A Dataset of Lost Opportunities The Case of 63 Developed And Emerging Countries Amid The COVID-19 Pandemic

The dataset provides the statistics on digital competitiveness, sustainable development, and the COVID-19 cases for 63 developed and developing countries. The dataset calculates digital competitiveness and sustainable development under the adverse impact of the pandemic in 2020. Unlike the stark change compared with 2019, it clears the estimated growth of the other factors’ influence and characterizes the effect of the pandemic and the COVID-19 crisis. Practical significance also comprises evaluating wasted opportunities in 2020 and increasing digital competitiveness and sustainable development, which reflect the difference between simple growth indicators in 2020 and 2019 and growth under the pandemic’s influence. Another advantage of this paper is the forecasting advantage and the alternativeness of the considered scenarios, which allows implementing the estimates in a broad range of scientific studies. The case of Australia and the world economy's forecast for 2021 are elaborated on in the paper.

Optimal Price Level Under Slowing Economic Performance Using Simple Growth-Inflation Threshold Models

The purpose of this study was to evaluate the threshold of inflation that is tolerant of Indonesia’s economic growth rate. The basic question to be answered was what level of inflation is safe enough for economic growth. To answer this question, this study used Indonesian macroeconomic data, specifically data on inflation and economic growth between 1969-2017 sourced from the Central Statistics Agency and Bank Indonesia. The data analysis method used was a threshold regression model that was repeated manually by entering an acceptable inflation simulation value based on inflation experience in Indonesia. The simulation results showed that the inflation threshold that is safe for growth is around 7 to 8 percent per year. However, the model showed that inflation of 3 percent is the optimal level for growth. One concludes that an inflation rate of around 3 percent can be used as a guide in determining the inflation target in Indonesia. Keywords: growth, inflation, stability, threshold

Present and Future Prospect of Algae: A Potential Candidate for Sustainable Pollution Mitigation

Pollution control and mitigation are critical to protect the ecosystem and make everyone's life safer and healthier. Different pollution mitigation strategies and measures are implemented to remove pollutants, which broadly involve physical, chemical, and biological methods. Biological methods are found to be more sustainable, effective, and eco-friendlier than the other two methods. These methods mainly use microbes like bacteria, fungi, algae, and plants, and their products like enzymes and metabolic products to remove pollutants. Due to their unique photosynthetic ability and simple growth requirements, Algae can be grown using simpler components like CO2, sunlight, and media, making them a potential candidate to be used as a pollution mitigator. Algae can indicate and remove pollutants like CO2, SO2, NO2, and particulate matter from the air; these pollutants and particulate matter are either used for their growth or these are accumulated inside them.. Algal species have shown the efficient removal of heavy metals, organic pollutants, explosives, petroleum contaminants, pesticides, polycyclic aromatic hydrocarbons (PAHs), and plastics from different water sources. There is a lot of scope in using algae to remove organic and inorganic pollutants in wastewater treatment plants. Algae hold great potential to remove radioactive pollutants from natural resources and involve removal mechanisms like biosorption and bioaccumulation. Algae can be used with different adsorbent materials to develop adsorption systems for the adsorption of radionuclides and heavy metals. This review elucidates different algal species, their cultural conditions, the removal efficiency of different types of pollutants from the air, water, soil, and their role in genetic engineering and the algae's potential for waste mitigation.

DOES ALTITUDE AND FOREST DENSITY AFFECT ECONOMIC GROWTH? A CASE STUDY OF KALIMANTAN BARAT

Kalimantan Barat is one of the individual provinces in Kalimantan due to its diverse geographical elevation among all districts. Mountains and hills dominate the districts near the border; lowlands and river banks dominate the urban areas. A geographical indication is a barrier to economic growth, as a simple growth from limited transportation. Efforts to optimize the economic sector are also carried out in forest management, including Kalimantan Barat as one of the world's lungs. The conversion of forest land functions is suspected to increase economic growth even though it must balance nature. This study aims to determine the significance of altitude as a fixed geographical indicator and forest density as a natural condition that can vary according to human activities. The height of area data and forest density, and the average economic growth in 14 districts/cities in Kalimantan Barat uses the Panel Least Square method. As a result, area height has a negative and significant effect on economic growth, whereas forest density has no such relationship. Simultaneously, both variable is having a substantial impact on economic growth in Kalimantan Barat.

The Economic Gains from Equity

How much is inequity costing us? Using a simple growth accounting framework we apply standard shift-share techniques to data from the Current Population Survey (1990-2019) to compute the aggregate economic costs of persistent educational and labor market disparities by gender and race. We find significant economic losses associated with these gaps. Building on this finding, we consider which disparities generate the largest costs, paying specific attention to differences in employment, hours worked, educational attainment, educational utilization, and occupational allocation. We also examine gaps in the returns on these variables. Our findings suggest that differences in employment opportunities and educational attainment make the largest contributions by race; differences in returns on these variables also contribute materially to the total costs. Differences by gender are primarily driven by gaps in employment and hours. Given the disproportionate impact of COVID-19 on the labor market outcomes of women and people of color, as well as the fact that the U.S. population is increasingly racially diverse, these costs will only increase in the future.

Sigma-Pi Structure with Bernoulli Random Variables: Power-Law Bounds for Probability Distributions and Growth Models with Interdependent Entities

The Sigma-Pi structure investigated in this work consists of the sum of products of an increasing number of identically distributed random variables. It appears in stochastic processes with random coefficients and also in models of growth of entities such as business firms and cities. We study the Sigma-Pi structure with Bernoulli random variables and find that its probability distribution is always bounded from below by a power-law function regardless of whether the random variables are mutually independent or duplicated. In particular, we investigate the case in which the asymptotic probability distribution has always upper and lower power-law bounds with the same tail-index, which depends on the parameters of the distribution of the random variables. We illustrate the Sigma-Pi structure in the context of a simple growth model with successively born entities growing according to a stochastic proportional growth law, taking both Bernoulli, confirming the theoretical results, and half-normal random variables, for which the numerical results can be rationalized using insights from the Bernoulli case. We analyze the interdependence among entities represented by the product terms within the Sigma-Pi structure, the possible presence of memory in growth factors, and the contribution of each product term to the whole Sigma-Pi structure. We highlight the influence of the degree of interdependence among entities in the number of terms that effectively contribute to the total sum of sizes, reaching the limiting case of a single term dominating extreme values of the Sigma-Pi structure when all entities grow independently.

Resolving phylogenetic and biochemical barriers to functional expression of heterologous iron-sulphur cluster enzymes

Many of the most promising applications of synthetic biology, including engineering of microbes for renewable chemical production, relies upon the ability of genetically-tractable hosts to express heterologous enzymes from foreign species. While countless methods for facilitating heterologous enzyme expression have been developed, comparable tools for facilitating heterologous enzyme activity are generally lacking. Such tools are needed to fully exploit the biosynthetic potential of the natural world. Here, using the model bacterium Escherichia coli, we investigate why iron-sulphur (Fe-S) enzymes are often inactive when heterologously expressed. By applying a simple growth complementation assay with collections of Fe-S enzyme orthologs from a wide range of prokaryotic diversity, we uncover a striking correlation between phylogenetic distance and probability of functional expression. Moreover, co-expression of a heterologous Fe-S biogenesis pathway increases the phylogenetic range of orthologs that can be functionally expressed. On the other hand, we find that heterologous Fe-S enzymes that require specific electron carrier proteins within their natural host are rarely functionally expressed unless their specific reducing partners are identified and co-expressed. We demonstrate in vitro that such selectivity in part derives from a need for low-potential electron donors. Our results clarify how phylogenetic distance and electron transfer biochemistry each separately impact functional heterologous expression and provide insight into how these barriers can be overcome for successful microbial engineering involving Fe-S enzymes.

The Trend and Growth Rate of Brinjal in Dhamtari Block and Chhattisgarh State, India

The research work was carried out with objectives to estimate the trend and growth rate in area, production & productivity of brinjal in Dhamtari block of Chhattisgarh state. The study was conducted in Dhamtari district which comprises of 4 blocks and among which Dhamtari block occupies maximum area and production of Brinjal. The secondary data was collected from Directorate of Horticulture, Directorate of Land record, Directorate of Economics and Statistics, and annual horticultural statistics, Raipur Chhattisgarh. The annual area, production and productivity of Brinjal in Dhamtari district is collected from Directorate of Horticulture Dhamtari, Chhattisgarh. The secondary data were collected for the last 10 years (2006-07 to 2015-16). Compound growth rate and simple growth rate were used to analyse the collected data. To reveal the behavior of selected variables in the district over time, regression analysis was carried out. The following form of linear production function was fitted by least square technique to estimate the trend and growth rate of the selected variable for the study period. Area, production and productivity of Brinjal in Chhattisgarh state was found to be increased at highly significant rate, whereas, in Dhamtari district, it was found that only area of Brinjal increased at highly significant rate.

ВИВЧЕННЯ ЕФЕКТИВНОСТІ ХЛОРЕЛИ ЩОДО ЗМЕНШЕННЯ ЦИТОТОКСИЧНИХ ПРОЯВІВ У СМУГАСТОГО ДАНІО ЗА ВПЛИВУ ОРГАНОФОСФАТНИХ ПЕСТИЦИДІВ

The ecological potential of microalgae for purification of aquatic and soil ecosystems and natural restoration of their homeostatic functional state is considered to be high due to the rapid growth and development of algae, their labile and dynamic metabolism and simple growth conditions. The aim of present work was to study the effectiveness of Chlorella as a potential bioremediator to reduce the toxic effects of pesticides, roundup and chlorpyrifos after their individual and complex influence on zebrafish Danio rerio. The effect of environmental concentrations of roundup (15 μg⋅L-1) and chlorpyrifos (0,1 μg⋅L-1) provoked partial depletion of the cell thiols pool when compared to the control, which appeared as a decrease in glutathione transferase activity (under combined exposure) and total glutathione concentration. A decrease in the level of total antioxidant capacity, which was consistent with an increase in the level of reactive oxygen species in the liver tissue was also shown. Meanwhile, the studied organophosphate pesticides didn’t cause severe signs of neurotoxicity, but activated acetylcholinesterase in line with no visual manifestations of locomotion reactions. Chlorpyrifos determined an increase in the concentration of methylglyoxal and the most noticeable sign of endocrine disruption from all studied groups in terms of vitellogenin concentration. Principal component analysis allowed to identify a separate localization of each of the studied groups and the interim position of animals after combined exposure when compared to the individual action. The introduction of Chlorella vulgaris in the exposure media in the amount of about 100 thousand cells / dm3 did not show a significant corrective effect on the toxicity of pesticides for non-target species Danio rerio, which doesn’t exclude the positive impact of algae on the functioning of the ecosystem in general and requires a more detailed analysis.

Simple rapid in vitro screening method for SARS-CoV-2 anti-virals that identifies potential cytomorbidity-associated false positives

The international SARS-CoV-2 pandemic has resulted in an urgent need to identify new anti-viral drugs for treatment of COVID-19 patients. The initial step to identifying potential candidates usually involves in vitro screening. Here we describe a simple rapid bioassay for drug screening using Vero E6 cells and inhibition of cytopathic effects (CPE) measured using crystal violet staining. The assay clearly illustrated the anti-viral activity of remdesivir, a drug known to inhibit SARS-CoV-2 replication. A key refinement involves a simple growth assay to identify drug concentrations that cause cellular stress or “cytomorbidity”, as distinct from cytotoxicity or loss of viability. For instance, hydroxychloroquine shows anti-viral activity at concentrations that slow cell growth, arguing that its purported in vitro anti-viral activity arises from non-specific impairment of cellular activities.