazzi, Jacobo Ebrero, William Alston, Erin Kara, Giancarlo Cusumano
https://arxiv.org/abs/2405.07494<…

The Energy Sources, the Physical Properties, and the Mass-loss History of SN 2017dio
Deng-Wang Shi, Shan-Qin Wang, Wen-Pei Gan, En-Wei Liang
https://arxiv.org/abs/2405.07485