Given the task definition, example input & output, solve the new input case.
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".
Example: Paragraph: The severe acute respiratory syndrome (SARS) epidemic originating from China in 2002 was caused by a previously uncharacterized coronavirus that could be identified by specific RT-PCR amplification. Efforts to control future SARS outbreaks depend on the accurate and early identification of SARS-CoV infected patients. A real-time fluorogenic RT-PCR assay based on the 3 -noncoding region (3 -NCR) of SARS-CoV genome was developed as a quantitative SARS diagnostic tool. The ideal amplification efficiency of a sensitive SARS-CoV RT-PCR assay should yield an E value (PCR product concentration increase per amplification cycle) equal to 2.0. It was demonstrated that the 3 -NCR SARS-CoV based RT-PCR reactions could be formulated to reach excellent E values of 1.81, or 91% amplification efficacy. The SARS-CoV cDNA preparations derived from viral RNA extract and the cloned recombinant plasmid both exhibit the identical amplification characteristics, i.e. amplification efficacy using the same PCR formulation developed in this study. The viral genomic copy (or genomic equivalences, GE) per infectious unit (GE/pfu) of SARS-CoV used in this study was also established to be approximate 1200-1600:1. The assay's detection sensitivity could reach 0.005 pfu or 6-8 GE per assay. It was preliminarily demonstrated that the assay could efficiently detect SARS-CoV from clinical specimens of SARS probable and suspected patients identified in Taiwan. The 3 -NCR based SARS-CoV assay demonstrated 100% diagnostic specificity testing samples of patients with acute respiratory disease from a non-SARS epidemic region.
Title: Development and evaluation of an efficient 3 -noncoding region-based SARS coronavirus (SARS-CoV) RT-PCR assay for detection of SARS-CoV
Output: True
The answer is true because the title of the paragraph is correct where it described the development of 3 -noncoding region of SARS-CoV genome and assay efficiently detecting SARS-CoV from clinical specimens.

New input case for you: Paragraph: Bovine coronavirus (BCoV) is a recognized cause of severe neonatal calf diarrhea, with a negative impact on animal welfare, leading to economic losses to the livestock industry. Cattle production is one of the most important economic sectors in Uruguay. The aim of this study was to determine the frequency of BCoV infections and their genetic diversity in Uruguayan calves and to describe the evolutionary history of the virus in South America. The overall detection rate of BCoV in Uruguay was 7.8% (64/824): 7.7% (60/782) in dairy cattle and 9.5% (4/42) in beef cattle. The detection rate of BCoV in samples from deceased and live calves was 10.0% (6/60) and 7.6% (58/763), respectively. Interestingly, there was a lower frequency of BCoV detection in calves born to vaccinated dams (3.3%, 8/240) than in calves born to unvaccinated dams (12.2%, 32/263) (OR: 4.02, 95%CI: 1.81-8.90; p = 0.00026). The frequency of BCoV detection was higher in colder months (11.8%, 44/373) than in warmer months (1.5%, 3/206) (OR: 9.05, 95%CI: 2.77-29.53, p = 0.000013). Uruguayan strains grouped together in two different lineages: one with Argentinean strains and the other with Brazilian strains. Both BCoV lineages were estimated to have entered Uruguay in 2013: one of them from Brazil (95%HPD interval: 2011 and the other from Argentina (95%HPD interval: 2010-2014). The lineages differed by four amino acid changes, and both were divergent from the Mebus reference strain. Surveillance should be maintained to detect possible emerging strains that can clearly diverge at the antigenic level from vaccine strains.
Title: Bovine coronavirus in Uruguay: genetic diversity, risk factors and transboundary introductions from neighboring countries
Output:
False