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Exceedance Analysis of the Fluctuation in the Economic Trends Using Statistical Probability

December 13, 2019

AbstractThere have been numerous different kinds of data such as stock prices and interest rates observed and gathered in the past. The sequential nature of these data require us to account for the dynamic nature using special statistical skill and techniques. Time series analysis provide the appropriate methods necessary in order to analyze sequential data.
It may be problematic to picture the essential, underlying trend of the data if the time series has a lot of noise. To distinguish the signal and the noise from each other, various linear and nonlinear smoothers must be applied.

This paper collected a century’s worth of P/E ratio data and used the static distribution to map out the overall trend of the P/E ratio in terms of its return period. Also, the data was plotted in Matlab, and multiple fitting models were tested out to see which one fit the data the best. The P/E ratio was chosen due to its significance in the evaluation of stocks’ values, and the static distribution due to its ability to incorporate rapidly fluctuating data into statistical analysis.

Keywords – Multiple fitting models, P/E ratio, statistical analysis, lnear and nonlinear smoothers


References

[1] Peres, D. J.; Cancelliere, A. (2016-10-01). "Estimating return period of landslide triggering by Monte Carlo simulation". Journal of Hydrology. Flash floods, hydro-geomorphic response and risk management. 541: 256–271.
[2] Anonymous (2014-11-07). "Flood Estimation Handbook". UK Centre for Ecology & Hydrology. Retrieved 2019-12-21.
[3] https://en.wikipedia.org/wiki/Gumbel_distribution
[4] ASCE, Task Committee on Hydrology Handbook of Management Group D of (1996). Hydrology Handbook | Books. doi:10.1061/9780784401385. ISBN 978-0-7844-0138-5. doi:10.1016/j.jhydrol.2016.03.036.

Study of Correlations Between Multiculturalism and Economic Growth in the United States

November 21, 2019

 


Abstract: In our modern world, the concept of multiculturalism is not only prevalent but also encouraged. To have people from a diversity of backgrounds coexisting in one single area was an unfathomable concept nearly a century ago. Multiculturalism at its root refers to an amalgamation of different cultures and a single bounded territory; the inhabitants are protected by right to practice and enact on their views—regardless of whether they are in line with those of the majority. Everyone makes up a part of the whole. This paper discussed the effects of political and geographical isolation and cultural diversity in different eras and countries, as well as the details of successful heterogenous makeup of America together with the changes in the population of the United States and the impact of multiculturalism on the economy. The “ethnic minority” and mixed-race population is increasing every year in America, along with the increase in bilingual populations. Finally, this research states the reasons why diversity makes us smarter and more effective: racially diverse groups share information better, diversity enhances creativity, different points of views leads to broader thinking, having different points of views gives you new platforms and tactics of analyzing/solving a problem, and diversity encourages you to push the boundaries and reconsider your perception.

Keywords – Multiculturalism, cultural diversity, political and geographical aspects, and economic growth


Introduction: The United States, in particular, is a paradigm of a multicultural nation. Home to millions of immigrants, the US serves as a beacon of potential. Since the second half of the twentieth century, multiculturalism has quickly risen among various nations. Naturally, debates have also arisen regarding the productivity of such a concept; some believe there are various negatives to the rise of multiculturalism. But, research has revealed that diversity and co-existence can actually give rise to many positive events within a nation. According to Vincent Parillo, the diverse, heterogeneous makeup of the US is steadfast and integral to the nation. As a nation’s strength lies in its citizens and inhabitants, the US serves as a model for the true power of the people. The diversity of the US constitutes a large part of the American identity; from inception to modern times immigrants have contributed largely to the country’s evolution.

Some counter that diversity is a product of economic development rather than a contributor, that multicultural populations are attracted to certain locations because of affluence or gained economic success. An important new study by economists Quamrul Ashraf of Williams College and Oded Galor of Brown University, "Cultural Diversity, Geographical Isolation and the Origin of the Wealth of Nations," was recently released by the National Bureau of Economic Research. The paper carefully follows the role of geographic isolation, proximity, and cultural exchange in regard to economic development—spanning from pre-industrial times to the modern era. The study shows that "the interplay between cultural assimilation and cultural diffusion have played a significant role in giving rise to differential patterns of economic development across the globe." Diversity in fact gives way to economic growth whereas homogeneity enacts the opposite effect.

During the formative years of the United States’ industrialization, immigrants contributed greatly to the workforce. They helped create transportation systems, cities, and labor unions. Similarly, immigrants now also strengthen American economy. The United States is influential on the world stage due to the immigrants who have devoted themselves to advancement and the potential to be greater. They have brought billions of dollars with them — boosting the nation’s economy via business, consumerism, and labor.


References

[1] Clayton-Pedersen and Musil, 2008
[2]https://www.psychologytoday.com/us/blog/life-bilingual/201809/the-amazing-rise-bilingualism-in-the-united-states
[3] “Prosperity 2050.” Center for American Progress, 2011
[4] “Current Population Survey, 1968 through 2015”, Annual Social and Economic Supplements, U.S. Census Bureau, 2015
[5]“Multiculturalism: America's Competitive Advantage.” The Atlantic, Morgan Stanley Smith Barney LLC, 2016, www.theatlantic.com/sponsored/morgan-stanley-wealth-management-2016/multiculturalism-americas-competitive-advantage/1007/.
[6] https://www.nielsen.com/wp-content/uploads/sites/3/2019/04/the-multicultural-edge-rising-super-consumers-march-2015.pdf

Neuroprotection in Temperature and Oxygen Stressed Turtles

October 17, 2019

AbstractThis study is designed to detect the expression levels of heat shock protein 72 in the forebrain, midbrain, hindbrain, and ventricles of T. scripta, when subjected to anoxia and warm and cold temperatures for various periods of time. Previous studies have shown that HSP72 is induced early in anoxia, increasing for 8 hours but then falling to normoxic levels by 12 hours of anoxia showing that HSP72 may play a key role in the initial transition to the anoxic state (Milton and Prentice 2007).  This study examined the brain in sections, rather than the previous whole brain.

Keywords – Neuroprotection, temperature, oxygen stress, turtles, and Trachemys scripta


Introduction: The freshwater turtle, Trachemys scripta, has a unique ability to survive without oxygen for prolonged periods of time.  Unlike a vast majority of vertebrates that die after a few minutes of being deprived of molecular oxygen (anoxia), anoxia- tolerant vertebrates can survive from hours to weeks (Stecyk et al., 2007).  Anoxia followed by reoxygenation produces a rapid transient increase in reactive oxygen species (ROS) that destroys cells and its contents (Hashimoto et al. 2003). The mammalian brain is susceptible to ROS; however T. scripta may employ protective mechanisms to survive anoxia, thus preventing ROS damage.  Not only is brain function protected, but heart function is, too. One protective mechanism is the over expression of heat shock proteins (HSPs).  HSPs are overexpressed when cells are stressed, acting as a molecular chaperone. The brains and hearts of T. scripta were exposed to anoxia at 21°C, normoxia at 5°C, and anoxia at 5°C, with normoxia at 21°C as the control group. Exposure times ranged from 1.5 hours to 2 weeks. Each sample, weighing at least 200mg, was homogenized and the proteins were extracted.  Protein assays were performed on the extracts to determine the respective concentrations. Western blots were done to detect the presence of heat shock protein 72. Results are expressed as ±SD.


References

[1] Hashimoto, T., Yonetani, M., Nakamura, H. 2003. Selective brain hypothermia protects against hypoxic- ischemic injury in newborn rats by reducing hydroxyl radical production. Kobe J. Med. Sci. 49(4), 83-91. 
[2] Milton, S.L., Prentice, H.M. 2007. Beyond anoxia: The physiology of the metabolic downregulation and recovery in the anoxia- tolerant turtle.  Comp. Biochem. Physiol. A 147, 277- 290.
Stecyk, J.A.W., Stensløkken, K.-O., Nilsson, G.E., Farrell, A.P. 2007. 
[3] Adenosine does not save the heart of anoxia- tolerant vertebrates 
during prolonged oxygen deprivation. Comp. Biochem. Physiol. A  
147, 961- 973.

 

Advancements in the Structural Resolution of Bovine Thyroglobulin

August 30, 2019

Abstract – Thyroglobulin is a protein located in the thyroid and controls hormone production. These hormones work to modulate behavior, central nervous system function, and energy metabolism in vertebrates (Holzer et al., 2016). In addition, it is a dimeric glycoprotein with a molecular mass of 660 kDa. Specifically, bovine thyroglobulin is heavily decorated with alpha-gal and can be used to diagnose the red meat allergy (Apostolovic et al., 2017). For these reasons, the structure of bovine thyroglobulin is crucial to find and can lead to new information about the relationship between alpha-gal and the IgE antibodies.
 Keywords – bovine thyroglobulin, alpha-gal, IgE antibodies


Introduction: Alpha-gal, an oligosaccharide, is a major blood group substance in mammals such as cattle and pigs. Studies strongly suggest that bites from the Lone Star Tick Amblyomma americanum infect the human host with the carbohydrate alpha-gal (Commins & Platts-Mills, 2013). After some time, when beef or another red meat is consumed, an immune response is initiated by the IgE antibodies, that results in an immediate allergic reaction characterized by symptoms of anaphylaxis (Sim et al., 2017). Currently, the structure of bovine thyroglobulin is unresolved. The aim of this research was to determine the molecular structure of bovine thyroglobulin using Macromolecular crystallography (MX) and Small Angle X-ray Scattering (SAXS). With MX, the aim was to test whether lysozyme is a nucleation inducing reagent of thyroglobulin, and with SAXS, the aims were to obtain a low-resolution image of the structure of bovine thyroglobulin and discover the bead model of bovine thyroglobulin. It was hypothesized that lysozyme will aid in the crystallization in thyroglobulin and that the bead model will be a complex globular structure containing alpha and beta helices, factoring inflexibility. 


References

  1. Apostolovic, D., Krstic, M., Mihailovic, J., Starkhammar, M., Velickovic, T. C., Hamsten, C., & van Hage, M. (2017). Peptidomics of an in vitro digested α-Gal carrying protein revealed IgE-reactive peptides. Scientific reports, 7(1), 5201. 

  2. Benkert, P., Biasini, M., Schwede, T. Toward the estimation of the absolute quality of individual protein structure models. Bioinformatics 27, 343-350 (2011). 


  3. Bertoni, M., Kiefer, F., Biasini, M., Bordoli, L., Schwede, T. Modeling protein quaternary structure of homo- and hetero-oligomers beyond binary interactions by homology. Scientific Reports 7 (2017). 


  4. Biosis. (2013). PRIMUS (WINDOWS ONLY). Retrieved from 
http://www.bioisis.net/tutorial/4 
http://iramis.cea.fr/Phocea/Vie_des_labos/Ast/ast_sstechnique.php?id_ast=1065 


  5. Bruno Di Jeso, Peter Arvan; Thyroglobulin From Molecular and Cellular Biology to Clinical Endocrinology, Endocrine Reviews, Volume 37, Issue 1, 1 February 2016, Pages 2–36, https://doi.org/10.1210/er.2015-1090 


  6. Commins, S. P., & Platts-Mills, T. E. (2013). Delayed anaphylaxis to red meat in patients with IgE specific for galactose alpha-1,3-galactose (alpha-gal). Current Allergy And Asthma Reports, 13(1), 72-77. doi:10.1007/s11882-012-0315-y 


  7. Edelhoch, H., J. Biol. Chem., 235, 1326 (1960). 


  8. Franke, D., Petoukhov, M.V., Konarev, P.V., Panjkovich, A., Tuukkanen, A., Mertens, 
H.D.T., Kikhney, A.G., Hajizadeh, N.R., Franklin, J.M., Jeffries, C.M. and Svergun, D.I. (2017) ATSAS 2.8: a comprehensive data analysis suite for small-angle scattering from macromolecular solutions J. Appl. Cryst. 50, 1212-1225 


  9. Gentile, F., Salvatore, G., & Salvatore, G. (1995). Molecular heterogeneity of covalently-linked bovine thyroglobulin dimers. Rendiconti Lincei, 6(2), 165.
Holzer, G., Lorin, T., Gillet, B., Hughes, S., Tohme, M., Laudet, V., & ... Deleage, G. (n.d). Thyroglobulin Represents a Novel Molecular Architecture of Vertebrates. Journal Of Biological Chemistry, 291(32), 16553-+. 


  10. Jakoby, W. B., Labaw, L., Edelhoch, H., Pastan, I., & Rall, J. E. (1966). Thyroglobulin: Evidence for Crystallization and Association. Science, 153(3744), 1671-1672. doi:10.1126/science.153.3744.1671 


  11. Leszczyszyn, O., Hydrodynamic Radius. (2018, December 11). Retrieved from
https://www.materials-talks.com/blog/2012/11/15/size-matters-rh-versus-rg/ 


 

Study on the Model to Predict the Spread of Drugs

July 11, 2019

Abstract: This paper addresses the problem of addiction in society. We focus on the United States specifically and limit our model to the following drugs:  nicotine, marijuana, prescription drugs, alcohol. The problem is to create a model that can accurately predict the spread of nicotine. This is followed by the creation of a model that can be applied to different drugs with inputs depending on an individual's income, education level, and race.

From the information above, we conclude that the most dangerous substances are: Tobacco, Opioid-based Unprescribed Painkillers, and Alcohol, while the least dangerous is marijuana. This is deduced from a combination of its health impacts, explicit and implicit costs of using. While marijuana is the least dangerous according to our model, it still possesses significant dangers to productivity, safety, and cognitive function. 

Our models functioned on several assumptions. We assumed that nationwide trends are directly applicable to all individual populations, which may not be the case. A study can be conducted to provide evidence of drug usage in specific areas across the country in order to pinpoint our data. The spread of nicotine abuse as well as the abuse of other drugs is on the rise throughout the country. This is especially alarming in the younger generation as model 2 suggests. The amount of high school seniors predicted to be using these substances indicates a societal issue that needs to be addressed in order to prevent damage to today's youth and lower these numbers for later generations.  The impact of these drugs, while varied between them, signifies how abuse can quickly lead to poverty and strain on the economy that must support them.

Keywords: Addictive substances, Opioid-based Unprescribed Painkillers, Computer Modeling


Introduction:  The model developed for part 1 details how the predicted growth of nicotine usage is anticipated to level off in the future as it currently is following a pattern of logistic growth. We use information provided to graph the function from 2011 to 2018. According to the data from the table, we create a logistic function (Figure 2) y = (15.1173)/(1+1111.39e^(-2.15689x)) by calculator. In order to minimize the number for y, we use 1 for 2011, 2 for 2012, 3 for 2013, and so on. Then, we plug 29 as the corresponding number for 2029 to x to find the percentage of high school students who vape for the next 10 years, which is 15.1173 percent. This number may not be correct because there is a rising number of events created dedicate to educate students to stop/prevent them from vaping.

An alteration in this model that could more accurately depict the expansion of vaping could include increased education about its dangers which would slow its growth. As seen in Figure 1, the model closely follows the data found on the high school vaping data provided in the question. The data would follow a line of best fit calculated with a logistic regression formula because the percent of users must reach a limit as it cannot exceed 100%. Figure 3 demonstrates the age demographics of the United States which we use to determine how the percentage of growth translates into sheer numbers in terms of age. For example, if 15% of individuals use nicotine for a given year, we can multiply this by the number of individuals in their age groups and get how many people use nicotine. 


References

  1. Marijuana Street Prices: How Much Should You Pay For Weed? (n.d.). Retrieved from https://addictionresource.com/drugs/marijuana/marijuana-street-prices/
  2. Morbidity and Mortality Weekly Report (MMWR). (2017, June 21). Retrieved from https://www.cdc.gov/mmwr/volumes/65/ss/ss6511a1.htm
  3. Motor Vehicle Safety. (2017, June 16). Retrieved from https://www.cdc.gov/motorvehiclesafety/impaired _driving/impaired-drv_factsheet.html
  4. National Institute on Drug Abuse. (n.d.). What is the scope of tobacco use and its cost to society? Retrieved from https://www.drugabuse.gov/publications/research-reports/tobacco- nicotine-e-cigarettes/what-scope-tobacco-use-its-cost-to-society
  5. FDA. (2018, June). Youth Tobacco Use in the U.S. Retrieved March 2, 2019
  6. Race/Ethnicity and Gender Differences in Drug Use and Abuse. Retrieved March 2, 2019, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2377408/

Analysis of Substance Abuse and Impacts Using Mathematical and Computational Modeling

May 24, 2019
John Luc and Duong Dai Dinh

Abstract: In 2003, Hon Lik, a Chinese pharmacist and inventor, created what would become the first commercially successful e-cigarette. Hon Lik’s invention quickly swept across the continent, gaining popularity and ultimately being introduced to the European market in April 2006. From Europe, it was a quick hop across the pond to the United States. This new, “safe” form of smoking quickly spread throughout the states. This wave quickly formed a new, highly profitable industry. With such a rapid rise to popularity, governing bodies such as the Food and Drug Administration and Federal Trade Commission have not yet regulated this industry effectively. Although, steps are being taken to do so, the damage has been done. The vaping industry has successfully targeted the youth population, creating high rates of teen and adolescent addiction. Similar to the vaping epidemic plaguing the United States, in 2011, there were approximately 20.6 million people in the United States over the age of 12 with an addiction ranging from alcohol to inhalants and hallucinogens. This number has only grown in recent years. This is why it is paramount to be able to model and predict which communities are most at risk and assess the true cost of addiction. Through complex mathematical modelling and analysis, the ability to assess the prevalence and impact of alcohol, nicotine, marijuana, and nonprescription drugs is available today.

Keywords: Substance abuse, nonfinancial and financial impacts, alcohol, marijuana, and tobacco.


Introduction: While the United States is currently experiencing an opioid epidemic with over 72,000 people dying each year from overdoses, there have also been increases in the use of other drugs such as nicotine, marijuana, and alcohol throughout the country. This is especially concerning due to an increasing proportion of the demographic is middle schoolers and high schoolers. Moreover, this is the first time in the history of the United States that the leading cause of death is opioid overdose (it surpassed vehicle crashes). It is important to understand the factors that lead individuals to use these substances so that the spread can be effectively combatted.

This section addresses the problem of addiction in society. We focus on the United States specifically and limit our model to the following drugs:  nicotine, marijuana, prescription drugs, alcohol.

The problem is to create a model that can accurately predict the spread of nicotine. This is followed by the creation of a model that can be applied to different drugs with inputs depending on an individual's income, education level, and race. These factors were chosen because we determined them to be the most significant factors in terms of influencing people to do drugs. We would have also liked to include calculations involving environmental factors such as family use and ease of access but due to time and calculating restraints, we omitted these variables.

Because of the advancement in technology, people try to find an alternative for smoking cigarettes. They found this alternative in vaping. As a result, cigarette sales are reaching an all-time low (as shown in the graph below). Overall, this indicates that the growth of vaping will more than replace the decreasing usage of cigarettes.

Our models functioned on several assumptions. We assumed that nationwide trends are directly applicable to all individual populations, which may not be the case. A study can be conducted to provide evidence of drug usage in specific areas across the country in order to pinpoint our data.

The spread of nicotine abuse as well as the abuse of other drugs is on the rise throughout the country. This is especially alarming in the younger generation as model 2 suggests. The amount of high school seniors predicted to be using these substances indicates a societal issue that needs to be addressed in order to prevent damage to today's youth and lower these numbers for later generations.  The impact of these drugs, while varied between them, signifies how abuse can quickly lead to poverty and strain on the economy that must support them.


References

  1. Race/Ethnicity and Gender Differences in Drug Use and Abuse. Retrieved March 2, 2019, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2377408/
  2. FDA. (2018, June). Youth Tobacco Use in the U.S. Retrieved March 2, 2019
  3. Marijuana Street Prices: How Much Should You Pay For Weed? (n.d.). Retrieved from https://addictionresource.com/drugs/marijuana/marijuana-street-prices/
  4. Morbidity and Mortality Weekly Report (MMWR). (2017, June 21). Retrieved from https://www.cdc.gov/mmwr/volumes/65/ss/ss6511a1.htm
  5. Motor Vehicle Safety. (2017, June 16). Retrieved from https://www.cdc.gov/motorvehiclesafety/impaired _driving/impaired-drv_factsheet.html
  6. National Institute on Drug Abuse. (n.d.). What is the scope of tobacco use and its cost to society? Retrieved from https://www.drugabuse.gov/publications/research-reports/tobacco- nicotine-e-cigarettes/what-scope-tobacco-use-its-cost-to-society
  7. The Price Paid for Automobile Accidents and Injuries. (n.d.). Retrieved from http://www.tavss.com/library/va-nc-lawyer-economic-and-comprehensive-auto-accident-costs.cfm

Assessment of Lake Water Quality and Quantity Using Satellite Remote Sensing

May 21, 2019

Abstract: Assessment of both water quality and quantity pose a great challenge to those studying the effects of anthropogenic activities on bodies of water. Eutrophication created by the increased concentration of nutrients including nitrates and phosphates has been known to contribute to the development of both toxic algal blooms, which serve as limiting factors in the ecosystems of the water, rendering it useless for consumption.1,2 Another common development is the buildup of suspended sediments (SS/TSS), contributing to the anoxic conditions characterizing environmental hypoxia.3 Because current methods for the assessment of the presence of such issues rely upon tedious and costly methods, a timely and cost-efficient method is desirable for application to the practice.4  This research relies upon analysis of the inherent optical properties of chlorophyll and sedimentation present within the bodies of water in question, achieved through analysis of the reflectance values of the red and blue bands from Landsat satellite images of five bodies of water. 5 The analysis, performed using Geographic Information System ArcMap, allows for determination of the values that attest to changes in surface area, turbidity, and eutrophication. The trends in the data hold consistency with the natural occurrences surrounding the bodies of water associated with the three parameters outlined above, supporting usage of remote sensing for qualitative and quantitative analysis of water.


Introduction: Lakes are popular hosts of environmental problems as a result of anthropogenic activities. For the majority of these lakes, causes of these problems often involve sediment loading or nutrient enrichment, also known as eutrophication.1 Eutrophication is also the cause of algal bloom in water. Both eutrophication and algal bloom are a natural phenomenon, but human activities may accelerate them, which can cause harm in terrestrial ecosystems. In fact, eutrophication and harmful algal blooms are the leading source of impairment of water quality in many lakes around the world.2 Specifically, human-derived sources due to industrialization, urbanization, or agricultural wastes due to the amount of excess nutrient that these sources then load onto their local freshwater bodies. Anthropogenic activities change the amount of Nitrogen and Phosphate - both of which are nutrients essential to algal growth - present in water. For instance, sewage, agricultural, and household discharges often contain large quantities of P minerals.3 Harmful algal blooms may cause anoxic conditions, which is the depletion of oxygen in water. Such conditions are especially dominated by cyanobacteria, which is a blue alga that produces cyanotoxins and makes lake water toxic, causing wildlife deaths and seafood poisoning in humans.4 

Traditional methods to measure water quality parameters like algal blooms involves field surveying techniques while measuring suspended solids involves the filtration technique.Unlike the other methods, studies show that satellite remote sensing is more cost-effective, economic, and ideal for acquiring spatial data from lakes with large surface areas7 like the ones that will be investigated. For the purpose of this study, there are two other water quality parameters measured, besides the quantity factor with surface area. One is the chlorophyll, which will indicate the severity of algal bloom, and the other is total suspended solids, as a measure of water turbidity. The Inherent Optical Property (IOP) - which refers to absorption and scattering properties of underwater contents - of chlorophyll and suspended solids were used to determine algal and sediment presence. And because of the optical properties of chlorophyll and suspended solids in water, one can use commercially available optical instruments to measure their respective concentrations.7 This can be applied to satellite data because of the way in which satellite sensors collects the intensity of light reflected. And since satellites measure reflectance values in different intervals of the electromagnetic spectrum, the focus will be placed on reflectance values on certain intervals - also known as band values - in this paper. In summary, a lower reflectance value of blue band correlates to a higher concentration of sediments. As a lower reflectance value of the red band would suggest a higher presence of chlorophyll.

In this study, two lakes across the world are analyzed, and each is chosen for the significance of their impact on local livelihood. The five lakes investigated are Lake Kasumigaura of Japan and Lake Maggiore of Europe.


References

[1] Smith, V., Tilman, G., & Nekola, J. (1999). Eutrophication: Impacts of excess nutrient inputs on freshwater, marine, and terrestrial ecosystems. ​Environmental Pollution,100(​ 1-3), 179-196. doi:10.1016/s0269-7491(99)00091-3 12 

[2] Chislock, M.F.; Doster, E.; Zitomer, R.A.; Wilson, A.E. (2013)."Eutrophication: Causes, Consequences, and Controls in Aquatic Ecosystems". Nature Education Knowledge. 4 (4): 10. Retrieved 10 March 2018.         

[3] Anderson, D. M., Glibert, P. M., & Burkholder, J. M. (2002). “Harmful algal blooms and eutrophication: Nutrient sources, composition, and consequences.” Estuaries,25(4), 704-726. doi:10.1007/bf02804901            

How Racism Kills: Poussey Washington’s Death in Orange is the New Black

May 02, 2019

Abstract: Racism is one of the important social problems in the United States that must be addressed. Racism and its consequences are well highlighted in popular culture, including movies and shows, to further emphasize the effect of racism. This paper will discuss institutional racism and how it is demonstrated in the context of the judicial and prison system through an analysis of a show called Orange is the New Black. From analyzing one of the characters, Poussey, and her death, this research will discuss different ways racism could be manifested and the different forms of racism in an institution. This paper will also discuss the extreme outcome of racism in our society – death.  


Introduction: Racism, quite literally, kills. In the United States, racism is ubiquitous and stems from the legacy of race-based slavery. One area where racism is particularly salient is in the criminal justice system. Despite the constitutional promise of equal protection under the law, racist policies such as the War on Drugs have led to laws that disproportionately affect Black people such as severe penalties for drug use and possession, mandatory minimums, life sentences, and three strikes laws [1]. These policies are examples of institutional racism. Institutional racism is racism embedded in political and social structures, resulting in disadvantages for minorities based on socially assigned race [2]. On the other hand, personally mediated racism describes the prejudice and discrimination that occurs between people of different races [2]. Importantly, personally mediated racism upholds the social norms that prevent institutional racism from being eradicated. In the Netflix series Orange is the New Black, the death of a Poussey Washington, a young Black female inmate, demonstrates how personally mediated and institutional racism work together to allow her death to happen while simultaneously protecting the white correctional officers from being held responsible.


 

References

  1. Jerram, Leif. “Space: A Useless Historical Category for Historical Analysis.” History and Theory 52 (2013) p. 400-419.
  2.  Sewell in R. Percy, ‘Picket Lines and Parades: Labour and Urban Space in Early Twentieth-Century London and Chicago’, Urban History, 41/4 (2013), p. 457.
  3. Percy, Ruth. “Picket Lines and Parades: Labour and Urban Space in Early Twentieth-Century London and Chicago.” Urban History 41 (2014): 456-477.
  4.  Lefebvre, Henri. “Space: Social Product and Use Value.” In State, Space, World: Selected Essays, edited by N. Brenner and S. Elden, translated by J. W. Freiberg, 185-195. Minneapolis: University of Minnesota Press, 2009.
  5. Herod, Andrew. “From a Geography of Labor to a Labor Geography: Labor’s Spatial Fix and the Geography of Capitalism.” Antipode 29 (1997): 1-31.
  6. Remus, Emily A. Remus, Tippling Ladies and the Making of Consumer Culture: Gender and Public Space in Fin-de-Siècle Chicago (2014).
  7. R. Kelley, “‘We are not what we seem’: Rethinking black working-class opposition in the Jim Crow South” (1993) p. 99.
  8. Kruse, Kevin M. “The Politics of Race and Public Space: Desegregation, Privatization, and the Tax Revolt in America.” Journal of Urban History 31 (2005): 610-633.
  9. Butler, J. 'Bodies in Alliance and the Politics of the Street' http://eipcp.net/transversal/1011/butler/en.

     

A New Ring Theory Based Algorithm and Stopping Criterion for Image Segmentation

April 20, 2019

Abstract: Ring theory is most widely known as a branch of pure mathematics under the field of abstract algebra. Some of the uses of Ring Theory in the modern world involve cryptography, computer vision, and image segmentation. As of now, finite cyclic rings have been incorporated into performing image segmentations for the Mean Shift Iterative Algorithm. This paper analyzes the Mean Shift Iterative Algorithm and devises an improved algorithm and stopping criterion using finite cyclic rings and matrices in Ring Theory that perform high-quality image segmentations for images that can be used in computer vision and possibly the segmentation(s) of grayscale (d = 1), colored (d = 3), and multispectral (d ≥ 3) images.

Keywords: ring theory, Mean Shift, and Iterative Algorithm


Introduction: Based on the concepts of Group Theory and the field of abstract algebra, Ring Theory is a concept where a “ring” is a set of elements with two binary factors: addition and multiplication. To subtract within a ring would essentially mean to add an element to its additive inverse. Likewise, to divide would mean to multiply an element by its multiplicative inverse. A ring also satisfies the following axioms:                                    

  • The ring, under addition, is an abelian group.
  • The multiplication operation is associative, and therefore closed.
  • All operations satisfy the distributive law of multiplication over addition.                                       

An example of a ring includes the set of real polynomials. Within this ring, you can freely add, subtract, and multiply one polynomial, essentially an element within the ring, to get another polynomial - another element. The additive identity is presented as zero. Since zero is a constant polynomial, it is also considered to be an element in the ring of real polynomials. The multiplicative identity is presented as one. Since multiplication is always commutative among all polynomials, the ring of real polynomials is deduced as a commutative ring with an identity element.

Some rings are finite, meaning that the amount and type of elements may be limited. Some rings may not have the additive identity zero or the multiplicative identity one. Upon adding, subtracting, or multiplying two even numbers, the result is always another even number. The value of 1 does not fall within the set of even numbers. Therefore, the set of even integers does not have the multiplicative identity of one - and is only a commutative ring. Image segmentation is the practice of breaking a picture up into pixels and assigning each pixel a value based on a given class. The purpose of image segmentation is to partition images into more meaningful, easy to examine, sections. The segmentation of images is primarily applied to image editing/compression, as well as the recognition of certain objects or another relevant aspects of a taken image. The Mean Shift Iterative Algorithm uses finite cyclic rings to detect specific features of an image (i.e. eyes of a face, abnormalities in an MRI scan of a heart, tumors in a brain) and the probability of there being a specific part of an image. A finite cyclic ring is any ring where the elements derive from a single element (hence, they are limited in regards to what elements may be present within the ring and, when brought back within range of said ring, the elements repeat in a cycle).

A primary factor in determining the stopping criteria for a segmentation algorithm is the entropy, or number of consistent microscopic configurations, of an image. The number of consistent microscopic configurations is significant to constructing a stopping criterion for an algorithm for image segmentation because while images may interchangeably be weakly and strongly equivalents, images that are strongly equivalent are not weakly equivalent. Images are defined in a finite cyclic ring when the Mean Shift Iterative Algorithm is used for image segmentation. However, an established stopping criterion for the Mean Shift Iterative Algorithm has not been formulated thus far; instead, the entropy formula has been in place as the stopping criterion for Mean Shift for stability purposes.


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Study of Correlations Between Quality of Education and the Economic Growth of a Developing Country

April 07, 2019

Abstract: The belief that increasing years of education guarantees economic success has yet to be proven true even if more schooling is associated with a higher income. Attaining an education is not the only factor that contributes to individual success because there are other critical factors, such as one’s cognitive skills, influence of families and peers, and proper health and nutrition. The quality of educational programs and the discrepancy in workers' skills and income levels become significantly noticeable when people fully integrate into the labor force.

Based on the current research on "quality education" and its effect on the economic growth of a country, this paper shows how the education reform is necessary. Instead of solely focusing on education attainment, more policies to improve education quality in developing countries is imperative. The quality of education should be measured by cognitive skills which have robust correlations with the GDP per capita growth as well as individual earning rates.  Stronger accountability systems, local autonomy of schools, and incorporating choice and competition in schools are all effective policies that can improve the overall incentives in schools to improve the quality of education in developing countries.


Introduction: The belief that increasing years of education guarantees economic success has yet to be proven true even if more schooling is associated with a higher income [1]. Attaining an education is not the only factor that contributes to individual success because there are other critical factors, such as one’s cognitive skills, influence of families and peers, and proper health and nutrition. The quality of educational programs and the discrepancy in workers' skills and income levels become significantly noticeable when people fully integrate into the labor force [2].

UNESCO's “Education for All” initiative and the “Millennium Development Goals” have focused on raising the population’s schooling levels to increase education attainment[1]. However, this  approach is flawed for mainly four reasons. First, many countries in the past that have expanded schooling opportunities have not seen improvements in their economy. Second, there are many differences between developed and developing countries, aside from schooling levels within their respective population.  In addition, some developing countries may not have established, effective educational policies and programs. Lastly, even if effective programs and policies are in place, the approach in implementing these programs may be ineffective, and therefore may not result in the anticipated outcomes. [1]  Research on the economic impact of schools tends to ignore these differences that exist between developing and developed countries, which can distort education and economic outcomes.

Therefore, rather than focusing on educational attainment and increased years of schooling, assessment of success should measure knowledge or cognitive skills especially in an international context [2].These quality differences are crucial and important in recognizing the reasons for discrepancies in education, skills, and individual earnings.

Educational quality is a driving factor in the individual earnings and overall economic growth of a country. [1] Currently, there is a lack of effective policies that can substantially increase cognitive skills, but evidence suggests that changing school policies and incentives can have a positive impact on the economic outcome. Overall, educational quality, which has significant effects on economic growth, is much worse in developing countries and cannot be solved with increase years of schooling alone. To effectively solve this problem, major institutional changes would be required.

Based on the current research on "quality education" and its effect on the economic growth of a country, education reform is necessary. Instead of solely focusing on education attainment, more policies to improve education quality in developing countries is imperative. The quality of education should be measured by cognitive skills which have robust correlations with the GDP per capita growth as well as individual earning rates.  Stronger accountability systems, local autonomy of schools, and incorporating choice and competition in schools are all effective policies that can improve the overall incentives in schools to improve the quality of education in developing countries.


References

[1] https://www.brookings.edu/articles/unequal-opportunity-race-and-education/

[2] https://inequality.stanford.edu/sites/default/files/Pathways_SOTU_2017_education.pdf

[3] https://www.nap.edu/read/10256/chapter/6#71

[4] https://news.stanford.edu/2017/06/16/report-finds-significant-racial-ethnic-disparities/

[5] https://www.brookings.edu/research/race-gaps-in-sat-scores-highlight-inequality-and-hinder-upward-mobility/

[6] https://www.brookings.edu/research/the-importance-of-high-quality-general-education-for-students-in-special-education/


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