eLife

Contractile peri-nuclear actomyosin network repositions peripheral and polar chromosomes to promote early kinetochore–microtubule interactions

This important study demonstrates that a peri-nuclear actomyosin network, present in some types of human cells, facilitates kinetochore-spindle attachment of chromosomes in unfavorable locations - ...
Journal of Accountancy

AI tools for finance professionals to prepare and visualize data

AI tools are frequently used in data visualization — this article describes how they can make data preparation more efficient ...
eLife

Arousal modulates functional connectivity through structured and hemispherically asymmetric community architecture during wakefulness

Arousal fluctuates continuously during wakefulness, yet how these moment-to-moment variations shape large-scale functional connectivity (FC) remains unclear. Here, we combined 7T fMRI with concurrent ...
Unite.AI

Easy Rewording Breaks AI Safety, Even for Gemini and Claude

AI safety tests found to rely on 'obvious' trigger words; with easy rephrasing, models labeled 'reasonably safe' suddenly fail, with attacks succeeding up to 98% of the time. New corporate research ...
Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
Edutopia

Making Use of a Worked Example to Improve Learning

It’s a familiar moment in math class—students are asked to solve a problem, and some jump in confidently while others freeze, unsure where to begin. When students don’t yet have a clear mental model ...
IEEE

Direct Spectral Clustering With New Graph Learning for Better Fitting

Abstract: Traditional spectral clustering methods struggle with scalability and robustness in large datasets due to their reliance on similarity matrices and EigenValue Decomposition. We introduce two ...
IEEE

Deep Incomplete Multi-View Clustering via Dynamic Imputation and Triple Alignment With Dual Optimization

Abstract: In recent years, Incomplete Multi-View Clustering (IMVC) has become an important and challenging task. Although several methods have been proposed to address IMVC, they still have the ...
Engadget

You can turn a cluster of Macs into an AI supercomputer in macOS Tahoe 26.2

Who needs a revamped Mac Pro when you can just turn several Mac Studios into a unified computing system? With the upcoming macOS Tahoe 26.2 release, Apple is introducing a new low-latency feature that ...
Scientific Research Publishing

On Prediction of Stock Return and Volatility Using Clustering Techniques: Taking an Example of Japanese Stock Market ()

Graduate School of Economics, The University of Osaka, Osaka, Japan. Stock returns exhibit nonlinear dynamics and volatility clustering. It is well known that we cannot forecast the movements of stock ...
marktechpost

What is Asyncio? Getting Started with Asynchronous Python and Using Asyncio in an AI Application with an LLM

In many AI applications today, performance is a big deal. You may have noticed that while working with Large Language Models (LLMs), a lot of time is spent waiting—waiting for an API response, waiting ...