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".

Ex Input:
Paragraph: Middle East Respiratory Syndrome Coronavirus (MERS-CoV) is one of the major threats to the healthcare systems in some countries, especially in the Arabian Peninsula. MERS-CoV is considered an ideal example of the One Health concept. This is due to the animals, especially dromedary camels, play important roles in the transmission and sustainability of the virus, and the virus can be transmitted through aerosols of infected patients into the environment. However, there is some debate regarding the origin of MERS-CoV either from bats or other unknown reservoirs. The dromedary camel is the only identified animal reservoir to date. These animals play important roles in sustaining the virus in certain communities and may act as an amplifier of the virus by secreting it in their body fluids, especially in nasal and rectal discharges. MERS-CoV has been detected in the nasal and rectal secretions of infected camels, and MERS-CoV of this origin has full capacity to infect human airway epithelium in both in vitro and in vivo models. Other evidence confirms the direct transmission of MERS-CoV from camels to humans, though the role of camel meat and milk products has yet to be well studied. Human-to-human transmission is well documented through contact with an active infected patient or some silently infected persons. Furthermore, there are some significant risk factors of individuals in close contact with a positive MERS-CoV patient, including sleeping in the same patient room, removing patient waste (urine, stool, and sputum), and touching respiratory secretions from the index case. Outbreaks within family clusters have been reported, whereby some blood relative patients were infected through their wives in the same house were not infected. Some predisposing genetic factors favor MERS-CoV infection in some patients, which is worth investigating in the near future. The presence of other comorbidities may be another factor. Overall, there are many unknown/confirmed aspects of the virus/human/animal network. Here, the most recent advances in this context are discussed, and the possible reasons behind the emergence and sustainability of MERS-CoV in certain regions are presented. Identification of the exact mechanism of transmission of MERS-CoV from camels to humans and searching for new reservoir/s are of high priority. This will reduce the shedding of the virus into the environment, and thus the risk of human infection can be mitigated. 
 Title: Middle East Respiratory Syndrome Coronavirus and the One Health concept

Ex Output:
False


Ex Input:
Paragraph: Purpose: COVID-19 has become global threaten. CT acts as an important method of 60 diagnosis. However, human-based interpretation of CT imaging is time consuming. 61 More than that, substantial inter-observer-variation cannot be ignored. We aim at 62 developing a diagnostic tool for artificial intelligence (AI)-based classification of CT 63 images for recognizing COVID-19 and other common infectious diseases of the lung. 64 Experimental Design: In this study, images were retrospectively collected and 65 prospectively analyzed using machine learning. CT scan images of the lung that show 66 or do not show COVID-19 were used to train and validate a classification framework 67 based on convolutional neural network. Five conditions including COVID-19 68 pneumonia, non-COVID-19 viral pneumonia, bacterial pneumonia, pulmonary 69 tuberculosis, and normal lung were evaluated. Training and validation set of images 70 were collected from Wuhan Jin Yin-Tan Hospital whereas test set of images were 71 collected from Zhongshan Hospital Xiamen University and the fifth Hospital of 72 Wuhan. 73 Results: Accuracy, sensitivity, and specificity of the AI framework were reported. For 74 test dataset, accuracies for recognizing normal lung, COVID-19 pneumonia, 75 non-COVID-19 viral pneumonia, bacterial pneumonia, and pulmonary tuberculosis 76 were 99.4%, 98.8%, 98.5%, 98.3%, and 98.6%, respectively. For the test dataset, 77 accuracy, sensitivity, specificity, PPV, and NPV of recognizing COVID-19 were 78 98.8%, 98.2%, 98.9%, 94.5%, and 99.7%, respectively. 79 All rights reserved. No reuse allowed without permission. the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 
 Title: Deep Learning-Based Recognizing COVID-19 Deep Learning-Based Recognizing COVID-19 and other Common Infectious Diseases of the Lung by Chest CT 2 Scan Images

Ex Output:
False


Ex Input:
Paragraph: Ocular disorders of rabbits and rodents are caused by genetic defects, infections, nutritional deficiencies, congenital malformations, as well as environmental and management problems. Their investigation and diagnosis rely on implementation of diagnostic approaches and instrumentation used commonly for other companion animal species. Special considerations of importance include the small size of the eye in some species, necessitating use of magnification for accurate assessment, and the vulnerability of some species to complications of parenteral and even topical antibiotic and anti-inflammatory therapy. Copyright 9 1997 by W. B. Saunders Company. 
 Title: Rabbit and Rodent Ophthalmology

Ex Output:

True