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: One-hundred sixty Escherichia coli isolates obtained from piglets with diarrhea from different parts of Slovakia were examined for the presence of genes coding for F4, F5, F6 and F41 fimbrial adhesins, and hemolytic activity. According to polymerase chain reaction tests 74 (46 %) E. coli isolates were positive for primers that detected genes coding for fimbrial adhesins. Of these 74 isolates, 64 were positive for genes encoding for F4 + , four for F5 + , five for F6 + , and one for both F41 + and F5 + adhesins. 
 Title: Genotyping of Fimbrial Adhesins in Escherichia coli Strains Isolated from Slovak Piglets Suffering from Diarrhea

Ex Output:
False


Ex Input:
Paragraph: Knowledge of the evolution of pathogens is of great medical and biological significance to the prevention, diagnosis, and therapy of infectious diseases. In order to understand the origin and evolution of the SARS-CoV (severe acute respiratory syndrome-associated coronavirus), we collected complete genome sequences of all viruses available in GenBank, and made comparative analyses with the SARS-CoV. Genomic signature analysis demonstrates that the coronaviruses all take the TGTT as their richest tetranucleotide except the SARS-CoV. A detailed analysis of the forty-two complete SARS-CoV genome sequences revealed the existence of two distinct genotypes, and showed that these isolates could be classified into four groups. Our manual analysis of the BLASTN results demonstrates that the HE (hemagglutinin-esterase) gene exists in the SARS-CoV, and many mutations made it unfamiliar to us. 
 Title: Evolution and Variation of the SARS-CoV Genome

Ex Output:
False


Ex Input:
Paragraph: In this letter we analyze the real-time infection data of COVID-19 epidemic for nine nations. We observe that till 27 March 2020, the number of infected individuals (I(t)) in USA, Spain, Germany, Iran, France, and India are growing exponentially. On the contrary, I(t) curves for China and South Korea exhibits power law behavior before flattening of the curve. The derivativeİ(t), which is also the daily infection count, is proportional to I(t) for the exponential regime, but not for the power law regime. These valuable indicators could be used for epidemic forecast. We also argue that long-term community transmission and/or the transmission by asymptomatic carriers traveling long distances may be inducing the power law growth of the epidemic. 
 Title: COVID-19 epidemic: Power law spread and flattening of the curve

Ex Output:

False