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: Fast simulation tools for the prediction of transient particle transport are critical in designing the air distribution indoors to reduce the exposure to indoor particles and associated health risks. This investigation proposed a combined fast fluid dynamics (FFD) and Markov chain model for fast predicting transient particle transport indoors. The solver for FFD-Markov-chain model was programmed in OpenFOAM, an open-source CFD toolbox. This study used two cases from the literature to validate the developed model and found well agreement between the transient particle concentrations predicted by the FFD-Markov-chain model and the experimental data. This investigation further compared the FFD-Markov-chain model with the CFD-Eulerian model and CFD-Lagrangian model in terms of accuracy and efficiency. The accuracy of the FFD-Markov-chain model was similar to that of the other two models. For the two studied cases, the FFD-Markovchain model was 4.7 and 6.8 times faster, respectively, than the CFD-Eulerian model, and it was 137.4 and 53.3 times faster than the CFD-Lagrangian model in predicting the steady-state airflow and transient particle transport. Therefore, the FFD-Markov-chain model is able to greatly reduce the computing cost for predicting transient particle transport in indoor environments. computational fluid dynamics, indoor environment, Eulerian model, Lagrangian model, particle dispersion, aerosol dynamics Article History 
 Title: Modeling transient particle transport by fast fluid dynamics with the Markov chain method
[EX A]: True

[EX Q]: Paragraph: Background: Hirschsprung's disease (HSCR) is a type of megacolon induced by defi ciency or dysfunction of ganglion cells in the distal intestine and is associated with developmental disorders of the enteric nervous system. To explore the mechanisms of HSCR, we analyzed the RNAsequencing data of the expansion and the narrow segments of colon tissues separated from children with HSCR. Methods: RNA-sequencing of the expansion segments and the narrow segments of colon tissues isolated from children with HSCR was performed. After differentially expressed genes (DEGs) were identified using the edgeR package in R, functional and pathway enrichment analyses of DEGs were carried out using DAVID software. To further screen the key genes, protein-protein interaction (PPI) network and module analyses were conducted separately using Cytoscape software. Results: A total of 117 DEGs were identified in the expansion segment samples, including 47 up-regulated and 70 down-regulated genes. Functional enrichment analysis suggested that FOS and DUSP1 were implicated in response to endogenous stimulus. In the PPI network analysis, FOS (degree=20), EGR1 (degree=16), ATF3 (degree=9), NOS1 (degree=8), CCL5 (degree=8), DUSP1 (degree=7), CXCL3 (degree=6), VIP (degree=6), FOSB (degree=5), and NOS2 (degree=4) had higher degrees, which could interact with other genes. In addition, two significant modules (module 1 and module 2) were identifi ed from the PPI network. Conclusion: Several genes (including FOS, EGR1, ATF3, NOS1, CCL5, DUSP1, CXCL3, VIP, FOSB, and NOS2) might be involved in the development of HSCR through their effect on the nervous system. World J Pediatr 2017;13(3):267-273 
 Title: Genes involved in HSCR Identifying key genes associated with Hirschsprung's disease based on bioinformatics analysis of RNA-sequencing data
[EX A]: False

[EX Q]: Paragraph: 125 words). The SARS-CoV-2 pandemic is straining healthcare resources worldwide, prompting social distancing measures to reduce transmission intensity. The amount of social distancing needed to curb the SARS-CoV-2 epidemic in the context of seasonally varying transmission remains unclear. Using a mathematical model, we assessed that one-time interventions will be insufficient to maintain COVID-19 prevalence within the critical care capacity of the United States. Seasonal variation in transmission will facilitate epidemic control during the summer months but could lead to an intense resurgence in the autumn. Intermittent distancing measures can maintain control of the epidemic, but without other interventions, these measures may be necessary into 2022. Increasing critical care capacity could reduce the duration of the SARS-CoV-2 epidemic while ensuring that critically ill patients receive appropriate care. Full text. The COVID-19 pandemic is causing substantial mortality and a major strain on healthcare systems (1,2) . With no pharmaceutical treatments available, interventions have focused on contact tracing, quarantine, and social distancing. Intensive testing, tracing, and isolation of cases has enabled control of transmission in some places, such as Singapore and Hong Kong (3). At the opposite extreme, many countries lack the testing and public health resources to mount similar responses to the COVID-19 epidemic, which could result in unhindered spread and catastrophic outbreaks. Between these responses, many countries are adopting measures termed "social distancing" or "physical distancing," closing schools and workplaces and limiting the sizes of gatherings. The goal of these strategies is to slow the spread of infection and reduce the intensity of the epidemic ("flatten the curve") (3), thus reducing risk of overwhelming health systems and buying time to develop treatments and vaccines. However, there is concern that such measures may have to stay in place over long . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity. is the (which was not peer-reviewed) The copyright holder for this preprint . 
 Title: Social distancing strategies for curbing the COVID-19 epidemic
[EX A]:
False