Research performance of academic psychologists in the United Kingdom

Scientometrics - Research performance metrics inform decision making across the higher education sector. In this study we calculated up-to-date lifetime bibliometric research performance norms for...     

The effects of (di-,tri-valent)-cation partitioning and intercalant anion-type on the solubility of hydrotalcites

Synthetic hydrotalcites were produced by a co-precipitation method. The hydrotalcites are represented by the general formula [M^II_(1-x)M^III_(x)(OH)₂][Aⁿ⁻]_x/n·zH₂O, where M^II is a divalent cation (eg, Mg²⁺or Ca²⁺), M^III is a trivalent cation (eg, Al³⁺) and Aⁿ⁻ is the interlayer anion. Herein, M^II = Mg, and M^III = Al such that [Mg/Al] = [2, 3] (atomic units) and Aⁿ⁻, represents intercalant species including: OH⁻, SO₄²⁻ and CO₃²⁻ anions. The thermochemical data of each compound including their solubility constants (K_so), density and molar volume were quantified at T = 25 ± 0.5°C, and P = 1 bar. The solubilities of the synthetic hydrotalcites, irrespective of their divalent-trivalent cation partitioning ratio, scaled as CO₃²⁻ < SO₄²⁻ < OH⁻; in order of decreasing solubility. The type of anion, very slightly, affected the solubility with less than ±1 log unit of variation for [Mg/Al] = 2, and ±2 log units of variation for [Mg/Al] = 3. The solubilities of these phases were strongly correlated with that of gibbsite (Al(OH)₃); such that activity of the [AlO₂⁻] species was solubility determining with increasing pH. The tabulated thermodynamic data were used to construct solid-solution models for phases encompassing both cation distribution ratios and to calculate stable phase equilibria relevant to alkali-activated slag (AAS) systems for diverse activator compositions.     

Detecting and Mitigating Adversarial Perturbations for Robust Face Recognition

International Journal of Computer Vision - Deep neural network (DNN) architecture based models have high expressive power and learning capacity. However, they are essentially a black box method...     

An Intelligent Fine-Tuned Forecasting Technique for Covid-19 Prediction Using Neuralprophet Model

COVID-19, being the virus of fear and anxiety, is one of the most recent and emergent of various respiratory disorders. It is similar to the MERS-COV and SARS-COV, the viruses that affected a large population of different countries in the year 2012 and 2002, respectively. Various standard models have been used for COVID-19 epidemic prediction but they suffered from low accuracy due to lesser data availability and a high level of uncertainty. The proposed approach used a machine learning-based time-series Facebook NeuralProphet model for prediction of the number of death as well as confirmed cases and compared it with Poisson Distribution, and Random Forest Model. The analysis upon dataset has been performed considering the time duration from January 1^st 2020 to16^th July 2021. The model has been developed to obtain the forecast values till September 2021. This study aimed to determine the pandemic prediction of COVID-19 in the second wave of coronavirus in India using the latest Time-Series model to observe and predict the coronavirus pandemic situation across the country. In India, the cases are rapidly increasing day-by-day since mid of Feb 2021. The prediction of death rate using the proposed model has a good ability to forecast the COVID-19 dataset essentially in the second wave. To empower the prediction for future validation, the proposed model works effectively.     

Influence of particle size on spin switching properties and magnetoelectric coupling in SmFeO<Subscript>3</Subscript>

Controlling the magnetic properties of a material is of great importance for spintronics and magnetoelastic devices. We studied effect of reduced particle size on structural, dielectric and magnetic properties of SmFeO₃ nanoparticles prepared by co-precipitation method (SFO-C) and by combustion (SFO-S). Reduced particle size modified interesting magnetic features of SmFeO₃. Temperature dependent magnetic study reveal significant enhancement in magnetization reversal temperature and drop in spin reorientation transition temperature. The signature of spin reorientation transition for SFO-C (~?300 nm) is marked at ~?450 K, while this temperature drops down to ~?400 K for SFO-C (~?50 nm). The magnetization reversal temperature is achieved at 30.5 K for SFO-C, much higher than 4 K, reported for the single crystal and bulk SmFeO₃. The presence significant anomalies in the temperature dependent dielectric behavior of SmFeO₃ samples across spin reorientation transition temperature indicate magneto electrical coupling. Strong exchange–bias effect is observed at low temperature for both the samples. The lowering of spin reorientation/switching transition temperature due to reduction in particle size and the signature of magnetoelectric coupling at this temperature are useful for room temperature devices. The observed experimental results establish that the spin switching properties of SmFeO₃ can be modified for practical applications in devices.     

Structural,electrical and ferroelectric characteristics of Bi(Fe0.9La 0.1)O3

Nowadays, much attention is paid for the development of lead-free complex or mixed metal oxides, which can be utilized for multi-functional devices. This communication provides the information on synthesis (by mixed oxide route) and physical properties (structural, electrical and ferroelectric) of the polycrystalline sample of Bi(Fe_0.9La_0.1)O₃ Analysis of the phase formation and basic crystal data of the material using X-ray diffraction (XRD) technique shows an orthorhombic symmetry with well-defined cell parameters. It has been shown that a small amount (10%) of La substitution at the Fe site of BiFeO₃ suppresses the impurity phase usually observed during phase formation of BiFeO₃. The average crystallite size, calculated through applying Scherrer's technique, was found to be 68?nm. For the study of surface morphology (grain size and distribution) of the compound, the scanning electron microscope (SEM) was used. The grains of different dimension were found homogeneously distributed at the entire surface of the sample. The La substitution strongly affects the capacitive (dielectric) and resistive (electrical) characteristics of bismuth ferrite in a wide range of frequency and temperature. The contributions of grains and grain boundaries in the capacitive as well as in the resistive properties of the material at different temperatures and frequencies were studied by means of the impedance spectroscopy technique. This study has provided numerous useful and interesting data which may find potential industrial applications.     

FADU-EV an automated framework for pre-release emotive analysis of theatrical trailers

Multimedia Tools and Applications - Release of a theatrical movie trailer is a major marketing practice and a considerable cost is associated with it. Evaluating the effectiveness of a theatrical...