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".

Input: Consider Input: Paragraph: Background: The World Health Organization recommends periodic evaluations of influenza surveillance systems to identify areas for improvement and provide evidence of data reliability for policymaking. However, data about the performance of established influenza surveillance systems are limited in Africa, including in the Democratic Republic of Congo (DRC). Methods: We used the Centers for Disease Control and Prevention guidelines to evaluate the performance of the influenza sentinel surveillance system (ISSS) in DRC during 2012-2015. The performance of the system was evaluated using eight surveillance attributes: (i) data quality and completeness for key variables, (ii) timeliness, (iii) representativeness, (iv) flexibility, (v) simplicity, (vi) acceptability, (vii) stability and (viii) utility. For each attribute, specific indicators were developed and described using quantitative and qualitative methods. Scores for each indicator were as follows: < 60% weak performance; 60-79% moderate performance; ≥80% good performance. Results: During 2012-2015, we enrolled and tested 4339 patients with influenza-like illness (ILI) and 2869 patients with severe acute respiratory illness (SARI) from 11 sentinel sites situated in 5 of 11 provinces. Influenza viruses were detected in 446 (10.3%) samples from patients with ILI and in 151 (5.5%) samples from patients with SARI with higher detection during December-May. Data quality and completeness was > 90% for all evaluated indicators. Other strengths of the system were timeliness, simplicity, stability and utility that scored > 70% each. Representativeness, flexibility and acceptability had moderate performance. It was reported that the ISSS contributed to: (i) a better understanding of the epidemiology, circulating patterns and proportional contribution of influenza virus among patients with ILI or SARI; (ii) acquisition of new key competences related to influenza surveillance and diagnosis; and (iii) continuous education of surveillance staff and clinicians at sentinel sites about influenza. However, due to limited resources no actions were undertaken to mitigate the impact of seasonal influenza epidemics. Conclusions: The system performed overall satisfactorily and provided reliable and timely data about influenza circulation in DRC. The simplicity of the system contributed to its stability. A better use of the available data could be made to inform and promote prevention interventions especially among the most vulnerable groups. 
 Title: Evaluation of the influenza sentinel surveillance system in the Democratic Republic of Congo, 2012-2015

Output: True


Input: Consider Input: Paragraph: Similarity in time series is an important feature of dynamical systems such as financial systems, with potential use for clustering of series in system. Here, we mainly introduce a novel method: the reconstructed phase space information clustering method to analyze the financial markets. The method is used to examine the similarity of different sequences by calculating the distances between them, which the main difference from previous method is the way to map the original time series to symbolic sequences. Here we make use of the state space reconstruction to construct the symbolic sequences and quantify the similarity of different stock markets and exchange rate markets considering the chaotic behavior between the complex time series. And we compare the results of similarity of artificial and real data using the modified method, information categorization method and system clustering method. We conclude that the reconstructed phase space information clustering method is effective to research the close relationship in time series and for short time series especially. Besides, we report the results of similarity of different exchange rate time series in different periods and find the effect of the exchange rate regime in 2008 on the time series. Also we acquire some characteristics of exchange rate time 
 Title: The similarity analysis of financial stocks based on information clustering

Output: False


Input: Consider Input: Paragraph: Background: Foodborne norovirus outbreak data in Japan from [2005][2006], involving virological surveillance of all symptomatic and asymptomatic individuals, were reanalyzed to estimate the asymptomatic ratio of norovirus infection along with the risk of infection and the probability of virus shedding. Methods: Employing a statistical model that is considered to capture the data-generating process of the outbreak and virus surveillance, maximum likelihood estimation of the asymptomatic ratio was implemented. Results: Assuming that all norovirus outbreaks (n = 55) were the result of random sampling from an identical distribution and ignoring genogroup and genotype specificities, the asymptomatic ratio was estimated at 32.1% (95% confidence interval [CI], 27.7-36.7). Although not significant, separate estimation of the asymptomatic ratio of the GII.4 genotype appeared to be greater than other genotypes and was estimated at 40.7% (95% CI, 32.8-49.0). Conclusion: The present study offered the first explicit empirical estimates of the asymptomatic ratio of norovirus infection in natural infection settings. The estimate of about 30% was consistent with those derived from volunteer challenge studies. Practical difficulty in controlling GII.4 outbreaks was supported by the data, considering that a large estimate of the asymptomatic ratio was obtained for the GII.4 genotype. 
 Title: Estimating the Asymptomatic Ratio of Norovirus Infection During Foodborne Outbreaks With Laboratory Testing in Japan


Output: False