The extent of upskilling of the argentine labor market: a simple analysis

Over the last three decades the labor market of most developed countries have experienced a sustained period of upskilling. This means an overall increase in the skill requirement of jobs determined by the demand for skilled labor. This suggests that their labor demand has become more skill intensive, shifting towards skilled workers relatively to unskilled workers. An analysis of job growth of the Argentine labor market between 1997 and 2009 using data from the EPH, evidences a process of deskilling over this period, with serious implications in terms of competitiveness and about issues related to increasing social and economic inequality.

Optical Gain in Commercial Laser Diodes

Optical gain and optical losses are separately measured in commercial laser diodes by simple analysis of spectral and electrical characteristics, and with no special specimen preparation or handling. The aim is to bring device analysis, for characterization and reliability purposes, closer to the intimate physical processes that rule over laser diode operation. Investigation includes resonating and non-resonating optical cavities.

Corporate Tax Planning: Impact of COVID-19 and Transfer Pricing: Approaches for Comparability Adjustments

The impact of the COVID-19 pandemic has varied significantly across market sectors and companies, and the disruptions generated by the pandemic have had major implications for the transfer-pricing practices of many multinationals. The COVID-19 crisis has challenged the efficiency of traditional benchmarking of profit margins and markups on the basis of the profitability of comparable companies. In this article, we provide a framework for addressing two key questions: (1) how to ensure that the data used for setting or testing transfer-pricing results are appropriate in terms of comparability and that they adequately reflect economic reality for the tested party; and (2) what adjustments need to be made if the tested party's results fall below the arm's-length range. Given the extraordinary circumstances, we cannot rely on a simple analysis of historical data to adjust for the impact faced by businesses as a result of COVID-19. For example, in situations where the taxpayer's results have been affected by the COVID-19 pandemic to a greater extent than the results of comparable companies, the approaches outlined in this article will provide the taxpayer with an estimated arm's-length range of profitability for the comparable companies that is calibrated to the impact of the pandemic on the tested party's results. These approaches are aligned with the transfer-pricing guidance for COVID-19 adjustments issued by the Organisation for Economic Co-operation and Development in December 2020.

Online-to-offline advertisements as field experiments

Online advertisements have become one of today’s most widely used tools for enhancing businesses partly because of their compatibility with A/B testing. A/B testing allows sellers to find effective advertisement strategie,s such as ad creatives or segmentations. Even though several studies propose a technique to maximize the effect of an advertisement, there is insufficient comprehension of the customers’ offline shopping behavior invited by the online advertisements. Herein, we study the difference in offline behavior between customers who received online advertisements and regular customers (i.e., the customers visits the target shop voluntary), and the duration of this difference. We analyze approximately three thousand users’ offline behavior with their 23.5 million location records through 31 A/B testings. We first demonstrate the externality that customers with advertisements traverse larger areas than those without advertisements, and this spatial difference lasts several days after their shopping day. We then find a long-run effect of this externality of advertising that a certain portion of the customers invited to the offline shops revisit these shops. Finally, based on this revisit effect findings, we utilize a causal machine learning model to propose a marketing strategy to maximize the revisit ratio. Our results suggest that advertisements draw customers who have different behavior traits from regular customers. This study demonstrates that a simple analysis may underrate the effects of advertisements on businesses, and an analysis considering externality can attract potentially valuable customers.

Pixel calculations using Orca or GAUSSIAN for electron density automated within the Oscail package

Many discussions of the intermolecular interactions in crystal structures concentrate almost exclusively on an analysis of hydrogen bonding. A simple analysis of atom–atom distances is all that is required to detect and analyse hydrogen bonding. However, for typical small-molecule organic crystal structures, hydrogen-bonding interactions are often responsible for less than 50% of the crystal lattice energy. It is more difficult to analyse intermolecular interactions based on van der Waals interactions. The Pixel program can calculate and partition intermolecular energies into Coulombic, polarization, dispersion and repulsion energies, and help put crystal structure discussions onto a rational basis. This Windows PC implementation of Pixel within the Oscail package requires minimal setup and can automatically use GAUSSIAN or Orca for the calculation of electron density.

Examples of the use of the embedded systems for the long-term collection of slowly-changing parameters in the traction of a car

The article presents how embedded systems can be used to collect data in the long-term traction of a car. It is assumed that the long period is the time of a travelled distance, e.g. a few thousands of kilometers, or a time, e.g. a month. Such data can be used to optimize the control systems and to diagnose unusual faults in mechatronic systems. The research paper presents how, with the use of very cheap devices, it is possible to collect data that quite often could not be collected even with the use of very expensive measuring devices. The possibility of simple analysis of signals in real time was also noted.

INCREASED PM2.5 LEVELS ASSOCIATED WITH INCREASED INCIDENCE OF COVID-19: THE WASHINGTON WILDFIRES OF 2020

Yakima County, Washington was subject to the extrordinary Washington Wildfire Season of 2020 in which unhealty air (PM2.5) persisted for a 14-day period. This remarkable fire and smoke season began in tandem with the COVID-19 pandemic. SARS-CoV-2 virus, like inhaled particulate matter is known to cause respiratory illness or injury. This study sought to determine through publicly available data whether increased levels of PM2.5 were associated with increased cases of COVID-19. Using a 12-day lag analysis, Pearson product correlations were performed between PM2.5 24-hour averages in Yakima County Washington and daily confirmed cases of COVID-19 for data available on March 1, 2020-October 15, 2020. In addition, total running cases of confirmed COVID-19, daily mortality and total running mortality rates were compared in the lag analyses. All days (PM2.5) in the lag analysis were found to have a statistically significant positive correlation with COVID-19 case counts and total running counts of COVID-19 (p<.001) with correlation coefficients ranging from 0.24-0.28. The total running mortality rates were also significantly associated with daily PM2.5 (p<.001); however, the daily mortality rates were not found to be statistically significantly related to PM2.5. This simple analysis provides preliminary evidence that increased air pollution (PM2.5) is associated with higher rates of confirmed COVID-19 cases. However, further research is required to determine the potentially confounding factors in this relationship.