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 Q]: Paragraph: Human coronavirus OC43 (HCoV-OC43) is a causative agent of the common cold. The nucleocapsid (N) protein, which is a major structural protein of CoVs, binds to the viral RNA genome to form the virion core and results in the formation of the ribonucleoprotein (RNP) complex. We have solved the crystal structure of the N-terminal domain of HCoV-OC43 N protein (N-NTD) (residues 58 to 195) to a resolution of 2.0Å. The HCoV-OC43 N-NTD is a single domain protein composed of a five-stranded -sheet core and a long extended loop, similar to that observed in the structures of N-NTDs from other coronaviruses. The positively charged loop of the HCoV-OC43 N-NTD contains a structurally well-conserved positively charged residue, R106. To assess the role of R106 in RNA binding, we undertook a series of site-directed mutagenesis experiments and docking simulations to characterize the interaction between R106 and RNA. The results show that R106 plays an important role in the interaction between the N protein and RNA. In addition, we showed that, in cells transfected with plasmids that encoded the mutant (R106A) N protein and infected with virus, the level of the matrix protein gene was decreased by 7-fold compared to cells that were transfected with the wild-type N protein. This finding suggests that R106, by enhancing binding of the N protein to viral RNA plays a critical role in the viral replication. The results also indicate that the strength of N protein/RNA interactions is critical for HCoV-OC43 replication. 
 Title: Crystal structure-based exploration of the important role of Arg106 in the RNA-binding domain of human coronavirus OC43 nucleocapsid protein NIH Public Access Author Manuscript
[EX A]: True

[EX Q]: Paragraph: Autoregressive distributed lag (ARDL) approach Economic growth Error correction model US air travel and freight demand a b s t r a c t This paper examines the short-and long-run effects of economic growth and market shocks (e.g., 9/11 terrorist attacks, Iraq war, SARS epidemic, and 2008 financial crisis) on air passenger and freight services using an autoregressive distributed lag (ARDL) approach to cointegration. Results show that, in the longrun, both air passenger and freight services tend to increase with economic growth. In the short-run, however, only air passenger service is responsive to economic growth. Finally, only the 9/11 terrorist attacks and the SARS have detrimental effects on air passenger demand both in the short-and long-run, and in the long-run, respectively. However, these market shocks are found to have little impact on air freight demand. 
 Title: Dynamic relationship between air transport demand and economic growth in the United States: A new look
[EX A]: False

[EX Q]: Paragraph: Text mining was used to extract technical intelligence from the open source global SARS research literature. A SARS-focused query was applied to the Science Citation Index (SCI) (SCI 2008) database for the period 1998-early 2008. The SARS research literature infrastructure (prolific authors, key journals/institutions/countries, most cited authors/journals/documents) was obtained using bibliometrics, and the SARS research literature technical structure (hierarchical taxonomy) was obtained using computational linguistics/document clustering. 
 Title: Structure and infrastructure of infectious agent research literature: SARS
[EX A]:
False