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Motivated by the seminal work of Dupire (2009) on functional Itô formulas, this work investigates asymptotic properties of systems represented by stochastic functional differential equations (SFDEs). Stability of general delay-dependent SFDEs is investigated using degenerate Lyapunov functionals, which are only positive semi-definite rather than positive definite as used in the classical work. This paper first establishes boundedness and regularity of SFDEs by using degenerate Lyapunov functionals. Then moment and almost sure exponential stabilities are obtained based on degenerate Lyapunov functionals and the semi-martingale convergence theorem. As an application of the stability criteria, consentability of stochastic multi-agent systems with nonlinear dynamics is studied. [ABSTRACT FROM AUTHOR]

This paper proposes an architectural solution to enhance the resilience of distributed decision-making and control in microgrids and smart grids with respect to communication delays. The paper develops a resource allocation framework to optimally place the multiple-input multiple-output (MIMO) communication technology on critical channels to reduce the communication bottle neck and expedite the convergence speed of distributed online optimization algorithms, which require convergence in the cyber network before the solution can be implemented on the physical grid. The paper shows that optimal placement of the MIMO technology can decrease communication transmission delays, which in turn improves the reliability of power system operational protocols, such as distributed frequency regulation. Illustrative case studies using data from real-world power systems show that only upgrading the critical communication channels is sufficient to achieve system-wide performance improvement. • Proposing an architectural solution to enhance the resilience of distributed optimization in smart grids with respect to communication delays. • Determining an upper bound on the communication delays under different MIMO communication architectures. • Developing a resource allocation algorithm to optimally place the MIMO technology and to increase the resilience of communication networks. [ABSTRACT FROM AUTHOR]

This work develops a generalization of the Goodwin–Lotka–Volterra models. The traditional model describes the evolution of the employment rate and the labor share. Motivated by recent developments on business cycles and Goodwin-type models, we consider a generalized Goodwin business cycle model with noise. We aim at investigating the impact of telegraph noise and white noise on the evolution of trajectories and the energy on trajectories of the model. It is proved that with the presence of the noises, all trajectories exit any compact subset of the open unit square D = ( 0 , 1 ) × ( 0 , 1 ) and the energy along trajectories can be arbitrarily large. Moreover, under certain additional conditions, the boundary of D is the stable limit cycle of the perturbed model by white noise. Noise impact on the period of business cycles is also discussed. Numerical examples are provided to demonstrate our findings. [ABSTRACT FROM AUTHOR]

This paper considers the problem of identifiability and parameter estimation of single-input–single-output, linear, time-invariant, stable, continuous-time systems under irregular and random sampling schemes. Conditions for system identifiability are established under inputs of exponential polynomial types and a tight bound on sampling density. Identification algorithms of Gauss–Newton iterative types are developed to generate convergent estimates. When the sampled output is corrupted by observation noises, input design, sampling times, and convergent algorithms are intertwined. Persistent excitation (PE) conditions for strongly convergent algorithms are derived. Unlike the traditional identification, the PE conditions under irregular and random sampling involve both sampling times and input values. Under the given PE conditions, iterative and recursive algorithms are developed to estimate the original continuous-time system parameters. The corresponding convergence results are obtained. Several simulation examples are provided to verify the theoretical results. [ABSTRACT FROM AUTHOR]

This paper introduces distributed adaptive algorithms for optimal step size selection in a distributed constrained optimization problem that involves stochastic target variations and noisy observations. The limit behavior of the step size sequences reflects fundamental impact that must be balanced between tracking the target changes and attenuating observation noises. Algorithms for simultaneously estimating target variation, tracking the global optimal solution, and finding the optimal step size are derived, which are shown to achieve convergence on all the sequences simultaneously to their respective optimal values. [ABSTRACT FROM AUTHOR]

• A sufficient-necessary condition is given to design a delay controller for one area. • A criterion is established for simplifying delay control design in multi-area LFC. • Proposed method has better performance compared with conventional approaches. Load frequency control (LFC) has been considered as one of the most important frequency regulation mechanisms in modern power system. One of the inevitable problems involved in LFC over a wide area is communication delay. Not only can the delay deteriorate the system performance but also cause system instability. In this paper, an alternative design method is proposed to devise delay compensators for LFC in one or multiple control areas. For one-area LFC, a sufficient and necessary condition is given for designing a delay compensator. For multi-area LFC with area control errors (ACEs), it is demonstrated that each control area can have its delay controller designed as that in a one-area system if the index of coupling among the areas is below the threshold value determined by the small gain theorem. Effectiveness of the proposed method is verified by simulation studies on LFCs with communication delays in one and multiple interconnected areas with and without time-varying delays, respectively. [ABSTRACT FROM AUTHOR]

The implementation of Personal Carbon Trading (PCT) holds promise in facilitating a noteworthy contribution towards the attainment of emissions reduction predicated on consumption patterns and consequently motivating lifestyle modifications. As individual consumption behaviors usually lead to continuous changes in carbon emissions, it is crucial to rethink PCT from a systematic perspective. This review employed a bibliometric analysis of 1423 papers related to PCT, highlighting the key themes of carbon emissions from energy consumption, climate change, and public opinion on policies in the context of PCT. Most of the existing PCT researches focus on theoretical assumptions and public attitudes, while the quantification of carbon emissions and simulation of PCT require further investigation. Furthermore, the concept of Tan Pu Hui is seldom addressed in PCT studies and case analyses. Moreover, there are limited PCT schemes worldwide that can be directly implemented in practice, leading to a scarcity of large-scale, high-participation case studies. To address these gaps, this review proposes a framework to clarify how PCT can stimulate individual emission reductions on the consumption side, comprising two phases, from motivation to behavior and behavior to target. Future endeavors should prioritize the enhancement of the systematic study of the theoretical foundation of PCT, encompassing carbon emissions accounting and policy design, the incorporation of cutting-edge technology, and the reinforcement of integrated policy practice. This review serves as a valuable reference for future research endeavors and policymaking efforts. • Emissions accounting and simulation for Personal Carbon Trading (PCT) research require further improvements. • Lacking large-scale and high-participation PCT practice cases. • A framework consisting of two phases has been proposed to clarify PCT. [ABSTRACT FROM AUTHOR]

This paper provides a further step towards popularizing the proposed Butler-Volmer (BV) equation-based model and its implementation on state of power (SOP) prediction at various temperatures, which is based on the relationship between state of charge and state of useful charge. The actual 10 s SOP of battery is obtained using the constant current pulse when the restriction of voltage is exactly managed. The COMPLEX method is taken to determine the coefficients of the simplified form of BV equation, enabling online estimation of battery states. Robustness analysis of the proposed model and algorithm on SOP prediction over a large temperature range is analyzed and verified, showing their reliability and accuracy in estimating the terminal voltage and predicting power capability. [ABSTRACT FROM AUTHOR]

Coenzyme Q10 (CoQ10) is an essential medicinal ingredient. In this study, we obtained a high-yielding mutant strain of CoQ10, VK-2-3, by subjecting R. sphaeroides V-0 (V-0) to a 12 C 6+ heavy ion beam and high-voltage prick electric field treatment. To investigate the mutation mechanism, the complete genomes of VK-2-3 and V-0 were sequenced. Collinearity analysis revealed that the nicotinamide adenine dinucleotide-dependent dehydrogenase (NAD) gene underwent rearrangement in the VK-2-3 genome. The NAD gene was overexpressed and silenced in V-0, and this construct was named RS.NAD and RS.ΔNAD. The results showed that the titers of CoQ10 in the RS.NAD and RS.ΔNAD increased and decreased by 16.00 and 33.92%, respectively, compared to those in V-0, and these differences were significant. Our results revealed the mechanism by which the VK-2-3 CoQ10 yield increases through reverse metabolic engineering, providing insights for genetic breeding and mechanistic analysis., Competing Interests: Y-jH, Y-xL, and Z-jT were employed by Shenzhou Biotechnology Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zhang, Wang, Han, Liu, Li, Hu, Tian and Liu.)

Amyotrophic lateral sclerosis (ALS) is a rare neurodegenerative disease with a challenging treatment landscape, due to its complex pathogenesis and limited availability of clinical drugs. Ferroptosis, an iron-dependent form of programmed cell death (PCD), stands distinct from apoptosis, necrosis, autophagy, and other cell death mechanisms. Recent studies have increasingly highlighted the role of iron deposition, reactive oxygen species (ROS) accumulation, oxidative stress, as well as systemic Xc- and glutamate accumulation in the antioxidant system in the pathogenesis of amyotrophic lateral sclerosis. Therefore, targeting ferroptosis emerges as a promising strategy for amyotrophic lateral sclerosis treatment. This review introduces the regulatory mechanism of ferroptosis, the relationship between amyotrophic lateral sclerosis and ferroptosis, and the drugs used in the clinic, then discusses the current status of amyotrophic lateral sclerosis treatment, hoping to provide new directions and targets for its treatment., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Retinitis pigmentosa (RP) is a rare, progressive, and hereditary disorder that leads to the progressive loss of vision and visual field, and in some cases blindness. The specific relationship between RP and glaucoma has been debated for decades., Methods: In this study, we examined a Han RP family with concomitant angle-closure glaucoma (ACG), performed an inductive analysis of their clinical features and assistant results, and applied whole-exome sequencing (WES) technology for a molecular diagnosis., Results: A novel transversion mutation (c.626 T > A) was identified in the peripherin-2 (PRPH2) gene in the proband, resulting in the substitution of Valine to aspartic acid in codon 209. A full ophthalmic examination showed that the proband with the c.626 T > A mutation had a typical RP manifestation, with close angles; however, the proband's elder brother, who lacked the novel mutation, had a normal fundus and open angles., Conclusion: Our results extend the genetic mutation spectrum of PRPH2 in RP, and provide evidence to support a genetic correlation between RP and ACG., (© 2021. The Author(s).)

This article considers a general model of distributed convex optimization with possibly local constraints, coupled equality constraints, and coupled inequality constraints, where the coupled equality constraints are affine and the coupled inequality constraints can be nonaffine. To solve this problem, we present two algorithms. The first algorithm is similar to a dual subgradient algorithm that requires a center node in the network. The main advantage of the first algorithm is that it achieves the optimal convergence rate O([1/√k]) . Moreover, it does not require additional treatment for the primal recovery. These merits are achieved by using an iterate-averaging feedback technique on the basis of the dual subgradient method. The second algorithm further removes the requirement of a center node by employing consensus tracking iterates. As a result, the second algorithm is fully distributed at the price of achieving an O([lnk/√k]) convergence rate.

This paper studies the problem of outcome prediction in anesthesia procedures. Anesthesia depth and blood pressures are used as typical outcomes in this study. Traditional diagnosis and control in anesthesia focus on a one-drug-one-outcome scenario. It is well understood, however, that consideration of multiple outcomes is necessary and beneficial for anesthesia managements. This paper introduces a method of modeling that significantly reduces the complexity of the problem and yet retains model accuracy. Utility of the modeling method is demonstrated in the areas of anesthesia outcome prediction and decision assistance.