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: Flu response centre Public health Helpline Emerging disease s u m m a r y Objective: To assess the operational experience and knowledge of staff who worked in the West Midlands Flu Response Centre (FRC) during the 'containment' phase of influenza A(H1N1)pdm09. using an online self-administered questionnaire. The questionnaire included sections related to the respondents' FRC experience, knowledge about influenza A(H1N1)pdm09 and the containment phase. Results: This study had a 51% (89/176) response rate. Of the respondents, 59% were female, 64% were of White ethnicity, 55% were clinicians, 46% were aged 25e44 years, and 67% had no previous call centre experience. A significant proportion (P < 0.001) of respondents believed that the FRC had made a positive contribution to the public health management of the containment phase. Nearly all respondents indicated that they were familiar with the terms 'pandemic flu' or 'influenza pandemic' (99%), understood the aim of the containment phase (90%), and knew the severity of the illness caused by the virus (97%). However, specific knowledge was lacking regarding a number of public health interventions, and overall knowledge scores for clinicians and non-clinicians were similar. Conclusion: This study is the first to report on the characteristics of FRC staff during the containment phase of influenza A(H1N1)pdm09 pandemic. Although overall, staff evaluation of the West Midlands FRC was very positive, a number of knowledge gaps were identified. This study provides valuable insights which can contribute to preparedness planning. 
 Title: Characteristics of flu response centre staff in the West Midlands

Output: False


Input: Consider Input: Paragraph: Mechanistic hypotheses about airborne infectious disease transmission have traditionally emphasized the role of coughing and sneezing, which are dramatic expiratory events that yield both easily visible droplets and large quantities of particles too small to see by eye. Nonetheless, it has long been known that normal speech also yields large quantities of particles that are too small to see by eye, but are large enough to carry a variety of communicable respiratory pathogens. Here we show that the rate of particle emission during normal human speech is positively correlated with the loudness (amplitude) of vocalization, ranging from approximately 1 to 50 particles per second (0.06 to 3 particles per cm 3 ) for low to high amplitudes, regardless of the language spoken (english, spanish, Mandarin, or Arabic). Furthermore, a small fraction of individuals behaves as "speech superemitters," consistently releasing an order of magnitude more particles than their peers. our data demonstrate that the phenomenon of speech superemission cannot be fully explained either by the phonic structures or the amplitude of the speech. these results suggest that other unknown physiological factors, varying dramatically among individuals, could affect the probability of respiratory infectious disease transmission, and also help explain the existence of superspreaders who are disproportionately responsible for outbreaks of airborne infectious disease. It has long been recognized that particles expelled during human expiratory events, such as sneezing, coughing, talking, and breathing, serve as vehicles for respiratory pathogen transmission 1-6 . The relative contribution of each expiratory activity in transmitting infectious microorganisms, however, remains unclear 4 . Much previous research has focused on coughing 7-12 and sneezing 11,13,14 activities that yield relatively large droplets (approximately 50 μm or larger) easily visible to the naked eye. Less noticeable, but arguably more infectious for some diseases, are the smaller particles emitted during sneezing and coughing as well as during breathing 15-17 and talking 16, 18, 19 . These small particles are believed to be generated during breathing and talking from the mucosal layers coating the respiratory tract via a combination of a "fluid-film burst" mechanism within the bronchioles and from vocal folds adduction and vibration within the larynx 6,20,21 . The particles emitted during breathing and typical speech predominantly average only 1 μm in diameter 15-17 and are thus too small to see without specialized equipment; most people outside of the community of bioaerosol researchers are less aware of them. Despite their small size, however, these micron-scale particles are sufficiently large to carry a variety of respiratory pathogens such as measles virus (50-500 nm) 22 , influenza virus (100 nm-1 µm) 23 , and Mycobacterium tuberculosis (1-3 µm) 24 . Indeed, recent work by Yan et al. has confirmed that significant amounts of influenza viral RNA are present in small particles (<5 μm) emitted by influenza-infected individuals during natural breathing, without coughing or sneezing 25 . These small particles are potentially more infectious than larger sneeze-or 
 Title: Aerosol emission and superemission during human speech increase with voice loudness

Output: False


Input: Consider Input: Paragraph: The very rapid growth in molecular sequence data from the daily accretion of large gene and protein sequencing projects have led to issues regarding viewing and analyzing the massive amounts of data. Graphical representation and numerical characterization of DNA, RNA and protein sequences have exhibited great potential to address these concerns. We review here in brief several different formulations of these representations and examples of applications to diverse problems based on what this author had presented at the Second Mathematical Chemistry Workshop of the Americas in Bogota, Colombia in 2010. In particular, we note several insights that were gained from such representations, and the applications to the bio-medicinal field. 
 Title: The GRANCH Techniques for Analysis of DNA, RNA and Protein Sequences


Output: True