In this task, you're given a paragraph and title from the research paper. Your task is to classify whether the given title is suitable or not for the research paper based on the given paragraph. Return "True" if title is proper according to paragraph else "False".

Ex Input:
Paragraph: People in the Middle East have been affected by the Middle East Respiratory Syndrome CoronaVirus (MERS Co-V) since 2012. New cases are continuously reported especially in the Kingdom of Saudi Arabia, and the risk of exposure remains an issue. Data visualization plays a vital role in effective analysis of the data. In this paper, we introduce an interactive visualization application for MERS data collected from the Control and Command Centre, Ministry of Health website of Saudi Arabia. The data corresponding to the period from January 1, 2019 to February 28, 2019 was used in the present work. The attributes considered include gender, age, date of reporting, city, region, camel contact, description and status of the patient. The visualization tool has been developed using Shiny framework of R programming language. The application presents information in the form of interactive plots, maps and tables. The salient feature of the tool is that users can view and download data corresponding to the period of their choice. This tool can help decision makers in the detailed analysis of data and hence devise measures to prevent the spread of the disease.
Title: Shiny Framework Based Visualization and Analytics Tool for Middle East Respiratory Syndrome

Ex Output:
False

Ex Input:
Paragraph: The yeast two-hybrid (Y2H) system is a powerful method to identify and analyze binary protein interactions. In the fi eld of virology, the Y2H system has signifi cantly increased our knowledge of structure and function of viral proteins by systematically assessing intraviral protein interactions. Several comprehensive approaches to determine virus-host interactions have provided insight into viral strategies to manipulate the host for effi cient replication and to escape host-derived countermeasures. To expand our knowledge of intraviral and virus-host protein interactions, we here present a Y2H protocol that is well suited for high-throughput screening. Yeast mating followed by liquid handling in a 96-well format as well as fl uorescent readout of the reporter system provides a highly standardized and fully automated screening situation. The protocol can either be applied to screen complex host cDNA libraries or protein pairs arrayed for cross-testing. The ease of use, the cost-effectiveness as well as the robotic handling allows for extensive and multiple rounds of screening providing high coverage of protein-protein interactions. Thus, this protocol represents an improved "deep" screening method for high-throughput Y2H assays.
Title: Chapter 1 A High-Throughput Yeast Two-Hybrid Protocol to Determine Virus-Host Protein Interactions

Ex Output:
True

Ex Input:
Paragraph: Mathematical models when applied to infectious disease data can provide extremely useful insights into the possible future impacts of potential emerging epidemics and how they might be best controlled or mitigated. Modelling, which is like any other hypothesis-driven approach, aims to develop a better understanding of biological phenomena. However, diseases processes generally, and particularly those related to transmission, will in many cases be imperfectly understood or too complex to systematically describe, so models will necessarily be simplifications of the overall system. It is essential, therefore, that models are designed carefully and used appropriately. Key to this is identifying what specific questions a model might be expected to answer and what data is available to inform the model. A particular type of model might be fine for one particular situation but highly inappropriate for another. It is also important to appreciate and communicate what simplifications and assumptions have had to be made and how this might affect the robustness of the modelling results. It is also particularly important to understand that models frequently make what can be hidden assumptions about underlying processes because of the way they have been constructed and these assumptions also need to be carefully considered and made explicit, particularly for non-expert audiences. This chapter, therefore, provides a brief introduction to some of these aspects of epidemic modelling for those that might be less familiar with them.
Title: Chapter 23 Modelling Emerging Viral Epidemics for Public Health Protection

Ex Output:
False