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Stimulation of the energy sensor AMP-activated Kinase (AMPK) has been viewed as a targeted approach to increase glucose uptake by skeletal muscle and control blood glucose homeostasis. Rosemary extract (RE) has been reported to activate AMPK in hepatocytes and reduce blood glucose levels in vivo but its effects on skeletal muscle are not known. In the present study, we examined the effects of RE and the mechanism of regulation of glucose uptake in muscle cells. RE stimulated glucose uptake in L6 myotubes in a dose- and time-dependent manner. Maximum stimulation was seen with 5 ug/mL of RE for 4 h (184% +/= 5.07% of control, p

The reconfigurable intelligent surface (RIS) has been recognized as an essential enabling technology for sixth-generation (6G) mobile communication networks. An RIS comprises a large number of small and low-cost reflecting elements whose parameters can be dynamically adjusted with a programmable controller. Each of these elements can effectively reflect a phase-shifted version of the incident electromagnetic wave. By configuring the wave phases in real time, the propagation environment of the information-bearing signals can be dynamically manipulated to enhance communication reliability, boost transmission rate, expand cellular coverage, and strengthen communication security. In this study, we provide an overview on RIS-assisted wireless communications. Specifically, we elaborate on the state-of-the-art enabling techniques for the RIS technology as well as their corresponding substantial benefits from the perspectives of RIS reflection and RIS modulation. With these benefits, we envision the integration of RISs into emerging applications for 6G. In addition, communication security is of unprecedented importance in future 6G networks with ubiquitous wireless services in multifarious verticals and areas. We highlight potential contributions of RISs to physical-layer security, in terms of secrecy rate and secrecy outage probability, exemplified by a typical case study from both theoretical and numerical aspects. Finally, we discuss challenges and opportunities on the deployment of RISs in practice to motivate future research.

Future wireless networks are expected to constitute a distributed intelligent wireless communications, sensing, and computing platform, which will have the challenging requirement of interconnecting the physical and digital worlds in a seamless and sustainable manner. Currently, two main factors prevent wireless network operators from building such networks: (1) the lack of control of the wireless environment, whose impact on the radio waves cannot be customized, and (2) the current operation of wireless radios, which consume a lot of power because new signals are generated whenever data has to be transmitted. In this paper, we challenge the usual “more data needs more power and emission of radio waves” status quo, and motivate that future wireless networks necessitate a smart radio environment: a transformative wireless concept, where the environmental objects are coated with artificial thin films of electromagnetic and reconfigurable material (that are referred to as reconfigurable intelligent meta-surfaces), which are capable of sensing the environment and of applying customized transformations to the radio waves. Smart radio environments have the potential to provide future wireless networks with uninterrupted wireless connectivity, and with the capability of transmitting data without generating new signals but recycling existing radio waves. We will discuss, in particular, two major types of reconfigurable intelligent meta-surfaces applied to wireless networks. The first type of meta-surfaces will be embedded into, e.g., walls, and will be directly controlled by the wireless network operators via a software controller in order to shape the radio waves for, e.g., improving the network coverage. The second type of meta-surfaces will be embedded into objects, e.g., smart t-shirts with sensors for health monitoring, and will backscatter the radio waves generated by cellular base stations in order to report their sensed data to mobile phones. These functionalities will enable wireless network operators to offer new services without the emission of additional radio waves, but by recycling those already existing for other purposes. This paper overviews the current research efforts on smart radio environments, the enabling technologies to realize them in practice, the need of new communication-theoretic models for their analysis and design, and the long-term and open research issues to be solved towards their massive deployment. In a nutshell, this paper is focused on discussing how the availability of reconfigurable intelligent meta-surfaces will allow wireless network operators to redesign common and well-known network communication paradigms.

Reconfigurable intelligent surfaces (RISs) constitute the key enabler for programmable electromagnetic propagation environments and are lately being considered as a candidate physical-layer technology for the demanding connectivity, reliability, localisation, and sustainability requirements of next-generation wireless networks. In this paper, we first present the deployment scenarios for RIS-enabled smart wireless environments that have been recently designed within the ongoing European Union Horizon 2020 RISE-6G project, as well as a network architecture integrating RISs with existing standardised interfaces. We identify various RIS deployment strategies and sketch the core architectural requirements in terms of RIS control and signalling, depending on the RIS hardware architectures and respective capabilities. Furthermore, we introduce and discuss, with the aid of simulations and reflect array measurements, two novel metrics that emerge in the context of RIS-empowered wireless systems: the RIS bandwidth of influence and the RIS area of influence. Their extensive investigation corroborates the need for careful deployment and planning of the RIS technology in future wireless networks.

A new {Dy5} cluster compound has been synthesized and structurally characterized from the initial use of the Schiff base ligand N-naphthalidene-2-amino-5-chlorophenol (nacpH2) in coordination chemistry. The 1:1 reaction between Dy(hpd)3∙2H2O and nacpH2, in a solvent mixture comprising CH2Cl2 and MeOH, afforded orange crystals of [Dy5(OH)2(hpd)3(nacp)5(MeOH)5] (1) in 70% yield, where hpd− is the anion of 3,5-heptadione. The {Dy5} complex can be described as two vertical {Dy3(μ3-OH)}8+ triangles sharing a common vertex; such a metal topology is unprecedented in 4f-metal cluster chemistry. Direct current (dc) magnetic susceptibility studies revealed the presence of some weak ferromagnetic exchange interactions between the five DyIII ions at low temperatures. Alternating current (ac) magnetic susceptibility measurements at zero applied dc field showed that complex 1∙3MeOH∙CH2Cl2 exhibits temperature- and frequency-dependent out-of-phase signals below ~20 K, characteristics of a single-molecule magnet (SMM). The resulting relaxation times were used to construct an Arrhenius-type plot and determine an effective energy barrier, Ueff, of 100 K for the magnetization reversal. The application of a small dc field of 200 Oe resulted in the surpassing of the quantum tunneling process and subsequently the increase of the Ueff to a value of 170 K. The reported results are part of a long-term program aiming at the preparation of structurally and magnetically interesting lanthanide complexes bearing various Schiff base chelating/bridging ligands.

A new Dy5 cluster compound has been synthesized and structurally characterized from the initial use of the Schiff base ligand N-naphthalidene-2-amino-5-chlorophenol (nacpH2) in coordination chemistry. The 1:1 reaction between Dy(hpd)3∙2H2O and nacpH2, in a solvent mixture comprising CH2Cl2 and MeOH, afforded orange crystals of [Dy5(OH)2(hpd)3(nacp)5(MeOH)5] (1) in 70% yield, where hpd− is the anion of 3,5-heptadione. The Dy5 complex can be described as two vertical Dy3(μ3-OH)8+ triangles sharing a common vertex; such a metal topology is unprecedented in 4f-metal cluster chemistry. Direct current (dc) magnetic susceptibility studies revealed the presence of some weak ferromagnetic exchange interactions between the five DyIII ions at low temperatures. Alternating current (ac) magnetic susceptibility measurements at zero applied dc field showed that complex 1∙3MeOH∙CH2Cl2 exhibits temperature- and frequency-dependent out-of-phase signals below ~20 K, characteristics of a single-molecule magnet (SMM). The resulting relaxation times were used to construct an Arrhenius-type plot and determine an effective energy barrier, Ueff, of 100 K for the magnetization reversal. The application of a small dc field of 200 Oe resulted in the surpassing of the quantum tunneling process and subsequently the increase of the Ueff to a value of 170 K. The reported results are part of a long-term program aiming at the preparation of structurally and magnetically interesting lanthanide complexes bearing various Schiff base chelating/bridging ligands.

In this paper, we propose a novel algorithm for energy-efficient, low-latency, accurate inference at the wireless edge, in the context of 6G networks endowed with reconfigurable intelligent surfaces (RISs). We consider a scenario where new data are continuously generated/collected by a set of devices and are handled through a dynamic queueing system. Building on the marriage between Lyapunov stochastic optimization and deep reinforcement learning (DRL), we devise a dynamic learning algorithm that jointly optimizes the data compression scheme, the allocation of radio resources (i.e., power, transmission precoding), the computation resources (i.e., CPU cycles), and the RIS reflectivity parameters (i.e., phase shifts), with the aim of performing energy-efficient edge classification with end-to-end (E2E) delay and inference accuracy constraints. The proposed strategy enables dynamic control of the system and of the wireless propagation environment, performing a low-complexity optimization on a per-slot basis while dealing with time-varying radio channels and task arrivals, whose statistics are unknown. Numerical results assess the performance of the proposed RIS-empowered edge inference strategy in terms of trade-off between energy, delay, and accuracy of a classification task.

The plethora of wirelessly connected devices, whose deployment density is expected to largely increase in the upcoming sixth Generation (6G) of wireless networks, will naturally necessitate substantial advances in multiple access schemes. Reconfigurable Intelligent Surfaces (RISs) constitute a candidate 6G technology capable to offer dynamic over-the-air signal propagation programmability, which can be optimized for efficient non-orthogonal access of a multitude of devices. In this paper, we study the downlink of a wideband communication system comprising multiple multi-antenna Base Stations (BSs), each wishing to serve an associated single-antenna user via the assistance of a Beyond Diagonal (BD) and frequency-selective RIS. Under the assumption that each BS performs Orthogonal Frequency Division Multiplexing (OFDM) transmissions and exclusively controls a distinct RIS, we focus on the sum-rate maximization problem and present a distributed joint design of the linear precoders at the BSs as well as the tunable capacitances and the switch selection matrices at the multiple BD RISs. The formulated non-convex design optimization problem is solved via successive concave approximation necessitating minimal cooperation among the BSs. Our extensive simulation results showcase the performance superiority of the proposed cooperative scheme over non-cooperation benchmarks, indicating the performance gains with BD RISs via the presented optimized frequency selective operation for various scenarios.

The technology of Reconfigurable Intelligent Surfaces (RISs) has lately attracted considerable interest from both academia and industry as a low-cost solution for coverage extension and signal propagation control. In this paper, we study the downlink of a multi-cell wideband communication system comprising single-antenna Base Stations (BSs) and their associated single-antenna users, as well as multiple passive RISs. We assume that each BS controls a separate RIS and performs Orthogonal Frequency Division Multiplexing (OFDM) transmissions. Differently from various previous works where the RIS unit elements are considered as frequency-flat phase shifters, we model them as Lorentzian resonators and present a joint design of the BSs' power allocation, as well as the phase profiles of the multiple RISs, targeting the sum-rate maximization of the multi-cell system. We formulate a challenging distributed nonconvex optimization problem, which is solved via successive concave approximation. The distributed implementation of the proposed design is discussed, and the presented simulation results showcase the interplay of the various system parameters on the sum rate, verifying the performance boosting role of RISs.

This work lies at the intersection of two cutting edge technologies envisioned to proliferate in future 6G wireless systems: Multi-access Edge Computing (MEC) and Reconfigurable Intelligent Surfaces (RISs). While the former will bring a powerful information technology environment at the wireless edge, the latter will enhance communication performance, thanks to the possibility of adapting wireless propagation as per end users' convenience, according to specific service requirements. We propose a joint optimization of radio, computing, and wireless environment reconfiguration through an RIS, with the goal of enabling low power computation offloading services with reliability guarantees. Going beyond previous works on this topic, multi-carrier frequency selective RIS elements' responses and wireless channels are considered. This opens new challenges in RIS optimization, accounting for frequency dependent RIS response profiles, which strongly affect RIS-aided wireless links and, as a consequence, MEC service performance. We formulate an optimization problem accounting for short and long-term constraints involving device transmit power allocation across multiple subcarriers and local computing resources, as well as RIS reconfiguration parameters according to a recently developed Lorentzian model. Besides a theoretical optimization framework, numerical results show the effectiveness of the proposed method in enabling low power reliable computation offloading over RIS-aided frequency selective channels.