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 Input:
Paragraph: The goal of this study was to determine whether the use of nesting material or polycarbonate shelters, as enrichment devices would have an impact on endpoints commonly measured during the conduct of the National Toxicology Program (NTP) 13-week studies. The study design was consistent with the NTP 13-week toxicity studies. Harlan Sprague Dawley (HSD) rats and their offspring, and B6C3F1/N mice were assigned to control (unenriched) and enriched experimental groups. Body weight, food and water consumption, behavioral observations, fecal content, clinical pathology, gross pathology, organ weights, and histopathology were evaluated. Enriched male mice and male and female rats exhibited decreased feed intake without a subsequent decrease in body weight; this may have been the result of the nesting material reducing the effect of cold stress thereby allowing for more efficient use of feed. There were statistical differences in some hematological parameters, however these were not considered physiologically relevant since all values were within the normal range. Gross pathology and histopathological findings were background changes and were not considered enrichment-related. Nesting material and shelters were used frequently and consistently and allowed animals to display species typical behavior. There was no significant impact on commonly measured endpoints in HSD rats and B6C3F1/N mice given enrichment devices.
Title: Impact of Environmental Enrichment Devices on NTP In Vivo Studies

Ex Output:
True

Ex Input:
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

Ex Output:
True

Ex Input:
Paragraph: Human metapneumovirus (hMPV) and respiratory syncytial virus (RSV) are important respiratory pathogens with similar symptomatology. The aim of this prospective birth cohort study was to identify risk factors for an hMPV or RSV infection during the first year of life in unselected healthy children. We followed 217 children from birth to 1 year of age. Nasal swabs and symptom diaries were collected monthly. Anti-hMPV and anti-RSV IgG antibodies by age 1 year were detected by ELISA, and nasal swabs were analysed for hMPV and RSV by RT-PCR. Logistic regression was used for risk factor analysis. Anti-hMPV IgG was found in 38 children (17.5%), and anti-RSV IgG in 172 children (79%). Risk factors for being anti-hMPV IgG-positive were: (1) being born in the spring (OR =2.36; 95% CI:1.06-5.27), and (2) having older siblings (OR=3.82; 95% CI:1.75-8.34). Risk factors for being anti-RSV IgG-positive were: (1) gestational age <38 weeks (OR=3.39; 95% CI:1.42-8.05), (2) increasing paternal age (OR=1.85 per 5 yrs; 95% CI:1.28-2.68), and (3) wall-to-wall carpeting (OR=3.15; 95% CI:1.29-7.68). Being born in the spring was associated with decreased odds of being anti-RSV IgG-positive (OR=0.27, 95% CI:0.09-0.85). Risk factors for RSV hospitalisation (n= 11) were: (1) older siblings (OR=4.49; 95% CI: 1.08-18.73) and (2) smoking in the household (OR=5.06; 95% CI: 1.36-18.76). Exclusive breastfeeding for the first 14 days of life protected against hospitalisation (OR= 0.21; 95% CI:0.06-0.79). In conclusion, this study identifies risk factors for mild and asymptomatic hMPV infections in infancy. Abbreviations hMPV human metapneumovirus RSV respiratory syncytial virus OR odds ratio PBS phosphate-buffered saline NPA nasopharyngeal aspirate RT-PCR reverse transcription-polymerase chain reaction ELISA enzyme-linked immunosorbent assay RT room temperature M-PBS PBS with 2% skim-milk powder HRP horseradish peroxidase TMB tetramethyl benzidine OD optical density SD standard deviation PDV Phocine Distemper Virus Eur
Title: A community study of clinical traits and risk factors for human metapneumovirus and respiratory syncytial virus infection during the first year of life

Ex Output:
False