25 papers · ranked by Valyu relevance
Charlotte K. Boughton, Roman Hovorka
Title: Graphical abstract Advances in diabetes technologies have enabled the development of automated closed-loop insulin delivery systems. Several hybrid closed-loop systems have been commercialised, reflecting rapid transition of this evolving technology from research into clinical practice, where it is gradually…
Felice T. Sun, Martha J. Morrell
Neurostimulation is now an established therapy for the treatment of movement disorders, pain, and epilepsy. While most neurostimulation systems available today provide stimulation in an open-loop manner (i.e., therapy is delivered according to preprogrammed settings and is unaffected by changes in the patient’s…
Steve M. Potter, Ahmed El Hady, Eberhard E. Fetz
Feedback and closed-loop circuits exist in just about every part of the nervous system. It is curious, therefore, that for decades neuroscientists have been probing the nervous system in an open-loop manner to understand it. Instead of the linear, reductionistic “stimulate → record response” approach, a more modern…
Valerio Francioni, Anna Beltramini, Linlin Z Fan, Mark T. Harnett
Brain-Computer Interfaces (BCI) have catalyzed advancements in both clinical applications and basic neuroscience research. However, technical barriers such as steep learning curves and complex synchronization requirements often impede their widespread adoption. In response to the increasing demand for optical BCI…
Pankaj K. Gupta, Timothy H. Murphy
Most investigations study brain activity and behavior as separate channels that do not interact in real time. Assessments are typically made post hoc, and experimental contingencies are not dependent on regional brain activity fluctuations. In contrast, closed-loop brain stimulation/manipulation requires a continuous…
Authors not listed
The discovery of radiation-resistant polymers is vital for aerospace, medical, and energy applications, where ionizing radiation rapidly degrades conventional materials. Inspired by the impact of Google DeepMind’s AlphaFold in structural biology, this study presents a closed-loop generative AI framework for polymer…
Charlotte K. Boughton, Sara Hartnell, Janet M. Allen, Julia Fuchs + 1 more
'Roman Hovorka'] Hybrid closed-loop therapy is an emerging technology transforming the management of type 1 diabetes (T1D). Research studies demonstrate glycemic and quality of life benefits of hybrid closed-loop therapy for people with T1D. Translating these outcomes into standard clinical practice is critical for…
Liron Gruber, Ehud Ahissar
The human visual system perceives its environment via eye movements, which are typically classified as saccades and drifts. Saccades are quick transitions of the gaze from one Region of Interest (ROI) to another and drifts are slower scanning motions in each ROI. Here we examine two contrasting schemes of perception…
Oluwasegun Ayokunle Somefun, Kayode Akingbade, Folasade M. Dahunsi
—The proportional-integral-derivative (PID) control law is often overlooked as a computational imitation of the critic control in human decision. This paper provides a formulation to remedy this problem. Further, based on the characteristic settling-behaviour of dynamical systems, the "closed PID-loop model" following…
C. Goupil, Henni Ouerdane, Éric Herbert, Giuliano Benenti + 2 more
'Yves D’Angelo' 'Ph. Lecoeur'] We present the closed loop approach to linear nonequilibrium thermodynamics considering a generic heat engine dissipatively connected to two temperature baths. The system is usually quite generally characterized by two parameters: the output power P and the conversion efficiency η, to…
Charlotte K. Boughton, Lia Bally, Roman Hovorka
The prevalence of diabetes in the hospital is increasing and approximately 18-20% of hospital beds are occupied by someone with diabetes . Diabetes disproportionally affects the elderly, with three times greater prevalence in hospitalised people aged over 65 years than in those aged under 45 years . Maintaining near…
Malcolm Sim, Mohammad Ghazi Vakili, Felix Strieth-Kalthoff, Han Hao + 4 more
Self-driving laboratories (SDLs), which combine automated experimental hardware with computational experiment planning, have emerged as powerful tools for accelerating materials discovery. The intrinsic complexity created by their multitude of components requires an effective orchestration platform to ensure the…
Nayeon Kim, Hyuk Jun Yoo, Daeho Kim, Heeseung Lee + 1 more
Autonomous laboratories hold great promise for accelerating material discovery but are often restricted by static, predefined experimental constraints. We present SPACESHIP, an AIdriven framework for dynamic, constraint-free exploration of synthesizable regions in chemical parameter spaces. SPACESHIP integrates…
Authors not listed
Self-driving laboratories (SDLs) are poised to transform materials discovery by integrating automation with machine learning (ML) to accelerate data-driven experimentation. However, most SDL frameworks remain limited by single-feedback optimization and lack the multi-modal diagnostics needed to resolve both optical and…
Iñaki Iturrate, Stephanie Martin, Ricardo Chavarriaga, Bastien Orset + 7 more
Closed-loop or adaptive deep brain stimulation (DBS) for Parkinson’s Disease (PD) has shown comparable clinical improvements to continuous stimulation, yet with less stimulation times and side effects. In this form of control, stimulation is driven by pathological beta oscillations recorded from the subthalamic…
Rory Crean, Marina Corbella, Ana Rita Calixto, Alvan Hengge + 1 more
Protein tyrosine phosphatases are crucial regulators of cellular signaling. Their activity is regulated by the motion of a conserved loop, the WPD-loop, from a catalytically inactive open to a catalytically active closed conformation. WPD-loop motion optimally positions a catalytically critical residue into the active…
Ching-Hsiang Chang, Asterios Arampatzis, Samuel Balula, Mucun Hou + 4 more
Adaptive, closed-loop control of cellular behavior is essential for next-generation therapies, yet most current treatments operate in an open-loop manner and lack robustness to patient variability and disease dynamics. Here, we establish a controltheoretic platform for rational engineering of closed-loop cell-based…
Supraja S. Chittari, Zhiyue Lu
Simulating stochastic systems with feedback control is challenging due to the complex interplay between the system's dynamics and the feedback-dependent control protocols. We present a single-step-trajectory probability analysis to time-dependent stochastic systems. Based on this analysis, we revisit several…
Cédric Join, Jakub Orłowski, Antoine Chaillet, Madeleine M. Lowery + 2 more
Deep brain stimulation (DBS) is an advanced surgical treatment for the symptoms of Parkinson's disease (PD), involving electrical stimulation of neurons within the basal ganglia region of the brain. DBS is traditionally delivered in an open-loop manner using fixed stimulation parameters, which may lead to suboptimal…
Xiaoyu Zhang, Zhou Fang
This paper introduces a biomolecular Linear Quadratic Regulator (LQR) to investigate the design principles of gene regulatory networks. We show that for fundamental gene regulation network, the bio-controller derived from LQR theory precisely recapitulate natural network motifs, such as auto-regulation and incoherent…
Authors not listed
Realizing the promise of artificial intelligence (AI) to accelerate scientific progress and deliver technological impact depends on how effectively AI can be integrated into real-world decision- making processes. As Peter Norvig states, “Somewhat remarkably, almost all AI research until very recently has assumed that…
Megan Morrison, J. Nathan Kutz
—We develop a principled mathematical framework for controlling nonlinear, networked dynamical systems. Our method integrates dimensionality reduction, bifurcation theory and emerging model discovery tools to find low-dimensional subspaces where feed-forward control can be used to manipulate a system to a desired…
Alexander Pomberger, Antonio Pedrina McCarthy, Ahmad Khan, Simon Sung + 4 more
Multivariate chemical reaction optimization involving catalytic systems is a non-trivial task due to the high number of tuneable parameters and discrete choices. Closed-loop optimization featuring active Machine Learning (ML) represents a powerful strategy for automating reaction optimization. However, the translation…
Authors not listed
Despite the promise of self-driving laboratories to accelerate discovery, their widespread implementation is hindered by prohibitive cost and technical complexity. We introduce BrickSDLab, a fully functional self-driving lab platform built entirely from LEGO® components, designed to bridge this accessibility gap.…
Niloofar Shadab, Tyler Cody, Alejandro Salado, Peter A. Beling
There is a lack of formalism for some key foundational concepts in systems engineering. One of the most recently acknowledged deficits is the inadequacy of systems engineering practices for engineering intelligent systems. In our previous works, we proposed that closed systems precepts could be used to accomplish a…