Results 11 to 20 of about 195 (118)

Are physiological oscillations physiological?

The Journal of Physiology, EarlyView., 2023
Abstract figure legend Mechanisms and functions of physiological oscillations. Abstract Despite widespread and striking examples of physiological oscillations, their functional role is often unclear. Even glycolysis, the paradigm example of oscillatory biochemistry, has seen questions about its oscillatory function.
Lingyun (Ivy) Xiong, Alan Garfinkel
wiley   +1 more source

Linearizing and Forecasting: A Reservoir Computing Route to Digital Twins of the Brain

Advanced Science, EarlyView.
A new approach uses simple neural networks to create digital twins of brain activity, capturing how different patterns unfold over time. The method generates and recovers key dynamics even from noisy data. When applied to fMRI, it predicts brain signals and reveals distinctive activity patterns across regions and individuals, opening possibilities for ...
Gabriele Di Antonio, Tommaso Gili, Andrea Gabrielli, Maurizio Mattia   +3 more
wiley   +1 more source

A Perspective on Interactive Theorem Provers in Physics

Advanced Science, EarlyView.
Into an interactive theorem provers (ITPs), one can write mathematical definitions, theorems and proofs, and the correctness of those results is automatically checked. This perspective goes over the best usage of ITPs within physics and motivates the open‐source community run project PhysLean, the aim of which is to be a library for digitalized physics
Joseph Tooby‐Smith
wiley   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +1 more source

Joint modelling of annual precipitation maxima over several durations for the construction of intensity–duration–frequency curves

Canadian Journal of Statistics, EarlyView.
Abstract Intensity–duration–frequency curves are used by a wide range of professionals to manage the risks related to extreme rainfall. In Canada, these curves are produced by Environment and Climate Change Canada on the basis of Gumbel distributions fitted independently for each accumulation period.
Paul Mathivon, Christian Genest, Jonathan Jalbert   +2 more
wiley   +1 more source

Self‐Similar Blowup for the Cubic Schrödinger Equation

Communications on Pure and Applied Mathematics, EarlyView.
ABSTRACT We give a rigorous proof for the existence of a finite‐energy, self‐similar solution to the focusing cubic Schrödinger equation in three spatial dimensions. The proof is computer‐assisted and relies on a fixed point argument that shows the existence of a solution in the vicinity of a numerically constructed approximation.
Roland Donninger, Birgit Schörkhuber
wiley   +1 more source

Shock wave propagation characteristics of aluminum‐containing explosive in corrugated steel‐lined tunnel

Deep Underground Science and Engineering, EarlyView.
Aluminum‐enhanced afterburning renders AE explosives more hazardous than conventional ones. Corrugated steel linings reduce far‐field AE blast overpressure by ~50% through wave reflection and dissipation. The developed model accurately predicts peak pressure (<10% error) and arrival time (<3% error), supporting protective design.
Zhen Wang, Jiayu Peng, Hujun Li, Yuguo Ji, Shuobiao Li, Guokai Zhang   +5 more
wiley   +1 more source

From Contingency Management to Transformative Climate Risk Adaptation? Analysis of Private Sector Agency in Navigating Complex Climate Risk Realities

Environmental Policy and Governance, EarlyView.
ABSTRACT The growing complexity and severity of cross‐border climate risks characterised by non‐linear impact chains and deep uncertainty questions the capacity of environmental governance to tackle these problems effectively and in a just manner. To increase the efficiency of climate action, the private sector has been called upon to leverage market ...
Päivi Tikkakoski, Sirkku Juhola
wiley   +1 more source

Coherent Forecasting of Realized Volatility

Journal of Forecasting, EarlyView.
ABSTRACT The QLIKE loss function is the stylized favorite of the literature on volatility forecasting when it comes to out‐of‐sample evaluation and the state of the art model for realized volatility (RV) forecasting is the HAR model, which minimizes the squared error loss for in‐sample estimation of the parameters.
Marius Puke, Karsten Schweikert
wiley   +1 more source