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: Numerous living organisms possess biophotonic nanostructures that provide coloration and other diverse functions for survival. While such structures have been actively studied and replicated in the laboratory, it remains unclear whether they can be used for biomedical applications. Here we show a transparent photonic nanostructure inspired by the longtail glasswing (Chorinea faunus) butterfly and demonstrate its use in intraocular pressure (IOP) sensors in vivo. We exploit the phase separation between two immiscible polymers (poly(methyl methacrylate) and polystyrene) to form nanostructured features on top of a Si 3 N 4 substrate. The membrane thus formed shows good angle-independent white light transmission, strong hydrophilicity and anti-biofouling properties that prevent adhesion of proteins, bacteria, and eukaryotic cells. We then developed a microscale implantable IOP sensor using our photonic membrane as an optomechanical sensing element. Finally, we performed in vivo testing on New Zealand white rabbits and show that our Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#termsReprints and permission information is available online at www.nature.com/reprints. 
 Title: Multifunctional biophotonic nanostructures inspired by longtail glasswing butterfly for medical devices HHS Public Access Author manuscript
[A]: True


[Q]: Paragraph: Background: Reconstructing individual transmission events in an infectious disease outbreak can provide valuable information and help inform infection control policy. Recent years have seen considerable progress in the development of methodologies for reconstructing transmission chains using both epidemiological and genetic data. However, only a few of these methods have been implemented in software packages, and with little consideration for customisability and interoperability. Users are therefore limited to a small number of alternatives, incompatible tools with fixed functionality, or forced to develop their own algorithms at considerable personal effort. Results: Here we present outbreaker2, a flexible framework for outbreak reconstruction. This R package re-implements and extends the original model introduced with outbreaker, but most importantly also provides a modular platform allowing users to specify custom models within an optimised inferential framework. As a proof of concept, we implement the within-host evolutionary model introduced with TransPhylo, which is very distinct from the original genetic model in outbreaker, and demonstrate how even complex model results can be successfully included with minimal effort. Conclusions: outbreaker2 provides a valuable starting point for future outbreak reconstruction tools, and represents a unifying platform that promotes customisability and interoperability. Implemented in the R software, outbreaker2 joins a growing body of tools for outbreak analysis. 
 Title: outbreaker2: a modular platform for outbreak reconstruction
[A]: True


[Q]: Paragraph: Background: COVID-19 originated in China and has quickly spread worldwide causing a pandemic. Countries need rapid data on the prevalence of the virus in communities to enable rapid containment. However, the equipment, human and laboratory resources required for conducting individual RT-PCR is prohibitive. One technique to reduce the number of tests required is the pooling of samples for analysis by RT-PCR prior to testing. We conducted a mathematical analysis of pooling strategies for infection rate classification using group testing and for the identification of individuals by testing pooled clusters of samples. Findings: On the basis of the proposed pooled testing strategy we calculate the probability of false alarm, the probability of detection, and the average number of tests required as a function of the pool size. We find that when the sample size is 256, using a maximum pool size of 64, with only 7.3 tests on average, we can distinguish between prevalences of 1% and 5% with a probability of detection of 95% and probability of false alarm of 4%. Interpretation: The pooling of RT-PCR samples is a cost-effective technique for providing much-needed course-grained data on the prevalence of COVID-19. This is a powerful tool in providing countries with information that can facilitate a response to the pandemic that is evidence-based and saves the most lives possible with the resources available. 
 Title: Pooling RT-PCR or NGS samples has the potential to cost-effectively generate estimates of COVID-19 prevalence in resource limited environments
[A]:
True