Pricing for Reconfigurable Intelligent Surface Aided Wireless Networks: Models and Principles

Owing to the recent advancements of meta-materials and meta-surfaces, the concept of reconfigurable intelligent surface (RIS) has been embraced to meet the spectral- and energy-efficient, and yet cost-effective solutions for the sixth-generation (6G) wireless networks. From an operational standpoint, RISs can be easily deployed on the facades of buildings and indoor walls. Albeit promising, in the actual network operation, the deployment of RISs may face challenges because of the willingness and benefits of RIS holders from the aspect of installing RISs on their properties. Accordingly, RIS-aided wireless networks are faced with a formidable mission: how to balance the wireless service providers (WSPs) and RIS holders in terms of their respective interests. To alleviate this deadlock, we focus on the application of pricing models in RIS-aided wireless networks in pursuit of a win-win solution for both sides. Specifically, we commence with a comprehensive introduction of RIS pricing with its potential applications in RIS networks, meanwhile the fundamentals of pricing models are summarized in order to benefit both RIS holders and WSPs. In addition, a Stackelberg game-based model is exemplified to illustrate the operation of utility-maximization pricing. Finally, we highlight open issues and future research directions of applying pricing models to the RIS-aided wireless networks

Personal Identification Based on Brain Networks of EEG Signals

Personal identification is particularly important in information security. There are numerous advantages of using electroencephalogram (EEG) signals for personal identification, such as uniqueness and anti-deceptiveness. Currently, many researchers focus on single-dataset personal identification, instead of the cross-dataset. In this paper, we propose a method for cross-dataset personal identification based on a brain network of EEG signals. First, brain functional networks are constructed from the phase synchronization values between EEG channels. Then, some attributes of the brain networks including the degree of a node, the clustering coefficient and global efficiency are computed to form a new feature vector. Lastly, we utilize linear discriminant analysis (LDA) to classify the extracted features for personal identification. The performance of the method is quantitatively evaluated on four datasets involving different cognitive tasks: (i) a four-class motor imagery task dataset in BCI Competition IV (2008), (ii) a two-class motor imagery dataset in the BNCI Horizon 2020 project, (iii) a neuromarketing dataset recorded by our laboratory, (iv) a fatigue driving dataset recorded by our laboratory. Empirical results of this paper show that the average identification accuracy of each data set was higher than 0.95 and the best one achieved was 0.99, indicating a promising application in personal identification

Identification of a Novel ACE Inhibitory Hexapeptide from Camellia Seed Cake and Evaluation of Its Stability

The camellia seed cake proteins (CP) used in this study were individually hydrolyzed with neutral protease, alkaline protease, papain, and trypsin. The results showed that the hydrolysate had the highest ACE inhibitory activity at 67.36 ± 0.80% after four hours of neutral protease hydrolysis. Val-Val-Val-Pro-Gln-Asn (VVVPQN) was then obtained through ultrafiltration, Sephadex G-25 gel chromatography separation, LC-MS/MS analysis, and in silico screening. VVVPQN had ACE inhibitory activity with an IC50 value of 0.13 mg/mL (198.66 μmol/L), and it inhibited ACE in a non-competitive manner. The molecular docking indicated that VVVPQN can combine with ACE to form eight hydrogen bonds. The results of the stability study showed that VVVPQN maintained high ACE-inhibitory activity in weakly acidic and neutral environments and that heat treatment (20–80 °C) and Na+, Mg2+, as well as Fe3+ metal ions had little effect on the activity of VVVPQN. Moreover, it remained relatively stable after in vitro simulated gastrointestinal digestion. These results revealed that VVVPQN identified in camellia seed cake has the potential to be applied in functional food or antihypertensive drugs

Low-temperature anode-free potassium metal batteries

Abstract In contrast to conventional batteries, anode-free configurations can extend cell-level energy densities closer to the theoretical limit. However, realizing alkali metal plating/stripping on a bare current collector with high reversibility is challenging, especially at low temperature, as an unstable solid-electrolyte interphase and uncontrolled dendrite growth occur more easily. Here, a low-temperature anode-free potassium (K) metal non-aqueous battery is reported. By introducing Si-O-based additives, namely polydimethylsiloxane, in a weak-solvation low-concentration electrolyte of 0.4 M potassium hexafluorophosphate in 1,2-dimethoxyethane, the in situ formed potassiophilic interface enables uniform K deposition, and offers K||Cu cells with an average K plating/stripping Coulombic efficiency of 99.80% at −40 °C. Consequently, anode-free Cu||prepotassiated 3,4,9,10-perylene-tetracarboxylicacid-dianhydride full batteries achieve stable cycling with a high specific energy of 152 Wh kg−1 based on the total mass of the negative and positive electrodes at 0.2 C (26 mA g−1) charge/discharge and −40 °C

Dynamic Optics with Transparency and Color Changes under Ambient Conditions

Mechanochromic materials have recently received tremendous attention because of their potential applications in humanoid robots, smart windows, strain sensors, anti-counterfeit tags, etc. However, improvements in device design are highly desired for practical implementation in a broader working environment with a high stability. In this article, a novel and robust mechanochromism was designed and fabricated via a facile method. Silica nanoparticles (NPs) that serve as a trigger of color switch were embedded in elastomer to form a bi-layer hybrid film. Upon stretching under ambient conditions, the hybrid film can change color as well as transparency. Furthermore, it demonstrates excellent reversibility and reproducibility and is promising for widespread application

Low-temperature and fast-charge sodium metal batteries

Abstract: Low-temperature operation of sodium metal batteries (SMBs) at the high rate faces challenges of unstable solid electrolyte interphase (SEI), Na dendrite growth, and sluggish Na+ transfer kinetics, causing a largely capacity curtailment. Herein, low-temperature and fast-charge SMBs are successfully constructed by synergetic design of the electrolyte and electrode. The optimized weak-solvation dual-salt electrolyte enables high Na plating/stripping reversibility and the formation of NaF-rich SEI layer to stabilize sodium metal. Moreover, an integrated copper sulfide electrode is in situ fabricated by directly chemical sulfuration of copper current collector with micro-sized sulfur particles, which significantly improves the electronic conductivity and Na+ diffusion, knocking down the kinetic barriers. Consequently, this SMB achieves the reversible capacity of 202.8 mAh g-1 at -20 degrees C and 1 C (1 C = 558 mA g-1). Even at -40 degrees C, a high capacity of 230.0 mAh g-1 can still be delivered at 0.2 C. This study is encouraging for further exploration of cryogenic alkali metal batteries, and enriches the electrode material for low-temperature energy storage. A low-temperature and fast-charge sodium metal battery is successfully constructed by simultaneous design of both the electrolyte and electrode. A weakly solvated dual-salt electrolyte enables fast ion desolvation and the formation of NaF-rich solid electrolyte interphase (SEI) layer to stabilize sodium metal, and meanwhile, CuS as the active material is simply prepared by in situ chemical sulfuration of copper current collector, knocking downg the kinitic barrier in electrode. This synergetic strategy could be extended to other cryogenic alkali metal batteries. imag