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: Benchmarks and metrics related to laboratory test utilization are based on evidence-based medical literature that may suffer from a positive publication bias. Guidelines are only as good as the data reviewed to create them. Disruptive technologies require time for appropriate use to be established before utilization review will be meaningful. Metrics include monitoring the use of obsolete tests and the inappropriate use of lab tests. Test utilization by clients in a hospital outreach program can be used to monitor the impact of new clients on lab workload. A multi-disciplinary laboratory utilization committee is the most effective tool for modifying bad habits, and reviewing and approving new tests for the lab formulary or by sending them out to a reference lab. 
 Title: Establishing benchmarks and metrics for disruptive technologies, inappropriate and obsolete tests in the clinical laboratory

Output: False


Input: Consider Input: Paragraph: was first discovered in 2012. MERS-CoV can infect multiple host species and cause severe diseases in human. We conducted a series of phylogenetic and bioinformatic analyses to study the evolution dynamics of MERS-CoV among different host species with genomic data. Our analyses show: 1) 28 potential recombinant sequences were detected and they can be classified into seven potential recombinant types; 2) The spike (S) protein of MERS-CoV was under strong positive selection when Middle East Respiratory Syndrome coronavirus (MERS-CoV) is a novel beta-coronavirus with high pathogenicity, which imposes a serious threat to human health 1 . Substantial evidence has showed that MERS-CoVs have existed in central and east Africa for decades 2,3 , and have many natural hosts including two species of bats (Neoromicia capensis and Vespertilio superans), dromedary camel (Camelus dromedarius), and European hedgehog (Erinaceus europaeus) 4-7 . Yet it seemed that human MERS-CoV first isolated in Saudi Arabian in 2012, and then spread among humans worldwide 8 . Studies of prototype human MERS-CoV also suggested that the tMRCA (the time of most recent common ancestor) of human MERS-CoV can be traced back to about 2011 9 . Because the genome sequence of bat MERS-CoV is highly identical to that of human MERS-CoV, it has been indicated that human MERS-CoV might have a bat origin 10 , while there is also some evidence of camel-to-human MERS-CoV transmission 11,12 . Together, these studies proposed that zoonotic event may play a nontrivial part in MERS-CoV evolution and transmission. Previous studies showed that recombination was common among the members of beta-coronavirus 13,14 . By joining the previously unlinked DNA, recombination event can create new viral strains which may be capable of infecting new hosts and evading host's immuno-responses. The phylogenetic analysis showed that there were two main MERS-CoV clades-clade A and B, and clade B can be further divided into five phylogenetic groups 15 . There is evidence that recombination event had happened between group III and group V 15 . However, whether there was potential recombination event happened between the other groups or among multiple phylogenetic groups remains unclear. The genome of MERS-CoV is over 30,000 nucleotides (nt) in length, which contains seven predicted open reading frames (ORFs) and four structural genes-spike (S), envelope (E), membrane (M), and nucleocapsid (N) 16 (supplementary Fig. 1c ). The surface located spike (S) protein of beta-coronaviruses is one of the major determinants in their cross-species transmission because it mediates the virus-receptor recognition and thereby activates viral infection process 17 . Additionally, the receptor binding domain (RBD) on S protein's N-terminal is the key element for beta-coronavirus entering into host cells and the mutations in coronavirus's RBD affects its infection and cross-species capability 18, 19 . For example, the study of the spike protein from severe acute respiratory syndrome coronavirus (SARS-CoV), another beta-coronavirus with high pathogenicity, revealed four amino 
 Title: Evolutionary Dynamics of MERS- CoV: Potential Recombination, Positive Selection and Transmission OPEN

Output: False


Input: Consider Input: Paragraph: Health-Emergency Disaster Risk Management (Health-EDRM) emerged as the latest knowledge, research and policy paradigm shift from response to preparedness and health risk management in non-emergency times [1] . This approach attempts to enlist and empower communities to invest and emphasize their disaster health risk reduction efforts, thereby strengthening health systems and supporting community health resilience building. This Special Issue has collected 20 scientific papers that attempt to examine the research frontier in Health-EDRM. Major Health-EDRM research evidence gaps were found during a global research agenda setting meeting of the 2018 WHO Health-EDRM global research group in Kobe. Kayano, Chan, Murry et al. [2] highlighted the development need for relevant research methodologies, risk communication approaches, health data management strategies, practical health emergency study ethical guidelines, bridging global research capacity disparities, and infrastructure constraints, to ensure knowledge advancement in Health-EDRM. The authors also pointed out the lack of understanding of psychosocial health risk profiling in population subgroups. Reifel's analysis showed a better understanding of current doctrines and practices in both clinical mental health practices and policy, which will help to bridge the conceptual interlinkages between the preventive-based disaster risk reduction policy agenda and the curative-focused disaster mental health discipline [3] . Genereux, Schluter, Tamahashi et al. [4] argued that standardizing psychometrically robust instruments would also be urgently needed to identify at-risk patients throughout-before, during, and after emergencies and disasters-to ensure that mental and social health needs are addressed throughout the pathway of care (prevention, screening, diagnosis, treatment, and rehabilitation). Aung, Murry and Kayano [5] discussed the need for new research and ethical guidelines to harmonize research efforts in Health-EDRM and Kubo, Yanasan, Herbosa et al. [6] described the challenges in the standardization of health data collection throughout the research processes. Existing surveillance databases, new study tools, and innovation methodologies may help to identify population health risks and support Health-EDRM policy development. Using a syndromic surveillance database in the Philippines, Salazar, Law, Winkler [7] showed how an existing clinical based database might be useful in assisting emergency health service planning decision making during outbreaks in armed conflict. Even with the database limitations to report injuries and death, this existing data system was nevertheless useful to support non-communicable diseases' service caseload planning. Using the computerized random digit dialling methods for rapid data collection after a major urban subway fire incident, Chan, Huang, Hung et al. [8] captured health risk perception, misconceptions, and community first-aid response knowledge in urban man-made emergency incidents. Using social media data from Twitter, Gruebner, Lowe, Sykora et al. [9] showed how the spatio-temporal distribution of Int. 
 Title: Environmental Research and Public Health Editorial Research Frontiers of Health Emergency and Disaster Risk Management: What Do We Know So Far?


Output: False