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.     

A facile synthesis of a novel three‐phase nanocomposite: Single‐wall carbon nanotube/silver nanohybrid fibers embedded in sulfonated polyaniline

A three‐phase water‐soluble nanocomposite of single wall carbon nanotube/silver nanoparticle hybrid fibers embedded in sulfonated polyaniline has been synthesized by a simple chemical solution mixing process. The nanocomposite has been characterized by high resolution electron microscopy, X‐ray diffractometry, FTIR spectroscopy, Raman spectroscopy, and thermogravimetric analysis. Optical and electrical characteristics of the nanocomposite have been determined by UV–vis absorption spectroscopy, photoluminescence spectroscopy, and four‐probe electrical conductivity measurement. A surface plasmon absorption band obtained around 460 nm indicates the presence of silver nanoparticles in the composite. The optical band gap calculation for sulfonated polyaniline vis‐a‐vis the nanocomposite supported the conductivity measurement. Over 1300 times increase in DC electrical conductivity has been observed for the three‐phase nanocomposite, with a filler loading of 20 wt %, at 306 K. This observation could be explained by Mott's variable range hopping model considering a three‐dimensional conduction. Such a nanocomposite has immense potential for use as a cathode material in lithium‐ion batteries and supercapacitors. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41692.     

Performance evaluation of saponin over other organic acid and tap water for removal of chromium in tannery sludge by electrokinetic enhancement

The performance of Saponin over different electrolyte-mediated electrokinetic (EK) process for removal of Cr(III) from tannery sludge was assessed. Saponin exhibited maximum Cr(III) removal efficiency, i.e. 67.6–80.75% as compared to other groups of processing fluids. The possible mechanistic approach for the highest removal efficiency of saponin over other electrolytes may be attributed to synchronized effect of micelle formation and subsequent complexation and sorption of chromium ions. The highest electroosmotic flow rate of saponin indicated low electroosmotic resistance during EK process, which validates the observed trend. Therefore, saponin can be considered as a promising electrolyte for EK treatment of tannery sludge.

Abbreviation: CA: Citric acid; LA: lactic acid; OA: oxalic acid; BOD: biochemical oxygen demand; COD: chemical oxygen demand; EK: electokinetic.     

Mechanical and tribological properties of silicon carbide coating on Inconel alloy from liquid pre-ceramic precursor

Liquid polycarbosilane (LPCS) derived hard coatings of silicon carbide (SiC) were deposited on Inconel alloy at three different moderately high temperatures by chemical vapour deposition. The deposited films were characterized by X-ray diffractometry and Field emission scanning electron microscopy. Liquid PCS yielded a mixture of α-SiC and β-SiC during decomposition having uniform round-shaped particles of dimension around 200–300 nm without extensive cracking and few discrete shaped particles were also found to form at higher temperature (i.e. 1100 °C and 1200 °C) deposited films. The coated samples showed substantial increment in hardness and fracture toughness as compared to the uncoated sample. The fracture toughness (K_IC) values of the deposited films were in the range of 6.7–10.7 MPa(m)^1/2. The tribological properties and hardness of the films were also found to vary with deposition temperature. The scratch tracks of the films revealed that brittle failures occurred in all SiC coated substrates.     

Self-Assembly and Neurotoxicity of β-Amyloid (21–40) Peptide Fragment: The Regulatory Role of GxxxG Motifs

The three GxxxG repeating motifs from the C-terminal region of β-amyloid (Aβ) peptide play a significant role in regulating the aggregation kinetics of the peptide. Mutation of these glycine residues to leucine greatly accelerates the fibrillation process but generates a varied toxicity profile. Using an array of biophysical techniques, we demonstrated the uniqueness of the composite glycine residues in these structural repeats. We used solvent relaxation NMR spectroscopy to investigate the role played by the surrounding water molecules in determining the corresponding aggregation pathway. Notably, the conformational changes induced by Gly³³ and Gly³⁷ mutations result in significantly decreased toxicity in a neuronal cell line. Our results indicate that G³³xxxG³⁷ is the primary motif responsible for Aβ neurotoxicity, hence providing a direct structure–function correlation. Targeting this motif, therefore, can be a promising strategy to prevent neuronal cell death associated with Alzheimer's and other related diseases, such as type II diabetes and Parkinson's.     

Studies on semi‐interpenetrating polymer network based on nitrile rubber and poly(methyl methacrylate)

Sequential interpenetrating polymer networks (IPNs) based on nitrile rubber and poly(methyl methacrylate) (PMMA) were synthesized. IPN compositions were varied by varying the swelling time. Two methods were adopted for making IPNs. The first method is “single‐step IPN” (SIPN) and the second method is “multistep IPN” (MIPN). The compositions were fixed around 90, 80, 70, 60 and 50% of NBR. In SIPN mode, swelling in monomer and subsequent curing was done once. In MIPN mode, swelling in monomer and curing was repeatedly done. Tensile strength of IPNs was found to increase with PMMA content, MIPN showing higher strength compared to SIPN. Dynamic modulus showed a similar trend. The tan δ value was found to decrease with PMMA content. At 62/38 nitrile rubber (NBR)/PMMA, MIPN composition isolated tan δ peaks appeared near glass transition temperatures of NBR and PMMA, respectively. Scanning electron micrograph showed phase‐separated morphology at the same MIPN composition. Solvent resistance increased with IPN formation maintaining higher resistance for MIPN compared to SIPN. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 91: 354–360, 2004     

Loading Rate Effect on Nanohardness of Soda-Lime-Silica Glass

To understand how hardness, the key design parameter for applications of brittle solids such as glass concerning contact deformation, is affected by loading rate variation, nanoindentation with a Berkovich tip was used to measure the nanohardness of a 330-μm-thick soda-lime-silica glass as a function of loading rate (1 to 1000 mN·s⁻¹). The results showed for the very first time that, with variations in the loading rate, there was a 6 to 9 pct increase in the nanohardness of glass up to a threshold loading rate (TLR), whereafter it did not appreciably increase with further increase in loading rate. Further, the nanohardness data showed an indentation size effect (ISE) that obeyed the Meyer’s law. These observations were explained in terms of a strong shear stress component developed just beneath the nanoindenter and the related shear-induced deformation processes at local microstructural scale weak links. The significant or insignificant presence of shear-induced serrations in load depth plots and corresponding scanning electron microscopic evidence of a strong or mild presence of shear deformation bands in and around the nanoindentation cavity supported such a rationalization. Finally, a qualitative picture was developed for different deformation processes induced at various loading rates in glass.     

Dielectric and Thermal Investigations on PbNb2O6 in Pure Piezoelectric Phase and Pure Non-Piezoelectric Phase

A high piezoelectric transition temperature is indicated for present orthorhombic samples of lead meta-niobate (PbNb₂O₆) by the high value of the temperature (T_m) at which the real part (?′) of electrical permittivity peaks. It is 573 to 580°C. The imaginary component (?″) increases sharply at these temperatures. Cooling run after heating to 700°C gives changed values of ?′ and ?″ and T_m. Present work reports impedance spectroscopy (up to 700°C over 20 Hz to 5.5 MHz) and Differential Scanning Calorimetry or DSC on the pure orthorhombic phase, and, for the first time, on the pure rhombohedral phase. DSC shows an endothermic dip across T_m during heating and an exothermic peak during cooling for the orthorhombic sample only.     

A novel training scheme for multilayered perceptrons to realize proper generalization and incremental learning

The response of a multilayered perceptron (MLP) network on points which are far away from the boundary of its training data is generally never reliable. Ideally a network should not respond to data points which lie far away from the boundary of its training data. We propose a new training scheme for MLPs as classifiers, which ensures this. Our training scheme involves training subnets for each class present in the training data. Each subnet can decide whether a data point belongs to a certain class or not. Training each subnet requires data from the class which the subnet represents along with some points outside the boundary of that class. For this purpose we propose an easy but approximate method to generate points outside the boundary of a pattern class. The trained subnets are then merged to solve the multiclass classification problem. We show through simulations that an MLP trained by our method does not respond to points which lies outside the boundary of its training sample. Also, our network can deal with overlapped classes in a better manner. In addition, this scheme enables incremental training of an MLP, i.e., the MLP can learn new knowledge without forgetting the old knowledge.     

A unified scheme for adaptive stroke-based rendering

This paper presents a comprehensive scheme for automatically generating a broad class of artistic illustrations from photographs. Using strokes as the major building blocks, our system optimizes the stroke attributes subject to the desired rendering style. The stroke attributes are computed adaptively to enable importance-based control of the abstraction level at each pixel. We propose a novel outline detection and refinement paradigm called edge painting to construct an outline map, and from which to derive the pixel-wise importance. We also introduce an adaptive bilateral filter to adaptively guide the curved stroke directions based on the importance map. Given the outline, importance, and direction maps, the system creates the illustration via selecting the representative colors, setting the style parameters, and optimizing the stroke attributes based on simulated annealing. The experimental results show that our scheme facilitates automatic production of artistic illustrations in a wide range of rendering styles.