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: Assembly of virus capsids and surface proteins must be regulated to ensure that the resulting complex is an infectious virion. Here we examine assembly of virus capsids, focusing on hepatitis B virus and bacteriophage MS2, and formation of glycoproteins in the alphaviruses. These systems are structurally and biochemically well-characterized and are simplest-case paradigms of self-assembly. Published data suggest that capsid and glycoprotein assembly is subject to allosteric regulation, that is, regulation at the level of conformational change. The hypothesis that allostery is a common theme in viruses suggests that deregulation of capsid and glycoprotein assembly by small molecule effectors will be an attractive antiviral strategy, as has been demonstrated with hepatitis B virus. 
 Title: Virus assembly, allostery, and antivirals

A: False
****
Q: Paragraph: Contact patterns among hosts are considered as one of the most critical factors contributing to unequal pathogen transmission. Consequently, networks have been widely applied in infectious disease modeling. However most studies assume static network structure due to lack of accurate observation and appropriate analytic tools. In this study we used high temporal and spatial resolution animal position data to construct a high-resolution contact network relevant to infectious disease transmission. The animal contact network aggregated at hourly level was highly variable and dynamic within and between days, for both network structure (network degree distribution) and individual rank of degree distribution in the network (degree order). We integrated network degree distribution and degree order heterogeneities with a commonly used contact-based, directly transmitted disease model to quantify the effect of these two sources of heterogeneity on the infectious disease dynamics. Four conditions were simulated based on the combination of these two heterogeneities. Simulation results indicated that disease dynamics and individual contribution to new infections varied substantially among these four conditions under both parameter settings. Changes in the contact network had a greater effect on disease dynamics for pathogens with smaller basic reproduction number (i.e. R 0 , 2). 
 Title: Highly dynamic animal contact network and implications on disease transmission

A: True
****
Q: Paragraph: Formal, quantitative approaches are now widely used to make predictions about the likelihood of an infectious disease outbreak, how the disease will spread, and how to control it. Several wellestablished methodologies are available, including risk factor analysis, risk modelling and dynamic modelling. Even so, predictive modelling is very much the 'art of the possible', which tends to drive research effort towards some areas and away from others which may be at least as important. Building on the undoubted success of quantitative modelling of the epidemiology and control of human and animal diseases such as AIDS, influenza, foot-and-mouth disease and BSE, attention needs to be paid to developing a more holistic framework that captures the role of the underlying drivers of disease risks, from demography and behaviour to land use and climate change. At the same time, there is still considerable room for improvement in how quantitative analyses and their outputs are communicated to policy makers and other stakeholders. A starting point would be generally accepted guidelines for 'good practice' for the development and the use of predictive models. 
 Title: How to make predictions about future infectious disease risks

A:
False
****