Results 101 to 110 of about 526,072 (238)

Machine Learning‐Enhanced Random Matrix Theory Design for Human Immunodeficiency Virus Vaccine Development

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah   +3 more
wiley   +1 more source

Accelerating Biosensor Discovery: A Computationally‐Driven Pipeline for Microplastics Monitoring

open access: yesAdvanced Intelligent Discovery, EarlyView.
A computationally guided pipeline unites molecular simulation, synthetic biology, electrochemical engineering, and machine learning to accelerate biosensor discovery. A Bacillus anthracis carbohydrate‐binding module is used to develop a high‐performance micro‐ and nanoplastics sensor with greatly reduced error and variability.
Gabriel X. Pereira   +13 more
wiley   +1 more source

Relationships of B12 and Homocysteine with Outcomes in the SURE-PD, SURE-PD3, and STEADY-PDIII Trials

open access: yesJournal of Parkinson’s Disease
Background: DATATOP was a study of early Parkinson’s disease (PD) conducted in the 1980 s, before mandatory folic acid fortification in the United States.
Chadwick W. Christine   +8 more
doaj   +1 more source

A Multimodal Intelligent System for Human Digital Twin Simulation with Continuous Kinematic Data Tracking, Biometric Prognosis, and Cognitive State Feedback in Industrial Environments

open access: yesAdvanced Intelligent Discovery, EarlyView.
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury   +4 more
wiley   +1 more source

Large‐Scale Machine Learning to Screen for Small‐Molecule Senolytics

open access: yesAdvanced Intelligent Discovery, EarlyView.
A consistent workflow underpins all experiments in this study. A dedicated model‐selection dataset first identifies optimal hyperparameters for each algorithm. Models are then trained and rigorously evaluated on independent sets of molecules using the senolytic ratio SR. Comprehensive hyperparameter exploration across SMILES representations, task types,
Alexis Dougha   +2 more
wiley   +1 more source

Large Language Model‐Based Chatbots in Higher Education

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci   +4 more
wiley   +1 more source

[Evaluation of the risk of abortion abuse resulting from the two-week legal delay in France]. [PDF]

open access: yes, 2002
A national consensus on foetal abnormalities to be searched for, and not to be searched for (Number of fingers? Upper lip?...) and the eventual detection of the gender during sonography of the 1st trimester is urgent in view of the technological progress
Alouini, Souhail   +4 more
core   +2 more sources

A Novel Parameter Estimation Method for Pneumatic Soft Hand Control Applying Logarithmic Decrement for Pseudo‐Rigid Body Modeling

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
In this research, a paradigm of parameter estimation method for pneumatic soft hand control is proposed. The method includes the following: 1) sampling harmonic damping waves, 2) applying pseudo‐rigid body modeling and the logarithmic decrement method, and 3) deriving position and force control.
Haiyun Zhang   +4 more
wiley   +1 more source

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

open access: yesAdvanced 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   +2 more
wiley   +1 more source

A General Approach for Securely Querying and Updating XML Data [PDF]

open access: yes, 2012
Over the past years several works have proposed access control models for XML data where only read-access rights over non-recursive DTDs are considered. A few amount of works have studied the access rights for updates. In this paper, we present a general
Imine, Abdessamad, Mahfoud, Houari
core   +4 more sources

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