Increasingly, student entrepreneurial ventures begin as emotional connections, artistic experiences, and expectations for delivering on research teams. This paper explores student team progress and responses to roadblocks while helping a maturing Silicon Valley start-up IMVU consider the role of avatars, creative expression and social interaction in the virtual world. Our goal was to seek a deep understanding of why users choose to spend their time and money to take part in the online community IMVU all the while creating a productive entrepreneurial team atmosphere. This paper explores the unique dynamics of the research team during the evolving investigation and delivery phase, all the while simultaneously examining the underlying emotions and motives of participants in one virtual community. We start with the belief that every new research team is like a start-up company and there are commonalities or differences between the student academic research environment and the company's organizational culture. Our collaborative research team includes members from areas of engineering, design, psychology, and communication. In this paper, we intend to correlate the factors that make the design team effective, utilize the findings to guide new student teams, and facilitate progress across the stages of the project. Two factors set the stage for insights on entrepreneuring: 1) evolving research team dynamics, and 2) the need-finding interactions with users both inside and outside the industry environment studied (IMVU). Surprising discoveries include a strong gender imbalance in the community as well as users reporting that online "was basically real life." A palette of stories abstractly parallels the student design team to the start-up they studied. Concepts include: self motivated, ambiguity readiness level, passion, and empathy. The team leader knowingly discussed using an open-process approach. Members noted a considerable lack of reluctance to prototype methods and team presentations; they also reported a deliberate lack of specific planning that they believe contributed to an entertaining and productive team ambiance. The full experiment offers stunning stories and compelling implications for creating effective design interventions in team-based engineering and design classes as well as for those pursuing the stories of compassion, empathy, and transformation in entrepreneuring.

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Pandemics and epidemics have plagued humanity throughout history. The modern world faced one such devastating disease in 2019 called Coronavirus. As the world is still trying to recover from Coronavirus, an epidemic that might not see its end anytime soon. This study focuses on analyzing and predicting the future  hospital admissions that arise due to Covid-19 .For this study, the choice of country is the United Kingdom. The data has been procured from reliable internet sources to carry out all necessary experiments. The data set contains daily hospitalisations due to Covid-19 in the United Kingdom. To carry out the time-series forecasting, the predictive model is built using a special Recurrent Neural Network, also known as Long Short-Term Memory (LSTM) . The final model was built using a Stacked LSTM to predict the number of hospitalisations due to Covid-19 that may arise in the United Kingdom for the next twenty days from the last day of the dataset used. The results of this study show a clear indication that a spike in the number of hospitalisations may arise in the upcoming days.