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This paper studies the analysis and synthesis of distributed adaptive control architectures for uncertain multiagent systems with coupled dynamics in a leader-follower setting, where overall closed-loop system stability is established, and sufficient stability conditions are defined. Specifically, we first analyse a standard distributed adaptive control law and reveal local stability conditions that guarantee the boundedness of the closed-loop system trajectories. We next synthesise fixed and adaptive robustifying terms to show relaxed local stability conditions. We also show that the fixed robustifying term can yield high-gain parameters in the resulting control signals, where the adaptive robustifying term removes this high-gain requirement. Finally, an illustrative numerical example is further presented to compare the proposed methods and demonstrate our theoretical contributions. [ABSTRACT FROM AUTHOR]

Abstract Background Periodontitis, a prevalent chronic inflammatory disease, offers insights into the broader landscape of chronic inflammatory conditions. The progression and treatment outcomes of periodontitis are closely related to the oral microbiota’s composition. Adjunctive systemic Amoxicillin 500 mg and Metronidazole 400 mg, often prescribed thrice daily for 7 days to enhance periodontal therapy’s efficacy, have lasting effects on the oral microbiome. However, the precise mechanism through which the oral microbiome influences clinical outcomes in periodontitis patients remains debated. This investigation explores the pivotal role of the oral microbiome's composition in mediating the outcomes of adjunctive systemic antibiotic treatment. Methods Subgingival plaque samples from 10 periodontally healthy and 163 periodontitis patients from a randomized clinical trial on periodontal therapy were analyzed. Patients received either adjunctive amoxicillin/metronidazole or a placebo after mechanical periodontal treatment. Microbial samples were collected at various intervals up to 26 months post-therapy. Using topic models, we identified microbial communities associated with normobiotic and dysbiotic states, validated with 86 external and 40 internal samples. Logistic regression models evaluated the association between these microbial communities and clinical periodontitis parameters. A Directed Acyclic Graph (DAG) determined the mediating role of oral microbiota in the causal path of antibiotic treatment effects on clinical outcomes. Results We identified clear distinctions between dysbiotic and normobiotic microbial communities, differentiating healthy from periodontitis subjects. Dysbiotic states consistently associated with below median %Pocket Probing Depth ≥ 5 mm (OR = 1.26, 95% CI [1.14–1.42]) and %Bleeding on Probing (OR = 1.09, 95% CI [1.00–1.18]). Factors like microbial response to treatment, smoking, and age were predictors of clinical attachment loss progression, whereas sex and antibiotic treatment were not. Further, we showed that the oral microbial treatment response plays a crucial role in the causal effect of antibiotic treatment on clinical treatment outcomes. Conclusions The shift towards a normobiotic subgingival microbiome, primarily induced by adjunctive antibiotics, underscores the potential for microbiome-targeted interventions to enhance therapeutic efficacy in chronic inflammatory conditions. This study reaffirms the importance of understanding the oral microbiome's role in periodontal health and paves the way for future research exploring personalized treatment strategies based on individual microbiome profiles. Video Abstract

Abstract Hydrogen will become a key player in transitioning toward a net-zero energy system. However, a clear pathway toward a unified European hydrogen infrastructure to support the rapid scale-up of hydrogen production is still under discussion. This study explores plausible pathways using a fully sector-coupled energy system model. Here, we assess the emergence of hydrogen infrastructure build-outs connecting neighboring European nations through hydrogen import and domestic production centers with Western and Central European demands via four distinct hydrogen corridors. We identify a potential lock-in effect of blue hydrogen in the medium term, highlighting the risk of long-term dependence on methane. In contrast, we show that a self-sufficient Europe relying on domestic green hydrogen by 2050 would increase yearly expenses by around 3% and require 518 gigawatts of electrolysis capacity. This study emphasizes the importance of rapidly scaling up electrolysis capacity, building hydrogen networks and storage facilities, deploying renewable electricity generation, and ensuring coherent coordination across European nations.

We propose a new distributed adaptive control architecture for finite-time control of uncertain nonlinear multiagent systems. The proposed architecture employs three key components for each agent; a nonlinear reference model, a weight update rule, and an adaptive control signal. Predicated on agent-wise reference model state exchange, an ideal finite-time behaviour of overall multiagent system is captured by nonlinear reference models. The weight update rule of each agent, which is driven by a local error signal between the actual uncertain state of an agent and its reference model state, then adjusts agent-wise controller parameters in real-time to drive the local error signals of each agent to zero in finite-time. That is, not only the states of agents converge to their nonlinear reference model states in finite-time, but also the latter states converge to the given ideal behaviour in finite-time. Considering safety, the distinct feature of our architecture is that it does not rely on agent-wise actual state exchange between agents, which involves the effect of system uncertainties. This implies that when a subset of agents exhibits, for example, Byzantine behaviour, then their behaviour do not affect the rest of multiagent system from functioning. [ABSTRACT FROM AUTHOR]

The problem of optimizing discrete phases in a reconfigurable intelligent surface (RIS) to maximize the received power at a user equipment is addressed. Necessary and sufficient conditions to achieve this maximization are given. These conditions are employed in an algorithm to achieve the maximization. New versions of the algorithm are given that are proven to achieve convergence in $N$ or fewer steps whether the direct link is completely blocked or not, where $N$ is the number of the RIS elements, whereas previously published results achieve this in $KN$ or $2N$ number of steps where $K$ is the number of discrete phases. Thus, for a discrete-phase RIS, the techniques presented in this paper achieve the optimum received power in the smallest number of steps published in the literature. In addition, in each of those $N$ steps, the techniques presented in this paper determine only one or a small number of phase shifts with a simple elementwise update rule, which result in a substantial reduction of computation time, as compared to the algorithms in the literature. As a secondary result, we define the uniform polar quantization (UPQ) algorithm which is an intuitive quantization algorithm that can approximate the continuous solution with an approximation ratio of ${\mathrm {sinc}}^{2}(1/K)$ and achieve low time-complexity, given perfect knowledge of the channel.

As it is well-known, system uncertainties and unmodeled dynamics can deteriorate stability properties of model reference adaptive control systems. Motivated by this standpoint, we first analyse stability conditions of model reference adaptive control architectures in the presence of unstructured system uncertainties and unmodeled dynamics. Wethen synthesise adaptive robustifying terms to relax the aforementioned stability condition, which presents our main contribution. Specifically, these terms in the feedback loop guarantee overall system stability even in the presence of significant system uncertainties when unmodeled dynamics satisfy a condition. We further demonstrate our theoretical findings in an experiment involving an inverted pendulum on a cart (modeled dynamics) coupled with another cart through a spring (unmodeled dynamics). [ABSTRACT FROM AUTHOR]

Tarhana is a popular Turkish fermented food, made of a mixture of cereal and yoghurt, generally consumed as soup. Both lactic acid bacteria and yeasts are responsible for the fermentation. The selection and proportions of ingredients integrated along with the production process specify the nutritional value and sensory properties of the final product. Therefore, the first objective of the present study was to process a dried “chicken meat powder (CMP)” that could be used in food formulations. The second objective was to determine the impact of CMP addition on the nutritional and sensorial properties of Uşak tarhana recipe with geographical indication. In order to fulfill these challenges dried chicken meat powder (CMP) at levels of 20, 25, 30, and 35% were included in tarhana recipes for the very first time. Within the scope of the study, organoleptic properties of tarhana soups (control and CMP added) were determined, and the formulation with 30% CMP (TCMP30) achieved the highest sensory evaluation scores. This sample was analyzed further, and its physicochemical properties were compared to a control sample strictly following the traditional Uşak tarhana recipe. In the tarhana samples, the moisture, protein, and total fat content increased with higher CMP additions, while the ash, crude cellulose, carbohydrates, energy, salt, and dietary fiber decreased significantly (p < 0.05). The calcium and sodium contents decreased, however, potassium, phosphorus, and zinc contents increased. The fatty acid composition analysis revealed that Uşak tarhana contained more saturated fatty acids than either CMP or TCMP30; adding 30% CMP reduced the total saturated fatty acids while increasing the monounsaturated fatty acids. The main fatty acids in traditional samples were linoleic, palmitic, and oleic acids, comprising 83.82% of the total fat. In TCMP30, the order changed to oleic > linoleic > palmitic with 83.89% of total fat. Over time, the total phenolic content and antioxidant capacity decreased in the control sample but increased in TCMP30. These results suggest that a formulation including 30% CMP effectively enhances the sensory, functional, and nutritional aspects in tarhana.

Our study aimed to investigate the role of endoplasmic reticulum stress (ER) in brain damage following hepatic ischemia-reperfusion (HIR) injury. Specifically, we characterized the expression of markers of ER stress and histopathologic changes in the brain following HIR.

This paper studies a class of coupled dynamical systems consisting of an actuated dynamical system interconnected with an unactuated dynamical system. The actuated dynamical system is considered to have a measurable state for feedback control, whereas only the output is available from the unactuated dynamical system. Specifically, the control objective for this class of dynamical systems is to allow a desired subset of the state of the actuated dynamical system to follow given commands in the presence of uncertain parameters and unactuated dynamical system coupling. To this end, our contribution is a mixed state and output feedback framework in the context of model reference adaptive control, which is predicated on integrated nominal and adaptive control laws. The key feature of the proposed model reference adaptive control architecture is to guarantee stability of the closed-loop coupled dynamical system as well as to assign user-defined bounds on system error trajectories utilised by the adaptive control law for achieving a prescribed level of overall system performance. [ABSTRACT FROM AUTHOR]