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".

Q: Paragraph: Using sequence data to infer population dynamics is playing an increasing role in the analysis of outbreaks. The most common methods in use, based on coalescent inference, have been widely used but not extensively tested against simulated epidemics. Here, we use simulated data to test the ability of both parametric and non-parametric methods for inference of effective population size (coded in the popular BEAST package) to reconstruct epidemic dynamics. We consider a range of simulations centred on scenarios considered plausible for pandemic influenza, but our conclusions are generic for any exponentially growing epidemic. We highlight systematic biases in non-parametric effective population size estimation. The most prominent such bias leads to the false inference of slowing of epidemic spread in the recent past even when the real epidemic is growing exponentially. We suggest some sampling strategies that could reduce (but not eliminate) some of the biases. Parametric methods can correct for these biases if the infected population size is large. We also explore how some poor sampling strategies (e.g. that over-represent epidemiologically linked clusters of cases) could dramatically exacerbate bias in an uncontrolled manner. Finally, we present a simple diagnostic indicator, based on coalescent density and which can easily be applied to reconstructed phylogenies, that identifies time-periods for which effective population size estimates are less likely to be biased. We illustrate this with an application to the 2009 H1N1 pandemic. Pandemic growth rates from sequences E. de Silva et al. 1799 Pandemic growth rates from sequences E. de Silva et al. 1807  
 Title: Inferring pandemic growth rates from sequence data

A: True
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Q: Paragraph: This study numerically investigated the thermal effect of human body on the time-dependent dispersion of cough droplets with evaporation process. The thermal flow of human body was imitated using a 3D thermal manikin with real body features, while a recent developed multi-component Eulerian-Lagrangian approach was used to address the effects of inhomogeneous temperature and humidity fields on droplet evaporation. By comparing the results yielded without and with the human body heat, the outcomes demonstrated strong impact of human body heat on the droplets mass fraction and local air velocity distributions. Inspirable droplets could potentially drop into respirable droplets by evaporation, although the evaporation rate was not significantly affected by body heat. The thermal effect of human body revealed its vital impacts on the time-dependent droplets dispersion. Due to the buoyancy driven thermal flow, both the vertical velocity and displacement of small droplets (≤20 μm) were completely reversed from descending to ascending, while the deposition time of large droplets (≥50 μm) were significantly delayed. With the reduced droplet size by evaporation and droplets lifted into breathing zone by human thermal effect, the inhalability and infection risks of cough droplets would be much higher in real occupied indoor spaces. 
 Title: Thermal effect of human body on cough droplets evaporation and dispersion in an enclosed space

A: True
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Q: Paragraph: Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) has been recognized as an invariant internal control for various gene expression studies due to its classical housekeeping role in the glycolytic metabolism. However recently, this enzyme has been proven to be a multifunctional protein involved in diverse non-glycolytic activities. In the present study, two paralogue isoforms of GAPDH mRNAs were characterized from a marine teleost species, rockbream (Oplegnathus fasciatus; Perciformes) and their transcriptional responses to bacterial and viral infections were examined. Rockbream GAPDH1 and GAPDH2 cDNAs encoded 333 and 335 amino acids, respectively, and the amino acid sequence identity between those two isoforms was 74%. Two isoform GAPDH mRNAs were detected ubiquitously in all of tissues examined, but their expression levels were quite variable among tissues. Based on the real-time RT-PCR analysis, the transcription of rbGAPDH1 was affected by neither bacterial (Escherichia coli, Edwardsiella tarda, Vibrio anguillarum or Streptococcus iniae) nor viral (rockbream iridovirus; RBIV) challenges. However on the contrary, the mRNA expression of rbGAPDH2 was significantly up-regulated in liver resulting from the bacterial infections (up to 25-fold), and in both liver (more than sixfold) and kidney (up to fivefold) from the viral infection. Results in the present study suggest that teleost GAPDH isoforms may also be potentially involved in immune modulations especially with respect to inflammatory responses, which is distinct from its classical glycolytic function. 
 Title: Differential modulations of two glyceraldehyde 3-phosphate dehydrogenase mRNAs in response to bacterial and viral challenges in a marine teleost Oplegnathus fasciatus (Perciformes)

A:
False
****