ABSTRACT
Depopulation of food-producing animals is becoming increasingly common in response to both disease outbreaks and supply chain disruptions. In 2019, the American Veterinary Medical Association released depopulation guidelines classifying certain heatstroke-based killing methods as "permitted in constrained circumstances", when circumstances of the emergency constrain reasonable implementation of "preferred" methods. Since then, tens of millions of birds and pigs have been killed by such methods, termed ventilation shutdown (VSD) Plus Heat and VSD Plus High Temperature and Humidity. While no research using validated measures of animal welfare assessment has been performed on these methods, their pathophysiology suggests that animals are likely to experience pain, anxiety, nausea, and heat distress prior to loss of consciousness. Heatstroke-based methods may result in prolonged suffering and often do not achieve 100% mortality. Potential and available alternative depopulation methods are briefly reviewed. The veterinary profession's ethical obligation to protect animal welfare in the context of depopulations is discussed.
ABSTRACT
COVID-19, a new coronavirus illness, initially reported in China in December 2019 has spread around the world. COVID-19 coronavirus has evolved into a worldwide health hazard, quickly infecting humans. Controlling the outbreak is crucial, and scientists have continued to look at potential treatments. COVID-19 can also be defeated with supportive treatment and hospital critical care services. COVID-19 might be avoided using statistical forecasting techniques. The purpose of this study is to create a forecasting model that could be used to predict the spread of COVID-19 in Saudi Arabia. An autoregressive (AR) integrated moving average (ARIMA) model was used to anticipate the number of deaths in three key Saudi Arabian regions: Riyadh, Eastern Region, and Qassim. According to our findings, the number of fatalities in Riyadh and Eastern Region was expected to decrease in August (2021), while the deaths in Qassim were expected to decrease in July (2021).
ABSTRACT
Bitcoin becoming more popular among investors as it provides high returns but due to unregulated property, it is highly volatile in nature. Amidst pandemic spread across world, anyone who hold bitcoin would have keenly watched market with alarming fluctuations recently. Investors are looking for assets that are not impacted by slowdown triggered by lockdown. The study aims to analyze volatility dynamics of Bitcoin from FY2015 to FY2020 by performing general GARCH analysis for modelling by extracting Daily price data from coinmarketcap.com. The study incorporates Augmented Dickey Fuller test for checking stationarity of the series, ARCH LM test for heteroskedasticity and Ljung Box test for determining the mean equation and estimating the variance equation with GARCH (1,1) model in EVIEWS. The results approve that GARCH model is better model works better in period of the high volatility. © Indian Institute of Finance.
ABSTRACT
Purpose: This study aims at exploring and understanding the effect of four independent variables related to dairy retail marketing and distribution (deep freezers, promotions, company support and distributor-retailer relationship) and one moderating variable Covid-19 lockdown on sales of dairy product during the Covid 19 pandemic situation. Research design and methodology: Personal interviews and door-to-door surveys and promotional tools were designed to publicise and collect data from the retailers. The sale data before, during and after promotion activity were all recorded and evaluated to draw an inferential conclusion. Factor analysis and multiple regression methods were adopted to analyses the data collected. Results: The research shows that four out of the five factors studied was found having significant impact on dairy retail sales. The highest impact on sales was contributed by promotions, secondly by the deep freezer impact followed by distributor-retailer relationship during the study period and lastly but not the least due to influence of Covid-19 lockdown. Conclusions: The study contributes to the body of knowledge in cold chain distribution process through utilization of right mix of tools and tactics for effective marketing and distribution of dairy products in developing countries especially during a pandemic situation. © Copyright: The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://Creat¡vecommons.org/l¡censes/by-nc/4.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
ABSTRACT
Recent attention has turned to drilled but uncompleted wells (DUCs) that exploration and production (E&P) companies may manage in order to address market uncertainties. DUCs act as potential supply that bridges the gap when supply and demand are unequal and can play a key role in the operations strategies of producers. This study provides evidence of mildly explosive behavior in the time series of DUCs by applying the Right-Tailed Augmented Dickey Fuller test of Phillips, Shi, and Yu (2015) (PSY). The PSY method tests for mildly explosive behavior of a time series defined by when the volume of DUCs move beyond what would be expected given the fundamental market conditions. The sample spans from December 2013 until May 2020 and includes the major oil producing regions of the United States. The analysis date stamps periods of mild explosivity and matches surges in DUCs with major contemporaneous events including the June 2014 precipitous drop in oil price, midstream bottlenecks and resource constraints, as well as the COVID-related fall in demand for oil. The findings are discussed in the context of exploration and production firms and the use of DUCs as a tool for understanding value and optimization of production over time.