Tootfinder

Top five NFL draft values of the millennium at WR: Tyreek Hill, Justin Jefferson bring booming returns https://www.nfl.com/news/best-nfl-draft-values-of-the-millennium-wide-receiver

Brazil’s Chamber of Deputies Approves Bill Banning Cosmetic Testing on Live Vertebrates https://vegconomist.com/politics-law/brazil-approves-bill-banning-cosmetic-testing-live-vertebrates/

Brazil's Chamber of Deputies Approves Bill Banning Cosmetic Testing on Live Vertebrates - vegconomist - the vegan business magazine
Brazil's Chamber of Deputies has approved the Senate's substitute text for a bill that would ban the testing of cosmetics, personal hygiene products, and

Russia turns to Kyrgyzstan’s booming crypto sector to evade sanctions, researchers say https://therecord.media/russia-turns-to-kyrgystan-crypto-sanctions

Oh, good grief. Banning "Calvin & Hobbes" books? This is what happens when people don't think critically and look at things out of context. "They Called Us Enemy?" Yeah, heaven forbid kids learn about #WW2 history. #TN

‘Magic Tree House’ Author, ‘Calvin and Hobbes’ among hundreds of Tennessee book bans - PEN America
The removals in Tennessee are the result of a growing political movement to control information through book banning.

Diffraction and Scattering Modeling for Laser Power Beaming in Lunar Environment
Yanni Jiwan-Mercier, Bar{\i}\c{s} D\"onmez, G\"une\c{s} Karabulut-Kurt, S\'ebastien Loranger
https://arxiv.org/abs/2507.13982

Diffraction and Scattering Modeling for Laser Power Beaming in Lunar Environment
Reliable energy delivery is a critical requirement for long-term lunar missions, particularly in regions with limited solar access, such as polar craters and during extended lunar nights. Optical Power Beaming (OPB) using high-power lasers offers a promising alternative to conventional solar power, but the effects of suspended lunar dust on beam propagation remain poorly understood. This study introduces a detailed simulation model that incorporates both diffraction and height-dep…

LEKIA: A Framework for Architectural Alignment via Expert Knowledge Injection
Boning Zhao, Yutong Hu
https://arxiv.org/abs/2507.14944 https://

LEKIA: A Framework for Architectural Alignment via Expert Knowledge Injection
Deploying Large Language Models (LLMs) in high-stakes domains is impeded by a dual challenge: the need for deep, dynamic expert knowledge injection and nuanced value alignment. Prevailing paradigms often address these challenges separately, creating a persistent tension between knowledge and alignment; knowledge-focused methods like Retrieval-Augmented Generation (RAG) have limited deep alignment capabilities, while alignment-focused methods like Reinforcement Learning from Human Feedback (RLHF…

Ohio lawmakers to introduce bill banning abortion, criminalizing the procedure (Mary Kekatos/ABC News)
https://abcnews.go.com/Health/ohio-lawmakers-introduce-bill-banning-abortion-criminalizing-procedure/story?id=122922580
http://www.memeorandum.com/250617/p160#a250617p160

Oregon just passed a law stopping schools from banning books just because LGBTQ people wrote them - LGBTQ Nation
https://www.lgbtqnation.com/2025/06/oregon-just-passed-a-law-stopping-schools-from-banning-books-just-because-lgbtq-people-wrote-them/

Towards a Proactive Autoscaling Framework for Data Stream Processing at the Edge using GRU and Transfer Learning
Eugene Armah, Linda Amoako Bannning
https://arxiv.org/abs/2507.14597

Towards a Proactive Autoscaling Framework for Data Stream Processing at the Edge using GRU and Transfer Learning
Processing data at high speeds is becoming increasingly critical as digital economies generate enormous data. The current paradigms for timely data processing are edge computing and data stream processing (DSP). Edge computing places resources closer to where data is generated, while stream processing analyzes the unbounded high-speed data in motion. However, edge stream processing faces rapid workload fluctuations, complicating resource provisioning. Inadequate resource allocation leads to bot…

A Distributional View of High Dimensional Optimization
Felix Benning
https://arxiv.org/abs/2507.16315 https://arxiv.org/pdf/2507.1631…

A Distributional View of High Dimensional Optimization
This PhD thesis presents a distributional view of optimization in place of a worst-case perspective. We motivate this view with an investigation of the failure point of classical optimization. Subsequently we consider the optimization of a randomly drawn objective function. This is the setting of Bayesian Optimization. After a review of Bayesian optimization we outline how such a distributional view may explain predictable progress of optimization in high dimension. It further turns out that th…