The combined contributions of the cue-familiarity and accessibility heuristics to feelings of knowing.

A model for the basis of feeling of knowing (FOK) is proposed, which combines 2 apparently competing accounts, cue familiarity (L. M. Reder, see record 1987-12470-001) and accessibility (A. Koriat, see record 1994-04361-001). Both cue familiarity and accessibility are assumed to contribute asynchronously to FOK, but whereas the effects of familiarity occur early, those of accessibility occur later and only when cue familiarity is sufficiently high to drive the interrogation of memory for potential answers. General information questions were used to orthogonally manipulate cue familiarity and accessibility. As expected, both familiarity and accessibility enhanced FOK judgments, but the effects of accessibility were found mostly when familiarity was high. This interactive pattern was replicated when FOK judgments were delayed but not when they were immediate. The results support the proposed cascaded model of FOK but also imply a differentiation between 2 variants of the accessibility heuristic. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Crystallization and Ability of Hydroxyapatite Formation in Some Trivalent Oxides Containing Na-Ca-Silicate Glass-Ceramics

The formation of glass-ceramics based on Na₂O–CaO-silicates containing P₂O₅ with minor additives of some trivalent oxides (e.g. La, In, Ga, and Al), has been investigated. Different crystalline phases including sodium-orthosilicate containing lanthanum, or aluminum were formed together with Na₂Ca₂Si₃O₉, NaInSi₂O₆, and Na₃Ga₂Si₃O₁₀. The nature and mechanism of HA formed in the glass-ceramics are considered. In general, the presence of trivalent oxides in the glass-ceramics progressively reduced the ability to form a calcium phosphate layer on the surfaces of the materials. The addition of In₂O₃ decreased the crystallization of the hydroxyapatite layer. However, in the presence of either Ga₂O₃ or Al₂O₃ only the amorphous calcium phosphate layer was formed after the immersion of the crystallized specimens in the SBF solution.     

Sparse leaky‐LMS algorithm for system identification and its convergence analysis

In this paper, a novel adaptive filter for sparse systems is proposed. The proposed algorithm incorporates a log‐sum penalty into the cost function of the standard leaky least mean square (LMS) algorithm, which results in a shrinkage in the update equation. This shrinkage, in turn, enhances the performance of the adaptive filter, especially, when the majority of unknown system coefficients are zero. Convergence analysis of the proposed algorithm is presented, and a stability criterion for the algorithm is derived. This algorithm is given a name of zero‐attracting leaky‐LMS (ZA‐LLMS) algorithm. The performance of the proposed ZA‐LLMS algorithm is compared to those of the standard leaky‐LMS and ZA‐LMS algorithms in sparse system identification settings, and it shows superior performance compared to the aforementioned algorithms. Copyright © 2013 John Wiley & Sons, Ltd.     

A Hybrid Higher Order Neural Classifier for handling classification problems

In this paper, we propose a novel Hybrid Higher Order Neural Classifier (HHONC) which contains different high-order units. In contrast with conventional fully-connected higher order neural networks (HONN), our proposed method uses fewer learning parameters and allocates the best fitted model in dealing with different datasets by modifying the orders of different high-order units and updating the learning parameters. Structure, model selection and updating the learning parameters of HHONC is introduced and is applied in classification of the Iris data set, the breast cancer data set, the Wine recognition data set, the Glass identification data set, the Balance scale data set, and the Pima diabetes data set. Acquired results are compared with the methods presented in Chen and Shie (2009). It is observed that the fewer features the dataset contains, the more accurate the HHONC performs, however the accuracy of datasets with more features are acceptable. Experimental results show about 3.5% and 0.6% improvements compared to the best accuracy obtained in previously methods for classifying the Pima diabetes and Iris datasets, respectively. In addition, by using a same method for reducing the feature number, it’s shown the proposed method perform more accurate than methods presented in Shie and Chen (2008). In this case, improvements compared to the best acquired accuracy of mentioned methods are about 1.7%, 1.3% and 0.2% in classification of Pima, Iris and Breast cancer datasets, respectively.     

Using Coal Fly Ash and Wastewater for Microwave Synthesis of LTA Zeolite

The reuse of industrial wastes from a coal‐fired power plant and a plasma electrolytic oxidation process was attempted to realize a zero discharge. The batch composition was adjusted by adding sodium hydroxide and sodium aluminate. A single‐mode microwave oven equipped with reflux condenser was used for crystallization under atmospheric pressure. The synthesized samples were characterized by X‐ray diffraction, scanning electron microscopy, BET, thermogravimetric analysis, and cation‐exchange capacity (CEC) measurement. Analytical results indicated that Na‐A zeolite with a defined maximum crystallinity could be successfully synthesized by hydrothermal treatment of fly ash with wastewater. Due to the high CEC, the product can be applied for gas purification and soil remediation processes.     

Twin screw wet granulation: Effect of powder feed rate

The twin screw extruder has recently become popular as a continuous wet granulation technique. It is logical that granulation using a twin screw granulator will depend on several process variables including powder feed rate but little is known about how these variables will affect the kinetics and mechanisms of granule growth and the eventual structure. The work focuses on understanding how granule properties like structure, surface, strength, dissolution etc., change with varying powder feed rate and attempts to develop the science behind granule formation which ultimately allows a priori process and product design. An attempt has been made to understand the steps involved in granule formation in twin screw granulator. The granules became denser and stronger with an increase in powder feed rate.     

Functionalized multi-walled carbon nanotubes for oil spill cleanup from water

The growing global economy resulted in an incessant increase in transportation and exploitation of oil. Hence, the oil spillage has been considered a serious threat to aquatic and terrestrial ecosystems. Therefore, water purification has been considered a major challenge around the world. There are numerous classical methods available for oil removal from water, but owing to multiple defects and disadvantages, research efforts have focused to find such adsorbents which can improve oil adsorption capability. Traditional adsorbent material typically applied in oil removal includes activated carbon, organoclays, wool, zeolites, etc. These materials suffer from several drawbacks such as low absorption capacity, non-selective absorption, and complicated reusability, whereas nano-adsorbents offer multiple advantages such as having multiple sorption sites, large surface area, short intra-particle diffusion distance, tuneable pore size, and ease of low-temperature modification. Multi-walled carbon nanotubes (MWCNTs) are extensively used adsorbent materials with a strong affinity for the removal of organic pollutants. The functionalization MWCNTs further increase the sorption capacity of adsorbents manifolds to remove organic materials. These nanocomposites are also compatible with green materials and considered environmentally friendly adsorbents. This review paper aims at providing an insight to understand the properties of the MWCNTs and their potential use to adsorb hydrocarbons from water. Moreover, the synthesis methods of those materials, their modification procedures including the functionalization with metal oxide nanoparticles, and applications are also discussed in detail.

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Functionalization of UiO-66-NH2 by In-Situ Incorporation of Nanomaterials to Enhance Photocatalytic Efficiency Towards Oxygen Evolution Reaction

The catalysts for oxygen evolution reaction (OER) are required to generate clean energy. Herein, one-step solvothermal synthesis and modification of amino functionalized Zr-based metal organic framework, UiO-66-NH₂, is reported. The catalytic efficiency of UiO-66-NH₂ towards OER is improved by incorporating the cerium-based nanocomposite such as Ce₂O₃, TiO₂/Ce₂O₃ and CoO/Ce₂O₃. The synthesized samples are characterized by X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy, energy dispersive X-ray, diffraction, and ultraviolet–visible spectroscopy. The synthesized materials are coated on nickel foam for investigating the catalytic activity towards OER by cyclic voltammetry and linear sweep voltammetry. Amongst, CoO/Ce₂O₃@UiO-66-NH₂/NF exhibits excellent OER-catalytic activity and delivers 10 mA cm^?2 current density at just 228 mV overpotential which is superior to many previously reported OER catalysts and its comparative products. To understand kinetics, Tafel slope is derived from LSV curve and is just 92 mV dec^?1.

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Synthesis and characterization of novel Pr6O11/Mn3O4 nanocomposites for electrochemical supercapacitors

This study presents the successful synthesis of praseodymium oxide, Pr₆O₁₁ and hausmannite manganese oxide, Mn₃O₄ nanoparticles, along with a novel synthesis of (Pr₆O₁₁/Mn₃O₄) nanocomposites by employing the hydrothermal route followed by post thermal annealing. X-ray Diffraction, Field Emission Scanning Electron Microscopy and Energy Dispersive X-ray characterization techniques are being adapted to analyze the physical characteristics of all the synthesized materials. XRD results reveal the crystalline nature of the synthesized materials. FE-SEM results display the irregular nanograins of Mn₃O₄ and a regular network of interconnected Pr₆O₁₁ nanoparticles. Nitrogen adsorption/desorption tests confirm the mesoporous nature of all the synthesized electrode materials. The Pr₆O₁₁/Mn₃O₄ ??2 electrode material exhibits an outstanding specific capacitance of 794.58?F/g at a current density of 0.5?A/g, as compared to the 521.24?F/g for the Pr₆O₁₁ electrode material. These investigations provide an easy and efficient method to develop nanocomposites (Pr₆O₁₁/Mn₃O₄) with better electrochemical characteristics, as electrode materials for supercapacitor applications.