Production of tocotrienols in seeds of cotton (Gossypium hirsutum L.) enhances oxidative stability and offers nutraceutical potential

Upland cotton (Gossypium hirsutum L.) is an economically important multi-purpose crop cultivated globally for fibre, seed oil and protein. Cottonseed oil also is naturally rich in vitamin E components (collectively known as tocochromanols), with a- and c-tocopherols comprising nearly all of the vitamin E components. By contrast, cottonseeds have little or no tocotrienols, tocochromanols with a wide range of health benefits. Here, we generated transgenic cotton lines expressing the barley (Hordeum vulgare) homogentisate geranylgeranyl transferase coding sequence under the control of the Brassica napus seed-specific promoter, napin. Transgenic cottonseeds had ~twofold to threefold increases in the accumulation of total vitamin E (tocopherols + tocotrienols), with more than 60% c-tocotrienol. Matrix assisted laser desorption ionization-mass spectrometry imaging showed that c-tocotrienol was localized throughout the transgenic embryos. In contrast, the native tocopherols were distributed unequally in both transgenic and non-transgenic embryos. a- Tocopherol was restricted mostly to cotyledon tissues and c-tocopherol was more enriched in the embryonic axis tissues. Production of tocotrienols in cotton embryos had no negative impact on plant performance or yield of other important seed constituents including fibre, oil and protein. Advanced generations of two transgenic events were field grown, and extracts of transgenic seeds showed increased antioxidant activity relative to extracts from non-transgenic seeds. Furthermore, refined cottonseed oil from the two transgenic events showed 30% improvement in oxidative stability relative to the non-transgenic cottonseed oil. Taken together, these materials may provide new opportunities for cottonseed co-products with enhanced vitamin E profile for improved shelf life and nutrition

Effect of gold coating on sensitivity of rhombic silver nanostructure array

The sensitivity is the most important parameter in the sensing field. Effort was made to study the effect of gold coating on the sensitivity of rhombic silver nanostructure array through numerical simulation using the discrete dipole approximation method. This study shows that thickness of the gold coating can be varied to tune the sensitivity of the rhombic silver nanostructure array. The Au-Ag nanostructure array is found to possess the maximum refractive index sensitivity of 714 nm/RIU when thickness of gold is 20 nm, thickness of silver is 25 nm, and refractive index of the medium is around 1.35. The condition for achieving the maximum refractive index sensitivity can be used for detecting many species of biomolecules and drugs in the future

The internal consistency reliability of the Santosh-Francis Scale of Attitude toward Hinduism among students in India

The Santosh–Francis Scale of Attitude toward Hinduism was originally developed and tested among Hindus in the UK as part of a programme designed to assess religious affect across faith traditions. The present study tests the internal consistency reliability and construct validity of the instrument among 149 students in Karnatak University Dharwad (74 males and 75 females), India. The data demonstrated an alpha coefficient of .90, suggesting a high level of internal consistency reliability and commending the instrument for further application within Hindu communities

The perception of spontaneous and volitional laughter across 21 societies

Data available at https://dataverse.harvard.edu/ dataverse/laughterperception</p

Role of Temperature in the Growth of Silver Nanoparticles Through a Synergetic Reduction Approach

This study presents the role of reaction temperature in the formation and growth of silver nanoparticles through a synergetic reduction approach using two or three reducing agents simultaneously. By this approach, the shape-/size-controlled silver nanoparticles (plates and spheres) can be generated under mild conditions. It was found that the reaction temperature could play a key role in particle growth and shape/size control, especially for silver nanoplates. These nanoplates could exhibit an intensive surface plasmon resonance in the wavelength range of 700–1,400 nm in the UV–vis spectrum depending upon their shapes and sizes, which make them useful for optical applications, such as optical probes, ionic sensing, and biochemical sensors. A detailed analysis conducted in this study clearly shows that the reaction temperature can greatly influence reaction rate, and hence the particle characteristics. The findings would be useful for optimization of experimental parameters for shape-controlled synthesis of other metallic nanoparticles (e.g., Au, Cu, Pt, and Pd) with desirable functional properties

Effects of Voice Pitch on Social Perceptions Vary With Relational Mobility and Homicide Rate

Fundamental frequency ( fo) is the most perceptually salient vocal acoustic parameter, yet little is known about how its perceptual influence varies across societies. We examined how fo affects key social perceptions and how socioecological variables modulate these effects in 2,647 adult listeners sampled from 44 locations across 22 nations. Low male fo increased men’s perceptions of formidability and prestige, especially in societies with higher homicide rates and greater relational mobility in which male intrasexual competition may be more intense and rapid identification of high-status competitors may be exigent. High female fo increased women’s perceptions of flirtatiousness where relational mobility was lower and threats to mating relationships may be greater. These results indicate that the influence of fo on social perceptions depends on socioecological variables, including those related to competition for status and mates

Generalised scheme for optimal learning in recurrent neural networks

A new learning scheme is proposed for neural network architectures like the Hopfield network and bidirectional associative memory. This scheme, which replaces the commonly used learning rules, follows from the proof of the result that learning in these connectivity architectures is equivalent to learning in the 2-state perceptron. Consequently, optimal learning algorithms for the perceptron can be directly applied to learning in these connectivity architectures. Similar results are established for learning in the multistate perceptron, thereby leading to an optimal learning algorithm. Experimental results are provided to show the superiority of the proposed method

On An Optimal Learning Scheme For Bidirectional Associative Memories

An optimal learning scheme is proposed for a class of Bidirectional Associative Memories(BAM's). This scheme based on Perceptron Learning Algorithems, is motivated by the inadequacies/incompleteness of the weighted learning by global optimization as derived by wang et al[l]. It is shown that the new scheme has superior properties. [1]Convergence to correct solution, when it exits; [2]A larger basin of attraction for the given set of patterns