TASK DEFINITION: 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".
PROBLEM: Paragraph: The majority of human emerging infectious diseases (EIDs) are zoonotic, with viruses originating in wild mammals of particular concern (e.g. HIV, Ebola, SARS) 1-3 . Understanding patterns of viral diversity in wildlife and determinants of successful cross-species transmission, or spillover, are therefore key goals for pandemic surveillance programs 4 . However, few analytical tools exist to identify which host species likely harbor the next human virus, or which viruses can cross species boundaries 5-7 . Here we conduct the most comprehensive analysis yet of mammalian hostvirus relationships and show that both the total number of viruses that infect a given species, and the proportion likely to be zoonotic are predictable. After controlling for research effort, the proportion of zoonotic viruses per species is predicted by phylogenetic relatedness to humans, host taxonomy, and human population within a species range -which may reflect human-wildlife contact. We demonstrate for the first time that bats harbor a significantly higher proportion of zoonotic viruses than all other mammalian orders. We identify the taxa and geographic regions with the largest estimated number of 'missing viruses' and 'missing zoonoses' and therefore of highest value for future surveillance. We then show that phylogenetic host breadth and other viral traits are significant predictors of zoonotic potential, providing a novel framework to assess if a newly discovered mammalian virus could infect people. Viral zoonoses are a serious threat to public health and global security, and have caused the majority of recent pandemics in people 4 , yet our understanding of the factors driving viral diversity in mammals, viral host range, and cross-species transmission to humans remain nascent. Recent studies have described broad patterns of pathogen host range 1,3 and various host or microbial factors that facilitate cross-species transmission 5,7,8 , or have focused on Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature. All datasets (host traits, viral traits, full list of host-virus associations and associated references, phylogenetic trees, and phylogenetic distance matrices) along with the R code and R package dependencies needed to fully replicate and evaluate these analyses are provided at http://doi.org/10.5281/zenodo.569079. The top-level README.txt file in the directory details the file structure and metadata provided. 
 Title: Host and viral traits predict zoonotic spillover from mammals HHS Public Access

SOLUTION: False

PROBLEM: Paragraph: Autoregressive distributed lag (ARDL) approach Economic growth Error correction model US air travel and freight demand a b s t r a c t This paper examines the short-and long-run effects of economic growth and market shocks (e.g., 9/11 terrorist attacks, Iraq war, SARS epidemic, and 2008 financial crisis) on air passenger and freight services using an autoregressive distributed lag (ARDL) approach to cointegration. Results show that, in the longrun, both air passenger and freight services tend to increase with economic growth. In the short-run, however, only air passenger service is responsive to economic growth. Finally, only the 9/11 terrorist attacks and the SARS have detrimental effects on air passenger demand both in the short-and long-run, and in the long-run, respectively. However, these market shocks are found to have little impact on air freight demand. 
 Title: Dynamic relationship between air transport demand and economic growth in the United States: A new look

SOLUTION: False

PROBLEM: Paragraph: The NIAID (National Institute for Allergy and Infectious Diseases) Biodefense Proteomics program aims to identify targets for potential vaccines, therapeutics, and diagnostics for agents of concern in bioterrorism, including bacterial, parasitic, and viral pathogens. The program includes seven Proteomics Research Centers, generating diverse types of pathogen-host data, including mass spectrometry, microarray transcriptional profiles, protein interactions, protein structures and biological reagents. The Biodefense Resource Center (www.proteomicsresource.org) has developed a bioinformatics framework, employing a protein-centric approach to integrate and support mining and analysis of the large and heterogeneous data. Underlying this approach is a data warehouse with comprehensive protein + gene identifier and name mappings and annotations extracted from over 100 molecular databases. Value-added annotations are provided for key proteins from experimental findings using controlled vocabulary. The availability of pathogen and host omics data in an integrated framework allows global analysis of the data and comparisons across different experiments and organisms, as illustrated in several case studies presented here. (1) The identification of a hypothetical protein with differential gene and protein expressions in two host systems (mouse macrophage and human HeLa cells) infected by different bacterial (Bacillus anthracis and Salmonella typhimurium) and viral (orthopox) pathogens suggesting that this protein can be prioritized for additional analysis and functional characterization. (2) The analysis of a vaccinia-human protein interaction network supplemented with protein accumulation levels led to the identification of human Keratin, type II cytoskeletal 4 protein as a potential therapeutic target. (3) Comparison of complete genomes from pathogenic variants coupled with experimental information on complete proteomes allowed the identification and prioritization of ten potential diagnostic targets from Bacillus anthracis. The integrative analysis across data sets from multiple centers can reveal potential functional significance and hidden relationships between pathogen and host proteins, thereby providing a systems approach to basic understanding of pathogenicity and target identification. 
 Title: Systems Integration of Biodefense Omics Data for Analysis of Pathogen-Host Interactions and Identification of Potential Targets

SOLUTION:
False