aiTPR: Attribute Interaction-Tensor Product Representation for Image Caption

Neural Processing Letters - Region visual features enhance the generative capability of the machines based on features. However, they lack proper interaction-based attentional perceptions and end...     

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.     

Analysis of continuous stirred ultrafiltration based on dimensional analysis approach

In this study an attempt has been made to obtain a dimensional analysis based empirical model of ultrafiltration process under stirred condition, which for a given membrane will predict the permeate flux and the rejection during the dynamic as well as the steady state phases of operation from the process conditions applied, viz. pressure drop, stirrer speed, bulk concentration of the filtered species etc. A dimensional analysis by Rayleigh’s method was performed and the obtained dimensionless groups were related with the help of experimentally obtained data in this study, by non-linear regression employing Levenberg and Marquardt technique. Two equations have been obtained, one for the prediction of flux and other for the rejection. The computed results are found to be in good agreement with the experimental data obtained in this study during the ultrafiltration of PEG-6000 by cellulose acetate membrane and the absolute average deviation was found to be within less than 7%.     

Synthesis and Biological Evaluation of Ferrocenylquinoline as a Potential Antileishmanial Agent

The emergence of resistance against antileishmanial drugs in current use necessitates the search for new classes of antileishmanial compounds. Herein we report the design, synthesis, and evaluation of a novel ferrocenylquinoline for activity against Leishmania donovani. 7‐Chloro‐N‐[2‐(1H‐5‐ferrocenyl‐1,2,3‐triazol‐1‐yl)ethyl]quinolin‐4‐amine ( 1 ) was generated by coupling an iron(II) ethynylferrocene species with 4‐(2‐ethylazido)amino‐7‐chloroquinoline using click chemistry. The synthesized compound 1 was tested for its antileishmanial activity using both promastigote and amastigote stages of L. donovani. Compound 1 showed promising anti‐promastigote activity, with an IC₅₀ value of 15.26 μM and no cytotoxicity toward host splenocytes. From the battery of tests conducted in this study, it appears that this compound induces parasite death by promoting oxidative stress and depolarizing the mitochondrial membrane potential, thereby triggering apoptosis. These results suggest that ferrocenylquinoline 1 is a suitable lead for the development of new antileishmanial drugs.     

A green chemistry approach for the synthesis and characterization of bioactive gold nanoparticles using Azolla microphylla methanol extract

This article reports the environmentally benign synthesis of gold nanoparticles （GNPs） using methanol extract of Azolla microphylla as the stabilizing and reducing agent. The GNPs were characterized by UV-vis spectrophotometry and FTIR, and the morphological characteristics were analyzed by XRD, FESEM-EDX and HRTEM. The GNPs could be formed in very short time, even in less than 30 min. The nanoparticles measured by UV-spectrophotometer demonstrated a peak at 540 nm corresponding to surface plasmon resonance spectra, and the peaks showed by FTIR suggested the presence of organic biomolecules on the surface of the GNPs. XRD results confirmed the crystalline nature of the GNPs, and FESEM-EDX and HRTEM analyses had been performed in the size ranges of 17-40nm and 1.25-17.5nm respectively. The synthesized GNPs showed excellent antioxidant activity. This study shows the feasibility of using plant sources for the biosynthesis of GNPs.     

Enhanced room-temperature magnetoelectric coupling effects in c-axis oriented polycrystalline BaSrCo2-xMgxFe11AlO22

The influence of applied magnetic field during annealing process as well as of Mg doping on the room-temperature magnetoelectric coupling effects in BaSrCo_2-xMg_xFe₁₁AlO₂₂ are experimentally studied through the magnetization, magnetodielectric, and magnetoelectric current measurements. Hexaferrite samples of Co₂Y were found to be highly oriented by an applied magnetic field (H_o) during the annealing process, leading to an enhancement of the room-temperature magnetoelectric coupling effects. Although the substitution of nonmagnetic Mg ions in Co sites tends to reduce the ferromagnetism at macroscopic scale, a proper amount of Mg doping content facilitates the superexchange interaction between the adjacent magnetic blocks; meanwhile modulates the magnetic anisotropy in the samples. An appropriate adjustment of the competition between the anisotropy and the superexchange could enhance the magnetoelectric coupling at room temperature, which can be confirmed by the magnetic-field-induced dielectric constant and current density study.     

Development of a knowledge based hybrid neural network (KBHNN) for studying the effect of diafiltration during ultrafiltration of whey

The membrane surface dynamics is very difficult to predict and can be roughly estimated by the available models but a true depiction is always difficult since the magnitude and direction of driving forces change as a function of time. The present study is an effort to address the issue, so that the combinatorial approach of deterministic and stochastic modelling might present a better understanding of membrane dynamics. The effect of diafiltration has also been incorporated to investigate the effects it has on the membrane. A stochastic model developed by a knowledge based hybrid neural network (KBHNN) was trained using the Levenberg–Marqurt algorithm where the film layer model was used as the deterministic layer, called the first principle model (FPM). Present work employs two different types of KBHNN architecture with an effort to understand the suitability and applicability of the hybrid network in case of predictions for an ultrafiltration (UF) process. In one sort of architecture neural part was in series with the FPM and in the other one it was in parallel with the FPM. The high correlation coefficient (R²) value portrays the correctness and preciseness of the underlining assumptions and establishes the validity of the developed network.     

Room temperature ammonia sensor based on jaw like bis-porphyrin molecules

A jaw-like bis-porphyrin (bis-TPP) molecule was synthesized anchoring of two porphyrin molecules to a benzene ring at the meta positions through the ester linkage. The bis-TPP molecule and its zinc-derivative (Zn-bis-TPP) were spin-coated on glass surfaces to construct two chemiresistive room temperature NH₃ gas sensors. Both the films showed high selectivity, reproducibility and reversibility in sensing NH₃ gas (5–40 ppm) in air. The sensing characteristics of the Zn-bis-TPP films (response (2 s) and recovery (2.5 min) times; linear response (952%)) were better than that of the bis-TPP films (response (8 s) and recovery (7.5 min) times; linear response (131%)). This is attributed to the amorphous nature of the former.     

Discrete bacteria foraging optimization algorithm for graph based problems – a transition from continuous to discrete

Bacteria Foraging Optimisation Algorithm is a collective behaviour-based meta-heuristics searching depending on the social influence of the bacteria co-agents in the search space of the problem. The algorithm faces tremendous hindrance in terms of its application for discrete problems and graph-based problems due to biased mathematical modelling and dynamic structure of the algorithm. This had been the key factor to revive and introduce the discrete form called Discrete Bacteria Foraging Optimisation (DBFO) Algorithm for discrete problems which exceeds the number of continuous domain problems represented by mathematical and numerical equations in real life. In this work, we have mainly simulated a graph-based road multi-objective optimisation problem and have discussed the prospect of its utilisation in other similar optimisation problems and graph-based problems. The various solution representations that can be handled by this DBFO has also been discussed. The implications and dynamics of the various parameters used in the DBFO are illustrated from the point view of the problems and has been a combination of both exploration and exploitation. The result of DBFO has been compared with Ant Colony Optimisation and Intelligent Water Drops Algorithms. Important features of DBFO are that the bacteria agents do not depend on the local heuristic information but estimates new exploration schemes depending upon the previous experience and covered path analysis. This makes the algorithm better in combination generation for graph-based problems and combination generation for NP hard problems.     

A first principle study of SO3 decomposition on silver nano-clusters: Implications toward hydrogen production

In this work, based on first principles density functional theory, we have investigated the interaction of SO₃ molecule on three different substrates; (i) clean Al₂O₃ surface (0001) (ii) an isolated Ag₆ cluster and (iii) Ag₆ clusters deposited on the Al₂O₃ surface. All calculations were carried out using the plane wave based pseudopotential method under the framework of density functional theory. For the clean Al₂O₃ surface, the SO₃ molecule was adsorbed in parallel orientation on the surface resulting in an elongation of the S–O bond from 1.44 to 1.52 Å with interaction energy of 1.67 eV. In contrast, the interaction of SO₃ with Ag₆ was found to be weak with 0.4 eV interaction energy and 1.47 Å as the largest S–O bond length. Remarkably, when SO₃ molecule interacted with Ag₆ cluster deposited on the Al₂O₃ support, the binding was found to be higher than both Al₂O₃ and Ag₆ clusters in their isolated state. In particular, upon adsorption of SO₃ on Ag₆/@Al₂O₃, the S–O bond length was found to increases from 1.44 to 1.64 Å and the interaction energy was estimated to be 2.00 eV. As the bond elongation bears the signature of bond weakening, a comparison of the above three results clearly suggests that the dissociation barrier of S–O bond on the Ag₆@Al₂O₃ support will be significantly lower than that on the isolated Ag₆ or Al₂O₃ surface. The nature of chemical interaction of SO₃ on these three systems has been discussed based on the electronic density of states analysis.