Passivity and robust passivity of inertial memristive neural networks with time-varying delays via non-reduced order method.

This study examines the concepts of passivity and robust passivity in inertial memristive neural networks (IMNNs) that feature time-varying delays. By using non-smooth analysis and the passivity theorem, algebraic criteria for both passivity and robust passivity are derived by using the non-reduced order method. The proposed criteria, based on the non-reduced order method, effectively reduce the complexity of derivation and computation, thereby simplifying the verification process.

Implicit calibration method for underwater stereo cameras.

Underwater stereo cameras can effectively capture intricate environments with restricted accessibility, offering an appealing solution for precise perception. Stereo imaging is however susceptible to distortions caused by the refraction of incoming rays. These distortions are nonlinear and challenge the standard single viewpoint projection assumption.

Multistability of Almost Periodic Solutions for Fuzzy Competitive NNs With Time-Varying Delays.

In this article, the multistability problem of almost periodic solutions of fuzzy competitive neural networks (FCNNs) with time-varying delays is investigated. Considering more general activation functions, which are nonmonotonic and nonlinear, and incorporating the almost periodic property of the parameters in FCNNs, sufficient conditions for the multistability of almost periodic solutions are given. ∏(L+1) stable almost periodic solutions are obtained, where L depends on the geometric features of the activation functions, which enriches and extends the research on multistability in fuzzy systems.

Cannabidiol finds dihydrocannabidiol as its twin in anti-inflammatory activities and the mechanism.

Ethnopharmacological Relevance: The hemp (cataloged at the "Medicinal Plant Names Services" as Cannabis sativa L.) extracts, cannabinoids have been used for centuries in Southeast Asia as folk medicines and now authorized by about 50 countries for application in medicine, health care products and cosmetics. As the most consumed cannabinoid, cannabidiol (CBD) has been recognized due to its various bioactivities, including anti-inflammatory and antibacterial properties.

Neural Network Adaptive Iterative Learning Control for Strict-Feedback Unknown Delay Systems Against Input Saturation.

Neural network adaptive iterative learning control (ILC) is developed in this article to treat strict-feedback nonlinear systems with unknown state delays and input saturation. These delays are treated by constructing the Lyapunov-Krasovskii (L-K) functions for each subsystem. A command filter is employed to avoid the derivative explosion caused by continuous differentiation of the virtual controller.

Deciphering the code: the pivotal role of lncRNAs in advancing TNBC therapy.

Triple-negative breast cancer (TNBC) represents the most formidable subtype of breast cancer, characterized by a notable dearth in targeted therapeutic options. Deciphering the underlying molecular mechanisms of TNBC is pivotal for improving patient outcomes. Recent scientific advancements have spotlighted long non-coding RNAs (lncRNAs) as key players in the genesis, progression, and metastasis of cancers.

Enhancing glass-ionomer cements with flake-shaped glass: A new frontier in dental restoration.

This study aims to investigate whether the combined use of thin sheet glass (FSG) and polyurethane acrylate (PUA) can enhance the mechanical properties and biocompatibility of glass ionomer cements (GICs) to improve the overall performance of commercial GICs. In this study, an innovative approach was employed by incorporating diluents and photoinitiators into PUA to develop a novel light-curable PUA material. The PUA was then used to modify the GIC to obtain PUA-modified GIC.

Compressible Hollow Microlasers in Organoids for High-Throughput and Real-Time Mechanical Screening.

Mechanical stress within organoids is a pivotal indicator in disease modeling and pharmacokinetics, yet current tools lack the ability to rapidly and dynamically screen these mechanics. Here, we introduce biocompatible and compressible hollow microlasers that realize all-optical assessment of cellular stress within organoids. The laser spectroscopy yields identification of cellular deformation at the nanometer scale, corresponding to tens of pascals stress sensitivity.

Input-to-state stability of delayed memristor-based inertial neural networks via non-reduced order method.

This paper is concerned with the input-to-state stability (ISS) for a kind of delayed memristor-based inertial neural networks (DMINNs). Based on the nonsmooth analysis and stability theory, novel delay-dependent and delay-independent criteria on the ISS of DMINNs are obtained by constructing different Lyapunov functions. Moreover, compared with the reduced order approach used in the previous works, this paper consider the ISS of DMINNs via non-reduced order approach.

Emulsion-Templated Gelatin/Amino Acids/Chitosan Macroporous Hydrogels with Adjustable Internal Dimensions for Three-Dimensional Stem Cell Culture.

The demand for macroporous hydrogel scaffolds with interconnected porous and open-pore structures is crucial for advancing research and development in cell culture and tissue regeneration. Existing techniques for creating 3D porous materials and controlling their porosity are currently constrained. This study introduces a novel approach for producing highly interconnected aspartic acid-gelatin macroporous hydrogels (MHs) with precisely defined open pore structures using a one-step emulsification polymerization method with surface-modified silica nanoparticles as Pickering stabilizers.

Evaluation of the activity and mechanisms of oregano essential oil against PRV in vivo and in vitro.

Background: The Pseudorabies Virus (PRV) leading to pseudorabies and causes huge economic losses in pig industry. The development of novel PRV variations has diminished the efficacy of traditional vaccinations, and there is yet no medication that can stop the spread of PRV infection. Therefore, PRV eradication is challenging.

Finite-Time Stabilization of Inertial Memristive Neural Networks via Nonreduced Order Method.

This article investigates the finite-time stabilization problem of inertial memristive neural networks (IMNNs) with bounded and unbounded time-varying delays, respectively. To simplify the theoretical derivation, the nonreduced order method is utilized for constructing appropriate comparison functions and designing a discontinuous state feedback controller. Then, based on the controller, the state of IMNNs can directly converge to 0 in finite time.

Unified analysis on multistablity of fraction-order multidimensional-valued memristive neural networks.

This article provides a unified analysis of the multistability of fraction-order multidimensional-valued memristive neural networks (FOMVMNNs) with unbounded time-varying delays. Firstly, based on the knowledge of fractional differentiation and memristors, a unified model is established. This model is a unified form of real-valued, complex-valued, and quaternion-valued systems.

Effect of dentin conditioners on dentin bond strength: A systematic review and meta-analysis.

Statement Of Problem: Although composite resin restorations have been widely used for dental restorations, the durability of the bond affects the rate of restoration failure. However, how multiple strategies for enhancing the resin-dentin bond affect durability is unclear.

Purpose: The purpose of this systematic review and meta-analysis was to evaluate the impact of dentin conditioners on resin-dentin bond strength with different pretreatments before the application of adhesives.

Selenium-enriched yeast, a selenium supplement, improves the rheological properties and processability of dough: From the view of yeast metabolism and gluten alteration.

This study investigated the effect mechanism of selenium (Se)-enriched yeast on the rheological properties of dough from the perspective of yeast metabolism and gluten alteration. As the yeast Se content increased, the gas production rate of Se-enriched yeast slowed down, and dough viscoelasticity decreased. The maximum creep of Se-enriched dough increased by 29%, while the final creep increased by 54%, resulting in a softer dough.

Ion exchange-assisted surface passivation toward highly stable red-emitting fluoride phosphors for light-emitting diodes.

A facile and environmentally friendly ion exchange-assisted surface passivation (IASP) strategy is presented for synthesizing red emitting Mn-activated fluoride phosphors. A substantial, pristine Mn-free shell layer, applied as a coating to Mn doped potassium fluorosilicate KSiF:Mn (KSFM) phosphors, enhances both water resistance and luminescence efficiency. The stability test of fluoride in water at ambient temperature and boiling water demonstrates that IASP-treated KSFM phosphors are highly water resistant.

The Performance and Evolutionary Mechanism of in Enhancing Selenite Tolerance and Bioaccumulation.

Background: Selenium (Se) pollution poses serious threats to terrestrial ecosystems. Mushrooms are important sources of Se with the potential for bioremediation. Pre-eminent Se resources must possess the ability to tolerate high levels of Se.

Clinical significance of serum lactate dehydrogenase combined with a multivariate model for predicting the near-term outcome of primary nasopharyngeal carcinoma.

Background And Objectives: This investigation explores the clinical significance of integrating serum lactate dehydrogenase (LDH) with a multivariate model for assessing the short-term prognosis of primary nasopharyngeal carcinoma (NPC). Epstein-Barr virus (EBV) quantification is a crucial prognostic indicator in NPC cases, but not all patients with NPC test positive for EBV. Furthermore, widespread adoption of EBV-DNA quantification remains challenging due to its high cost.

Hyper-Exponential Stabilization of Neural Networks by Event-Triggered Impulsive Control With Actuation Delay.

This brief studies the hyper-exponential stabilization of neural networks (NNs) by event-triggered impulsive control, where the impulse instants are determined by the event-triggered conditions. In the presence of actuation delay, an event-triggered impulsive control scheme is devised. For reducing the sampling task of continuous detection, a periodic-detection scheme is also introduced.