Influence of Mg concentration on structural,morphological and optical properties of nanoceria

Nano crystalline pure and Mg doped ceriaparticles were synthesized by simple chemical co-precipitation method using cerium nitrate hexahydrate as a source material and magnesium nitrate as doping precursor at room temperature. The effect of doping were investigated by X-ray diffraction pattern(XRD), FT-Raman,fourier transform infrared spectroscopy(FTIR), Ultraviolet spectroscopy(UV), photoluminescence spectroscopy(PL), field emission scanning electron microscope(FESEM) and high resolution transmission electron microscopy with energy dispersive spectroscopy (HRTEM &EDS). The X-ray diffraction pattern and FT-Raman studies showed that the prepared samples were nano particulates with cubic fluorite structure. The XRD pattern analysis showed that the size of the particles ranged from 13 to 20?nm, however 4?wt% Mg doping results in reduction of particle size compared with other doping concentrations. The effects of Mg concentration on various structural parameters of the prepared samples were also determined. The slight blue shift observed upon doping in UV–Vis absorption region around 330–360nmrecorded for reduction in particle size. The FTIR unveils the presence of Metal oxygen bonds below 700?cm^?1in the prepared samples. All samples showed a broad emission band at 430?nm with linearly increasing intensity with respect to dopant concentrations. The Spherical morphology with weak agglomeration was identified through FESEM and HRTEM analysis. The elemental analysis of Ce, O and Mg were confirmed through EDS analysis.     

A genetic‐based neuro‐fuzzy controller for blind equalization of time‐varying channels

This paper presents a neuro‐fuzzy network (NFN) where all its parameters can be tuned simultaneously using genetic algorithms (GAs). The approach combines the merits of fuzzy logic theory, neural networks and GAs. The proposed NFN does not require a priori knowledge about the system and eliminates the need for complicated design steps such as manual tuning of input–output membership functions, and selection of fuzzy rule base. Although, only conventional GAs have been used, convergence results are very encouraging. A well‐known numerical example derived from literature is used to evaluate and compare the performance of the network with other equalizing approaches. Simulation results show that the proposed neuro‐fuzzy controller, all parameters of which have been tuned simultaneously using GAs, offers advantages over existing equalizers and has improved performance. From the perspective of application and implementation, this paper is very interesting as it provides a new method for performing blind equalization. The main contribution of this paper is the use of learning algorithms to train a feed‐forward neural network for M‐ary QAM and PSK signals. This paper also provides a platform for researchers of the area for further development. Copyright © 2008 John Wiley & Sons, Ltd.     

Multipartite entangled magnon states as quantum communication channels

We investigate the entanglement properties of the two magnon states and explicate conditions under which, the two magnon state becomes useful for several quantum communication protocols. We systematically study the temporal behaviour of concurrence to find out the effect of exchange interaction on entanglement. The two magnon state, which is potentially realizable in quantum dots using Heisenberg exchange interaction, is found to be suitable for carrying out deterministic teleportation of an arbitrary two qubit composite system. Further, conditions for which the channel capacity reaches “Holevo bound”, allowing four classical bits to be transmitted through two qubits are derived. Later, an unconventional protocol is given to demonstrate that this state can be used for sharing of a two qubit entangled state among two parties.     

Cover Feature: Superior Proton-Transfer Catalytic Promiscuity of Cytochrome c in Self-Organized Media (7/2021)

Evolutionarily elderly proteins commonly feature greater catalytic promiscuity. Cytochrome c is among the first set of proteins in evolution to have known prospects in electron transport and peroxidative properties. Here, we report that cyt c is also a proficient proton-transfer catalyst and enhances the Kemp elimination (KE; model reaction to show proton transfer catalytic property) by ∼750-fold on self-organized systems like micelles and vesicles. The self-organized systems mimic the mitochondrial environment in vitro for cyt c. Using an array of biophysical and biochemical mutational assays, both acid–base and redox mechanistic pathways have been explored. The histidine moiety close to hemin group (His18) is mainly responsible for proton abstraction to promote the concerted E2 pathway for KE catalysis when cyt c is in its oxidized form; this has also been confirmed by a H18A mutant of cyt c. However, the redox pathway is predominant under reducing conditions in the presence of dithiothreitol over the pH range 6–7.4. Interestingly, we found almost 750-fold enhanced KE catalysis by cyt c compared to aqueous buffer. Overall, in addition to providing mechanistic insights, the data reveal an unprecedented catalytic property of cyt c that could be of high importance in an evolutionary perspective considering its role in delineating the phylogenic tree and also towards generating programmable designer biocatalysts.     

BUBBLE TEMPERATURES OF THE BINARY MIXTURES OF 1,2-DIMETHYLBENZENE WITH 2-PROPANOL, 1-BUTANOL, 2-BUTANOL, 2-METHYLPROPAN-1-OL AND 2-METHYLPROPAN-2-OL AT 95 kPa

Bubble temperatures at 95 kPa over the entire composition range are measured for the five binary systems formed by 1,2-dimethylbenzene with 2-propanol, 1-butanol, 2-butanol, 2- methylpropan-1-ol, and 2-methylpropan- 2-ol. A Swietoslawski - type ebulliometer was used for the measurements. The composition versus temperature measurements are well represented by the Wilson model.     

Effect of organic modifiers on dynamic and static nanomechanical properties and crystallinity of intercalated clay–polycaprolactam nanocomposites

Polymer clay nanocomposites (PCN) of Polyamide6 and sodium montmorillonite are prepared using different organic modifiers (12‐aminolauric acid, n‐dodecylamine, and 1,12‐diaminododecane) to study effect of organic modifiers on structure and nanomechanical properties of PCN. Using X‐ray diffraction and differential scanning calorimetry, crystalline nature of PCNs are evaluated. Nanoscale viscoelastic properties of PCNs are evaluated using nanodynamic mechanical analyzer (NanoDMA). Nanoscale elastic modulus and hardness of PCNs are evaluated using nanoindenter. PCNs show enhancement in elastic modulus, storage modulus, loss modulus, and loss factor by maximum amount of 62.88%, 56.38%, 145.74%, and 71.43%, respectively, and decrease in percentage crystallinity by 16.52% compared to pure polymer. This result indicates that organic modifiers have effect on crystallinity and nanomechanical properties of PCN. To evaluate effect of clay loading on nanomechanical properties of PCN, PCN containing 12‐aminolauric acid is synthesized with different weight percent (3, 6, and 9% of weight of polymer) of organically modified montmorillonite (OMMT), which shows that nanomechanical properties of PCN improves with increase in clay loading. Our study reveals that change in crystallinity of polymer in PCN may have role in the enhancement of nanomechanical properties of PCNs in comparison to pristine polymer. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 2007     

Differential evolution with Gaussian mutation for combined heat and power economic dispatch

This paper presents differential evolution with Gaussian mutation to solve the complex non-smooth non-convex combined heat and power economic dispatch (CHPED) problem. Valve-point loading and prohibited operating zones of conventional thermal generators are taken into account. Differential evolution (DE) is a simple yet powerful global optimization technique. It exploits the differences of randomly sampled pairs of objective vectors for its mutation process. This mutation process is not suitable for complex multimodal optimization. This paper proposes Gaussian mutation in DE which improves search efficiency and guarantees a high probability of obtaining the global optimum without significantly impairing the simplicity of the structure of DE. The effectiveness of the proposed method has been verified on five test problems and three test systems. The results of the proposed approach are compared with those obtained by other evolutionary methods. It is found that the proposed differential evolution with Gaussian mutation-based approach is able to provide better solution.     

How In-Home Technologies Mediate Caregiving Relationships in Later Life

In-home technologies can support older adults' activities of daily living, provide physical safety and security, and connect elders to family and friends. They facilitate aging in place while reducing caregiver burden. One of older adults' primary concerns about in-home technologies is their potential to reduce human contact, particularly from cherished caregivers. In this exploratory in situ study, we provided an ecosystem of networked monitoring technologies to six older adults and their caregivers. We analyzed the amount and content of communication between them. The amount of noncomputer-mediated communication did not decrease through the 6-week study. The content of communication coalesced into four themes: communication about the technologies, communication facilitated by technologies, intrusiveness of technologies, and fun and playfulness with the technologies. Results suggest that in-home technologies, designed with sensitivity to older adults' primary motivations, have the potential to shape and tailor important relationships in later life.     

Two-stage database intrusion detection by combining multiple evidence and belief update

Insider threats have gained prominence and pose the most challenging threats to a database system. In this paper, we have proposed a new approach for detecting intrusive attacks in databases by fusion of information sources and use of belief update. In database intrusion detection, only intra-transactional features are not sufficient for detecting attackers within the organization as they are potentially familiar with the day-to-day work. Thus, the proposed system uses inter-transactional as well as intra-transactional features for intrusion detection. Moreover, we have also considered three different sensitivity levels of table attributes for keeping track of the malicious modification of the highly sensitive attributes more carefully. We have analyzed the performance of the proposed database intrusion detection system using stochastic models. Our system performs significantly better compared to two intrusion detection systems recently proposed in the literature.