Introductory Models of COVID-19 in the United States

ABSTRACT Students develop and test simple kinetic models of the spread of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Microsoft Excel is used as the modeling platform because it is nonthreatening to students and it is widely available. Students develop finite difference models and implement them in the cells of preformatted spreadsheets following a guided inquiry pedagogy that introduces new model parameters in a scaffolded step-by-step manner. That approach allows students to investigate the implications of new model parameters in a systematic way. Students fit the resulting models to reported cases per day data for the United States using least squares techniques with Excel's Solver. Using their own spreadsheets, students discover for themselves that the initial exponential growth of COVID-19 can be explained by a simplified unlimited growth model and by the susceptible-infected-recovered (SIR) model. They also discover that the effects of social distancing can be modeled using a Gaussian transition function for the infection rate coefficient and that the summer surge was caused by prematurely relaxing social distancing and then reimposing stricter social distancing. Students then model the effect of vaccinations and validate the resulting susceptible-infected-recovered-vaccinated (SIRV) model by showing that it successfully predicts the reported cases per day data from Thanksgiving through the holiday period up to 14 February 2021. The same SIRV model is then extended and successfully fits the fourth peak up to 1 June 2021, caused by further relaxation of social distancing measures. Finally, students extend the model up to the present day (27 August 2021) and successfully account for the appearance of the delta variant of the SARS-CoV-2 virus. The fitted model also predicts that the delta variant peak will be comparatively short, and the cases per day data should begin to fall off in early September 2021, counter to current expectations. This case study makes an excellent capstone experience for students interested in scientific modeling.

The Influence of CSR Practices on the Financial Performance of Microfinance Institutions in Togo

Microfinance pursues a dual objective: reduce poverty (social performance) and ensure lasting profitability (financial performance). However, beyond these two performances, microfinance institutions (MFIs) have a social responsibility (CSR) towards their stakeholders. The main objective of this article is to measure the influence of the CSR practices of Togolese MFIs on their financial performance. The analysis is conducted over a sample of 60 Togolese MFIs, using the principal component analysis and generalized least squares techniques. The results show that CSR through the dimensions customer, employees and community positively and significantly impact on the financial performance of MFIs when measured by ROA, while the environment dimension has a negative significant influence.

Multivariate Six Sigma: A Case Study in Industry 4.0

The complex data characteristics collected in Industry 4.0 cannot be efficiently handled by classical Six Sigma statistical toolkit based mainly in least squares techniques. This may refrain people from using Six Sigma in these contexts. The incorporation of latent variables-based multivariate statistical techniques such as principal component analysis and partial least squares into the Six Sigma statistical toolkit can help to overcome this problem yielding the Multivariate Six Sigma: a powerful process improvement methodology for Industry 4.0. A multivariate Six Sigma case study based on the batch production of one of the star products at a chemical plant is presented.

MODELS TO PREDICT SLOPE LENGTH FROM OTHER WATERSHED ATTRIBUTES

Soil erosion by water is an extensive and increasing problem worldwide. Albeit, this problem has been recognized as a significant hazard in Iraq, yet the number of studies on this topic is very limited. Most of the models used for estimating soil erosion contain parameters for slope length factor (LS). A major constraint is the difficulty in extracting the LS factor. Accordingly, the current study was initiated with the main objective of deriving models to predict the slope length from relatively easy to measure basin characteristics with a reasonable accuracy. To achieve the above objective, standard methodologies were employed to describe 30 main basins with the upper part of Iraq in terms linear, areal and relief morphometric parameters. The majority of the delineated watersheds were characterized by having high slope lengths indicating lower drainage density and higher erosion rate. Linear and non-linear least squares techniques were applied to predict the slope length from other basin characteristics. Different indicators were used to test the performance of the proposed models and the approach was validated using K-fold procedure at independent basins. The results indicated that the 4-parameter regression model outperformed the remaining models of watershed slope length. The regressors of this model are bifurcation ratio, perimeter, and basin length and slope gradient.

Refereeing articles including SEM – what should referees look for?

Purpose After expressing an initial disquiet about the nature of many studies that are published using structural equation modelling (SEM), a rationale for using the technique is provided. Given the advantages provided by the technique, the differences between covariance-based and partial least squares techniques are briefly described. The argument progresses by indicating assumptions behind the techniques and what it is that referees require before being able to properly referee the paper. Some issues are fundamental to survey-based materials and include the requirement to distinguish between importance and discriminatory power, and the over-dependency on cross-sectional analysis when making claims of generalisation. Other issues of scale creation and sample size are touched upon. This paper finishes by suggesting a checklist for referees who are asked to review papers using SEM.

Export Sophistication and Trade Elasticities

Does a country’s export structure impact the way that exchange rates affect trade? Do more sophisticated products exhibit lower demand elasticities? Using panel data for major exporters over the 1992–2016 period and dynamic ordinary least squares techniques, we find that price elasticities are higher for low-technology goods such as textiles and footwear than for high-technology goods such as pharmaceuticals and medical equipment. We also find that elasticities are larger for less advanced countries such as China than for more advanced countries such as Switzerland. We draw policy implications from these findings for countries exposed to safe haven capital flows, for countries facing long-term appreciation pressures and for countries that specialise in low-technology exports. JEL Classification: F14, F10

Linking knowledge management processes to innovation

Purpose This paper aims to analyse the relationship between knowledge management processes and innovation (KM-IN) in Brazilian and Portuguese companies. Design/methodology/approach The tests were performed using a sequential mixed-method approach. Quantitative analysis was conducted using 341 observations from Brazilian and Portuguese companies and partial least squares techniques. Qualitative analysis was conducted using ten interviews and content analysis techniques. Findings Results showed differences between Brazilian and Portuguese companies with respect to the relationship between knowledge sharing process and innovation. Portuguese companies cope with the geographical dispersal of operations and the lack of interpersonal skills by introducing formal knowledge sharing processes. Practical implications Findings demonstrate that the transfer of knowledge processes to foreign countries may demand adjustments according to cultural traits. Specifically, the findings will be of interest to firms intending to expand their activities between Brazil and Portugal. Originality/value Although researchers have investigated the influence of the national context in many countries, country comparisons are still scarce.

Planting a Problem: Examining the Spread of Seed-Borne Potato Virus Y

Potato virus Y (PVY) is among the most economically impactful potato pathogens, yet the spread of PVY from infected seed potatoes within commercial potato fields has not been adequately studied. Test lots containing various seed-borne PVY levels were created by mixing different proportions of seed pieces from healthy and infected tubers drawn from the same seed source. These seed lots were planted in commercial potato fields near the Teton Seed Potato Management Area from 2010 to 2012. Regression analyses on data from these test plots produced models of the in-season spread of PVY originating from infected seed. Conventional ordinary least squares techniques were supplemented with the use of quantile regression; the resulting models indicate the significance of seed-borne PVY on end-of-season infection levels and highlight the need of seed potato buyers to review postharvest testing results.

Automating Passport Localization Process Based on WLST-RFID Algorithm

The electronic-passport is majorly used in worldwide. Many countries have started changing their conventional passports to electronic-passports due to upgraded security of the passport holder. Passports and any document probably enhanced using recent technology advancements - Radio Frequency Identification (RFID) technology for e-passports. The e-Passport is one of the important identification system of these applications of RFID, where the number of forged passports is increasing worldwide. It is great importance to examine a policy regarding to these information of the passport holder according to electronic approaches and developments, which are moving toward electronic data storage that focuses on the localization techniques. In this paper, we propose Weighted Least Squares Techniques (WLST) of generalized least squares that specifically estimate the accuracies of different measurements of the Passport Position (PP) to obtain a better estimation in airports. This algorithm achieves greater robustness results for accuracy in localization and tracking with a very limited in computational cost.

Fluid flow and heat transfer investigation of blood with nanoparticles through porous vessels in the presence of magnetic field

In this study, the blood flow was investigated involving nanoparticles through porous blood vessels in the presence of magnetic field by means of collocation and least squares techniques. Blood was assumed to be non-Newtonian fluid having nanoparticles in which different models were used to determine the viscosity of the nanofluids. Vogel’s, Reynolds, variable, and constant viscosity models were discussed by using the two aforementioned techniques. Hence, we compared our results with a numerical technique RK-4 and already existing results to show the credibility of our solutions. Further, some physical parameters and their effects are also stated in this research. Increase in the thermophoresis parameter and pressure gradient along with the decrease in the Brownian motion parameter provide a rapid change in the velocity profile, which has been disclosed by results. Additionally, a dramatic change in the velocity has been realized by using Vogel’s model.