Employing DFT technique, we perform Pt/Ni doping and Pt-Ni co-doping into CeO2. We study the structural, electronic, magnetic, and optical properties of CeO2 with selected dopants using Wien2k code. Spin-polarized DOS illustrate non-magnetic character of pure CeO2 while Pt/Ni/Pt-Ni doping yields magnetism into CeO2 with magnetic moment values of 2.2502 μ_B, 2.5683 μ_B, and 3.9190 μ_B, respectively. Active participation of Ce 4f-, Pt 4d- and Ni 3d-states at the Fermi level suggests remarkable improvement in the conduction process. p-d hybridization is observed and it produces good response in electronic properties. [email protected] and [email protected] exhibit blueshift while [email protected] exhibit redshift in absorption spectrum. We notice an enhancement in optical absorption and conductivity with decreased reflectivity of these proposed materials in the UV region. Tuning of absorption spectra and decrease in band gap of these materials indicate their uses for photocatalytic, photonic, optoelectronics and power electronic devices.

Using the ergodicity of chaotic iterative sequences to realize data compression is a new research perspective. We find that, under suitable initial conditions, one or more local segments that are numerically identical to random integer sequences appear on the iterative sequence, which is a prerequisite for compression. Based on this, this paper designs a random integer lossless compression method based on three-dimensional product-triangular chaotic iterative sequences. The method proposed only needs to input a small amount of iterative initial information to compress a large amount of data through an iterative sequence of limited length. The key lies in three aspects. First, according to the characteristics of the data to be compressed, the iterative initial conditions suitable for compression are obtained by screening. Secondly, map the traversal results into a sequence of binary integers to complete the recording of key information. Finally, this binary integer sequence is rapidly compressed using a designed parity symmetric transformation algorithm, and decompression is achieved in its reverse process. As a new way to achieve compression, this approach is not only simple, but also requires less computation time. The experimental results show that the compression effect achieved by this method has obvious advantages in terms of compression ratio, data reconstruction quality, and compression and decompression speed. Keywords: trigonometric function, chaos, data compression

Rumors are abnormal children of public opinion, they usually arise with environmental crisis and have serious negative functions. Hence, how to control rumor propagation has become an urgent topic for the government. Since the communication between people in the real world is inevitably interfered by random factors, and time delay exists in the process of rumor propagation not only influence rumor- forwarding individuals by rumor-hesitant individuals but also in government decision-making. Based on these premises, we propose a stochastic delayed rumor propagation model with generalized incidence function. By setting the suitable Lyapunov functions, we show that the asymptotic behavior of stochastic rumor spreading model is constrained by some conditions. Finally, our analytical results are supported by numerical simulations. The results show that (1) the increase of noise intensity in social environment will reduce rumor propagation; (2) time delay has an impact on rumor propagation to a certain extent. Extending the thinking time may reduce the number of rumor-forwarding individuals and even lead to the disappearance of rumors; (3) improve scientific literacy and accelerate rumor refutation (i.e. reduce the value of β), strengthen rumor suppression (i.e. increase the value of γ) can effectively control rumor transmission.

In this paper, the sensor was proposed by combination of grapefruit photonic crystal fiber (GPCF) and femtosecond laser fabricated fiber Bragg grating (FBG) based on Sagnac interferometer. The GPCF was sandwiched between two single-mode fibers (SMFS) to form a SMF-GPCF-SMF structure, which was based on intermodal interference. The FBG with a central wavelength of 1535.32 nm was inscribed through polyimide coating and cladding by the femtosecond laser point-by-point inscribing method. The spectrum drift data of sensing structure were collected and the dual-parameters matrix of temperature-strain was constructed to realize the simultaneous measurement of temperature and strain. The experimental results showed that the linear range of the strain measurement was from 0 με to 2,000 με at different temperature, the wavelength of FBG and GPCF was red drift and blue drift, respectively, the average strain sensitivity at different temperature was 1.25 pm/με and -2.05 pm/με, all the linearity R2 are higher than 0.999, and has the high repeatability. The linear range of temperature measurement was from 20 ℃ to 450 ℃, the wavelength of FBG and GPCF was red drift and blue drift, respectively, the temperature sensitivity of FBG and GPCF was 15.17 pm/℃ and -8.87 pm/℃, the linearity was 0.99983 and 0.99989, respectively.

Most hBN nanostructures were fabricated using the chemical method. However, growing by the physical method also has many advantages, they are easy to synthesize this material on a large area with up- scaling setups. Even two-dimensional hexagonal boron nitride is similar to graphene structure, however there is a little work referring to the fabrication process of this material. Hence, a sufficiently detailed report on physically fabricated hBN materials is essential. This review analyzes the results that we have studied over the past ten years with the synthesis and fabrication of this material using physical vapor deposition - RF sputtering, incorporation with other techniques, strongly emphasized on growth mechanisms of this material.

We examine information loss, resource costs, and run time from practical application of quantum data compression. Compressing quantum data to fewer qubits enables efficient use of resources, as well as applications for quantum communication and denoising. In this context, we provide a description of the quantum and classical components of the hybrid quantum autoencoder algorithm, implemented using IBM’s Qiskit language. Utilizing our own data sets, we encode bitmap images as quantum superposition states, which correspond to linearly independent vectors with density matrices of discrete values. We successfully compress this data with near-lossless compression using simulation, and then run our algorithm on an IBMQ quantum chip. We describe conditions and run times for training and compressing our data on quantum devices, and relate trainability to specific characteristics and performance metrics of our parametric quantum circuits.

We show a new class of interaction terms with higher derivatives that can be added to every low derivative real scalar, such that the first order perturbations induced by the higher derivative terms on the low derivative background are ghost-free. This follows without imposing additional constraints. Furthermore, we show a related class of theories with an additional stabilizer variable and a constraint which are ghost-free without restricting to a perturbative expansion. In this case the field equation followed by the stabilizer variable may have interesting physical applications: namely, in contrast to some models with first-order derivative interactions with applications for dark energy and inflation, these constrained second-order derivative self-interactions do not necessarily affect the luminal propagation, hence, avoiding the common superluminality issues of the former.

We investigate in detail the effects of some factors on the optical refractive index change (RICs) in GaAs/AlGaAs parabolic quantum dot (QD) with tangent-square potential (TSP) in our paper, such as the radius of quantum dot, the depth and width limit potential. In the first place, we increase the limit of tangent square potential in the z-direction of the system, which is based on the original parabolic QD, then the Schrödinger equation corresponding to the modified system is solved, and the expressions of different splitting energy levels and wave functions are obtained. At last, the numerical simulations indicate that these physical factors have a great effect on the nonlinear optical performances of the tunable system.

This paper studies a class of circuit network model with fractional n-V-structure, the model contains several independent resistance elements, so it is the topology of multiple network models. First, this paper calculates the equivalent resistance of n-V circuit network by constructing equivalent model, and gives two closed equivalent resistance analytic expressions. Additionally, the concept of negative resistance is put forward. A series of special results of equivalent resistance are discussed. Finally, the complex impedance characteristics of fractional n-V structure circuit networks are studied in detail by using variable substitution technique. The amplitude frequency characteristics and phase frequency characteristics of fractional n-V structure circuit network are revealed through Matlab drawing research.

Plasma activated water (PAW) is a unique highly reactive medium, traditionally used in medicine and agriculture because of its decontamination and disinfection abilities. Recently, we have shown that this medium can also be beneficial for tailoring the surface chemistry of semiconductor nanostructures if its composition is tuned to contain a high concentration of nitrogen-related species (HiN:PAW). However, pathways leading to the production of HiN:PAW remained unclear, which we address in this article. By monitoring the composition of the produced PAW and the concentration of selected species in the discharge under different activation geometries and discharge conditions, we identify the activation geometries favourable for the production of HiN:PAW using two phenomenological factors, a barrier parameter P and a maximum effective radius of the vessel rmax. A key point is the presence of a barrier area in the discharge reactor, which forms as a result of the favourable activation geometry and a discharge with prevailing more reactive atomic species. This area acts as a partial barrier between the discharge and the surrounding air atmosphere, limiting, but still allowing a flow of source N2 molecules from the surrounding atmosphere. The minimal and ideal build-up times of 10 and 30 minutes, respectively, for the discharge to stabilize are also reported. Using the reported experimental settings, we were able to produce HiN:PAW containing a mixture of various reactive species beneficial for the surface modification of nanoparticles, with the NO3- to H2O2¬ ratio of at least 20×103: 1, in contrast to approximately 1:1 under more traditional conditions.