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mTOR signalling pathway - A root cause for idiopathic autism?
( Harsha Ganesan ),( Venkatesh Balasubramanian ),( Mahalaxmi Iyer ),( Anila Venugopal ),( Mohana Devi Subramaniam ),( Ssang-goo Cho ),( Balachandar Vellingiri ) 생화학분자생물학회(구 한국생화학분자생물학회) 2019 BMB Reports Vol.52 No.7
Autism spectrum disorder (ASD) is a complex neurodevelopmental monogenic disorder with a strong genetic influence. Idiopathic autism could be defined as a type of autism that does not have a specific causative agent. Among signalling cascades, mTOR signalling pathway plays a pivotal role not only in cell cycle, but also in protein synthesis and regulation of brain homeostasis in ASD patients. The present review highlights, underlying mechanism of mTOR and its role in altered signalling cascades as a triggering factor in the onset of idiopathic autism. Further, this review discusses how distorted mTOR signalling pathway stimulates truncated translation in neuronal cells and leads to downregulation of protein synthesis at dendritic spines of the brain. This review concludes by suggesting downstream regulators such as p70S6K, eIF4B, eIF4E of mTOR signalling pathway as promising therapeutic targets for idiopathic autistic individuals. [BMB Reports 2019; 52(7): 424-433]
Inkjet Printing of Yttria Stabilized Zirconia Nano Particles on Metal Substrates
S. H. Rahul,K. Balasubramanian,Sriram Venkatesh 한국정밀공학회 2015 International Journal of Precision Engineering and Vol. No.
This paper describes a novel methodology of coating Yttria stabilized Zirconia (YSZ) suspensions on AISI316L steel substrates and involves a micro structural investigation to understand the sintering behavior. Nano sized particles are used at lowering of sintering temperature. Nano particle suspension inks prepared through high energy milling process is visibly stable due to ionic charge carriers in binder and solvent. Deposition of suspended material was done through inkjet printing (IJP) and spin coating (SC) processes. Print head offset in X and Y directions lead to fabrication of homogeneous layers. Inkjet printing at elevated temperatures is useful especially in controlling nano particle seepage through porous substrates. Low temperature sintering of suspended particles in the ink leads to development of porous YSZ films due to the presence of carrier solvent and binder/dispersants in the ink. Sintered films exhibit completely stable tetragonal zirconia with uniformly porous microstructure. Pore sizes of 50 nm and 100 nm have been reported at least for inkjet printed and spin coated films respectively. The homogeneity observed in pores of YSZ film is a typical characteristic of inkjet printing process which is attributed to the layer by layer stacking of nano particles during the deposition process.
Stress Level Based Emotion Classification Using Hybrid Deep Learning Algorithm
Sivasankaran Pichandi,Gomathy Balasubramanian,Venkatesh Chakrapani 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.11
The present fast-moving era brings a serious stress issue that affects elders and youngsters. Everyone has undergone stress factors at least once in their lifetime. Stress is more among youngsters as they are new to the working environment. whereas the stress factors for elders affect the individual and overall performance in an organization. Electroencephalogram (EEG) based stress level classification is one of the widely used methodologies for stress detection. However, the signal processing methods evolved so far have limitations as most of the stress classification models compute the stress level in a predefined environment to detect individual stress factors. Specifically, machine learning based stress classification models requires additional algorithm for feature extraction which increases the computation cost. Also due to the limited feature learning characteristics of machine learning algorithms, the classification performance reduces and inaccurate sometimes. It is evident from numerous research works that deep learning models outperforms machine learning techniques. Thus, to classify all the emotions based on stress level in this research work a hybrid deep learning algorithm is presented. Compared to conventional deep learning models, hybrid models outperforms in feature handing. Better feature extraction and selection can be made through deep learning models. Adding machine learning classifiers in deep learning architecture will enhance the classification performances. Thus, a hybrid convolutional neural network model was presented which extracts the features using CNN and classifies them through machine learning support vector machine. Simulation analysis of benchmark datasets demonstrates the proposed model performances. Finally, existing methods are comparatively analyzed to demonstrate the better performance of the proposed model as a result of the proposed hybrid combination.
S. RAJA BALACHANDAR,S.G. VENKATESH,S.K.AYYASWAMY,K. BALASUBRAMANIAN,K. KRISHNAVENI 장전수학회 2019 Proceedings of the Jangjeon mathematical society Vol.22 No.4
In this paper, the Chebyshev wavelets method for solving a model for HIV infection of CD4+ T-cells is studied. The properties of Chebyshev wavelets and their operational matrices are rst presented and then are used to convert into algebraic equations. Also the convergence and error analysis for the proposed technique is discussed. Illustrative examples are given to demonstrate the valid- ity and applicability of the technique. The eciency of the proposed method is compared with other traditional methods and it is observed that the Chebyshev wavelet method is more convenient than the other methods in terms of applica- bility, eciency, accuracy, error and computational eort.