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- 저자 : Najam Us SAHAR (검색결과 3 건)
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( Munazza Fatima ),( Najam Us Sahar Sadaf Zaidi ),( Deeba Amraiz ),( Farhan Afzal ) 한국미생물 · 생명공학회 2016 Journal of microbiology and biotechnology Vol.26 No.1
Nanoparticles have wide-scale applications in various areas, including medicine, chemistry, electronics, and energy generation. Several physical, biological, and chemical methods have been used for synthesis of silver nanoparticles. Green synthesis of silver nanoparticles using plants provide advantages over other methods as it is easy, efficient, and eco-friendly. Nanoparticles have been extensively studied as potential antimicrobials to target pathogenic and multidrug-resistant microorganisms. Their applications recently extended to development of antivirals to inhibit viral infections. In this study, we synthesized silver nanoparticles using Cinnamomum cassia (Cinnamon) and evaluated their activity against highly pathogenic avian influenza virus subtype H7N3. The synthesized nanoparticles were characterized using UVVis absorption spectroscopy, scanning electron microscopy, and Fourier transform infrared spectroscopy. Cinnamon bark extract and its nanoparticles were tested against H7N3 influenza A virus in Vero cells and the viability of cells was determined by tetrazolium dye (MTT) assay. The silver nanoparticles derived from Cinnamon extract enhanced the antiviral activity and were found to be effective in both treatments, when incubated with the virus prior to infection and introduced to cells after infection. In order to establish the safety profile, Cinnamon and its corresponding nanoparticles were tested for their cytotoxic effects in Vero cells. The tested concentrations of extract and nanoparticles (up to 500 μg/ml) were found non-toxic to Vero cells. The biosynthesized nanoparticles may, hence, be a promising approach to provide treatment against influenza virus infections.
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Herding Behavior and Cryptocurrency: Market Asymmetries, Inter-Dependency and Intra-Dependency
JALAL, Raja Nabeel-Ud-Din,SARGIACOMO, Massimo,SAHAR, Najam Us,FAYYAZ, Um-E-Roman Korea Distribution Science Association 2020 The Journal of Asian Finance, Economics and Busine Vol.7 No.7
The study investigates herding behavior in cryptocurrencies in different situations. This study employs daily returns of major cryptocurrencies listed in CCI30 index and sub-major cryptocurrencies and major stock returns listed in Dow-Jones Industrial Average Index, from 2015 to 2018. Quantile regression method is employed to test the herding effect in market asymmetries, inter-dependency and intra-dependency cases. Findings confirm the presence of herding in cryptocurrency in upper quantiles in bullish and high volatility periods because of overexcitement among investors, which lead to high volume trading. Major cryptocurrencies cause herding in sub-major cryptocurrencies, but it is a unidirectional relation. However, no intra-dependency effect among cryptocurrencies and equity market is observed. Results indicate that in the CKK model herding exists at upper quantile in market that may be due when the market is moving fast, continuously trading, and bullish trend are prevailing. Further analysis confirms this narrative as, at upper quantile, the beta of bullish regime is negative and significant, meaning the main source of market herding is a bullish trend in investment, which increases market turbulence and gives investors opportunity to herd. Also, we found that herding in cryptocurrencies exits in high volatility periods, but this herding mostly depends on market activity, not market movement.
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Commodity Prices, Tax Purpose Recognition and Bitcoin Volatility: Using ARCH/GARCH Modeling
Raja Nabeel-Ud-Din JALAL,Massimo SARGIACOMO,Najam Us SAHAR 한국유통과학회 2020 The Journal of Asian Finance, Economics and Busine Vol.7 No.11
The study investigates the role of commodity prices and tax purpose recognition on bitcoin prices. Since the introduction of bitcoin in 2008, emphasis has focused on economists, policy-makers and analysts drastically increasing bitcoin’s accessibility and commodity values (Dumitrescu & Firică, 2014). This study employs GARCH and EGARCH from ARCH/GARCH family on daily nature data. We measure the volatile behavior of bitcoin by employing auto-regressive conditional heteroscedasticity model with the aim to explore the relationship between major commodities and bitcoin volatility. We focus on major commodities like gold, silver, platinum, and crude oil to be regressed with bitcoin. The daily prices of commodities were retrieved from www.investing.com and bitcoin prices from www.coindesk.com for the period from 29 April 2013 to 16 October 2018. Results confirmed the currency’s long-term volatile behavior, which is due to its composition and market dynamics, whereas the existence of asymmetric information effect is not confirmed. Tax recognition by other countries may in future help in controlling the volatility as bitcoin is not a country-specific security. But, only silver impacts on volatility in comparison to oil prices and platinum, which is due to its similar features with gold. Eventually, bitcoin can be used for risk diversification and money making.
ScienceON
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