Hasil untuk "Other systems of medicine"

M. Graber, N. Franklin, Ruthanna Gordon

P. Pound, N. Britten, M. Morgan et al.

Naglaa M. Hamdy, Ahmed Ismail, Hoda S. Sherkawy et al.

Abstract Ethnopharmacological relevance Punica granatum (pomegranate) peel is traditionally used for its antimicrobial and health-promoting properties in several cultures. Rich in polyphenols, the peel has attracted interest for its potential applications in treating infections and cancer, particularly in integrative approaches for immunocompromised patients. Materials and methods Pomegranate peel extracts were prepared using solvents of increasing polarity, with emphasis on the ethyl acetate fraction (PPE-EA). A nano-formulated version (n-PPE-EA) was developed using a standard nano-encapsulation technique. Cytotoxic activity was evaluated in THP-1 human leukemia cells using MTT assay, flow cytometry, and biochemical analyses. Antimicrobial activity was assessed against Streptococcus pyogenes via agar diffusion. Gene expression of BCL2, PI3K, and CDK8 was measured to elucidate mechanisms of action. Results Among all tested extracts, PPE-EA showed the strongest dual activity, reducing THP-1 cell viability by over 50% at 100 µg/mL and inhibiting S. pyogenes with a 10.5 ± 1.1 mm zone. Nano-encapsulation enhanced both effects, reducing the IC₅₀ from 1.48 ± 0.03 µg/mL to 0.19 ± 0.01 µg/mL and increasing the bacterial inhibition zone to 15.6 ± 0.5 mm. n-PPE-EA induced apoptosis, cell cycle arrest, elevated catalase activity, and reduced malondialdehyde levels. It also downregulated BCL2, PI3K, and CDK8 expression. Conclusion The nano-formulated PPE-EA demonstrated potent cytotoxic and antimicrobial activities, with enhanced efficacy attributed to improved bioavailability and modulation of apoptotic and cell cycle pathways. These findings support its potential as a multifunctional therapeutic agent in integrative cancer care.

H. Sox, S. Greenfield

F. Baluška, M. Levin

The central nervous system (CNS) underlies memory, perception, decision-making, and behavior in numerous organisms. However, neural networks have no monopoly on the signaling functions that implement these remarkable algorithms. It is often forgotten that neurons optimized cellular signaling modes that existed long before the CNS appeared during evolution, and were used by somatic cellular networks to orchestrate physiology, embryonic development, and behavior. Many of the key dynamics that enable information processing can, in fact, be implemented by different biological hardware. This is widely exploited by organisms throughout the tree of life. Here, we review data on memory, learning, and other aspects of cognition in a range of models, including single celled organisms, plants, and tissues in animal bodies. We discuss current knowledge of the molecular mechanisms at work in these systems, and suggest several hypotheses for future investigation. The study of cognitive processes implemented in aneural contexts is a fascinating, highly interdisciplinary topic that has many implications for evolution, cell biology, regenerative medicine, computer science, and synthetic bioengineering.

Sumit S. Kamat, T. Michael Seigler, Jesse B. Hoagg

This article presents a feedback control algorithm for electromagnetic formation flying with constraints on the satellites' states and control inputs. The algorithm combines several key techniques. First, we use alternating magnetic field forces to decouple the electromagnetic forces between each pair of satellites in the formation. Each satellite's electromagnetic actuation system is driven by a sum of amplitude-modulated sinusoids, where amplitudes are controlled in order to prescribe the time-averaged force between each pair of satellites. Next, the desired time-averaged force is computed from a optimal control that satisfies state constraints (i.e., no collisions and an upper limit on intersatellite speeds) and input constraints (i.e., not exceeding satellite's apparent power capability). The optimal time-averaged force is computed using a single relaxed control barrier function that is obtained by composing multiple control barrier functions that are designed to enforce each state and input constraint. Finally, we demonstrate the satellite formation control method in numerical simulations.

Wenxin Liu, Jiakun Fang, Shichang Cui et al.

The growing coupling among electricity, gas, and hydrogen systems is driven by green hydrogen blending into existing natural gas pipelines, paving the way toward a renewable-dominated energy future. However, the integration poses significant challenges, particularly ensuring efficient and safe operation under varying hydrogen penetration and infrastructure adaptability. This paper reviews progress in optimization and control technologies for hydrogen-blended integrated gas-electricity system. First, key technologies and international demonstration projects are introduced to provide an overview of current developments. Besides, advances in gas-electricity system integration, including modeling, scheduling, planning and market design, are reviewed respectively. Then, the potential for cross-system fault propagation is highlighted, and practical methods for safety analysis and control are proposed. Finally, several possible research directions are introduced, aiming to ensure efficient renewable integration and reliable operation.

Francisco M. F. R. Gonçalves, Ryan M. Bena, Néstor O. Pérez-Arancibia

We introduce a new class of attitude control laws for rotational systems; the proposed framework generalizes the use of the Euler \mbox{axis--angle} representation beyond quaternion-based formulations. Using basic Lyapunov stability theory and the notion of extended class $\mathcal{K}$ function, we developed a method for determining and enforcing the global asymptotic stability of the single fixed point of the resulting \mbox{\textit{closed-loop}} (CL) scheme. In contrast with traditional \mbox{quaternion-based} methods, the introduced generalized \mbox{axis--angle} approach enables greater flexibility in the design of the control law, which is of great utility when employed in combination with a switching scheme whose transition state depends on the angular velocity of the controlled rotational system. Through simulation and \mbox{real-time} experimental results, we demonstrate the effectiveness of the developed formulation. According to the recorded data, in the execution of \mbox{high-speed} \mbox{tumble-recovery} maneuvers, the new method consistently achieves shorter stabilization times and requires lower control effort relative to those corresponding to the \mbox{quaternion-based} and \mbox{geometric-control} methods used as benchmarks.

Themistoklis Charalambous, Zheng Chen, Christoforos N. Hadjicostis

In this paper, we address the average consensus problem of multi-agent systems over wireless networks. We propose a distributed average consensus algorithm by invoking the concept of over-the-air aggregation, which exploits the signal superposition property of wireless multiple-access channels. The proposed algorithm deploys a modified version of the well-known Ratio Consensus algorithm with an additional normalization step for compensating for the arbitrary channel coefficients. We show that, when the noise level at the receivers is negligible, the algorithm converges asymptotically to the average for time-invariant and time-varying channels. Numerical simulations corroborate the validity of our results.

Rauhaan Tahir, Sadeed Ahmed Choudhury, Rasi Mizori et al.

Mayara de Souza Dadda, Maria Beatriz Luce

Introdução: A Lei de Cotas é uma política pública educacional instituída no Brasil há mais de 10 anos, que visa democratizar o acesso de estudantes egressos de escolas públicas às instituições federais de educação superior e de ensino técnico por um recorte étnico-racial e de renda familiar per capita. Objetivo: Analisar progressos e desafios encontrados por universidades federais na aplicação do sistema de reserva de vagas, para avaliar se o grau de engajamento dessas com tal política promove a justiça social para os estudantes negros. Metodologia: Análise qualitativa de documentos oficiais relativos às cotas nas seis universidades federais com sede no Rio Grande do Sul. A coleta de informações foi realizada nas respectivas páginas institucionais, focando em resoluções dos conselhos universitários e normativas sobre ações afirmativas. A técnica de análise documental permitiu reconstruir contextos históricos e adicionar uma perspectiva temporal à compreensão social. Resultados: A aplicação da Lei de Cotas variou significativamente entre as universidades federais estudadas. Quatro  já adotavam políticas de ação afirmativa antes de 2012, enquanto outras duas implementaram tais medidas pela obrigação legal. Duas universidades mostraram avanços não apenas no acesso, mas também na permanência dos estudantes cotistas, aproximando-se das medidas transformativas de Fraser, que visam mudanças estruturais. Em contrapartida, duas ainda precisam avançar para além das medidas afirmativas de acesso, adotando políticas que assegurem a permanência e a diplomação dos estudantes. Conclusão: A implementação de ações afirmativas é crucial para a promoção da justiça social na Educação Superior. As universidades federais sediadas no Rio Grande do Sul apresentam diferentes níveis de engajamento com essas políticas, refletindo suas histórias e contextos institucionais. É essencial continuar avançando nas políticas de inclusão, garantindo não apenas o acesso, mas também a permanência e o sucesso acadêmico dos estudantes cotistas para construir um sistema educacional mais inclusivo e equitativo.

Yonca Coluk, Emine Gulceri Gulec Peker, Sembol Yildirmak et al.

Abstract Background Chronic Rapid eye movement (REM) sleep deprivation has been associated with various cardiovascular alterations, including disruptions in antioxidant defense mechanisms, lipid metabolism, and inflammatory responses. This study investigates the therapeutic potential of green tea extract (GTE) in mitigating these adverse effects. Methods A total of 24 male Wistar albino rats were used in this study and divided into the control group (n = 8), Chronic-REM Sleep Deprivation (CRSD) Group (n = 8) and Chronic-REM SD + Green Tea 200 (CRSD + GTE200) Group (n = 8). After 21 days, a comprehensive analysis of paraoxonase (PON1), arylesterase (ARE), malondialdehyde (MDA), glutathione (GSH), nitric oxide (NOx), proinflammatory cytokines, and lipid profiles in aortic tissue, heart tissue, and serum was conducted in a sleep-deprived rat model. Results Chronic REM sleep deprivation led to a significant reduction in PON1 and ARE levels in aortic (p = 0.046, p = 0.035 respectively) and heart tissues (p = 0.020, p = 0.019 respectively), indicative of compromised antioxidant defenses. MDA levels increased, and NOx levels decreased, suggesting oxidative stress and impaired vascular function. Lipid profile alterations, including increased triglycerides and total cholesterol, were observed in serum. Elevated levels of inflammatory cytokines (IL-6 and TNF-alpha) further indicated an inflammatory response (p = 0.007, p = 0.018 respectively). GTE administration demonstrated a protective role, restoring antioxidant enzyme levels, suppressing lipid peroxidation, and improving NOx levels. Conclusion These findings suggest the therapeutic potential of GTE in alleviating the cardiovascular impairments of chronic REM sleep deprivation, emphasizing its candidacy for further clinical exploration as a natural intervention in sleep-related disorders and associated cardiovascular risks.

Tatiana ABRAȘ, Marcel ABRAȘ, Petru NUCĂ

Obiceiurile alimentare nesănătoase, cât și malnutriția reprezintă factori de risc importanți și independenți cu o influență sporită asupra pacienților cu boală coronariană ischemică (BCI), fiind incomplet elucidate în literatura actuală. Studiul dat este unul observațional descriptiv în care au fost incluși 88 de pacienți (vârsta medie de 65,61 ± 8,40 ani, 68,18 % fiind bărbați) cu BCI, care au fost divizați în două grupe: grupul subiecților cu sindrom coronarian acut (SCA) și grupul subiecților cu sindrom coronarian cronic (SCC), ambele grupe fiind supuși procedurii de angioplastie coronariană. Obiectivele principale au fost stabilirea corelației între paternul alimentar nesănătos și riscul de BCI, precum și influența statutului nutrițional asupra SCA și SCC. Sa determinat că obezitatea, dislipidemia, hipertensiunea arterială, consumul frecvent de carne roșie și procesată, consumul rar de pește, crește riscul de apariție a BCI. Starea nutrițională evaluată prin scorul de control al stării nutriționale (CONUT) a fost mai frecvent crescută la pacienții cu SCA.

Andreas Katsanikakis, Nikolaos Bekiaris-Liberis, Delphine Bresch-Pietri

We develop an input delay-compensating feedback law for linear switched systems with time-dependent switching. Because the future values of the switching signal, which are needed for constructing an exact predictor-feedback law, may be unavailable at current time, the key design challenge is how to construct a proper predictor state. We resolve this challenge constructing an average predictor-based feedback law, which may be viewed as an exact predictor-feedback law for a particular average system without switching. We establish that, under the predictor-based control law introduced, the closed-loop system is exponentially stable, provided that the plant's parameters are sufficiently close to the corresponding parameters of the average system. In particular, the allowable difference is inversely proportional to the size of delay and proportional to the dwell time of the switching signal. Since no restriction is imposed on the size of delay or dwell time themselves, such a limitation on the parameters of each mode is inherent to the problem considered (in which no a priori information on the switching signal is available), and thus, it cannot be removed. The stability proof relies on two main ingredients-a Lyapunov functional constructed via backstepping and derivation of solutions' estimates for the difference between the average and the exact predictor states. We present consistent, numerical simulation results, which illustrate the necessity of employing the average predictor-based law for achieving stabilization and desired performance of the closed-loop system.

Airong Ren, Tingbiao Wu, Yarong Wang et al.

Abstract Background Ziziphi Spinosae Semen (ZSS) is a plant widely used as medicine and food in Asian countries due to its numerous health benefits. γ-aminobutyric acid (GABA), a non-proteinaceous amino acid, is one of the major inhibitory neurotransmitters with a relaxant function. In this study, a system pharmacology approach was employed to assess the effects of a mixture composed of ZSS and GABA (ZSSG) on sleep improvement. Methods Mice were divided into five groups (n = 10) and received either no treatment, sodium pentobarbital, or sodium barbital with diazepam or ZSSG. The effects of ZSSG on sleep quality were evaluated in mice, and differential metabolites associated with sleep were identified among the control, ZSS, GABA, and ZSSG groups. Additionally, network-based ingredient-insomnia proximity analysis was applied to explore the major ingredients. Results ZSSG significantly improved sleep quality by decreasing sleep latency and prolonging sleep duration in sodium pentobarbital-induced sleeping mouse model (P < 0.05). ZSSG significantly enhanced the brain content of GABA in mice. Furthermore, ZSSG also significantly decreased sleep latency-induced by sodium barbital in mice (P < 0.05). Metabolic analysis revealed significant differences in 10 metabolites between ZSSG group and the groups administering ZSS or GABA. Lastly, using the network-based ingredient screening model, we discovered potential four active ingredients and three pairwise ingredient combinations with synergistic effect on insomnia from ZSSG among 85 ingredients identified by UPLC-Q/TOF–MS. Also, we have constructed an online computation platform. Conclusion Our data demonstrated that ZSSG improved the sleeping quality of mice and helped to balance metabolic disorders-associated with sleep disorders. Moreover, based on the network-based prediction method, the four potential active ingredients in ZSSG could serve as quality markers-associated with insomnia. The network-based framework may open up a new avenue for the discovery of active ingredients of herbal medicine for treating complex chronic diseases or symptoms, such as insomnia.

Ali Baheri, Mykel J. Kochenderfer

Safety validation is a crucial component in the development and deployment of autonomous systems, such as self-driving vehicles and robotic systems. Ensuring safe operation necessitates extensive testing and verification of control policies, typically conducted in simulation environments. High-fidelity simulators accurately model real-world dynamics but entail high computational costs, limiting their scalability for exhaustive testing. Conversely, low-fidelity simulators offer efficiency but may not capture the intricacies of high-fidelity simulators, potentially yielding false conclusions. We propose a joint falsification and fidelity optimization framework for safety validation of autonomous systems. Our mathematical formulation combines counterexample searches with simulator fidelity improvement, facilitating more efficient exploration of the critical environmental configurations challenging the control system. Our contributions encompass a set of theorems addressing counterexample sensitivity analysis, sample complexity, convergence, the interplay between the outer and inner optimization loops, and regret bound analysis. The proposed joint optimization approach enables a more targeted and efficient testing process, optimizes the use of available computational resources, and enhances confidence in autonomous system safety validation.

Elizaveta Savchenko, Svetlana Bunimovich-Mendrazitsky

In today's complex healthcare landscape, the pursuit of delivering optimal patient care while navigating intricate economic dynamics poses a significant challenge for healthcare service providers (HSPs). In this already complex dynamics, the emergence of clinically promising personalized medicine based treatment aims to revolutionize medicine. While personalized medicine holds tremendous potential for enhancing therapeutic outcomes, its integration within resource-constrained HSPs presents formidable challenges. In this study, we investigate the economic feasibility of implementing personalized medicine. The central objective is to strike a balance between catering to individual patient needs and making economically viable decisions. Unlike conventional binary approaches to personalized treatment, we propose a more nuanced perspective by treating personalization as a spectrum. This approach allows for greater flexibility in decision-making and resource allocation. To this end, we propose a mathematical framework to investigate our proposal, focusing on Bladder Cancer (BC) as a case study. Our results show that while it is feasible to introduce personalized medicine, a highly efficient but highly expensive one would be short-lived relative to its less effective but cheaper alternative as the latter can be provided to a larger cohort of patients, optimizing the HSP's objective better.

Manolis Chiou, Mohammed Talha, Rustam Stolkin

This paper investigates learning effects and human operator training practices in variable autonomy robotic systems. These factors are known to affect performance of a human-robot system and are frequently overlooked. We present the results from an experiment inspired by a search and rescue scenario in which operators remotely controlled a mobile robot with either Human-Initiative (HI) or Mixed-Initiative (MI) control. Evidence suggests learning in terms of primary navigation task and secondary (distractor) task performance. Further evidence is provided that MI and HI performance in a pure navigation task is equal. Lastly, guidelines are proposed for experimental design and operator training practices.

Augustinos D. Saravanos, Yihui Li, Evangelos A. Theodorou

As the scale and complexity of multi-agent robotic systems are subject to a continuous increase, this paper considers a class of systems labeled as Very-Large-Scale Multi-Agent Systems (VLMAS) with dimensionality that can scale up to the order of millions of agents. In particular, we consider the problem of steering the state distributions of all agents of a VLMAS to prescribed target distributions while satisfying probabilistic safety guarantees. Based on the key assumption that such systems often admit a multi-level hierarchical clustered structure - where the agents are organized into cliques of different levels - we associate the control of such cliques with the control of distributions, and introduce the Distributed Hierarchical Distribution Control (DHDC) framework. The proposed approach consists of two sub-frameworks. The first one, Distributed Hierarchical Distribution Estimation (DHDE), is a bottom-up hierarchical decentralized algorithm which links the initial and target configurations of the cliques of all levels with suitable Gaussian distributions. The second part, Distributed Hierarchical Distribution Steering (DHDS), is a top-down hierarchical distributed method that steers the distributions of all cliques and agents from the initial to the targets ones assigned by DHDE. Simulation results that scale up to two million agents demonstrate the effectiveness and scalability of the proposed framework. The increased computational efficiency and safety performance of DHDC against related methods is also illustrated. The results of this work indicate the importance of hierarchical distribution control approaches towards achieving safe and scalable solutions for the control of VLMAS. A video with all results is available in https://youtu.be/0QPyR4bD2q0 .

G. Pezzulo, M. Levin