Histology of the pituitary gland of the grey mullet, Mugil cephalus L.

The present communication deals with a histological study of the pituitary gland of the teleost fish Mugil cephalus , found in the estuarine waters of Cochin area. Six different cell types were identified in the pituitary gland on the basis of their grouping, distribution and staining properties. The prolactin and the TSH cells (thyroid stimulating hormone producing cells or thyrotrops) were identified in the rostral pars distalis and the ACTH cells (adrenocorticotropic hormone producing cells or corticotrops) in the interphase between the neurohypophysis and the rostral pars distalis. The STH cells (somatotropic hormone producing cells or somatotrops) and the gonadotropic cells were distinguished in the proximal pars distalis and the MSH cells (melanin stimulating hormone producing cells or melanotrops) in the pars intermedia.     

Effect of mersalyl on mitochondrial Mg++ flux

The mercurial mersalyl has little effect either on rapid Mg⁺⁺ binding by isolated rat liver mitochondria or on the total Mg⁺⁺ content of these organelles measured after 0.75 min of incubation at 20°C. The data do not support the previous suggestion that the increased permeability to K⁺ of mitochondria treated with mersalyl results from release of endogenous Mg⁺⁺. An increased pH-dependence of unidirectional Mg⁺⁺ flux into respiring rat liver mitochondria is suggested to arise indirectly from inhibition by mersalyl of pH shifts associated with exchanges of endogenous phosphate. In addition, mersalyl appears to have a stimulatory effect on Mg⁺⁺ influx. Mersalyl also increases the average rate of unidirectional efflux of endogenous Mg⁺⁺. The stimulatory effects of mersalyl on Mg⁺⁺ flux are similar to, although quantitatively less than, the previously reported effects of mersalyl on mitochondrial K⁺ flux.     

Multi-layered Graphene Silica-Based Tunable Absorber for Infrared Wavelength Based on Circuit Theory Approach

Graphene can be utilized as a tunable material for a wide range of infrared wavelength regions due to its tunable conductivity property. In this paper, we use Y-shaped silver material resonator placed over the top of multiple graphene silica-layered structures to realize the perfect absorption over the infrared wavelength region. We propose four different designs by placing the graphene sheet over silica. The absorption and reflectance performance of the structures have been explored for 1500- to 1600-nm wavelength range. The proposed design also explores the absorption tunability of the structure for the different values of graphene chemical potential. We have reported the negative impedance for the perfect absorption for proposed metamaterial absorber structures. All the metamaterial absorbers have reported 99% of its absorption peaks in the infrared wavelength region. These designs can be used as a tunable absorber for narrowband and wideband applications. The proposed designs will become the basic building block of large photonics design which will be applicable for polariser, sensor, and solar applications.

     

Artificial neural network and response surface methodology: a comparative analysis for optimizing rice straw pretreatment and saccharification

Abstract

The present study demonstrates a comparative analysis between the artificial neural network (ANN) and response surface methodology (RSM) as optimization tools for pretreatment and enzymatic hydrolysis of lignocellulosic rice straw. The efficacy for both the processes, that is, pretreatment and enzymatic hydrolysis was evaluated using correlation coefficient (R²) & mean squared error (MSE). The values of R² obtained by ANN after training, validation, and testing were 1, 0.9005, and 0.997 for pretreatment and 0.962, 0.923, and 0.9941 for enzymatic saccharification, respectively. On the other hand, the R² values obtained with RSM were 0.9965 for cellulose recovery and 0.9994 for saccharification efficiency. Thus, ANN and RSM together successfully identify the substantial process conditions for rice straw pretreatment and enzymatic saccharification. The percentage of error for ANN and RSM were 0.009 and 0.01 for cellulose recovery and for 0.004 and 0.005 for saccharification efficiency, respectively, which showed the authority of ANN in exemplifying the non-linear behavior of the system.