Bistatic ISAR Imaging with a V-FM Waveform Based on a Dual-Channel-Coupled 2D-CS Algorithm.

Due to the sparsity of the space distribution of point scatterers and radar echo data, the theory of Compressed Sensing (CS) has been successfully applied in Inverse Synthetic Aperture Radar (ISAR) imaging, which can recover an unknown sparse signal from a limited number of measurements by solving a sparsity-constrained optimization problem. In this paper, since the V style modulation(V-FM) signal can mitigate the ambiguity apparent in range and velocity, the dual-channel, two-dimension, compressed-sensing (2D-CS) algorithm is proposed for Bistatic ISAR (Bi-ISAR) imaging, which directly deals with the 2D signal model for image reconstruction based on solving a nonconvex optimization problem. The coupled 2D super-resolution model of the target's echoes is firstly established; then, the 2D-SL0 algorithm is applied in each channel with different dictionaries, and the final image is obtained by synthesizing the two channels. Experiments are used to test the robustness of the Bi-ISAR imaging framework with the two-dimensional CS method. The results show that the framework is capable accurately reconstructing the Bi-ISAR image within the conditions of low SNR and low measured data.

Design of stimuli-responsive minimalist heptad surfactants for stable emulsions.

Peptide surfactants have been extensively investigated with various applications in detergents, foods, and pharmaceutics due to their biodegradability, biocompatibility, and customizable structures. Traditional peptide surfactants are often designed in a head-to-tail fashion mimicking chemical surfactants. Alternatively, a side-by-side design pattern based on heptad repeats offers an approach to designing peptide surfactants. However, minimalist peptide design using a single heptad for stabilizing interfaces remains largely unexplored. Here, we design four heptad surfactants (AM1.2, 6H, 6H7K, and HK) responsive to metal ions and compare their emulsification performance with a three-heptad peptide, AM1. Among them, the HK peptide generates emulsions exhibiting good stability over months. We further optimize factors such as buffering salts, ionic strength, and emulsion dilutions to uncover their impacts on emulsion properties. Our findings deepen the understanding of emulsion properties and provide practical insights for characterizing peptide-based emulsions, paving the way for their broader utilization in diverse applications.

Alginate-based materials for enzyme encapsulation.

Enzymes are widely used in industry due to their high efficiency and selectivity. However, their low stability during certain industrial processes can result in a significant loss of catalytic activity. Encapsulation is a promising technique that can stabilize enzymes by protecting them from environmental stresses such as extreme temperature and pH, mechanical force, organic solvents, and proteases. Alginate and alginate-based materials have emerged as effective carriers for enzyme encapsulation due to their biocompatibility, biodegradability, and ability to form gel beads through ionic gelation. This review presents various alginate-based encapsulation systems for enzyme stabilization and explores their applications in different industries. We discuss the preparation methods of alginate encapsulated enzymes and analyze the release mechanisms of enzymes from alginate materials. Additionally, we summarize the characterization techniques used for enzyme-alginate composites. This review provides insights into the use of alginate encapsulation as a means of stabilizing enzymes and highlights the potential benefits for various industrial applications.

Development of High-Drug-Loading Nanoparticles.

Formulating drugs into nanoparticles offers many attractive advantages over free drugs including improved bioavailability, minimized toxic side effects, enhanced drug delivery, feasibility of incorporating other functions such as controlled release, imaging agents for imaging, targeting delivery, and loading more than one drug for combination therapies. One of the key parameters is drug loading, which is defined as the mass ratio of drug to drug-loaded nanoparticles. Currently, most nanoparticle systems have relatively low drug loading (<10 wt%), and developing methods to increase drug loading remains a challenge. This Minireview presents an overview of recent research on developing nanoparticles with high drug loading (>10 wt%) from the perspective of synthesis strategies, including post-loading, co-loading, and pre-loading. Based on these three different strategies, various nanoparticle systems with different materials and drugs are summarized and discussed in terms of their synthesis methods, drug loadings, encapsulation efficiencies, release profiles, stabilities, and their applications in drug delivery. The advantages and disadvantages of these strategies are presented with an objective of providing useful design rules for future development of high-drug-loading nanoparticles.