Vignan University

About: Vignan University is a education organization based out in Guntur, Andhra Pradesh, India. It is known for research contribution in the topics: Control theory & CMOS. The organization has 1138 authors who have published 1381 publications receiving 7798 citations.

Hevea brasiliensis coniferaldehyde-5-hydroxylase (HbCAld5H) regulates xylogenesis, structure and lignin chemistry of xylem cell wall in Nicotiana tabacum

Abstract: The HbCAld5H1 gene cloned from Hevea brasiliensis regulates the cambial activity, xylem differentiation, syringyl–guaiacyl ratio, secondary wall structure, lignification pattern and xylan distribution in xylem fibres of transgenic tobacco plants. Molecular characterization of lignin biosynthesis gene coniferaldehyde-5-hydroxylase (CAld5H) from Hevea brasiliensis and its functional validation was performed. Both sense and antisense constructs of HbCAld5H1 gene were introduced into tobacco through Agrobacterium-mediated genetic transformation for over expression and down-regulation of this key enzyme to understand its role affecting structural and cell wall chemistry. The anatomical studies of transgenic tobacco plants revealed the increase of cambial activity leading to xylogenesis in sense lines and considerable reduction in antisense lines. The ultra-structural studies showed that the thickness of secondary wall (S2 layer) of fibre had been decreased with non-homogenous lignin distribution in antisense lines, while sense lines showed an increase in S2 layer thickness. Maule color reaction revealed that syringyl lignin distribution in the xylem elements was increased in sense and decreased in antisense lines. The immunoelectron microscopy revealed a reduction in LM 10 and LM 11 labelling in the secondary wall of antisense tobacco lines. Biochemical studies showed a radical increase in syringyl lignin in sense lines without any significant change in total lignin content, while S/G ratio decreased considerably in antisense lines. Our results suggest that CAld5H gene plays an important role in xylogenesis stages such as cambial cell division, secondary wall thickness, xylan and syringyl lignin distribution in tobacco. Therefore, CAld5H gene could be considered as a promising target for lignin modification essential for timber quality improvement in rubber.

IoT Based Dust bin Monitoring System Using Node MCU

Abstract: These days it is being quite common to see that large portions of the detritus over the roadside, also in many localities, dustbins are not being cleaned in appropriate time. It results as creation of an unhygienic condition and expansive number of creepy crawlies and mosquitoes. The traditional procedure following these days is time taking and requires high human effort which is not anywhere comparable to present day innovations in any scenario . To overcome this issue, an undertaking called IOT based garbage monitoring system is proposed. The theme of this project is to portray savvy dustbins in view of arduino, ultrasonic sensor, Node MCU, Flame sensor and water level indicator which are interfaced with the mobile application through web server to put on a brilliant dustbin which will quantify the status of the dustbin. This system screens the trash canisters and educates about the level of waste gathered in the junk containers. This will likewise send status of bins to waste accumulation vehicles.

Advanced And Effective Classification of Parkinson’s Disease Using Enhanced Neural Networks

Abstract: A disease that causes due to degeneration in the nerve cells in brain parts with which movements are controlled is a Parkinson's disease. Parkinson’s disease increased its occurrence with age and it's becoming the second most common neurodegenerative disorder. Due to this disease, people begin to experience difficulty in speaking, writing, walking. We can diagnose this disease by using voice recordings dataset, handwritten images, and by using several techniques. In this paper, we are using a voice dataset to identify Parkinson's disease which is collected from different people with and without Parkinson's disease. There are several medical tools to identify this disease but it may take time and laborious to identify this disease. In this patients has to take any number of tests as a single test cannot give an effective diagnosis of a disease. So to mitigate this, our work establishes a computer-based analysis technique. We can identify and diagnose this disease using several classification algorithms in machine learning like decision trees, naive bayes algorithm, SVM algorithm are few neural networks. In this paper, we use neural networks to classify the disease.

Synthesis and characterization of thermally stable and flame retardant poly (benzoxazine-co-urethane) matrices

Abstract: The flame-retardant behavior of organic polymers is considered as very important criteria to utilize them in the form of coatings, encapsulants, sealants, and matrices for high performance industrial applications. A new type of poly (benzoxazine-co-urethane) (PBZ-co-PU) matrices have been developed using dimethylol benzoxazine monomers (BZM and BZE) and tris(p-isocyanatophenyl)thiophosphate (Desmodur) through A2 + B3 approach followed by thermal curing. The molecular structure of developed PBZ-co-PU was confirmed by FT-IR spectra and their thermal stability and flame retardant behavior were studied by standard methods. Data obtained from TGA and DSC, indicate that the PBZ-co-PU possesses higher Tg, better thermal stability and LOI than those of neat PBZ. Further, it was also observed that among the two matrix systems (PBZ-co-PU-1 and PBZ-co-PU-2) studied, the PBZ-co-PU-1 based system exhibited higher Tg, thermal stability and flame retardant behavior than those of PBZ-co-PU-2.