Flame retardancy of ceramic-based rigid polyurethane foam composites

In this work, ceramic fillers zirconia and alumina powder were incorporated in the rigid polyurethane foams derived from modified castor oil and their impact on the mechanical, thermal, and fire performances of composite foams have been analyzed. It was observed that the addition of ceramic filler showed improved mechanical and thermal properties and best properties were shown by 6% zirconia with compressive strength of 6.61 MPa and flexural strength of 5.72 MPa. Zirconia also demonstrated an increase in T_5% up to 260 °C. Cone calorimetry shows a decrease in peak of heat release from 118 to 84 kW m⁻² and 94 kW m⁻² by the incorporation of alumina and zirconia powder, respectively. Furthermore, total heat release (THR), smoke production rate (SPR), and total smoke release (TSR) were also found to decrease remarkably on the incorporation of ceramic fillers. So, these fillers have a great potential as an additive to incorporate good mechanical, thermal, and fire properties in bio-based rigid PU foams. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 48250.     

Spin valve effect in sputtered FL-MoS2 and ferromagnetic shape memory alloy based magnetic tunnel junction

In the last decade, two-dimensional (2D) transition metal dichalcogenides have been introduced with great significance in the spintronic devices for their extraordinary electrical, optical, and spin-dependent properties. In this work, we have fabricated a few-layer molybdenum disulfide (FL-MoS₂) (~6 nm) as a non-magnetic spacer layer in Ni–Mn–In/FL-MoS₂/Ni–Mn–In magnetic tunnel junction (MTJ) using DC magnetron sputtering. FL-MoS₂ thin film sandwiched between two ferromagnetic shape memory alloy based electrodes exhibit semiconducting behavior, confirmed by current-voltage (I–V) characteristics and temperature dependent resistance measurement. The fabricated MTJ shows spin valve effect in the presence of an external magnetic field. The tunneling magnetoresistance (TMR) has been recorded in 10 K–300 K temperature range. The highest TMR ratio of 0.51% was obtained at a low temperature ~10 K, corresponding to the spin polarization of ~5%. This TMR ratio reduces to a value of 0.032% as the temperature of the device increases up to 300 K, displaying a finite TMR at room temperature. A detailed study of thickness and temperature-dependent magnetization versus magnetic field (M ? H) hysteresis loops of Ni–Mn–In thin films has been performed to understand the complex TMR behavior. The present study paves the way for the use of sputtered FL-MoS₂ and ferromagnetic shape memory alloy in ultrafast spintronics for advanced magnetic devices application.     

Analysis of Fatty Acid and Lignan Composition of Indian Germplasm of Sesame to Evaluate Their Nutritional Merits

An attempt was made to individually analyze a germplasm collection of 54 indigenous Indian sesame cultivars for fatty acid and lignan composition of their seed oil by gas chromatography and high performance liquid chromatography, respectively. The entries varied in their fatty acid and lignan composition. The mean percentage contents of palmitic, stearic, oleic, linoleic and α‐linolenic acids ranged between 10–22, 5–10, 38–50, 18–43 and less than 1 whereas sesamol, sesamin and sesamolin scored between 3–37, 27–67, 20–59 of the total percentage of lignan, respectively. The highest percentage of α‐linolenic acid (ALA) was obtained in Var‐9 (1.3 % of the total fatty acids). Among the lignans, high sesamin content is considered to be significant, particularly in terms of long shelf life and nutraceutical value of sesame seed oil. The study has broadened our understanding related to differential biochemical composition of the rich sesame germplasms, thereby providing us with a useful groundwork for identifying potential targets and suitable cultivars for genetic engineering approaches to be undertaken in order to improve the nutritional quality of sesame oil, which in turn would be beneficial towards human health.     

Conventional and Non-conventional Edible Oils: An Indian Perspective

The Indian dietary pattern has undergone major changes over the past 40 years. Many of these changes involve modification in dietary intake of fats and oils. In developing countries like India, vegetable oils are replacing animal fats because of the cost and health concerns. A wide range of vegetable oils are available in the market but the choice of healthy cooking oil has been a controversial subject since ideas keep on changing as new evidence accumulates. One of the factors holding back the increased use of value-added healthy oils in India is that most potential consumers are genuinely not aware of their health benefits. Edible oil consumption is primarily a community-driven phenomenon in India. The purpose of this paper is to highlight the current scenario of edible oils in India, their composition, health benefits, food applications, stability issues and future aspects as buying the right oil for health has become of great importance.     

A Conditionally Fluorescent Peptide Reporter of Secondary Structure Modulation

Proteins containing intrinsic disorder often form secondary structure upon interaction with a binding partner. Modulating such structures presents an approach for manipulating the resultant functional outcomes. Translational repressor protein 4E-BP1 is an example of an intrinsically disordered protein that forms an α-helix upon binding to its protein ligand, eIF4E. Current biophysical methods for analyzing binding-induced structural changes are low-throughput, require large amounts of sample, or are extremely sensitive to signal interference by the ligand itself. Herein, we describe the discovery and development of a conditionally fluorescent 4E-BP1 peptide that reports structural changes of its helix in high-throughput format. This reporter peptide is based on conditional quenching of fluorescein by thioamides. In this case, fluorescence signal increases as the peptide becomes more ordered. Conversely, destabilization of the α-helix results in decreased fluorescence signal. The low concentration and low volume of peptide required make this approach amenable for high-throughput screening to discover ligands that alter peptide secondary structure.     

Exact fuzzy optimal solution of fully fuzzy linear programming problems with unrestricted fuzzy variables

Kumar et al. (Appl. Math. Model. 35:817?C823, 2011) pointed out that there is no method in literature to find the exact fuzzy optimal solution of fully fuzzy linear programming (FFLP) problems and proposed a new method to find the fuzzy optimal solution of FFLP problems with equality constraints having non-negative fuzzy variables and unrestricted fuzzy coefficients. There may exist several FFLP problems with equality constraints in which no restriction can be applied on all or some of the fuzzy variables but due to the limitation of the existing method these types of problems can not be solved by using the existing method. In this paper a new method is proposed to find the exact fuzzy optimal solution of FFLP problems with equality constraints having non-negative fuzzy coefficients and unrestricted fuzzy variables. The proposed method can also be used to solve the FFLP problems with equality constraints having non-negative fuzzy variables and unrestricted fuzzy coefficients. To show the advantage of the proposed method over existing method the results of some FFLP problems with equality constraints, obtained by using the existing and proposed method, are compared. Also, to show the application of proposed method a real life problem is solved by using the proposed method.     

Robust kernelized approach to clustering by incorporating new distance measure

A new data clustering algorithm Density oriented Kernelized version of Fuzzy c-means with new distance metric (DKFCM-new) is proposed. It creates noiseless clusters by identifying and assigning noise points into separate cluster. In an earlier work, Density Based Fuzzy C-Means (DOFCM) algorithm with Euclidean distance metric was proposed which only considered the distance between cluster centroid and data points. In this paper, we tried to improve the performance of DOFCM by incorporating a new distance measure that has also considered the distance variation within a cluster to regularize the distance between a data point and the cluster centroid. This paper presents the kernel version of the method. Experiments are done using two-dimensional synthetic data-sets, standard data-sets referred from previous papers like DUNN data-set, Bensaid data-set and real life high dimensional data-sets like Wisconsin Breast cancer data, Iris data. Proposed method is compared with other kernel methods, various noise resistant methods like PCM, PFCM, CFCM, NC and credal partition based clustering methods like ECM, RECM, CECM. Results shown that proposed algorithm significantly outperforms its earlier version and other competitive algorithms.     

Layered axial force coupled membrane based metal contact single-pole quad-throw RF MEMS switch: design,RF performance and mechanical modeling

Microsystem Technologies - RF MEMS is a perfect candidate to replace the conventional switches used for microwave frequency. Most of the RF MEMS switches developed generally concentrate on...