Dye‐Doped Polyhedral Oligomeric Silsesquioxane (POSS)‐Modified Polymeric Matrices for Highly Efficient and Photostable Solid‐State Lasers

Here, the design, synthesis, and characterization of laser nanomaterials based on dye‐doped methyl methacrylate (MMA) crosslinked with octa(propyl‐methacrylate) polyhedral oligomeric silsesquioxane (8MMAPOSS) is reported in relation to their composition and structure. The influence of the silicon content on the laser action of the dye pyrromethene 567 (PM567) is analyzed in a systematic way by increasing the weight proportion of POSS from 1 to 50%. The influence of the inorganic network structure is studied by replacing the 8MMAPOSS comonomer by both the monofunctionalized heptaisobutyl‐methacryl‐POSS (1MMAPOSS), which defines the nanostructured linear network with the POSS cages appearing as pendant groups of the polymeric chains, and also by a new 8‐hydrogenated POSS incorporated as additive to the polymeric matrices. The new materials exhibit enhanced thermal, optical, and mechanical properties with respect to the pure organic polymers. The organization of the molecular units in these nanomaterials is studied through a structural analysis by solid‐state NMR. The domain size of the dispersed phase assures a homogeneous distribution of POSS into the polymer, thus, a continuous phase corresponding to the organic matrix incorporates these nanometer‐sized POSS crosslinkers at a molecular level, in agreement with the transparency of the samples. The silicon–oxygen core framework has to be covalently bonded into the polymer backbone instead of being a simple additive and both the silica content and crosslinked degree exhibit a critical influence on the laser action.     

Toward the Optimized Spintronic Response of Sn‐Doped IrO2 Thin Films

Amorphous and polycrystalline Sn‐doped IrO₂ thin films, Ir_1‐xSn_xO₂, are grown for the first time. Their electrical response and strength of the spin–orbit coupling are studied in order to better understand and tailor its performance as spin current detector material. These experiments prove that the resistivity of IrO₂ can be tuned over several orders of magnitude by controlling the doping content in both the amorphous and the polycrystalline state. In addition, growing amorphous samples increase the resistivity, thus improving the spin current to charge current conversion. As far as the spin–orbit coupling is concerned, the system not only remains in a strong spin–orbit coupling regime but it seems to undergo a slight enhancement in the amorphous state as well as in the Sn‐doped samples.     

Dynamic wavelet-based pilot allocation algorithm for OFDM-based cognitive radio systems

In a cognitive radio system, the goal is to make better use of the radio electric spectrum, allowing non-licensed users access to those currently unused electromagnetic bands assigned to licensed users (LUs). This can be achieved using OFDM, where the non-licensed users must select the temporarily available subcarriers and turn off those subcarriers used by LUs in order to avoid interference. Hence, only a subset of the subcarriers can be used for data or pilot tone transmission. To this end, some pilot allocation algorithms have been proposed for this dynamic scenario, but they are designed in such away that an equispaced pilot placement is respected (as much as possible) while minimizing the mean squared error of the channel estimate. Nevertheless, this equispaced placement can lead to the use of an increased number of pilots in order to achieve a good channel estimation. In this work, a new pilot allocation algorithm based on wavelet transform is presented. The proposed algorithm uses the discrete wavelet transform to analyze the previous channel state information, taking the knowledge of the available subcarriers into account to provide a suboptimal solution for the pilot positions. This solution leads to a non-equispaced pilot placement, which improves the channel estimation and consequently, the system performance. Likewise, the introduced algorithm allows a reduction of the number of necessary pilots, which aids in increasing the data rate. Finally, simulation results corroborate the effectiveness of the algorithm in dynamic channel scenarios.     

Assemblies of Functional Peptides and Their Applications in Building Blocks for Biosensors

This feature article highlights our recent applications of functional peptide nanotubes, self‐assembled from short peptides with recognition elements, as building blocks to develop sensors. Peptide nanotubes with high aspect ratios are excellent building blocks for a directed assembly into device configurations, and their combined structures with nanometric diameters and micrometric lengths enables to bridge the “nanoworld” and the “microworld”. When the peptide‐nanotube‐based biosensors, which incorporate molecular recognition units, apply alternating current probes to detect impedance signals, the peptide nanotubes behave as excellent building blocks of the transducer for the detection of target analyes such as pathogens, cells, and heavey metal ions with high specificity. In some sensor configurations, the electric signal can be amplified by coupling them with ion‐specific mineralization via molecular recognition of peptides. In general the detection limit of peptide nanotube chips sensors is very low and the dynamic range of detection can be widened by improved device designs.     

Impact of Ge-Sb-Te compound engineering on the set operation performance in phase-change memories

The phase-change memory (PCM) technology is considered as one of the most attractive non-volatile memory concepts for next generation data storage. It relies on the ability of a chalcogenide material belonging to the Ge-Sb-Te compound system to reversibly change its phase between two stable states, namely the poly-crystalline low-resistive state and the amorphous high-resistive state, allowing the storage of the logical bit. A careful study of the phase-change material properties in terms of the set operation performance, the program window and the electrical switching parameters as a function of composition is very attractive in order to enlarge the possible PCM application spectrum. Concerning the set performance, a crystallization kinetics based interpretation of the observed behavior measured on different Ge-Sb-Te compounds is provided, allowing a physics-based comprehension of the reset-to-set transition.     

Securing light clients in blockchain with DLCP

In blockchain, full nodes (FNs) are peers that store and verify entire chains of transactions. In contrast, light clients (LCs) are those with limited resources, and for this reason, they request only block headers from FNs for transaction verification—using protocols like Simple Payment Verification (SPV). In an approach to prevent FN tampering on transaction verification (byzantine fault), LCs request block headers from multiple FNs and compare received responses. One problem with this approach is that an LC must connect to each FN and perform the same cryptographic operations with each one repeatedly, which leads to client‐side complexity and slower response. We propose an alternate approach to tackle this issue, in which LCs can encrypt a request for block headers only once, and send that request to a predetermined set of FNs to access, process, and reply back in a single response. Our approach, called Distributed Lightweight Client Protocol (DLCP), enables LCs to verify with little effort if FNs have agreed on a response. From an experimental evaluation, we observed that DLCP provided lower latency and reduced computing and communication overhead in comparison with the existing conventional approach.     

A four-shell diffusion phantom of the head for electrical impedance tomography

A four-shell head phantom has been built and characterized. Its structure is similar to that of nonhomogeneous concentric shell domains used by numerical solvers that better approximate current distribution than phantoms currently used to validate electrical impedance tomography systems. Each shell represents a head tissue, namely, skin, skull, cerebrospinal fluid, and brain. A novel technique, which employs a volume conductive impermeable film, has been implemented to prevent ion diffusion between different agar regions without affecting current distribution inside the phantom. Comparisons between simulations and phantom measurements performed over four days are given to prove both the adherence to the model in the frequency range between 10 kHz and 1 MHz and its long-term stability.     

Metabolic P Systems： A Discrete Model for Biological Dynamics

A recent methodology to model biochem- ical systems is here presented. It is based on a concep- tual framework rooted in membrane computing and de- veloped with concepts typical of discrete dynamical sys- tems. According to our approach, from data observed at suitable macroscopic temporal scales, one can deduce, by means of algebraic and algorithmic procedures, a dis- crete model （called Metabolic P system） which accounts for the experimental data, and opens the possibility to under- stand the systemic logic of the investigated phenomenon. The procedures of such a method have been implemented within a computational platform, a Java software called MetaPlab, processing data and simulating behaviors of metabolic models. In the paper, we briefly describe the theory underlying the modeling of biochemical systems by Metabolic P systems, along with its development stages and the related extensive literature.