A probabilistic model of quantum states for classical data security

The phenomenal progress of quantum information theory over the last decade has substantially broadened the potential to simulate the superposition of states for exponential speedup of quantum algorithms over their classical peers. Therefore, the conventional and modern cryptographic standards (encryption and authentication) are susceptible to Shor’s and Grover’s algorithms on quantum computers. The significant improvement in technology permits consummate levels of data protection by encoding classical data into small quantum states that can only be utilized once by leveraging the capabilities of quantum-assisted classical computations. Considering the frequent data breaches and increasingly stringent privacy legislation, we introduce a hybrid quantum-classical model to transform classical data into unclonable states, and we experimentally demonstrate perfect state transfer to exemplify the classical data. To alleviate implementation complexity, we propose an arbitrary quantum signature scheme that does not require the establishment of entangled states to authenticate users in order to transmit and receive arbitrated states to retrieve classical data. The consequences of the probabilistic model indicate that the quantum-assisted classical framework substantially enhances the performance and security of digital data, and paves the way toward real-world applications.     

A Fluorine-19 Magnetic Resonance Probe,Shiga-Y5, Downregulates Thioredoxin-Interacting Protein Expression in the Brain of a Mouse Model of Alzheimer’s Disease

Thioredoxin-interacting protein (TXNIP) is involved in multiple disease-associated functions related to oxidative stress, especially by inhibiting the anti-oxidant- and thiol-reducing activity of thioredoxin (TXN). Shiga-Y5 (SY5), a fluorine-19 magnetic resonance probe for detecting amyloid-β deposition in the brain, previously showed therapeutic effects in a mouse model of Alzheimer’s disease; however, the mechanism of action of SY5 remains unclear. SY5 passes the blood–brain barrier and then undergoes hydrolysis to produce a derivative, Shiga-Y6 (SY6), which is a TXNIP-negative regulator. Therefore, this study investigates the therapeutic role of SY5 as the prodrug of SY6 in the thioredoxin system in the brain of a mouse model of Alzheimer’s disease. The intraperitoneal injection of SY5 significantly inhibited TXNIP mRNA (p = 0.0072) and protein expression (p = 0.0143) induced in the brain of APP/PS1 mice. In contrast, the levels of TXN mRNA (p = 0.0285) and protein (p = 0.0039) in the brain of APP/PS1 mice were increased after the injection of SY5. The ratio of TXN to TXNIP, which was decreased (p = 0.0131) in the brain of APP/PS1 mice, was significantly increased (p = 0.0072) after the injection of SY5. These results suggest that SY5 acts as a prodrug of SY6 in targeting the thioredoxin system and could be a potential therapeutic compound in oxidative stress-related diseases in the brain.     

Study of crystallization kinetics of Se77.5Te15Sb7.5 glass using isoconversional models

The crystallization process of Se_77.5Te₁₅Sb_7.5 glass is studied by differential scanning calorimetry (DSC) technique under non-isothermal conditions at various heating rates. The crystallization parameters are deduced using different models. The validity of the Johnson–Mehl–Avrami (JMA) model to describe the crystallization process for the studied composition is investigated. Comparing experimental and calculated DSC curves indicate that the crystallization process of Se_77.5Te₁₅Sb_7.5 glass cannot satisfactorily be described by the JMA model. In general, simulation results indicate that the Sestak–Berggren model is more suitable to describe the crystallization kinetics. The crystalline phases are identified using the X-ray diffraction technique and scanning electron microscopy.     

System for <Emphasis Type="Italic">In Situ</Emphasis> Characterization of Nanoparticles Synthesized in a Thermal Plasma Process

We have designed a particle diagnostic system that is able to measure particle size and charge distributions from low stagnation pressure (≥746 Pa) and high temperature (2000–4000 K) environments in near real time. This system utilizes a sampling probe interfaced to an ejector to draw aerosol from the low pressure chamber. Particle size and charge distributions are measured with a scanning mobility particle sizer. A hypersonic impactor is mounted in parallel with the scanning mobility particle sizer to collect particles for off-line microscopic analysis. This diagnostic system has been used to measure size and charge distributions of nanoparticles (Si, Ti, Si–Ti–N, etc.) synthesized with our thermal plasma reactor. We found that the mean particle size increases with operating pressure and reactant flow rates. We also found that most particles from our reactor are neutral for particles smaller than 20 nm, and that the numbers of positively and negatively charged particles are approximately equal.     

Electrode effects on the electrical properties of chalcogenide films

The effect of Al, Ag and Cr metal electrodes on the electrical properties of CeSeTe films was studied. The relative ease of the diffusion of metallic atoms and the accompanied tendency to nucleation leads to irreversible changes of the film resistivity while annealing. The recrystallization temperature of the chalcogenide film depends strongly on the type of the metal electrode. The observed increase in the values of resistivity after annealing, was interpreted on the basis of charged dangling bond theory.     

What Determines the Selectivity of Arginine Dihydroxylation by the Nonheme Iron Enzyme OrfP?

The nonheme iron enzyme OrfP reacts with l -Arg selectively to form the 3R,4R-dihydroxyarginine product, which in mammals can inhibit the nitric oxide synthase enzymes involved in blood pressure control. To understand the mechanisms of dioxygen activation of l -Arg by OrfP and how it enables two sequential oxidation cycles on the same substrate, we performed a density functional theory study on a large active site cluster model. We show that substrate binding and positioning in the active site guides a highly selective reaction through C³−H hydrogen atom abstraction. This happens despite the fact that the C³−H and C⁴−H bond strengths of l -Arg are very similar. Electronic differences in the two hydrogen atom abstraction pathways drive the reaction with an initial C³−H activation to a low-energy ⁵σ-pathway, while substrate positioning destabilizes the C⁴−H abstraction and sends it over the higher-lying ⁵π-pathway. We show that substrate and monohydroxylated products are strongly bound in the substrate binding pocket and hence product release is difficult and consequently its lifetime will be long enough to trigger a second oxygenation cycle.     

Structural and electrical properties of doped polypyrrole and its composite with montmorillonite clay

Polypyrrole is synthesized and doped with Dodecylbenzenesulphonic acid. The doped Polypyrrole with Dodecylbenzenesulphonic acid is intercalated into the layers of Montmorillonite clay successfully by in situ polymerization. The structural properties of synthesized doped Polypyrrole and intercalated doped Polypyrrole were studied by XRD analysis. The crystallinity of intercalated doped Polypyrrole into the layers of Montmorillonite clay is confirmed by means of X-rays diffraction studies, which is more than the doped Polypyrrole. Enhanced d-spacing of Montmorillonite confirmed that doped Polypyrrole is interclated into the layers of Montmorillonite clay at nanoscale. The scanning electron micrographs also confirm the formation of dual phase of platelet as well as of flaky structure of intercalated doped Polypyrrole. Temperature dependant conductivity showed three dimensional variable ranges hopping model. Activation energy, density of states and hopping length are calculated and found to be influenced by intercalating Doped Polypyrole into the layers of Montmorillonite clay.     

Synthesis of novel Schiff base doped sol–gel silicas

Sulfonamide Schiff bases were doped uniformly in silica sol–gels prepared from liquid precursors by a fast and easy way at room temperature and processed to form xerogels. Schiff bases are efficient chelating agents, bioactive and catalytically active compounds. The structures of the newly synthesized Schiff base doped xerogels were elucidated by their physical (morphology, surface area, porosity), spectral (FTIR) and analytical (CHNSO/Si) data. The powder X-ray diffraction studies were carried out to confirm the formation of single phase. Characterization confirmed that Schiff base molecules are entrapped inside the pores as well as physically bound onto the silica surface. All Schiff base doped xerogels are stable mesoporous materials showing hydrophilic properties. Loadings of Schiff bases from 0.10 to 0.23 g/g of xerogel were obtained resulting amorphous materials. The doping of Schiff bases with xerogel caused change in surface area, pore volume and pore diameter of xerogel without damaging the main framework of siliceous skeleton. Morphology and colour of xerogel was also changed after doping. The entrapment of Schiff bases in xerogel caused increase in their decomposition temperatures. The final Schiff base doped xerogels show remarkable thermal stability.     

Activated Anilide in Heterocyclic Synthesis: Synthesis of New Dihydropyridines,Dihydropyridazines and Thiourea Derivatives

A series of new dihydropyridines, butanamide, dihydropyridazines and thiourea derivatives have been prepared through the reactions of 3‐aminopyridine ( 1 ) and N‐(pyridin‐3‐yl)‐3‐(pyridin‐3‐ylimino)butanamide 3 with some electrophilic reagents, aryl diazonium salts and isothiocyanates. Elementary analysis, MS, IR, and ¹H NMR spectra confirmed the identity of the products.     

A phenomenological memristor model for short-term/long-term memory

Memristor is considered to be a natural electrical synapse because of its distinct memory property and nanoscale. In recent years, more and more similar behaviors are observed between memristors and biological synapse, e.g., short-term memory (STM) and long-term memory (LTM). The traditional mathematical models are unable to capture the new emerging behaviors. In this article, an updated phenomenological model based on the model of the Hewlett–Packard (HP) Labs has been proposed to capture such new behaviors. The new dynamical memristor model with an improved ion diffusion term can emulate the synapse behavior with forgetting effect, and exhibit the transformation between the STM and the LTM. Further, this model can be used in building new type of neural networks with forgetting ability like biological systems, and it is verified by our experiment with Hopfield neural network.