Heating frequency optimization for artificial field-aligned scattering

In this study, we present a simulation study of artificial field-aligned irregularities (AFAI) to calculate the scattering coefficient considering a Gaussian autocorrelation function for the wave number spectrum of the density fluctuation. By analyzing variations in the scattering coefficient under different ionospheric backgrounds, the optimal range of the heating frequency was found, which is about 0.9–1 times the critical frequency of the F2 layer. This is especially noticeable as when the heating frequency varies from 0.5 times to 0.9 times of the critical frequency, the scattering coefficient increases by 6.8–16.2 dB. These results should be useful for optimizing the heating frequency in the future artificial field-aligned scattering (AFAS) transmission applications at middle and low latitudes.     

A side-sensitive synthetic coefficient of variation chart

Control charts for monitoring the coefficient of variation (γ) are useful for processes with an inconsistent mean (μ) and a standard deviation (σ) which changes with μ, by monitoring the consistency in the ratio σ over μ. The synthetic-γ chart is one of the charts proposed to monitor γ, and its attractiveness lie in waiting until a second point to fall outside the control limits before a decision is made. However, existing synthetic-γ charts do not differentiate between the points falling outside the upper control limit (UCL) and lower control limit (LCL). Hence, this paper proposes a side-sensitive synthetic-γ chart, where successive nonconforming samples must either fall above the UCL or below the LCL. Formulae to compute the average run length (ARL), the standard deviation of the run length (SDRL) and expected average run length (EARL) are derived using the Markov chain approach, and the algorithms to obtain the optimal charting parameters are proposed. Subsequently, the optimal charting parameters, ARL, SDRL and EARL values for various numerical examples are shown. Comparisons show that the side-sensitive synthetic-γ chart consistently outperforms the existing synthetic-γ chart, especially for small shifts. The proposed chart also consistently outperforms the Shewhart-γ chart, while showing comparable or better performance than the Exponentially Weighted Moving Average (EWMA) chart for most shift sizes, except for very small shifts. Finally, this paper shows the implementation of the proposed chart on an industrial example.     

Simplification and applicability studies of a hydrogen-air detailed reaction mechanism

The research of hydrogen fuel internal combustion engine (HICE) had great significance facing the challenges of energy and environmental problems. Based on the detailed hydrogen-air reaction mechanism, the pre-mix model of CHEMKIN-Pro software was selected to simplify the detailed mechanism GRI-3.0. The most important elements and reactions was chose to construct framework mechanism firstly based on the sensitivity coefficient for H₂O and NO formation, and additional elements and reactions were added to framework mechanism for complementing the oxidation path of N2 and H₂. A simplified mechanism including 24-step elementary reaction was obtained and the laminar burning velocity calculated by this simplified mechanism matches well with the detailed mechanism in a wide range. This simplified mechanism was also applied in a CFD model which predicted the cylinder instantaneous pressure and NOx emission accurately within a large range of fuel air equivalent ratio. Showing that this mechanism has good applicability.     

热烧结矿竖式冷却过程传热特性

 与传统环冷相比，烧结竖冷拥有漏风率低、换热效率高的优势。为此利用竖冷试验装置，在某烧结厂取热风与热烧结矿研究了竖式冷却过程气固对流换热特性。研究表明，烧结矿竖式冷却过程中影响传热特性的主要因素为冷却风的流量及温度。烧结矿和冷却风对流换热系数随着烧结矿温度的升高而增大，且随着冷却风流量的增大以及冷却风温度的降低，对流换热系数也随之增大。基于白金汉定理，结合试验数据拟合得出了描述烧结矿与冷却风传热特性的准数关联式，其模拟性较好且平均相对误差为7.25%。     

TSL:predicting popularity of Facebook content based on tie strength

The rapid development of online social networks leads to an explosion of information,however,there are great differences in the popularity of different messages,and accurate prediction is always a great difficulty is the current study.Popularity prediction of online content aims to predict the popularity in the future based on its early diffusion status.Existing models for popularity prediction were mostly based on discovering network features or fitting the equation into a varying time function that the accuracy of current popularity prediction model was not high enough.Therefore,with the help of the weak ties theory in sociology,the concept of tie strength was introduced and a multilinear regression equation was constructed combined with the early popularity.A TSL model to predict the popularity of Facebook’s well-known pages was proposed.The main contribution of this article was to solve the problem and few or no work based on sociology.A high linear correlation between the proportion of faithful fans was existed in Facebook homepage with frequent shares in the early and the future popularity.Compared with other baseline models,an experimental study of Facebook (including 1.54 million shares) illustrates the effectiveness of the proposed TSL model,and the performance is better than the existing similar methods.     

Investigation of non-isothermal crystallization,dynamic mechanical and dielectric properties of poly(ether-ketone) matrix composites

ABSTRACT

Poly(ether-ketone)/hexagonal boron nitride (h-BN) composites reinforced with micrometer-sized h-BN particles were investigated. The composites exhibited glass transition temperature (T_g) and thermal stability over 160°C and 560°C, respectively. The melting point and peak crystallization temperatures of the composites decreased up to 17°C and 12°C, respectively. The linear CTE of the composites decreased both below and above the T_g. The storage modulus increased with increasing h-BN content at all temperatures (50–250°C). The composites possessed excellent dielectric properties with insignificant dispersion with increasing frequency. Thus, resultant composites are promising candidates for the printed circuit boards/electronic substrates.     

Diffusion Magnetic Resonance Imaging-Based Biomarkers for Neurodegenerative Diseases

There has been an increasing prevalence of neurodegenerative diseases with the rapid increase in aging societies worldwide. Biomarkers that can be used to detect pathological changes before the development of severe neuronal loss and consequently facilitate early intervention with disease-modifying therapeutic modalities are therefore urgently needed. Diffusion magnetic resonance imaging (MRI) is a promising tool that can be used to infer microstructural characteristics of the brain, such as microstructural integrity and complexity, as well as axonal density, order, and myelination, through the utilization of water molecules that are diffused within the tissue, with displacement at the micron scale. Diffusion tensor imaging is the most commonly used diffusion MRI technique to assess the pathophysiology of neurodegenerative diseases. However, diffusion tensor imaging has several limitations, and new technologies, including neurite orientation dispersion and density imaging, diffusion kurtosis imaging, and free-water imaging, have been recently developed as approaches to overcome these constraints. This review provides an overview of these technologies and their potential as biomarkers for the early diagnosis and disease progression of major neurodegenerative diseases.     

Symmetric and asymmetric membranes based on La0.5Sr0.5Fe0.7Ga0.3O3-δ perovskite with high oxygen semipermeation flux performances and identification of the rate-determining step of oxygen transport

This work focuses on identifying the rate-determining step of oxygen transport through La_0.5Sr_0.5Fe_0.7Ga_0.3O_3-δ membranes with symmetric and asymmetric architectures. The best oxygen semipermeation fluxes are 3.4 10⁻³ mol. m^-2.s^-1 and 6.3 10⁻³ mol. m^-2.s^-1 at 900 °C for the symmetric membrane and asymmetric membrane with a modified surface. The asymmetric membrane with a modified surface leads to an increase of approximately 7 times the oxygen flux compared to that obtained with the La_0.5Sr_0.5Fe_0.7Ga_0.3O_3-δ dense membrane without surface modification. This work also shows that the oxygen flux is mainly governed by gaseous oxygen diffusion through the porous support of asymmetric La_0.5Sr_0.5Fe_0.7Ga_0.3O_3-δ membranes.     

Diffusion behaviors and atomic mobilities in Mg–Sc hcp and bcc alloys: Investigation via single-phase and multi-phase diffusion couples

Diffusion behaviors in Mg–Sc hcp and bcc solid solutions between 773 and 873 K were investigated using both single-phase and multi-phase diffusion couple techniques. The EPMA detected composition-distance profiles were smoothed and fitted using the error function expansion (ERFEX). The interdiffusion coefficients were extracted using Sauer–Freise integral. The interdiffusion coefficients in hcp phase showed a slightly parabolic composition dependence at the Mg-rich part and the maximum value was around 2–3 at. % Sc. However, the interdiffusion coefficients in the bcc phase monotonously decreased with the increase of solubility of Sc. The determined inter- and impurity diffusion coefficients in the hcp Mg–Sc alloys were assessed to develop the atomic mobility database, and their validity was justified by reproducing the composition profiles and diffusion fluxes obtained in this diffusion couple experiment. Meanwhile, the development of bcc atomic mobility was realized via the Maclaurin approximation, extrapolation, and optimization. The results make up for the missing data of Mg–Sc diffusion kinetics.     

Deconvoluting Energy Transport Mechanisms in Metal Halide Perovskites Using CsPbBr3 Nanowires as a Model System

Understanding energy transport in metal halide perovskites is essential to effectively guide further optimization of materials and device designs. However, difficulties to disentangle charge carrier diffusion, photon recycling, and photon transport have led to contradicting reports and uncertainty regarding which mechanism dominates. In this study, monocrystalline CsPbBr₃ nanowires serve as 1D model systems to help unravel the respective contribution of energy transport processes in metal-halide perovskites. Spatially, temporally, and spectrally resolved photoluminescence (PL) microscopy reveals characteristic signatures of each transport mechanism from which a robust model describing the PL signal accounting for carrier diffusion, photon propagation, and photon recycling is developed. For the investigated CsPbBr₃ nanowires, an ambipolar carrier mobility of μ = 35 cm² V⁻¹ s⁻¹ is determined, and is found that charge carrier diffusion dominates the energy transport process over photon recycling. Moreover, the general applicability of the developed model is demonstrated on different perovskite compounds by applying it to data provided in previous related reports, from which clarity is gained as to why conflicting reports exist. These findings, therefore, serve as a useful tool to assist future studies aimed at characterizing energy transport mechanisms in semiconductor nanowires using PL.