Ilhan Omar is under investigation for her skyrocketing wealth... as she berates reporters for questioning her about'fraud' Trump puts $1 BILLION price tag on membership for his new'UN replacement'... and the president'will control ALL the money' Iconic '90s femme fatale Men In Black star hasn't been seen in 16 years... now the Daily Mail reveals distressing truth behind her disappearance Investigator reveals hidden clues in Ellen Greenberg's crime scene photos that PROVE bride-to-be was brutally murdered CBS News's star anchor caught on tape caving to Trump's demands as president issues blunt two-word warning over interview'edits' Jane Fonda, 88, is pushed in wheelchair at airport after Reiner murders left her'reeling' NFL fans fume Bills-Broncos was'rigged' as controversial late call sparks debate: 'Completely scripted' A-list pop star is unrecognizable in Saturday Night Live cameo... can YOU guess who she is? Read Melissa Gilbert's begging letter in defense of husband Timothy Busfield as she claims West Wing star is'honorable and compassionate' despite child sex allegations Nicole Kidman's subtle but devastating digs at Keith Urban revealed... as insiders claim country star has MOVED IN with new squeeze Secrets of one of America's oldest grocery stores that shuns self-checkouts and welcomes rich and famous customers The'marry me' sex move that'll make even the most commitment-phobic of men beg to see you again... and it worked for THREE of my friends Secret ranking of NFL WAGs revealed: From a'jealous' ex-cheerleader to the'annoying queen'... meet the stunning sideline spouses raking in MILLIONS Infectious disease expert reveals viruses to worry about as'super flu' overwhelms US... including one that could put the world'on cusp of a pandemic' Mysterious new owner of Wyoming ranch bigger than Rhode Island is unmasked amid speculation Ukraine's Zelensky was circling Sales of Toyota's EV stall as furious drivers say'impossible to fuel' cars have landed them in debt nightmare Criminal investigation launched into Renee Good's wife for'impeding' ICE agents before shooting My beautiful, brilliant wife took her final breath 10 years ago. I didn't think I would survive... then I witnessed something miraculous that as a scientist I just can't explain Dark side of America's favorite vacation hotspot... where women are subjected to the most horrific sex attacks imaginable No matter how harmonious your workplace might be, what temperature to set the thermostat seems to be the one thing that no one can ever agree on. Luckily, scientists have now revealed the ideal temperature to keep everyone happy - and it might be a little warmer than some people expect. According to research conducted by home heating experts BOXT, Britons feel happiest, calmest, and most productive at a balmy 21 C (70 F).

As intelligent systems are developed across diverse substrates - from machine learning models and neuromorphic hardware to in vitro neural cultures - understanding what gives a system agency has become increasingly important. Existing definitions, however, tend to rely on top-down descriptions that are difficult to quantify. We propose a bottom-up framework grounded in a system's information-processing order: the extent to which its transformation of input evolves over time. We identify three orders of information processing. Class I systems are reactive and memoryless, mapping inputs directly to outputs. Class II systems incorporate internal states that provide memory but follow fixed transformation rules. Class III systems are adaptive; their transformation rules themselves change as a function of prior activity. While not sufficient on their own, these dynamics represent necessary informational conditions for genuine agency. This hierarchy offers a measurable, substrate-independent way to identify the informational precursors of agency. We illustrate the framework with neurophysiological and computational examples, including thermostats and receptor-like memristors, and discuss its implications for the ethical and functional evaluation of systems that may exhibit agency.

Stochastic gradient Langevin dynamics and its variants approximate the likelihood of an entire dataset, via random (and typically much smaller) subsets, in the setting of Bayesian sampling. Due to the (often substantial) improvement of the computational efficiency, they have been widely used in large-scale machine learning applications. It has been demonstrated that the so-called covariance-controlled adaptive Langevin (CCAdL) thermostat, which incorporates an additional term involving the covariance matrix of the noisy force, outperforms popular alternative methods. A moving average is used in CCAdL to estimate the covariance matrix of the noisy force, in which case the covariance matrix will converge to a constant matrix in long-time limit. Moreover, it appears in our numerical experiments that the use of a moving average could reduce the stability of the numerical integrators, thereby limiting the largest usable stepsize. In this article, we propose a modified CCAdL (i.e., mCCAdL) thermostat that uses the scaling part of the scaling and squaring method together with a truncated Taylor series approximation to the exponential to numerically approximate the exact solution to the subsystem involving the additional term proposed in CCAdL. We also propose a symmetric splitting method for mCCAdL, instead of an Euler-type discretisation used in the original CCAdL thermostat. We demonstrate in our numerical experiments that the newly proposed mCCAdL thermostat achieves a substantial improvement in the numerical stability over the original CCAdL thermostat, while significantly outperforming popular alternative stochastic gradient methods in terms of the numerical accuracy for large-scale machine learning applications.

Fulu sets repair bounties on consumer products that employ sneaky features that limit user control. Just this week, it awarded more than $10,000 to the person who hacked the Molekule air purifier. Companies tend to be rather picky about who gets to poke around inside their products. Manufacturers sometimes even take steps that prevent consumers from repairing their device when it breaks, or modifying it with third-party products. But those unsanctioned device modifications have become the raison d'être of a bounty program set up by a nonprofit called Fulu, or Freedom from Unethical Limitations on Users.

Dynamics-based Markov Chain Monte Carlo methods (D-MCMCs) are sampling methods using dynamics simulation for state transition in a Markov chain.

Hamiltonian system built on the distribution of interest.

Hamiltonian system built on the distribution of interest.

We introduce ToPolyAgent, a multi-agent AI framework for performing coarse-grained molecular dynamics (MD) simulations of topological polymers through natural language instructions. By integrating large language models (LLMs) with domain-specific computational tools, ToPolyAgent supports both interactive and autonomous simulation workflows across diverse polymer architectures, including linear, ring, brush, and star polymers, as well as dendrimers. The system consists of four LLM-powered agents: a Config Agent for generating initial polymer-solvent configurations, a Simulation Agent for executing LAMMPS-based MD simulations and conformational analyses, a Report Agent for compiling markdown reports, and a Workflow Agent for streamlined autonomous operations. Interactive mode incorporates user feedback loops for iterative refinements, while autonomous mode enables end-to-end task execution from detailed prompts. We demonstrate ToPolyAgent's versatility through case studies involving diverse polymer architectures under varying solvent condition, thermostats, and simulation lengths. Furthermore, we highlight its potential as a research assistant by directing it to investigate the effect of interaction parameters on the linear polymer conformation, and the influence of grafting density on the persistence length of the brush polymer. By coupling natural language interfaces with rigorous simulation tools, ToPolyAgent lowers barriers to complex computational workflows and advances AI-driven materials discovery in polymer science. It lays the foundation for autonomous and extensible multi-agent scientific research ecosystems.

Our framework, HARMONIC (Human-AI Robotic Team Member Operating with Natural Intelligence and Communication, Figure 1), is an implemented dual-control cognitive robotic architecture featuring distinct layers of strategic reasoning and tactical, skill-level control [20]. This approach advances the hybrid control systems and architectures reviewed by Dennis et al. [21] and contrasts with DIARC's [22], [23] integration strategy, which embeds the strategic layer within the tactical layer to support concurrent operation. The strategic layer of HARMONIC adapts a mature cognitive architecture, OntoAgent [24], [25], [17] for high-level reasoning, leveraging explicit, structured knowledge representations that can be inspected, verified, and incre-mentally expanded.

Fox News senior national correspondent William La Jeunesse reports on proposed changes to California's electric bills on'Special Report.' Power saver programs are utility-sponsored demand response initiatives that help reduce electricity usage during periods of peak demand. These programs typically target central air conditioners (AC) and heat pumps, since cooling equipment drives spikes in summer energy demand. In exchange for incentives such as bill credits or rebates, participating homeowners allow the utility to temporarily adjust or cycle their HVAC systems on hot days. I recently received an email from Leah, an HVAC professional based in Rio Rancho, New Mexico.