In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

Example Input: Ten years after the severe acute respiratory syndrome epidemic, a second coronavirus, the Middle East respiratory syndrome coronavirus (MERS-CoV), has been identified as the cause of a highly lethal pneumonia in patients in the Middle East and in travelers from this region. Over the past 9 months, since the virus was first isolated, much has been learned about the biology of the virus. It is now clear that MERS-CoV is transmissible from person to person, and its close relationship with several bat coronaviruses suggests that these animals may be the ultimate source of the infection. However, many key issues need to be addressed, including identification of the proximate, presumably zoonotic, source of the infection, the prevalence of the infection in human populations, details regarding clinical and pathological features of the human infection, the establishment of a small rodent model for the infection, and the virological and immune basis for the severe disease observed in most patients. Most importantly, we do not know whether a MERS-CoV epidemic is likely or not. Infection with the virus has so far resulted in only 91 cases and 46 deaths (as of 29 July 2013), but it is nonetheless setting off alarm bells among public health officials, including Margaret Chan, Director-General of the World Health Organization, who called MERS-CoV "a threat to the entire world." This article reviews some of the progress that has been made and discusses some of the questions that need to be answered. Citation Perlman S. 2013. The Middle East respiratory syndrome-how worried should we be? mBio 4(4):e00531-13.
Example Output: The Middle East Respiratory Syndrome-How Worried Should We Be? A NOVEL VIRUS IS IDENTIFIED IN SAUDI ARABIA

Example Input: Colibacillosis results from infection with avian pathogenic Escherichia coli bacteria. Healthy broilers are resistant to inhaled E. coli, but previous infection with vaccine or virulent strains of Infectious Bronchitis Virus (IBV) predisposes birds for severe colibacillosis. We investigated whether IBV affects recruitment and function of phagocytic cells and examined NO production, phagocytic and bactericidal activity, and kinetics of peripheral blood mononuclear cells (PBMC) and splenocytes. Moreover, we measured cytokine mRNA expression in lung and spleen samples. Broilers were inoculated with IBV H120 vaccine or virulent M41 and challenged 5 days later with E. coli 506. A PBS control and E. coli group without previous virus inoculation were also included. Birds were sacrificed at various time points after inoculation (h/dpi). Inoculation with IBV induced extended and more severe colibacillosis than with E. coli alone. At 4 dpi, the number of KUL-01 + PBMC in all E. coli-inoculated groups was significantly higher than in PBS-inoculated birds, which correlated with lesion scores. From 1 to 4 dpi, NO production by PBMC from all E. coliinoculated animals was elevated compared to PBS birds. Bactericidal activity of PBMC in IBV-inoculated animals at 7 dpi was lower than in PBS-and E. coli-inoculated birds, but phagocytic capacity and recruitment were not severely impaired. In spleen samples of IBV-infected animals reduced expression of IL-1b, IL-6, IL-8, IL-10, IL-18 and IFN-g mRNA was found 1 dpi. Our results suggest that enhanced colibacillosis after IBV infection or vaccination is caused at least by altered innate immunity and less by impairment of phagocytic cell function. #
Example Output: The role of phagocytic cells in enhanced susceptibility of broilers to colibacillosis after Infectious Bronchitis Virus infection

Example Input: In commercial poultry production there are a number of diseases which are of particular importance due to the heavy economic losses that can arise if a flock becomes infected. The development of an automated and rapid disease detection system would therefore be of considerable benefit to both production and animal welfare. This study represents an intelligence device for diagnosing avian diseases by using Data-mining methods and Dempster-Shafer evidence theory (D-S). 14-day-old chickens were divided into four groups. Each group was deliberately infected with a disease: Newcastle Disease (ND), Bronchitis Virus (BV), Avian Influenenza (AI), and the last group was considered as control samples. Fast Fourier Transform (FFT) and Discrete Wavelet Transform (DWT) were used to process the chicken's sound signals in frequency and time-frequency domains, respectively. In order to achieve information, 25 statistical features from frequency domains, and 75 statistical features from time-frequency domains were extracted. During dimensionality reduction stage, the best features of the sound signals were selected, using improved distance evaluation (IDE) method. The chicken's sound signals were analyzed in two consecutive days after virus infection. Support vector machine (SVM) was used as the classifier in this study. The first classification was done with SVM and based on sound features in frequency and time-frequency domains with accuracy of 41.35 and 83.33%, respectively. The accuracy of the method based on D-S infusion of sound data reached 91.15%. The developed model based on achievement result could diagnose Newcastle Disease, Bronchitis Virus and Avian Influenza from sound signals.
Example Output:
Original papers