Notes

Neutron diffraction study in the monoclinic - tetragonal cycle move inside NdNbO4 along with NdTaO4.
Choosing pollution control instrument is an important environmental policy decision. Carbon taxes and subsidies for emissions reductions are two commonly used environmental policies. In practice, the government may be restricted to use only one policy instrument. In this paper, we compare the social welfare effect between policies of a carbon tax and a subsidy. We show that as the marginal environmental damage of the high carbon product increases, the control instrument should change from a subsidy policy to a carbon tax policy. It also turns out that Bertrand competition does not always incur a higher social welfare than Cournot competition when the government intervenes with a pollution control policy.Currently, 2019-nCoV has spread to most countries of the world. Understanding the environmental factors that affect the spread of the disease COVID-19 infection is critical to stop the spread of the disease. The purpose of this study is to investigate whether population density is associated with the infection rate of the COVID-19. We collected data from official webpages of cities in China and in the USA. The data were organized on Excel spreadsheets for statistical analyses. We calculated the morbidity and population density of cities and regions in these two countries. We then examined the relationship between morbidity and other factors. Our analysis indicated that the population density in cities in Hubei province where the COVID-19 was severe was associated with a higher percentage of morbidity, with an r value of 0.62. Similarly, in the USA, the density of 51 states and territories is also associated with morbidity from COVID-19 with an r value of 0.55. In contrast, as a control group, there is no association between the morbidity and population density in 33 other regions of China, where the COVID-19 epidemic is well under control. Interestingly, our study also indicated that these associations were not influenced by the first case of COVID-19. The rate of morbidity and the number of days from the first case in the USA have no association, with an r value of - 0.1288. Population density is positively associated with the percentage of patients with COVID-19 infection in the population. this website Our data support the importance of such as social distancing and travel restriction in the prevention of COVID-19 spread.Economic growth and the rapid increase in the world population has led to a greater need for natural resources, which in turn, has put pressure on said resources along with the environment. Water, food, and energy, among other resources, pose a huge challenge. Numerous essential resources, including organic substances and valuable nutrients, can be found in wastewater, and these could be recovered with efficient technologies. Protein recovery from waste streams can provide an alternative resource that could be utilized as animal feed. Membrane separation, adsorption, and microbe-assisted protein recovery have been proposed as technologies that could be used for the aforementioned protein recovery. This present study focuses on the applicability of different technologies for protein recovery from different wastewaters. Membrane technology has been proven to be efficient for the effective concentration of proteins from waste sources. The main emphasis of the present short communication is to explore the possible strategies that could be utilized to recover or restore proteins from different wastewater sources. The presented study emphasizes the applicability of the recovery of proteins from various waste sources using membranes and the combination of the membrane process. Future research should focus on novel technologies that can help in the efficient extraction of these high-value compounds from wastes. Lastly, this short communication will evaluate the possibility of integrating membrane technology. This study will discuss the important proteins present in different industrial waste streams, such as those of potatoes, poultry, dairy, seafood and alfalfa, and the possible state of the art technologies for the recovery of these valuable proteins from the wastewater.This study empirically analyzes the long-term relationship between agricultural production and carbon dioxide (CO2) emissions in Azerbaijan using annual data covering the period of 1992-2014. Additionally, real income and energy consumption variables were included in the model in testing the existence of the environmental Kuznets curve (EKC) hypothesis. Autoregressive distributed lag (ARDL) method is undertaken to reveal the existence of the long-term relationship between the CO2 and its determinants. The ARDL mechanism shows that gross domestic product (GDP) and energy consumption have a positive and statistically significant effect on carbon dioxide emissions. However, agricultural production and the square of GDP have a negative impact on air pollution. Furthermore, when the coefficients of real GDP and squared GDP included in the model were examined to analyze the inverted-U-shaped relationship between economic growth and environmental pollution, the EKC hypothesis was confirmed to be valid. According to Toda-Yamamoto causality test results, there is a bidirectional relationship between GDP, the square of GDP, and carbon emissions. From energy consumption and agricultural value-added to CO2 emissions, a unidirectional Granger causality relationship was found. Ultimately, the findings suggest that policies and reforms that increase or support agricultural production will help lower the country's CO2 emissions level.The current investigation examines causal relation between PPP investment in energy sector and CO2 emissions in selected developing countries by using non-parametric causality in quantiles and linear granger causality techniques. Range of the data is from January 1998 to December 2016. Although results obtained by linear granger causality test does not report any causal relation between PPP investment in energy and CO2 emissions, but findings from non-parametric test show that non-linear relationship exhibit between variables. The non-parametric outcomes indicate that PPP investment in non-renewable energy in the selected countries contribute to carbon emissions and thus degrade environment. And therefore, the need is to divert PPP investment to renewable energy where it is more effective. This investigation provides valuable information to policy-makers in developing countries to think out of box and address pressing environmental issues.
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