Brain Cholinergic and Dopaminergic Functions in Streptozotocin Induced Diabetic Rats: Effects of Curcumin and Vitamin D3 Supplementation

Department of Biotechnology, Cochin University of Science and Technology

Signatures of Higher Functions of Brain Dynamics in Electroencephalogram: A Nonlinear Analysis

The brain with its highly complex structure made up of simple units,imterconnected information pathways and specialized functions has always been an object of mystery and sceintific fascination for physiologists,neuroscientists and lately to mathematicians and physicists. The stream of biophysicists are engaged in building the bridge between the biological and physical sciences guided by a conviction that natural scenarios that appear extraordinarily complex may be tackled by application of principles from the realm of physical sciences. In a similar vein, this report aims to describe how nerve cells execute transmission of signals ,how these are put together and how out of this integration higher functions emerge and get reflected in the electrical signals that are produced in the brain.Viewing the E E G Signal through the looking glass of nonlinear theory, the dynamics of the underlying complex system-the brain ,is inferred and significant implications of the findings are explored.

Permutation entropy based real-time chatter detection using audio signal in turning process

Machine tool chatter is an unfavorable phenomenon during metal cutting, which results in heavy vibration of cutting tool. With increase in depth of cut, the cutting regime changes from chatter-free cutting to one with chatter. In this paper, we propose the use of permutation entropy (PE), a conceptually simple and computationally fast measurement to detect the onset of chatter from the time series using sound signal recorded with a unidirectional microphone. PE can efficiently distinguish the regular and complex nature of any signal and extract information about the dynamics of the process by indicating sudden change in its value. Under situations where the data sets are huge and there is no time for preprocessing and fine-tuning, PE can effectively detect dynamical changes of the system. This makes PE an ideal choice for online detection of chatter, which is not possible with other conventional nonlinear methods. In the present study, the variation of PE under two cutting conditions is analyzed. Abrupt variation in the value of PE with increase in depth of cut indicates the onset of chatter vibrations. The results are verified using frequency spectra of the signals and the nonlinear measure, normalized coarse-grained information rate (NCIR).

Permutation Entropy Based Analysis of Complex Signals for Characterising Change in System Dynamics

Timely detection of sudden change in dynamics that adversely affect the performance of systems and quality of products has great scientific relevance. This work focuses on effective detection of dynamical changes of real time signals from mechanical as well as biological systems using a fast and robust technique of permutation entropy (PE). The results are used in detecting chatter onset in machine turning and identifying vocal disorders from speech signal.Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. Here we propose the use of permutation entropy (PE), to detect the dynamical changes in two non linear processes, turning under mechanical system and speech under biological system.Effectiveness of PE in detecting the change in dynamics in turning process from the time series generated with samples of audio and current signals is studied. Experiments are carried out on a lathe machine for sudden increase in depth of cut and continuous increase in depth of cut on mild steel work pieces keeping the speed and feed rate constant. The results are applied to detect chatter onset in machining. These results are verified using frequency spectra of the signals and the non linear measure, normalized coarse-grained information rate (NCIR).PE analysis is carried out to investigate the variation in surface texture caused by chatter on the machined work piece. Statistical parameter from the optical grey level intensity histogram of laser speckle pattern recorded using a charge coupled device (CCD) camera is used to generate the time series required for PE analysis. Standard optical roughness parameter is used to confirm the results.Application of PE in identifying the vocal disorders is studied from speech signal recorded using microphone. Here analysis is carried out using speech signals of subjects with different pathological conditions and normal subjects, and the results are used for identifying vocal disorders. Standard linear technique of FFT is used to substantiate thc results.The results of PE analysis in all three cases clearly indicate that this complexity measure is sensitive to change in regularity of a signal and hence can suitably be used for detection of dynamical changes in real world systems. This work establishes the application of the simple, inexpensive and fast algorithm of PE for the benefit of advanced manufacturing process as well as clinical diagnosis in vocal disorders.

Broadband coaxial cavity resonator for complex permittivity measurements of liquids

A novel cavity perturbation technique using coaxial cavity resonators for the measurement of complex permittivity of liquids is presented. The method employs two types of resonators (Resonator I and Resonator II). Resonator I operates in the frequency range 600 MHz-7 GHz and resonator II operates in the frequency range 4 GHz-14 GHz. The introduction of the capillary tube filled with the sample liquid into the coaxial resonator causes shifts in the resonance frequency and loaded Q-factor of the resonator. The shifts in the resonance frequency and loaded Q-factor are used to determine the real and imaginary parts of the complex permittivity of the sample liquid, respectively. Using this technique, the dielectric parameters of water and nitrobenzene are measured. The results are compared with those obtained using other standard methods. The sources of errors are analyzed.

Synthesis and Characterization of Novel Ionomers based on Styrene Butadiene Copolymer

Novel thermo-reversible zinc sulphonated ionomers based on styrene butadiene rubber (SBR), and high styrene rubber (HSH) were synthesized by sulphonation followed by neutralization with zinc. The sulphonate content of the ionomer was estimated by using x-ray fluorescence spectroscopy. Presence of sulphonate groups has been confirmed by FTIR and FTNMR spectra. The TGA results show improvement in the thermo~oxidative stability of the modified rubber. Both DSC and DMTA studies show that the incorporation of the ionic groups affect the glass rubber transition of the base polymer. lntroduction ol ionic functionality in to the base material improved the physical properties. Retention of the improved physical properties of the novel ionomers even after three repeated cycles of mixing and molding may be considered as the evidence for the reprocessability of the ionomer. Effect of particulate fillers (HAF black, silica and zinc stearate) on the properties of the zinc sulphonated styrene butadiene rubber ionomer has been evaluated. Incorporation of tillers results in improvement in mechanical properties. Zinc stearate plays the dual role of reinforcement and plasticization. The evaluation of dielectric properties of zinc sulphonated styrene butadiene rubber iorpmers at microwave frequencies reveal that the materials show conductivity at semiconductor level. The real and imaginary parts of the complex permittivity increases with increase in ionic functionality. Use of the 38.5 ZnS-SBR ionomer as a compatibiliser for obtaining the technologically compatible blends from the immiscible SBR/NBR system has been discussed.

Effect of nickel nanofillers on the dielectric and magnetic properties of composites based on rubber in the X-band

Nickel–rubber nanocomposites were synthesized by incorporating ferromagnetic nickel nanoparticles in a natural rubber as well as neoprene rubber matrix. Complex dielectric permittivity and magnetic permeability of these composites were evaluated in the X-band microwave frequencies at room temperature using cavity perturbation technique. The dielectric loss in natural rubber is smaller compared to neoprene rubber. A steady increase in the dielectric permittivity is observed with increase in the content of nickel in both the composites. The magnetic permeability exhibits a steady decrease with increase in frequency and magnetic loss shows a relaxation at 8 GHz. The suitability of these composites as microwave absorbers is modeled based on the reflection loss which is dependant on the real and imaginary components of the complex dielectric permittivity and magnetic permeability.