AIMC Topic: Ions

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Bound ion effects: Using machine learning method to study the kinesin Ncd's binding with microtubule.

Biophysical journal
Drosophila Ncd proteins are motor proteins that play important roles in spindle organization. Ncd and the tubulin dimer are highly charged. Thus, it is crucial to investigate Ncd-tubulin dimer interactions in the presence of ions, especially ions tha...

Injection-on-Skin Granular Adhesive for Interactive Human-Machine Interface.

Advanced materials (Deerfield Beach, Fla.)
Realization of interactive human-machine interfaces (iHMI) is improved with development of soft tissue-like strain sensors beyond hard robotic exosuits, potentially allowing cognitive behavior therapy and physical rehabilitation for patients with bra...

Transformer-based deep learning models for adsorption capacity prediction of heavy metal ions toward biochar-based adsorbents.

Journal of hazardous materials
Biochar adsorbents synthesized from food and agricultural wastes are commonly applied to eliminate heavy metal (HM) ions from wastewater. However, biochar's diverse characteristics and varied experimental conditions make the accurate estimation of th...

Rapid identification of Salmonella serovars Enteritidis and Typhimurium using whole cell matrix assisted laser desorption ionization - Time of flight mass spectrometry (MALDI-TOF MS) coupled with multivariate analysis and artificial intelligence.

Journal of microbiological methods
Salmonella is a common food-borne pathogen with Enteritidis and Typhimurium being among the most important serovars causing numerous outbreaks. A rapid method was investigated to identify these serovars using whole-cell MALDI-TOF MS coupled with mult...

Deep learning-based fast denoising of Monte Carlo dose calculation in carbon ion radiotherapy.

Medical physics
BACKGROUND: Plan verification is one of the important steps of quality assurance (QA) in carbon ion radiotherapy. Conventional methods of plan verification are based on phantom measurement, which is labor-intensive and time-consuming. Although the pl...

Metal3D: a general deep learning framework for accurate metal ion location prediction in proteins.

Nature communications
Metal ions are essential cofactors for many proteins and play a crucial role in many applications such as enzyme design or design of protein-protein interactions because they are biologically abundant, tether to the protein using strong interactions,...

An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation.

Journal of chemical information and modeling
Force fields (FFs) for molecular simulation have been under development for more than half a century. As with any predictive model, rigorous testing and comparisons of models critically depends on the availability of standardized data sets and benchm...

Dip-coating electromechanically active polymer actuators with SIBS from midblock-selective solvents to achieve full encapsulation for biomedical applications.

Scientific reports
Soft and compliant ionic electromechanically active polymer actuators (IEAPs) are a promising class of smart materials for biomedical and soft robotics applications. These materials change their shape in response to external stimuli like the electric...

AlphaFill: enriching AlphaFold models with ligands and cofactors.

Nature methods
Artificial intelligence-based protein structure prediction approaches have had a transformative effect on biomolecular sciences. The predicted protein models in the AlphaFold protein structure database, however, all lack coordinates for small molecul...

An open-source deep learning model for predicting effluent concentration in capacitive deionization.

The Science of the total environment
To effectively evaluate the performance of capacitive deionization (CDI), an electrochemical ion separation technology, it is necessary to accurately estimate the number of ions removed (effluent concentration) according to energy consumption. Herein...