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".
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Question: Paragraph: This study numerically investigated the thermal effect of human body on the time-dependent dispersion of cough droplets with evaporation process. The thermal flow of human body was imitated using a 3D thermal manikin with real body features, while a recent developed multi-component Eulerian-Lagrangian approach was used to address the effects of inhomogeneous temperature and humidity fields on droplet evaporation. By comparing the results yielded without and with the human body heat, the outcomes demonstrated strong impact of human body heat on the droplets mass fraction and local air velocity distributions. Inspirable droplets could potentially drop into respirable droplets by evaporation, although the evaporation rate was not significantly affected by body heat. The thermal effect of human body revealed its vital impacts on the time-dependent droplets dispersion. Due to the buoyancy driven thermal flow, both the vertical velocity and displacement of small droplets (20 m) were completely reversed from descending to ascending, while the deposition time of large droplets (50 m) were significantly delayed. With the reduced droplet size by evaporation and droplets lifted into breathing zone by human thermal effect, the inhalability and infection risks of cough droplets would be much higher in real occupied indoor spaces.
Title: Thermal effect of human body on cough droplets evaporation and dispersion in an enclosed space

Answer: True

Question: 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

Answer: True

Question: Paragraph: Acute viral bronchiolitis is a major cause of morbidity and mortality in infants. 1,2 Bronchiolitis, which literally means inflammation of the bronchioles, was first described more than 150 years ago as 'congestive catarrhal fever' to illustrate the clinical pattern of fever, rhinorrhoea, wheezing, crepitations, dyspnoea and difficulty feeding. It was not until 1957 that the epidemiology and viral aetiology were first described. 3 Respiratory syncytial virus (RSV) is the main virus to cause bronchiolitis and is associated with over 75% of cases where a pathogen has been isolated. 4 Other viruses, including
Title: Innate immune response and bronchiolitis and preschool recurrent wheeze

Answer:
False