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: 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

A: False
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Q: Paragraph: Background: Adverse events are associated with significant morbidity, mortality and cost in hospitalized patients. Measuring adverse events is necessary for quality improvement, but current detection methods are inaccurate, untimely and expensive. The advent of electronic health records and the development of automated methods for encoding and classifying electronic narrative data, such as natural language processing, offer an opportunity to identify potentially better methods. The objective of this study is to determine the accuracy of using automated methods for detecting three highly prevalent adverse events: a) hospital-acquired pneumonia, b) catheter-associated bloodstream infections, and c) in-hospital falls. Methods/design: This validation study will be conducted at two large Canadian academic health centres: the McGill University Health Centre (MUHC) and The Ottawa Hospital (TOH). The study population consists of all medical, surgical and intensive care unit patients admitted to these centres between 2008 and 2014. An automated detection algorithm will be developed and validated for each of the three adverse events using electronic data extracted from multiple clinical databases. A random sample of MUHC patients will be used to develop the automated detection algorithms (cohort 1, development set). The accuracy of these algorithms will be assessed using chart review as the reference standard. Then, receiver operating characteristic curves will be used to identify optimal cut points for each of the data sources. Multivariate logistic regression and the areas under curve (AUC) will be used to identify the optimal combination of data sources that maximize the accuracy of adverse event detection. The most accurate algorithms will then be validated on a second random sample of MUHC patients (cohort 1, validation set), and accuracy will be measured using chart review as the reference standard. The most accurate algorithms validated at the MUHC will then be applied to TOH data (cohort 2), and their accuracy will be assessed using a reference standard assessment of the medical chart. Discussion: There is a need for more accurate, timely and efficient measures of adverse events in acute care hospitals. This is a critical requirement for evaluating the effectiveness of preventive interventions and for tracking progress in patient safety through time.
Title: Accuracy of using automated methods for detecting adverse events from electronic health record data: a research protocol

A: True
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Q: Paragraph: The aim of this review is to examine the causes, pathophysiology and experimental models of noninfectious pharyngitis (sore throat). Introduction The causes of sore throat can be infectious (viruses, bacteria, and fungi) or non-infectious, although the relative proportion of each is not well documented. Methods A PubMed database search was performed for studies of non-infectious sore throat. Results and conclusions Non-infectious causes of sore throat include: physico-chemical factors, such as smoking, snoring, shouting, tracheal intubation, medications, or concomitant illness; and environmental factors including indoor and outdoor air pollutants, temperature and humidity, and hazardous or occupational irritants. The pathophysiology underlying non-infectious sore throat is largely uncharacterised, although neurogenic inflammation looks to be a promising candidate. It is likely that there will be individual disposition factors or the coincidence of more than one irritant with possible-up to now unknown-interactions between them. Therefore, experimental models with defined conditions and objective endpoints are needed. A new model using cold dry air to directly induce pharyngeal irritation in humans, with pharyngeal lavage to measure biomarkers, may provide a useful tool for the study of mechanisms and treatment of non-infectious sore throat.
Title: Environmental and non-infectious factors in the aetiology of pharyngitis (sore throat)

A:
True
****