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: A number of emerging and re-emerging viruses have caused epidemics or pandemics of infectious diseases leading to major devastations throughout human history. Therefore, developing effective and safe vaccines against these viruses is clearly important for the protection of at-risk populations. Our previous studies have shown that the receptor-binding domain (RBD) in the spike protein of severe acute respiratory syndrome (SARS)-associated coronavirus (SARS-CoV) is a key target for the development of SARS vaccines. In this review, we highlight some key advances in the development of antiviral vaccines targeting the RBDs of spike proteins of emerging and re-emerging viruses, using SARS-CoV, influenza virus, Hendra virus (HeV) and Nipah virus (NiV) as examples. Figure 1 The interaction between the receptor-binding domain in the spike of an emerging virus and the corresponding receptor on the target cell. 
 Title: Emerging Microbes and Infections (2012) 1, e13

A: True
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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

A: True
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Q: Paragraph: The henipaviruses, represented by Hendra (HeV) and Nipah (NiV) viruses are highly pathogenic zoonotic paramyxoviruses with uniquely broad host tropisms responsible for repeated outbreaks in Australia, Southeast Asia, India and Bangladesh. The high morbidity and mortality rates associated with infection and lack of licensed antiviral therapies make the henipaviruses a potential biological threat to humans and livestock. Henipavirus entry is initiated by the attachment of the G envelope glycoprotein to host cell membrane receptors. Previously, henipavirus-neutralizing human monoclonal antibodies (hmAb) have been isolated using the HeV-G glycoprotein and a human naïve antibody library. One cross-reactive and receptor-blocking hmAb (m102.4) was recently demonstrated to be an effective post-exposure therapy in two animal models of NiV and HeV infection, has been used in several people on a compassionate use basis, and is currently in development for use in humans. Here, we report the crystal structure of the complex of HeV-G with m102.3, an m102.4 derivative, and describe NiV and HeV escape mutants. This structure provides detailed insight into the mechanism of HeV and NiV neutralization by m102.4, and serves as a blueprint for further optimization of m102.4 as a therapeutic agent and for the development of entry inhibitors and vaccines. 
 Title: Crystal Structure of the Hendra Virus Attachment G Glycoprotein Bound to a Potent Cross-Reactive Neutralizing Human Monoclonal Antibody

A:
False
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