Applied Sciences

The problem of identifying non-stationary communication channels with a sparseness property using the local basis function approach is considered. This sparseness refers to scenarios where a few impulse response coefficients significantly differ from zero. The sparsity-aware estimation algorithms are usually obtained using ${\mathit{\ell }}^1$ regularization. Unfortunately, the minimization problem lacks a sometimes closed-form solution; one must rely on numerical search, which is a serious drawback. We propose the fast regularized local basis functions (fRLBF) algorithm based on appropriately reweighted ${\mathit{\ell }}^2$ regularizers, which can be regarded as a first-order approximation of the ${\mathit{\ell }}^1$ approach. The proposed solution incorporates two regularizers, enhancing sparseness in both the time/lag and frequency domains. The choice of regularization gains is an important part of regularized estimation. To address this, three approaches are proposed and compared to solve this problem: empirical Bayes, decentralized, and cross-validation approaches. The performance of the proposed algorithm is demonstrated in a numerical experiment simulating underwater acoustics communication scenarios. It is shown that the new approach can outperform the classical one and is computationally attractive.

The high temperatures of the spray-drying process can cause thermal inactivation of probiotic bacteria. This study evaluated the effect of chia seed mucilage (CM) on the survival and viability of Lactobacillus rhamnosus GG (LGG) encapsulated by spray-drying in cross-linked alginate matrices (CLAM). Two types of microcapsules were used: CLAM without CM (M0-LGG) and with CM (M1-LGG). Viability was assessed under storage conditions (4 °C and 25 °C), heat treatments, and gastrointestinal simulations. The results show that LGG survival improved after spray drying in CLAM (M0-LGG), reaching levels above 92%. Microcapsules containing CM (M1-LGG) maintained high viability, exceeding 8 log CFU/g, under storage at 4 °C for 60 days. CM demonstrated the ability to preserve LGG viability during gastrointestinal digestion (above 6 log CFU/g) and to confer thermal stability under heat stress conditions at 80 °C for 5 min. This study can be a valuable reference for the food industry, as the incorporation of CM as an encapsulating agent for probiotics can improve their viability under adverse processing and storage conditions.

Control of reactive species generation lies at the core of atmospheric pressure plasma processing. In this work, we investigate the ability of a cold RF argon plasma jet source to produce reactive oxygen and nitrogen species (RONS) following the injection of a molecular gas (N₂ or O₂), either premixed with the main gas (Ar) or introduced separately into an already generated Ar discharge. We show that, when reactive gases are injected directly into the Ar discharge, the range of operating parameters—particularly the ratio of reactive gas to main gas—is considerably widened compared to conventional injections through the main argon flow. The plasma characteristics at the source exit were analyzed using optical emission spectroscopy (OES), including the determination of electron density, rotational temperature, and the emission intensities of plasma species such as Ar I, NO(A), OH(A), and N₂(C) for both injection types. Overall, the results show that plasmas generated using in-discharge injection are more stable and capable of sustaining enhanced production of reactive radicals such as NO(A) and OH(A), whereas injection through the main gas can be tuned to selectively enhance NO generation. These findings highlight the potential of plasma sources employing premixed or in-discharge reactive gas injection for surface treatment and for the processing of gas and liquid phases.