Phys 02 14b

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Objective 2.14b – Enzymes ,[object Object]

Enzymes and Specificity ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

[object Object],[object Object],[object Object],[object Object],Enzyme Activity and Substrate Concentration

Enzyme & Protein Shape ,[object Object],[object Object],[object Object],[object Object]

High Temperature, protein denaturation ,[object Object],[object Object],[object Object],[object Object],[object Object]

Low Temperature, less reaction collision ,[object Object],[object Object],[object Object],[object Object],[object Object]

pH, ions and Protein Shape ,[object Object],[object Object],[object Object],[object Object],[object Object]

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This powerpoint presentation talks about enzymes, specifically its functions, the different types according to its function, and the definition of enzyme activator and inhibitor. A picture diagram is also included to show the process of enzyme activity and as well as a table differentiating apoenzyme and coenzyme. The different factors that affects the enzyme activity are also explained and lastly, the other uses of enzyme in medicine, food and etc.The content of the powerpoint presentation has undergone a research through internet and the best answers has been selected for better understanding. The resources of all the research made that was in this presentation are acknowledged as shown in the Reference part of the slide.

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The presentation explores the development and application of artificial intelligence (AI) from its inception to its current status in the modern world. The term "artificial intelligence" was first coined by John McCarthy in 1956 to describe efforts to develop computer programs capable of performing tasks that typically require human intelligence. This concept was first introduced at a conference held at Dartmouth College, where programs demonstrated capabilities such as playing chess, proving theorems, and interpreting texts. In the early stages, Alan Turing contributed to the field by defining intelligence as the ability of a being to respond to certain questions intelligently, proposing what is now known as the Turing Test to evaluate the presence of intelligent behavior in machines. As the decades progressed, AI evolved significantly. The 1980s focused on machine learning, teaching computers to learn from data, leading to the development of models that could improve their performance based on their experiences. The 1990s and 2000s saw further advances in algorithms and computational power, which allowed for more sophisticated data analysis techniques, including data mining. By the 2010s, the proliferation of big data and the refinement of deep learning techniques enabled AI to become mainstream. Notable milestones included the success of Google's AlphaGo and advancements in autonomous vehicles by companies like Tesla and Waymo. A major theme of the presentation is the application of generative AI, which has been used for tasks such as natural language text generation, translation, and question answering. Generative AI uses large datasets to train models that can then produce new, coherent pieces of text or other media. The presentation also discusses the ethical implications and the need for regulation in AI, highlighting issues such as privacy, bias, and the potential for misuse. These concerns have prompted calls for comprehensive regulations to ensure the safe and equitable use of AI technologies. Artificial intelligence has also played a significant role in healthcare, particularly highlighted during the COVID-19 pandemic, where it was used in drug discovery, vaccine development, and analyzing the spread of the virus. The capabilities of AI in healthcare are vast, ranging from medical diagnostics to personalized medicine, demonstrating the technology's potential to revolutionize fields beyond just technical or consumer applications. In conclusion, AI continues to be a rapidly evolving field with significant implications for various aspects of society. The development from theoretical concepts to real-world applications illustrates both the potential benefits and the challenges that come with integrating advanced technologies into everyday life. The ongoing discussion about AI ethics and regulation underscores the importance of managing these technologies responsibly to maximize their their benefits while minimizing potential harms.

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