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Effects of digested Cheonggukjang on human microbiota assessed by in vitro fecal fermentation
Vineet Singh,Nakwon Hwang,Gwangpyo Ko,Unno Tatsuya 한국미생물학회 2021 The journal of microbiology Vol.59 No.2
In vitro fecal fermentation is an assay that uses fecal microbes to ferment foods, the results of which can be used to evaluate the potential of prebiotic candidates. To date, there have been various protocols used for in vitro fecal fermentation- based assessments of food substances. In this study, we investigated how personal gut microbiota differences and external factors affect the results of in vitro fecal fermentation assays. We used Cheonggukjang (CGJ), a Korean traditional fermented soybean soup that is acknowledged as healthy functional diet. CGJ was digested in vitro using acids and enzymes, and then fermented with human feces anaerobically. After fecal fermentation, the microbiota was analyzed using MiSeq, and the amount of short chain fatty acids (SCFAs) were measured using GC-MS. Our results suggest that CGJ was effectively metabolized by fecal bacteria to produce SCFAs, and this process resulted in an increase in the abundance of Coprococcus, Ruminococcus, and Bifidobacterium and a reduction in the growth of Sutterella, an opportunistic pathogen. The metabolic activities predicted from the microbiota shifts indicated enhanced metabolism linked to methionine biosynthesis and depleted chondroitin sulfate degradation. Moreover, the amount of SCFAs and microbiota shifts varied depending on personal microbiota differences. Our findings also suggest that in vitro fecal fermentation of CGJ for longer durations may partially affect certain fecal microbes. Overall, the study discusses the usability of in vitro gastrointestinal digestion and fecal fermentation (GIDFF) to imitate the effects of diet-induced microbiome modulation and its impact on the host.
Vineet Kumar Singh,Jampana Nagaraju,Sushobhan Avasthi 한국물리학회 2019 Current Applied Physics Vol.19 No.3
We demonstrate radial p-n junction silicon solar cells with micro-pillar array with higher short-circuit current and open-circuit voltage than comparable planar silicon solar cells. Micro-pillar array, fabricated by RIE, acts as an effective anti-reflection coating for visible light with less than 6% reflection. Compared to devices with planar surface, devices with micro-pillar array show a 27% enhancement in short circuit current. The radial p-n junction of the micro-pillars also improves extraction probability of the photogenerated carriers, which further increases the short circuit current. Typically, micro-pillar solar cells suffer from high recombination losses at the Si/metal interface, resulting in poor VOC. Our devices prevent these recombination losses by planarizing the Si/ metal interface, leading to an open circuit voltage of 622 mV, the highest ever reported for micro-pillar solar cells. This planarized contact also reduces the series resistance associated with radial junctions, leading to series resistance of ≤0.50 Ω-cm2 and fill factors up to 76.7%.
Effect of Indium Doping and Annealing on Photoconducting Property of Wurtzite Type CdS
Vineet Kumar Singh,Pratima Chauhan,Sheo Kumar Mishra,Rajneesh K Srivastava 대한금속·재료학회 2012 ELECTRONIC MATERIALS LETTERS Vol.8 No.3
In this paper we observed the effect of doping and annealing on the dark current and anomalous photoconducting behavior of hexagonal wurtzite CdS, synthesized by solid state reaction method. Undoped CdS sample shows higher anomalous behavior in photoconductivity as well as contains larger dark current of 19 nA. With the doping of Indium in CdS, dark current decreases from 19 nA to 1 nA but the anomalous behavior is not completely removed. While, after annealing at 150°C for four hour, indium doped CdS sample shows good switching property with rise and decay time of 360 ± 10 & 322 ± 6 seconds respectively. The anomalous photoconducting behavior is completely removed from annealed sample. X-ray diffraction patterns confirm the existence of hexagonal wurtzite phase of indium doped and undoped CdS samples while energy dispersion X-ray spectrum exhibits the elemental presence of cadmium, indium & sulfur in the indium doped sample. UV-Visible absorption spectra show the blue shift in absorption edge on indium doping from 475 nm to 425 nm in comparison to undoped sample. Photoluminescence spectra confirm the indium doping and reveal that annealed CdS sample has lesser defects among other samples due to which annealed sample has best switching performance.
Wavelet operator for multiscale modeling of a nuclear reactor
Vineet Vajpayee,Siddhartha Mukhopadhyay,Akhilanand Pati Tiwari 한국원자력학회 2018 Nuclear Engineering and Technology Vol.50 No.5
This article introduces a methodology of designing a wavelet operator suitable for multiscale modeling. The operator matrix transforms states of a multivariable system onto projection space. In addition, itimposes a specific structure on the system matrix in a multiscale environment. To be specific, the articledeals with a diagonalizing transform that is useful for decoupled control of a system. It establishes thatthere exists a definite relationship between the model in the measurement space and that in the projectionspace. Methodology for deriving the multirate perfect reconstruction filter bank, associated withthe wavelet operator, is presented. The efficacy of the proposed technique is demonstrated by modelingthe point kinetics nuclear reactor. The outcome of the multiscale modeling approach is compared withthat in the single-scale approach to bring out the advantage of the proposed method.
Speech Recognition using Machine Learning
Vineet Vashisht,Aditya Kumar Pandey,Satya Prakash Yadav 대한전자공학회 2021 IEIE Transactions on Smart Processing & Computing Vol.10 No.3
Speech recognition is one of the fastest-growing engineering technologies. It has several applications in different areas, and provides many potential benefits. A lot of people are unable to communicate due to language barriers. We aim to reduce this barrier via our project, which was designed and developed to achieve systems in particular cases to provide significant help so people can share information by operating a computer using voice input. This project keeps that factor in mind, and an effort is made to ensure our project is able to recognize speech and convert input audio into text; it also enables a user to perform file operations like Save, Open, or Exit from voice-only input. We design a system that can recognize the human voice as well as audio clips, and translate between English and Hindi. The output is in text form, and we provide options to convert audio from one language to the other. Going forward, we expect to add functionality that provides dictionary meanings for Hindi and English words. Neural machine translation is the primary algorithm used in the industry to perform machine translation. Two recurrent neural networks used in tandem to construct an encoder-decoder structure are the architecture behind neural machine translation. This work on speech recognition starts with an introduction to the technology and the applications used in different sectors. Part of the report is based on software developments in speech recognition.
Vineet Kumarand,Gurpreet Singh 보안공학연구지원센터 2015 International Journal of Bio-Science and Bio-Techn Vol.7 No.3
Electrocardiogram and Respiratory signal are correlated to each other. In this paper respiration rate has been estimated from ECG. We purpose a novel combination of Ensemble Empirical Mode Decomposition (EEMD) and Canonical Correlation Analysis (CCA) in order to remove the artifacts and we have estimated the respiratory rate from the denoised ECG by creating the envelope of the denoised signal. The canonical components corresponding to the artifacts were removed on the basis of correlation coefficient of denoised signal and ground truth signal. The MIT- Polysomonographic and Apnea-ECG databases of physionet bank were used to acquire the ECG signals. Real time Baseline wander noise from MIT-NSTDB was added to each record and the respiratory rate determined was compared with the corresponding respiratory signals. The average snr improvement in case of denoising using EEMD-CCA is 20.8989db. The average BPM error in respiration rate derived from ECG denoised from EEMD is ±2.7 BPM.