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: Previous studies have suggested that kennelled dogs are more likely to test positive for CECoV than household pets. Here we describe both cross sectional and longitudinal studies in two rescue kennels and two boarding kennels, together with molecular diagnostics, to provide a new insight into the epidemiology of CECoV. Prevalence of CECoV in the cross sectional studies tended to be higher in the rescue kennels (13.8% and 33.3%) than the boarding kennels (5.3% and 13.5%). In each kennel, type I CECoV was more prevalent than type 2 CECoV. The mean quantity of type I detected was equivalent to 6.3 A 10 8 gc/gm (range = 5 A 10 6 , 8.5 A 10 11 ), compared to 1.3 A 10 8 gc/gm (range = 3 A 10 6 , 2.4 A 10 10 ) for type II. In one rescue shelter where dogs were followed longitudinally, infection was significantly associated with accommodation block as well as the length of stay (increased risk of CECoV per week in residence of A1.9). Of those animals sampled on two or more occasions, none tested positive on arrival, and 54.5% later shed CECoV, suggesting that infection may have been acquired within the kennel. Shedding patterns and sequence analysis suggested both types I and II CECoV were maintained in this population by a combination of introductions into the shelter and within-shelter transmission. The findings suggest that some kennel environments may be important in maintaining CECoV infection in the population. We also propose that the diversity of viruses like CECoV in these populations may provide a novel surrogate marker for the success of biosecurity.
Title: Cross sectional and longitudinal surveys of canine enteric coronavirus infection in kennelled dogs: A molecular marker for biosecurity
Output:
True