A vast set of methodologies exist for predicting and estimating future values from a time series dataset such as a stock market price data. Deep learning techniques such as Convolutional Neural Networks (CNN) and Long-short term memory (LSTM) neural networks have been applied to the stock price prediction problem. In this work, using the MSE (Mean Squared Error) as the performance measure, we compare the performance of LSTM to that of the CNN. Additionally, this work was quantitatively able to express the difference in performance between the LSTM and the CNN, this work was also able to give evidence to the fact that LSTMs in fact are better in predicting stock price data, given the constraints within the paper, compared to CNNs.

COVID-19 was a globalized pandemic and its impacts have affected most countries in a profound way. Not only were the healthcare systems thrown into chaos and lockdown have put many lives in pause but the economic impacts were strenuous as well. Although the economies of several countries were hurt similarly, the United States and China have a disparity between them. Prior to understanding the gaps between the economic states of these two countries, it is imperative to understand each of them in turn.

Cystic Fibrosis is the most common autosomal recessive disorder that affects Caucasians. It is caused by a mutation of the expression of the CF transmembrane conductance regulator (CFTR) gene, which has over 2,500 noted variants, spawning irregular chloride channels in mucus and sweat-producing cells. The disease causes damage to the respiratory system and GI tract until the organs fail to function by causing thick mucus to build up in the lungs and pancreas. As the chronic disease currently has no cure, people with this condition can generally live normal lives, as many tools and techniques can be used to manage this complex condition. However, this does not mean that patients live perfectly healthy lives, as they still experience symptoms such as shortness of breath and coughing. This review article summarises the pathology and pathomechanism of the disease, what it is on a genetic expression level, and emerging therapies.

Among evolutionary problems, eukaryogenesis is one of the most interesting, with many published theories proposing different evolutionary transition states in an effort to explain how it may have occurred in a way that aligns with current empirical evidence 1. Among the most detailed and well known theories is the Hydrogen Hypothesis, first published in 1998, updated in 2015 and in the meantime popularised in the public conscience in no small part by Nick Lane’s 2005 book Power, Sex, Suicide: Mitochondria and the meaning of life. While the Hydrogen Hypothesis played a significant part in popularising symbiogenetic theories for eukaryogenesis, it is not the only such theory out there.

"The Genetics of Races" unveils a future teeming with promise — a future where scientific advancements unlock doors to prevention, treatment, and discovery. It beckons society to embrace the great humanitarian benefits that lie within our grasp, while advocating for responsible and ethical practices that safeguard against misuse. As you reach the final pages of this intellectual odyssey, a sense of purpose will infuse your being. The author's voice will reverberate within you, urging you to face the future with courage and conviction.

Type 1 Diabetes (T1D) is an autoimmune disease that results from the destruction of insulin-producing beta cells in the Islets of Langerhans of the pancreas. This destruction is caused by T cells and leads to insulin deficiency (Chen et al.). Insulin regulates blood glucose levels by facilitating the uptake of blood sugar into cells, which the cells can then use for energy. Without insulin, sugar builds up in the bloodstream, leading to hyperglycemia (CDC). Two HLA genes involved in antigen presentation, DR3 and DR4-DQ8, as well as around 60 non-HLA genes, are associated with the development of T1D (DiMeglio et al.); HLA genes code for surface proteins that are used to identify body cells and foreign cells (Nordquist and Radia). Also, viral infections, including enterovirus infections, might be linked to the development of T1D (DiMeglio et al.).

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