The effect of Na addition on the first hydrogen absorption kinetics of cast hypoeutectic Mg–La alloys

With superior properties of Mg such as high hydrogen storage capacity (7.6 wt% H/MgH₂), low price, and low density, Mg has been widely studied as a promising candidate for solid-state hydrogen storage systems. However, a harsh activation procedure, slow hydrogenation/dehydrogenation process, and a high temperature for dehydrogenation prevent the use of Mg-based metal hydrides for practical applications. For these reasons, Mg-based alloys for hydrogen storage systems are generally alloyed with other elements to improve hydrogen sorption properties. In this article, we have added Na to cast Mg–La alloys and achieved a significant improvement in hydrogen absorption kinetics during the first activation cycle. The role of Na in Mg–La has been discussed based on the findings from microstructural observations, crystallography, and first principles calculations based on density functional theory. From our results in this study, we have found that the Na doped surface of Mg–La alloy systems have a lower adsorption energy for H₂ compared to Na-free surfaces which facilitates adsorption and dissociation of hydrogen molecules leading to improvement of absorption kinetic. The effect of Na on the microstructure of these alloys, such as eutectic refinement and a density of twins is not highly correlated with absorption kinetics.     

Gelling of alginate fibres

Equipment was developed to measure the time for complete gelling of sodium alginate fibres in calcium chloride solution, taken as the time to achieve maximum tensile strength. The effects of fibre diameter, alginate concentration, alginate composition and calcium chloride concentration on gelling time were investigated. A diffusional model, developed to predict the gelling time, agreed with experimental results except for the effect of calcium ion concentration which was modelled empirically.     

A novel method for the classification of Alzheimer's disease from normal controls using magnetic resonance imaging

Alzheimer's disease (AD) is the most prevalent form of dementia. Although fewer people, who suffer from AD are correctly and promptly diagnosed, due to a lack of knowledge of its cause and unavailability of treatment, AD is more manageable if the symptoms of mild cognitive impairment (MCI) are in an early stage. In recent years, computer‐aided diagnosis has been widely used for the diagnosis of AD. The main motive of this paper is to improve the classification and prediction accuracy of AD. In this paper, a novel approach is developed to classify MCI, normal control (NC), and AD using structural magnetic resonance imaging (sMRI) from the Alzheimer's disease Neuroimaging Initiative (ADNI) dataset (50 AD, 50 NC, 50 MCI subjects). FreeSurfer is used to process these MRI data and obtain cortical features such as volume, surface area, thickness, white matter (WM), and intrinsic curvature of the brain regions. These features are modified by normalizing each cortical region's features using the absolute maximum value of that region's features from all subjects in each group of MCI, NC, and AD independently. A total of 420 features are obtained. To address the curse of dimensionality, the obtained features are reduced to 30 features using a sequential feature selection technique. Three classifiers, namely the twin support vector machine (TSVM), least squares TSVM (LSTSVM), and robust energy‐based least squares TSVM (RELS‐TSVM), are used to evaluate the classification accuracy from the obtained features. Five‐fold and 10‐fold cross‐validation are used to validate the proposed method. Experimental results show an accuracy of 100% for the studied database. The proposed approach is innovative due to its higher classification accuracy compared to methods in the existing literature.     

Generalized Twin Support Vector Machines

Neural Processing Letters - In this paper, we propose two efficient approaches of twin support vector machines (TWSVM). The first approach is to reformulate the TWSVM formulation by introducing...     

A systematic mapping of semi-formal and formal methods in requirements engineering of industrial Cyber-Physical systems

Journal of Intelligent Manufacturing - The requirements engineering of Industrial Cyber-Physical Systems is extremely challenging due to large system sizes, component heterogeneity, involvement of...     

An efficient implicit regularized Lagrangian twin support vector regression

Twin support vector regression (TSVR) and Lagrangian TSVR (LTSVR) satisfy only empirical risk minimization principle. Moreover, the matrices in their formulations are always positive semi-definite. To overcome these problems, we propose an efficient implicit Lagrangian formulation for the dual regularized twin support vector regression, called IRLTSVR for short. By introducing a regularization term to each objective function, the optimization problems in our IRLTSVR are positive definite and implement the structural risk minimization principle. Moreover, the 1-norm of the vector of slack variable is replaced with 2-norm to make the objective functions strongly convex. Our IRLTSVR solves two systems of linear equations instead of solving two quadratic programming problems (QPPs) in TSVR and one large QPP in SVR, which makes the learning speed of IRLTSVR faster than TSVR and SVR. Particularly, we compare three implementations of IRLTSVR with existing approaches. Computational results on several synthetic and real-world benchmark datasets clearly indicate the effectiveness and applicability of the IRLTSVR in comparison to SVR, TSVR and LTSVR.     

Carbon-coated iron oxide nanoparticles as contrast agents in magnetic resonance imaging

Coprecipitated ferrite nanoparticles were coated with carbon using a hydrothermal method. From transmission electron microscope pictures, we could see that the coated iron oxide nanoparticles were spherical in shape with an average diameter of 90 nm. The strong bonding of carbon on the nanoparticle surfaces was checked by noting the C = O and C = C vibrations in Fourier transform infrared spectra. The spin-lattice relaxation process [T ₁] and spin-spin relaxation process [T ₂] relaxivities of hydrogen protons in the aqueous solution of coated nanoparticles were determined to be 1.139 (mM·s)^-1 and 1.115 (mM·s)^-1, respectively. These results showed that the carbon-coated iron oxide nanoparticles are applicable as both T ₁ and T ₂ contrast agents in magnetic resonance imaging.     

Structural and opto-electrical properties of pyrolized ZnO-CdO crystalline thin films

A series of ZnO-CdO thin films of different molar ratios of Zn and Cd have been deposited on glass substrate at substrate temperature ~ 360 ℃ by the spray pyrolysis technique at an ambient atmosphere. X-ray diffraction (XRD) studies confirmed the polycrystalline nature of the film and modulated crystal structures of wurtzite (ZnO) and cubic (CdO) are formed. The evaluated lattice parameters, and crystallite size are consistent with literature. Dislocation density and strain increased in the film as the grain sizes of ZnO and CdO are decreased. The band gap energy varies from 3.20 to 2.21 eV depending on the Zn/Cd ratios in the film. An incident photon intensity dependent I-V study confirmed that the films are highly photosensitive. Current increased with the increase of the intensity of the light beam. The optical conductivity and the optical constants, such as extinction coefficient, refractive index and complex dielectric constants are evaluated from transmittance and reflectance spectra of the films and these parameters are found to be sensitive to photon energy and displayed intermediate optical properties between ZnO and CdO, making it preferable for applications as the buffer and window layers in solar cells.     

Carbonaceous microsphere-based superabsorbent polymer as filler for coating of NPK fertilizer: Fabrication,properties, swelling,and nitrogen release characteristics

Recently, the use of controlled release fertilizers in agriculture has resulted in huge benefits in plant growth and cultivation. Superabsorbent polymer (SAP)-coated fertilizers have the added advantage in retaining water in soil after irrigation and also reduce the nutrient release rate from soil in a controlled manner. This study aimed to produce a nitrogen–phosphorus–potassium (NPK) fertilizer coated with superabsorbent carbonaceous microspheres polymer (SPC) by inverse suspension polymerization method with water-retention and controlled release properties. Two sets of experiments were conducted: (1) three different weight percentages and (2) different materials. NPK coated with SPC showed increasing water-retention ability with respect to carbon microsphere percentages and retains >80% water at the 30th day of experiment compared with pure NPK and NPK coated with SAP. The slow release behavior of all samples was investigated by induced coupled plasma mass spectrometry spectrometry and results showed that NPK coated with SAP and SPC has a low release rate with <50% nutrient release compared with uncoated NPK at the 30th day. The release mechanism kinetics of NPK coated with SAP and SPC were studied based on the Kosmeyer–Peppas model. The mechanisms approached Fickian diffusion-controlled release as the n value for both samples was less than 0.5. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48396.     

Prediction of warp and weft yarn crimp in cotton woven fabrics

The aim of this study was to develop statistical models for the prediction of warp and weft crimp percentage of cotton woven fabrics. The developed models are based on the empirical data obtained from carefully developed 60 fabric samples with different yarn linear densities, fabric densities, and weave designs. The predictability and accuracy of the developed models was assessed by correlation analysis of the predicted and actual crimp values of another set of eight fabric samples which was not used for the development of models. The results show fairly good capability and accuracy of the prediction models.