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: Profiles of antibodies to the nucleocapsid protein of the severe acute respiratory syndrome (SARS)-associated coronavirus in 445 probable SARS patients and 3,749 healthy people or non-SARS patients were analyzed by antigen-capturing enzyme-linked immunosorbent assay. Antinucleocapsid antibodies were elucidated in 17.5% of the probable SARS patients 1 to 7 days after the onset of symptoms and in 80% of the patients 8 to 14 days after the onset. About 90% of the probable SARS patients were positive 15 or more days after illness. Antibody titers increased up to 70 days, and high antibody titers were maintained at least for another 3 months. Of the healthy people and non-SARS patients, only seven (0.187%) were weakly positive. FIG. 1. Development of anti-N protein antibody titers over time in 445 patients who probably had SARS. 228 NOTES CLIN. DIAGN. LAB. IMMUNOL. 
 Title: Profile of Antibodies to the Nucleocapsid Protein of the Severe Acute Respiratory Syndrome (SARS)-Associated Coronavirus in Probable SARS Patients
[EX A]: True

[EX Q]: Paragraph: Background. Precision public health is a state-of-the-art concept in public health research and its application in health care. Application of information technology in field of epidemiology paves the way to its transformation to digital epidemiology. A geospatial epidemiological model was simulated to estimate the spread of Ebola virus disease after a hypothetical outbreak in India. Methods. It was a simulation study based on SEIR (Susceptible-Exposed-Infectious-Recovered) compartmental model. Simulation was done in Spatiotemporal Epidemiological Modeler (STEM). Epidemiological profile of Ebola virus, that transmitted throughout the Sierra Leon in 2014-2016, was fitted into the SEIR deterministic compartment model designed for India. 
 Title: A Simulation Study on Hypothetical Ebola Virus Transmission in India Using Spatiotemporal Epidemiological Modeler (STEM): A Way towards Precision Public Health
[EX A]: False

[EX Q]: Paragraph: High-throughput sequencing (HTS) is becoming the state-of-the-art technology for typing of microbial isolates, especially in clinical samples. Yet, its application is still in its infancy for monitoring and outbreak investigations of foods. Here we review the published literature, covering not only bacterial but also viral and Eukaryote food pathogens, to assess the status and potential of HTS implementation to inform stakeholders, improve food safety and reduce outbreak impacts. The developments in sequencing technology and bioinformatics have outpaced the capacity to analyze and interpret the sequence data. The influence of sample processing, nucleic acid extraction and purification, harmonized protocols for generation and interpretation of data, and properly annotated and curated reference databases including non-pathogenic "natural" strains are other major obstacles to the realization of the full potential of HTS in analytical food surveillance, epidemiological and outbreak investigations, and in complementing preventive approaches for the control and management of foodborne pathogens. Despite significant obstacles, the achieved progress in capacity and broadening of the application range over the last decade is impressive and unprecedented, as illustrated with the chosen examples from the literature. Large consortia, often with broad international participation, are making coordinated efforts to cope with many of the mentioned obstacles. Further rapid progress can therefore be prospected for the next decade. 
 Title: High Throughput Sequencing for Detection of Foodborne Pathogens
[EX A]:
True