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".

Paragraph: Background: Health care planning for pandemic influenza is a challenging task which requires predictive models by which the impact of different response strategies can be evaluated. However, current preparedness plans and simulations exercises, as well as freely available simulation models previously made for policy makers, do not explicitly address the availability of health care resources or determine the impact of shortages on public health. Nevertheless, the feasibility of health systems to implement response measures or interventions described in plans and trained in exercises depends on the available resource capacity. As part of the AsiaFluCap project, we developed a comprehensive and flexible resource modelling tool to support public health officials in understanding and preparing for surges in resource demand during future pandemics. Results: The AsiaFluCap Simulator is a combination of a resource model containing 28 health care resources and an epidemiological model. The tool was built in MS Excel© and contains a user-friendly interface which allows users to select mild or severe pandemic scenarios, change resource parameters and run simulations for one or multiple regions. Besides epidemiological estimations, the simulator provides indications on resource gaps or surpluses, and the impact of shortages on public health for each selected region. It allows for a comparative analysis of the effects of resource availability and consequences of different strategies of resource use, which can provide guidance on resource prioritising and/or mobilisation. Simulation results are displayed in various tables and graphs, and can also be easily exported to GIS software to create maps for geographical analysis of the distribution of resources. The AsiaFluCap Simulator is freely available software (www.cdprg.org) which can be used by policy makers, policy advisors, donors and other stakeholders involved in preparedness for providing evidence based and illustrative information on health care resource capacities during future pandemics. The tool can inform both preparedness plans and simulation exercises and can help increase the general understanding of dynamics in resource capacities during a pandemic. The combination of a mathematical model with multiple resources and the linkage to GIS for creating maps makes the tool unique compared to other available software. 
 Title: Development of a resource modelling tool to support decision makers in pandemic influenza preparedness: The AsiaFluCap Simulator
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Paragraph: We previously reported widespread differential expression of long non-protein-coding RNAs (ncRNAs) in response to virus infection. Here, we expanded the study through small RNA transcriptome sequencing analysis of the host response to both severe acute respiratory syndrome coronavirus (SARS-CoV) and influenza virus infections across four founder mouse strains of the Collaborative Cross, a recombinant inbred mouse resource for mapping complex traits. We observed differential expression of over 200 small The small RNAs identified also included many non-miRNA small RNAs, such as small nucleolar RNAs (snoRNAs), in addition to nonannotated small RNAs. An integrative sequencing analysis of both small RNAs and long transcripts from the same samples showed that the results revealing differential expression of miRNAs during infection were largely due to transcriptional regulation and that the predicted miRNA-mRNA IMPORTANCE Most studies examining the host transcriptional response to infection focus only on protein-coding genes. However, mammalian genomes transcribe many short and long non-protein-coding RNAs (ncRNAs). With the advent of deepsequencing technologies, systematic transcriptome analysis of the host response, including analysis of ncRNAs of different sizes, is now possible. Using this approach, we recently discovered widespread differential expression of host long (>200 nucleotide [nt]) ncRNAs in response to virus infection. Here, the samples described in the previous report were again used, but we sequenced another fraction of the transcriptome to study very short (about 20 to 30 nt) ncRNAs. We demonstrated that virus infection also altered expression of many short ncRNAs of diverse classes. Putting the results of the two studies together, we show that small RNAs may also play an important role in regulating the host response to virus infection. Citation Peng X, et al. 2011. Integrative deep sequencing of the mouse lung transcriptome reveals differential expression of diverse classes of small RNAs in response to respiratory virus infection. mBio 2(6):e00198-11. 
 Title: Integrative Deep Sequencing of the Mouse Lung Transcriptome Reveals Differential Expression of Diverse Classes of Small RNAs in Response to Respiratory Virus Infection
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Paragraph: Porcine epidemic diarrhea virus (PEDV) Isobaric tags for relative and absolute quantitation (iTRAQ) Proteomics Pathway analysis The re-emerging porcine epidemic diarrhea virus (PEDV) variant related diarrhea has been documented in China since late 2010 and now with global distribution. Currently, a virulent PEDV CH/YNKM-8/2013 and a CV777 vaccine strain-like AH-M have been successfully isolated from the clinical samples. To dissect out the underlying pathogenic mechanism of virulent PEDV and clarify the differences between virulent and CV777 vaccine strainlike PEDV infections, we performed an iTRAQ-based comparative quantitative proteomic study of Vero cells infected with both PEDV strains. A total of 661 and 474 differentially expressed proteins were identified upon virulent and CV777 vaccine strain-like isolates infection, respectively. Ingenuity Pathway Analysis was employed to investigate the canonical pathways and functional networks involved in both PEDV infections. Comprehensive studies have revealed that the PEDV virulent strain suppressed protein synthesis of Vero cells through down-regulating mTOR as well as its downstream targets 4EBP1 and p70S6K activities, which were validated by immunoblotting. In addition, the virulent strain could activate NF-κB pathway more intensively than the CV777 vaccine strain-like isolate, and elicit stronger inflammatory cascades as well. These data might provide new insights for elucidating the specific pathogenesis of PEDV infection, and pave the way for the development of effective therapeutic strategies. Biological significance: Porcine epidemic diarrhea is now worldwide distributed and causing huge economic losses to swine industry. The immunomodulation and pathogenesis between PEDV and host, as well as the difference between virulent and attenuated strains of PEDV infections are still largely unknown. In this study, we presented for the first application of proteomic analysis to compare whole cellular protein alterations induced by virulent and CV777 vaccine strain-like PEDV infections, which might contribute to understand the pathogenesis of PEDV and anti-viral strategy development. 
 Title: iTRAQ-based comparative proteomic analysis of Vero cells infected with virulent and CV777 vaccine strain-like strains of porcine epidemic diarrhea virus

True