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Session 10A-10B 17:30-19:00 // day one

10A - Behavioural Science and Systems University of Warwick and Baruch College, City University of New York

This research studies to what extent Singapore's casino gambling industry has promoted economic growth. I consider the industry's contribution from the opening of the first casino in February 2010 to 2017. Without the timely introduction of casino gambling, travel and tourism in Singapore may have stagnated and it would not be the growing sector that it is today, totally accounting for 8.8% of employment and 10.2% of GDP in 2017 according to the World Travel and Tourism Council. Despite the commercial success of casinos in some other countries, there are many negative social consequences. The Singapore blend is very unique in that it combines resorts with casinos – in what are called Integrated Resorts with a focus on tourism while reducing the negative ramifications on the local population. In my research, I aim to evaluate the costs and benefits of casino gambling from an economic standpoint and how the fusion with non-gambling activities makes Singapore special. By considering the integrated resorts in Singapore as a case study, I aim to apply my findings to other prospective nations. Countries like Japan who have recently lifted their long- standing ban would greatly benefit from understanding Singapore's experience.

This research follows a Biophysics approach to engineer a novel type of neuromorphic computing in living bacteria, achieved via the development of a new genetic device that acts as a non-linear transcriptional logic gate able to adjust its gene expression based on its chemical history. This results in the foundation of a new type of artificial intelligence that is not based nor dependent on computer software but on the collective capacity of genetically modified bacterial ecosystems. This is done by engineering gene circuits that function as logic gates, which allow the bacteria to store analog information and to communicate through synthetic synapses. The investigation approach uses iterative cycles of computational Biophysics design, synthetic Biology construction and high-throughput characterisation to adjust the system so it can perform as a general-purpose modular memory machine. The inter-device communication allows for the design of an advanced cognitive computing hardware made of living cells able to be programmed through reinforcement learning. The ability of the microorganisms to behave as functional artificial neural networks is proven by the development of expertise in the game of Tic-Tac-Toe through self-play and reinforcement learning. The outcome will allow for the development of a precise experimental protocol for culturing the bacteria and for exploring their cognitive limits such as their ability to learn, attention and memory retention under different conditions. Furthermore, the experimental model can be re-designed to accommodate for further AI-specific implementations such as mastering more complex, well-known games (Hexapawn, AtariGO) or pattern generation and discrimination.

We have previously reported syntheses of a number of pyrroles from nitrodienes, based on an approach developed by Cadogan and Sundberg towards synthesis of indoles and carbazoles. Our work involves the use of a Molybdenum catalyst which considerably improves the yield of the cyclization reaction. Our approach is novel in that we showed pyrroles can be synthesized, for the first time, from nitrodienes. The aim of our present work is to investigate if our methodology can be used to make other important multisubstituted pyrroles of medicinal importance.

10B - Intersections of Conflict and Trade University of Warwick and Baruch College, City University of New York

Hong Kong does not sell land but instead only offers lease contracts, while creating artificial land scarcity, yet the country ranks number one on the economic freedom index. My research is questioning how such alternative housing and land regulations affect economic freedom and indirectly foreign direct investment. Is this model an exemplary solution to improve economic freedom in densely populated areas? Alternatively, is the regulation perhaps not fully understood and not taken into account when creating the economic freedom index? Or is the local regulation rather an intended tool to improve the ranking and attract investments? To find out, the aim is to research the policies' effect on public perception of the housing market, the degree to which financial models in the real estate market take these limitations into account, and the effect on foreign direct investments. These three research focuses will clarify the policies' effect on ordinary citizens and incentives for policymakers and investors.

To analyse the situation I'm taking a journalistic approach in reaching out to policymakers, real estate experts and investors to understand their different perspectives and relate them to the mathematic models which are applied in the financial sector. This research is made possible with the Warwick, Hong Kong exchange programme.

The amount of available cryptocurrency news data is constantly growing, posing the question of whether this can be exploited to create profitable automated cryptocurrency trading systems. This research explores the viability of using deep learning models to forecast changes in cryptocurrency prices using a vast data set of news articles and social media posts. A robust sentiment analysis model is used to extract sentiment scores, converting the news data into a quantitative data set. Three different models are built with corresponding trading strategies to test their profitability using a large 7-month test period of unseen data. All three models perform very well, especially during volatile periods, with the best model achieving an overall return on trades of 287.9%, as well as 91.3% profitable trades during the test period. One of the key findings is that models incorporating news data greatly outperform those that do not, suggesting that the Efficient Markets Hypothesis may not be applicable to cryptocurrency trading. Additionally, incorporating technical analysis indicators into the data set seems to make a small impact on the profitability of the models, bringing into question their widespread popularity.

Historians have offered different interpretations of the origins of the Pacific War. Interventionists have collided with revisionists over the ultimate cause of the Japanese attack on Pearl Harbor. According to the Interventionists, the Pacific War started with a handful of Japanese militarists displaying such extreme aggression that the United States had to resist. Revisionists assert that the Axis powers did not endanger American security; Roosevelt knew that his policies would result in war.

There were numerous milestones that led to the Pacific War. My research provides an in-depth analysis of two: first, the freezing of Japanese assets and placing an oil embargo on Japan in August 1941 and, second, the US final requirements to Japan to reopen trade in November 1941. These two milestones are important because they highlight two pivotal elements for Japan - its dependence on foreign oil and its historic interest in China.

The first part of the research analyzes the oil embargo, while the second part of the research reviews the US requirements to Japan to restart trade. Both parts start with a factual overview, referencing sources by such historians as Basil Rausch, Wayne S. Cole, and Minoru Nomura. Next, the oil embargo and the ultimate demands are presented through the lenses of revisionists (Harry E. Barnes and William H. Chamberlain) and interventionists (Basil Rauch, Forrest Davis, and Herbert Feis). Finally, it is explained why the revisionist perspective is more persuasive: the US provoked Japan for the US to enter WWII through the "Asiatic Back Door.�

Following the 2008 global financial crisis, investors have increasingly turned to emerging market investments to seek higher returns. However, lack of liquidity in such economies has been a source of barrier to foreign investment. In the next few years, 70% of global economic growth is expected to come from these emerging economies (IMF, 2019). Therefore, my presentation will examine how liquidity can be improved in these countries and the impact this will have on the global economy.

This work intends to develop understanding of liquidity in emerging markets, through comparative research of India, Colombia, South Africa and Brazil, to identify – (1) the causes of illiquidity in emerging economies. (2) the problems faced by foreign investors and (3) how improved financial infrastructure in these countries will improve future liquidity. By conducting this research, I hope to understand what companies and investors can do to improve liquidity.

Emerging markets provide investors with high risk and high returns, an alternative to the much lower interest rates found in developed countries. Accessing these markets can be tricky for investors due the lack of liquidity and this has had a large impact on foreign investment. However, as these countries grow and their financial infrastructure (i.e. Stock Market) develops, their markets will become increasingly accessible to foreigners.