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".

Input: Consider Input: Paragraph: Research on respiratory protection against biologic agents is important to address major concerns such as occupational safety and terrorist attack. This review describes the literature on respiratory protection against bioaerosols and identifies research gaps. Respiratory protection is a complex field involving a number of factors, such as the efficiency of respirator filter material; facepiece fitting; and maintenance, storage, and reuse of respirators. Several studies used nonpathogenic microorganisms having physical characteristics similar to that of Mycobacterium tuberculosis to analyze microbial penetration through respirators. Some studies showed that high-efficiency particulate air (HEPA) and N95 filters provided a higher level of protection than dust/mist (DM) and dust/mist/fume (DMF) filters. Flow rate and relative humidity appear to alter the level of penetration of microorganisms through respirator filters. The relationship between microbial penetration through respirator filters and the aerodynamic diameter, length, or other physical characteristics of microorganisms remains controversial. Whether reaerosolization of bioaerosol particles should be a concern is unclear, given the fact that one study has demonstrated significant reaerosolization of 1-to 5-mm particles loaded onto respirator filters. Respirator maintenance, storage, and decontamination are important factors to be considered when reusing respirators. The respiratory protection against biologic warfare agents such as anthrax in military and civilian situations is described. (Am J Infect Control 2004;32:345-54.)  
 Title: Respiratory protection against bioaerosols: Literature review and research needs

Output: False


Input: Consider Input: Paragraph: Accurate quantification of impurities existing as separate crystalline phases at trace levels in drug materials is an important issue in the pharmaceutical industry. In the present study, a thermoanalytical approach previously developed for quantifying trace levels of polymorphic impurity (form II metastable nuclei) in commercial salmeterol xinafoate powders has been successfully applied with slight modifications to ribavirin, an antiviral drug exhibiting roughly similar polymorph-dependent crystallization kinetics in melts to that of salmeterol xinafoate. Essentially, the approach involved modeling of the crystallization kinetics of both tested and reference drug materials in melts using the Avrami-Erofe'ev (AE) rate expression, derivation of a mathematical equation for relating the AE kinetic constant to the composition of reference polymorph mixtures, and the use of this derived equation (in the form of a calibration curve) to calculate the impurity contents of the tested samples from their computed AE constants. For ribavirin, modification of the latter equation by incorporation of an empirical exponent was found necessary to account for the compositiondependent changes in crystallization kinetics of the reference mixtures. Such modification has made possible the determination of polymorphic impurity content of as low as 0.004% (w/w) in ribavirin samples induced by different forms of grinding treatment. 
 Title: An improved thermoanalytical approach to quantifying trace levels of polymorphic impurity in drug powders

Output: True


Input: Consider Input: Paragraph: As the deployment of electronic medical records (EMR) expands, so is the availability of long-term datasets that could serve to enhance public health surveillance. We hypothesized that EMR-based surveillance systems that incorporate seasonality and other long-term trends would discover outbreaks of acute respiratory infections (ARI) sooner than systems that only consider the recent past. conditions, SARIMA could reduce detection delay by 5-16 days. It also was more sensitive at detecting the summer wave of the 2009 influenza pandemic. Time series modeling of long-term historical EMR data can reduce the time it takes to discover epidemics of ARI. Realistic surveillance simulations may prove invaluable to optimize system design and tuning. 
 Title: Can long-term historical data from electronic medical records improve surveillance for epidemics of acute respiratory infections? A systematic evaluation


Output: True