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Particle Size

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Formulation design and optimization of cationic-charged liposomes of brimonidine tartrate for effective ocular drug delivery by design of experiment (DoE) approach.

Drug development and industrial pharmacy
OBJECTIVE: The present study was aimed to design and optimize brimonidine tartrate (BRT) loaded cationic-charged liposome formulation with enhanced trans-corneal drug permeation, prolonged corneal residence, and sustained drug release for effective o...

Lignin-Incorporated Nanogel Serving As an Antioxidant Biomaterial for Wound Healing.

ACS applied bio materials
Oxidative phosphorylation is an important biological process in the body to produce energy, during which oxygen free radicals are generated as byproduct. Excessive oxygen free radicals cause cell death and reduce the rate of tissue regeneration and h...

Sensor-based particle mass prediction of lightweight packaging waste using machine learning algorithms.

Waste management (New York, N.Y.)
Sensor-based material flow characterization (SBMC) promises to improve the performance of future-generation sorting plants by enabling new applications like automatic quality monitoring or process control. Prerequisite for this is the derivation of m...

Generation of Interconnected Neural Clusters in Multiscale Scaffolds from Human-Induced Pluripotent Stem Cells.

ACS applied materials & interfaces
The development of in vitro neural networks depends to a large extent on the scaffold properties, including the scaffold stiffness, porosity, and dimensionality. Herein, we developed a method to generate interconnected neural clusters in a multiscale...

Hierarchically Structured and Scalable Artificial Muscles for Smart Textiles.

ACS applied materials & interfaces
Fiber-based artificial muscles with excellent actuation performance are gaining great attention as soft materials for flexible actuators; however, current advances in fiber-based artificial muscles generally suffer from high cost, harsh stimulation r...

Prediction of the performance of pre-packed purification columns through machine learning.

Journal of separation science
Pre-packed columns have been increasingly used in process development and biomanufacturing thanks to their ease of use and consistency. Traditionally, packing quality is predicted through rate models, which require extensive calibration efforts throu...

UV/VIS imaging-based PAT tool for drug particle size inspection in intact tablets supported by pattern recognition neural networks.

International journal of pharmaceutics
The potential of machine vision systems has not currently been exploited for pharmaceutical applications, although expected to provide revolutionary solutions for in-process and final product testing. The presented paper aimed to analyze the particle...

Deep learning in food science: An insight in evaluating Pickering emulsion properties by droplets classification and quantification via object detection algorithm.

Advances in colloid and interface science
Understanding the complicated emulsion microstructures by microscopic images will help to further elaborate their mechanisms and relevance. The formidable goal of the classification and quantification of emulsion microstructure appears difficult to a...

On the Possibility of Designing an Advanced Sensor with Particle Sizing Using Dynamic Light Scattering Time Series Spectral Entropy and Artificial Neural Network.

Sensors (Basel, Switzerland)
Dynamic Light Scattering is a well-established technique used in particle sizing. An alternative procedure for Dynamic Light Scattering time series processing based on spectral entropy computation and Artificial Neural Networks is described. An error...

Arithmetic optimization algorithm with deep learning enabled airborne particle-bound metals size prediction model.

Chemosphere
Recently, heavy metal air pollution has received significant interest in computing the total concentration of every toxic metal. Chemical fractionation of possibly toxic substances in airborne particles becomes a vital element. Among the primary and ...