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: Background The aim of this study was to assess multiplex PCR analysis in detecting causative viruses in children with febrile seizures. Methods The study was a retrospective analysis comparing data from a pre-multiplex era (2009) with a period after the introduction of routine respiratory multiplex analysis (2010-2013) in children with febrile seizures. Results We included 200 children with febrile seizures (mean age: 29.5 ± 1.4.months; 104 male) in the study. In 2009, in 10 out of 49 (20 %) children, microbiology testing (bacterial/fungal) was positive compared with a rate of 74 out of 151 (49 %) children during 2010-2013 (p < 0.01). The rate of positive virological studies increased from 10 (20 %) in 2009 to 73 (48.3 %) in the period 2010-2013 (p < 0.01). Multiplex PCR analysis confirmed viral infections in 52 of 73 cases (71.2 %). Conclusion Routine multiplex PCR analysis fosters the detection of respiratory viruses in children with febrile seizure. The precise role of multiplex analysis in the J. 
 Title: Role of multiplex PCR analysis in children with febrile seizures management of these children awaits further clarifi- cation
[EX A]: True

[EX Q]: Paragraph: The tertiary structures of the S1 and S2 domains of the spike protein of the coronavirus which is responsible of the severe acute respiratory syndrome (SARS) have been recently predicted. Here a molecular assembly of SARS coronavirus peplomer which accounts for the available functional data is suggested. The interaction between S1 and S2 appears to be stabilised by a large hydrophobic network of aromatic side chains present in both domains. This feature results to be common to all coronaviruses, suggesting potential targeting for drugs preventing coronavirus-related infections. 
 Title: Prediction of quaternary assembly of SARS coronavirus peplomer
[EX A]: False

[EX Q]: Paragraph: Infectious diseases, especially when new and highly contagious, could be devastating producing epidemic outbreaks and pandemics. Predicting the outcomes of such events in relation to possible interventions is crucial for societal and healthcare planning and forecasting of resource needs. Deterministic and mechanistic models can capture the main known phenomena of epidemics while also allowing for a meaningful interpretation of results. In this work a deterministic mechanistic population balance model was developed. The model describes individuals in a population by infection stage and age group. The population is treated as in a close well mixed community with no migrations. Infection rates and clinical and epidemiological information govern the transitions between stages of the disease. The present model provides a steppingstone to build upon and its current low complexity retains accessibility to non experts and policy makers to comprehend the variables and phenomena at play. 
 Title: A mechanistic population balance model to evaluate the impact of interventions on infectious disease outbreaks: Case for COVID19
[EX A]:
False