Special Issues

Listed below is a list of selected special articles.

Articles by Year

5 records are found

Study on Currency Exchange Rates Using LSTM( Long Short-Term Memory) Neural Networks and Statistical Analysis

November 29, 2022


This paper focuses on the studies conducted on the changes in the exchange rate behavior of selected currencies such as USD, EURO, KRW, and PESO. The importance of the exchange rate is immeasurable since the movement in currency exchange affects the trade and direction of all money between countries. The studies done for this paper were used to observe the changes in this exchange rate on a global basis. Data collection provided a clear overview of the distribution of these studied rates. The exchange rate of each currency was predetermined, and the information was used to create visual histograms and other graphs for prediction. The data from the line graph provided a specific accounting of the movement of the rates over a period of time. The histograms used the information to decide which rate was standard and it was found that the rates fluctuated regularly but always peaked at a specific time. The predictions show that there are no specific patterns and the rates peaked sharply while the modeling was being conducted.  

The average range of these fluctuation patterns continued to change regularly until 2021. The predictive model was found using LSTM where it was determined that this data could be used to make significant advancements in the exchange rate volatility on economic growth. It was found that several of the studies determined that the high volatility of the exchange rate had a positive effect on international trade and economic growth. Those who support this theory feel that increased flexibility combined with these volatile exchange rates allow countries to stimulate economic growth. They also determined that as the volatility decreases, the result could present a global financial crisis. When observing these contradictions, it was clear that the impact of exchange rate volatility affects international trade. The bottom line is that economic growth continues to be a significant financial issue. 

Keywords: Exploratory Data Analysis(EDA)Exchange Rates, LSTM( Long Short-Term Memory), Neural Networks and Statistical Analysis


  1.  Exchange Rates: What They Are, How They Work, Why They Fluctuate, Investopedia, https://www.investopedia.com/terms/e/exchangerate.asp

  2. O'Sullivan, Arthur; Steven M. Sheffrin (2003). Economics: Principles in action. Upper Saddle River, New Jersey 07458: Prentice Hall. p. 458. ISBN 0-13-063085-3.

  3.  Broz, J. Lawrence; Frieden, Jeffry A. (2001). "The Political Economy of International Monetary Relations". Annual Review of Political Science. 4 (1): 317–343. doi:10.1146/annurev.polisci.4.1.317. ISSN 1094-2939.

  4. The Economist – Guide to the Financial Markets (pdf)

  5.  "Triennial Central Bank Survey: Foreign (other countries) exchange turnover in April 2013 : preliminary global results : Monetary and Economic Department" (PDF). Bis.org. Retrieved 23 December 2017.

  6. Peters, Will. "Find the Best British Pound to Euro Exchange Rate". Pound Sterling Live. Retrieved 21 March 2015.

  7. Understanding foreign exchange: exchange rates Archived 2004-12-23 at the Wayback Machine

  8. https://www.wsj.com/market-data/quotes/fx/USDEUR/historical-prices

  9. https://www.wsj.com/market-data/quotes/fx/USDKRW/historical-prices

  10.  "Mean Squared Error (MSE)". www.probabilitycourse.com. Retrieved 2020-09-12.

  11. https://www.economicshelp.org/macroeconomics/exchangerate/

  12. Bickel, Peter J.; Doksum, Kjell A. (2015). Mathematical Statistics: Basic Ideas and Selected Topics. Vol. I (Second ed.). p. 20. 

  13.  Lehmann, E. L.; Casella, George (1998). Theory of Point Estimation (2nd ed.). New York: Springer. ISBN 78-0-387-98502-2. 

  14.  Gareth, James; Witten, Daniela; Hastie, Trevor; Tibshirani, Rob (2021). An Introduction to Statistical Learning: with Applications in R. Springer. ISBN 978-1071614174.

  15.  Wackerly, Dennis; Mendenhall, William; Scheaffer, Richard L. (2008). Mathematical Statistics with Applications (7 ed.). Belmont, CA, USA: Thomson Higher Education. ISBN 978-0-495-38508-0.

  16. ​​How to Interpret Histograms, https://www.labxchange.org/library/items/lb:LabXchange:10d3270e:html:1


The Effect of Apis mellifera Propolis on the Growth of Tumors on Solanum lycopersicum

September 21, 2022
(*Please email us at info@jyem.org for the information on membership to get access to the full article.)


Plants are an integral part of human life. Crops, especially fruits and vegetables, provide humans with energy and nutrients. What would happen if we didn’t have these foods at all? The aim for this research study was to determine if the plant ridding disease, Tobacco Mosaic Virus
(TMV), could be mitigated if treated with propolis; a substance collected from Apis mellifera (honey bees) when they pollinate flowers. The plant selected for this study was Solanum lycopersicum (tomato plant) due to its commonality with the virus itself. Due to the hardships of germination, the plants were bought and not grown and only the leaf count was measured. The plants were split into two groups, control and experimental. TMV was applied to both groups, but only the experimental group was treated with Apis mellifera propolis. Several days later, the experimental group received the propolis. With the control group, about 6 leaves were destroyed and wrinkle while in the experimental group only 2 leaves were shriveled and destroyed. The control group plant had a tilt as the stem was weakening, while the experimental group was upright. The colors didn't change all too much in either except for the leaf color. In the control group, the leaves looked black and brown, while in the experimental it looked slightly brown
rather than black. According to the data collected, the plant-ridden disease of the Tobacco Mosaic Virus can be rid of with the propolis of Apis mellifera.

KeywordsSolanum lycopersicum,  Apis mellifera Propolis,  Growth of Tumors, Tobacco Mosaic Virus


  1. References
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  2. Annila, T. (2019). Natural bee products and their apitherapeutic applications - ScienceDirect. Sciencedirect, 117(1), 508-508. https://doi.org/10.5248/117.508
  3. El-Seedi, H., Yosri, N., Chen, L., Abd El-Waheed, A., & Ghulam Musharraf, S. (2020). Antimicrobial Properties of Apis mellifera’s Bee. Proquest.com. Retrieved 24 March 2022, from https://www.proquest.com/docview/2424016008/F7926CD3CA434259PQ/1.
  4. Enderling, K. (2019). What are the different types of tumor?. Medical News Today, 23-25. https://doi.org/10.18773/austprescr.2017.005
  5. Kolayi, S., 2021. Bee venom. [online] Bee venom - an overview. Available at 0a%20very,phospholipase%2DA2%20%5B4%5D.> [Accessed 21 December 2021].
  6. Wollaeger, H. (2014). Common questions and answers about tobacco mosaic virus. Michigan State University Extension. Retrieved 16 February 2022, from.
  7. Wagh V. D. (2013). Propolis: a wonder bees product and its pharmacological potentials. Advances in pharmacological sciences, 2013, 308249. https://doi.org/10.1155/2013/308249
  8. Yin, Z., KOBIKI, A., & KAWADA, H. (2012). Tobacco Mosaic Virus as a New Carrier for Tumor Associated Carbohydrate Antigens. Tobacco Mosaic Virus As A New Carrier For Tumor
    Associated Carbohydrate Antigens, 2012(0), 47. https://doi.org/10.1299/jsmeintmp.2005.47_2


The Effects of Sublethal Doses of Hexavalent Chromium on the Health Eisenia fetida

July 15, 2022


 In this experiment  working with Chromium and Eisenia fetida studying the health and behaviors of Eisenia fetida and how Chromium will affect their behaviors when exposed to Chromium. Other researchers that have done similar research showed that their Eisenia fetida have died because of being exposed to too much Chromium or in other experiments they did not have an outcome because the Eisenia fetida was not exposed to enough Chromium. The Eisenia fetida will be exposed to Chromium for about 2 weeks. The worms  will be monitored. The habitat of the Eisenia fetida is moist soil, although some Eisenia fetida actually prefer mud, such as the mud that is found along the shores of lakes or swamps. Eisenia fetida can be found in the soil of backyards as well as near bodies of fresh and saltwater.  When the  Eisenia Fetida arrive  there will be an enclosure for them to be in. Earthworms eat soil. Their nutrition comes from things in soil, such as decaying roots and leaves. The entire surface of a worm's body absorbs oxygen and releases carbon dioxide. Moisture Eisenia Fetida moves  by squeezing muscles around their water- filled bodies. The Earthworms  will lose weight  when being exposed to Chromium. They will also shrink and the regeneration process for the earthworms will slow down. This shows how Chromium does have an effect on Eisenia fetida  and can cause the worms to have different effects.

Keywords: Eisenia fetida, Earthworms, Sublethal doses, Hexavalent chromium


  1. Burlinson, B., Tice, R.R., Speit, G., Agurell, E., Brendler-Schwaab, S.Y., Collins, A.R., Escobar, P., Honma, M., Kumaravel, T.S., Nakajima, M., Sasaki, Y.F., Thybaud, E., Uno, Y., Vasquez, M., Hartmann, A., 2007. Fourth international workgroup on genotoxicity testing: results of in vivo comet assay workgroup. Mutat. Res.

  2. Ching, E.W.K., Siu, W.H.L., Lam, P.K.S., Xu, L., Zhang, Y., Richardson, B.J., Wu, R.S.S., 2001. DNA adduct formation and DNA strand breaks in green-lipped mussels (Perna viridis) exposed to benzo[a]pyrene: dose- and time-dependent relationships. Mar. Pollut. Bull. 42, 603–610. Cotelle, S., Ferard, J.-F., 1999. Comet assay in genetic ecotoxicology: a review. Environ. Mol. Mutagen. 34, 246–255.

  3. Di Marzio, W.D., Saenz, M.E., Lemière, S., Vasseur, P., 2005. Improved single-cell gel electrophoresis assay for detecting DNA damage in Eisenia foetida. Environ. Mol. Mutagen. 46, 246–252. Fourie, F., Reinecke, S.A., Reinecke, A.J., 2007. The determination of earthworm species sensitivity differences to cadmium genotoxicity using the comet assay. Ecotoxicol. Environ. Saf. 67, 361–368. 

  4. Di Palma, L., Gueye, M.T., Petrucci, E., 2015. Hexavalent chromium reduction in contaminated soil : a comparison
    between ferrous sulfate and nanoscale zero-valent iron. J. Hazard Mater. 70–76.https://doi.org/10.1016/j.jhazmat.2014.07.058.

  5. Dong, H., Deng, J., Xie, Y., Zhang, C., Jiang, Z., Cheng, Y., Hou, K., Zeng, G., 2017.Stabilization of nanoscale
    zero-valent iron (nZVI) with modified biochar for Cr(VI)removal from aqueous solution. Journal of Hazardous Materials.
    Elsevier B.V.

  6. Inzunza, B., Orrego, R., Peñalosa, M., Gavilán, J.F., Barra, R., 2006. Analysis of CYP4501A1, PAHs metabolites in bile, and genotoxic damage in Oncorhynchus mykiss exposed to Biobío River sediments, Central Chile. Ecotoxicol. Environ. Saf. 65, 242–251. 

A Novel Deep Learning Algorithm to Calculate and Model the Age-Standardized COVID-19 Mortality Rate of a Subpopulation When Compared to a Standard Population

March 16, 2022
(*Please email us at info@jyem.org for the information on membership to get access to the full article.)


Coronavirus disease -19 (COVID-19) has gained widespread interest in the field of mathematical epidemiology in order to inform the public on basic statistics surrounding COVID-19. However, the age-standardized mortality rates (ASMRs), which adjust age and population discrepancies between different regions by comparing a subpopulation to a standard population, have not been shown publicly. Usually, COVID-19 ASMRs have not been calculated due to the lengthy process required to calculate them; however, ASMRs for COVID-19 have occasionally been calculated, but their effectiveness have been hindered due to the use of a hand-written formula and graphical manual methods. My study involved the development of a deep learning algorithm to calculate ASMR and to instantly graph the ASMR of a subpopulation versus the crude mortality rate of the standard population. This algorithm was used to compare the ASMRs for COVID-19 in American states to the crude mortality rate of the standard population, America. In this study, the algorithm shows efficiency with a consistent runtime of time≤5seconds, within 95% confidence interval error bars among trials. ASMRs show statistically significant differences in expected COVID-19 deaths among most populations. There is at least 95% confidence (p≤0.05) that differences in ASMR are independent of age and population distributions. These findings suggest that there are more factors than just age discrepancy that affect COVID-19 mortality rates.

Keywords: COVID-19, Age-Standardization, Mortality Rate, Algorithm, Deep Learning


  1. Wang, D., Li, Z., & Liu, Y. (2020). An overview of the safety, clinical application and antiviral research of the COVID-19 therapeutics. Journal of Infection and Public Health. doi:10.1016/j.jiph.2020.07.004
  2. Brown, S. M., Doom, J. R., Lechuga-Peña, S., Watamura, S. E., & Koppels, T. (2020). Stress and parenting during the global COVID-19 pandemic. Child Abuse & Neglect. doi:10.1016/j.chiabu.2020.104699
  3. Overton, C. E., Stage, H. B., Ahmad, S., Curran-Sebastian, J., Dark, P., Das, R., . . . Webb, L. (2020). Using statistics and mathematical modelling to understand infectious disease outbreaks: COVID-19 as an example. Infectious Disease Modelling, 5, 409-441. doi:10.1016/j.idm.2020.06.008
  4. Tiirinki, H., Tynkkynen, L., Sovala, M., Atkins, S., Koivusalo, M., Rautiainen, P., . . . Keskimäki, I. (2020). COVID-19 pandemic in Finland – preliminary analysis on health system response and economic consequences. Health Policy and Technology. doi:10.1016/j.hlpt.2020.08.005
  5. Russell, T. W., Hellewell, J., Jarvis, C. I., Zandvoort, K. V., Abbott, S., Ratnayake, R., . . . Kucharski, A. J. (2020). Estimating the infection and case fatality ratio for coronavirus disease (COVID-19) using age-adjusted data from the outbreak on the Diamond Princess cruise ship, February 2020. Eurosurveillance, 25(12). doi:10.2807/1560-7917.es.2020.25.12.2000256
  6. Bernardino, G., Benkarim, O., Garza, M. S., Prat-Gonzàlez, S., Sepulveda-Martinez, A., Crispi, F., . . . Ballester, M. A. (2020). Handling confounding variables in statistical shape analysis - application to cardiac remodelling. Medical Image Analysis, 65. doi:10.1016/j.media.2020.101792
  7. Xu, L., Polya, D. A., Li, Q., & Mondal, D. (2020). Association of low-level inorganic arsenic exposure from rice with age-standardized mortality risk of cardiovascular disease (CVD) in England and Wales. Science of The Total Environment, 743. doi:10.1016/j.scitotenv.2020.140534
  8. Shende, R., Gupta, G., & Macherla, S. (2019). Determination of an inflection point for a dosimetric analysis of unflattened beam using the first principle of derivatives by python code programming. Reports of Practical Oncology & Radiotherapy, 24(5), 432-442. doi:10.1016/j.rpor.2019.07.009
  9. Mohamed, M. O., Gale, C. P., Kontopantelis, E., Doran, T., Belder, M. D., Asaria, M., . . . Mamas, M. A. (2020). Sex-differences in mortality rates and underlying conditions for COVID-19 deaths in England and Wales. Mayo Clinic Proceedings. doi:10.1016/j.mayocp.2020.07.009
  10. Kavadi, D. P., Patan, R., Ramachandran, M., & Gandomi, A. H. (2020). Partial derivative Nonlinear Global Pandemic Machine Learning prediction of COVID 19. Chaos, Solitons & Fractals, 139. doi:10.1016/j.chaos.2020.110056
  11. Minicozzi, P., Cassetti, T., Vener, C., & Sant, M. (2018). Analysis of incidence, mortality and survival for pancreatic and biliary tract cancers across Europe, with assessment of influence of revised European age standardisation on estimates. Cancer Epidemiology, 55, 52-60. doi:10.1016/j.canep.2018.04.011
  12. Bosch, Jaume, et al. “Asynchronous Runtime with Distributed Manager for Task-Based Programming Models.” Parallel Computing, vol. 97, 2020, p. 102664., doi:10.1016/j.parco.2020.102664.
  13. Rodriguez-Diaz, Carlos E., et al. “Risk for COVID-19 Infection and Death among Latinos in the United States: Examining Heterogeneity in Transmission Dynamics.” Annals of Epidemiology, 23 July 2020, doi:10.1016/j.annepidem.2020.07.007.
  14. Wiemers, Emily, et al. “Disparities in Vulnerability to Severe Complications from COVID-19 in the United States.” Research in Social Stratification and Mobility, vol. 69, 2020, doi:10.3386/w27294.
  15. Etkin, Yana, et al. “Acute Arterial Thromboembolism in Patients with COVID-19 in the New York City Area.” Annals of Vascular Surgery, 28 Aug. 2020, doi:10.1016/j.avsg.2020.08.085.
  16. Centers for Disease Control and Prevention. www.cdc.gov/.
  17. 2020 World Population by Country, worldpopulationreview.com/

Impact of Mask Policies on Social and Psychological Consequences During the Covid-19 Pandemic

January 26, 2022

Abstract: COVID-19 has proven detrimental to the economy and changed the nature of social interactions. Governments at every level have increasingly required the use of face masks in public spaces. Evidence has shown that mandatory mask-wearing policies can effectively control the outbreak of the virus, protecting susceptible populations (i.e., individuals with preexisting conditions, and individuals 65 and older). Many communities encourage mask-wearing to reduce the chance of viral transmission. 

While mandatory mask policies appear to effectively reduce transmission of the virus, their long-term psychological effects are not yet known. In this study, we examine the association between the implementation of face mask mandates and detrimental psychological and social consequences as well as other relevant aspects. Also, this study tries to figure out if the mandatory mask policies are advisable, and if so, how it benefits the public. 

Keywords:  Mask policies, Social behavior, Psychological consequences, Covid-19, Face mask during the pandemic


  1. Detsky, A. S. and Bogoch, I. I. (2020, August 25). The Canadian Response To COVID-19. Retrieved from https://jamanetwork.com/journals/jama/fullarticle/276943

  2. Duan, L. and Zhu, G. (2020). Psychological interventions for people affected by the COVID-19 epidemic. Lancet. Psych. 7 300–302. 10.1016/s2215-0366(20)30073-

  3. Greenberg, N., Docherty, M., Gnanapragasam, S. and Wessely, S. (2020). Managing mental health challenges faced by healthcare workers during covid-19 pandemic. BMJ 368:m1211. 10.1136/bmj.m121

  4. Liu S., Yang L., Zhang C., Xiang Y. T., Liu Z., Hu S., et al. (2020). Online mental health services in China during the COVID-19 outbreak. Lancet. Psych. 7 E17–E18. 10.1016/S2215-0366(20)30077-

  5. Maheu, M. P., McMenamin, J. and Posen, L. (2012). Future of telepsychology, telehealth, and various technologies in psychological research and practice. Profess. Psychol. Res. Prac. 43 613–621. 10.1037/a0029458

  6. Parshley, L. and Zhou, Y. (2020, December 4). Why every state should adopt a mask mandate, in 4 charts. Retrieved from https://www.vox.com/science-and-health/21546014/mask-mandates-coronavirus-covid-19

  7. The Economist. (2020, October 14). Tracking covid-19 excess deaths across countries. Retrieved from https://www.economist.com/graphic-detail/coronavirus-excess-deaths-tracker

  8. The Economist. (2020, October 11). Covid-19 has led to a sharp increase in depression and anxiety. Retrieved from https://www.economist.com/graphic-detail/2021/10/11/covid-19-has-led-to-a-sharp-increase-in-depression-and-anxiety

  9. Wang, C. J., Chun, Y. and Brook, R. H. (2020, April 14). Response to COVID-19 in Taiwan: Big Data Analytics, New Technology, and Proactive Testing. Retrieved October 18, 2020, from https://jamanetwork.com/journals/jama/fullarticle/2762689

  10. Zhou X., Snoswell C. L., Harding L. E. (2020). The Role of Telehealth in Reducing the Mental Health Burden from COVID-19. Telemed. E Health. 26 377–379. 10.1089/tmj.2020.0068