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: OBJECTIVE: To determine the frequency, etiology and impact of respiratory viral infection (RVI) on infants evaluated for late-onset sepsis (LOS), defined as sepsis occurring 472 h of life, in the neonatal intensive care unit. STUDY DESIGN: Prospective observational study conducted from 6 March 2014 to 3 May 2016 on infants evaluated for LOS. PCR viral panel performed on nasopharyngeal specimens among infants with clinical suspicion for RVI. Sequence analysis was performed to determine viral subtypes. Fisher's exact or χ 2 tests were done to determine the impact of RVI. RESULTS: During the 26-month study, there were 357 blood cultures obtained for LOS evaluations, 29 (8%) had a respiratory virus detected. Only 88 (25%) of infants evaluated for LOS also had clinical suspicion for a respiratory viral infection. RSV (14 of 29; 48%) was the predominant virus detected. Almost all infants (13 of 14; 93%) with RSV required increased respiratory support. Antimicrobial therapy was withheld or discontinued on most infants with a virus detected (18 of 29; 62%) and in the majority where there was no confirmed bacterial co-infection (18 of 20; 90%). CONCLUSION: The incidence of RVI in infants being evaluated for LOS is about 8%. RVI should be considered in LOS evaluation to prevent unnecessary antibiotic therapy. 
 Title: Incidence of respiratory viral infection in infants with respiratory symptoms evaluated for late-onset sepsis

Output: False


Input: Consider Input: Paragraph: Contact patterns among hosts are considered as one of the most critical factors contributing to unequal pathogen transmission. Consequently, networks have been widely applied in infectious disease modeling. However most studies assume static network structure due to lack of accurate observation and appropriate analytic tools. In this study we used high temporal and spatial resolution animal position data to construct a high-resolution contact network relevant to infectious disease transmission. The animal contact network aggregated at hourly level was highly variable and dynamic within and between days, for both network structure (network degree distribution) and individual rank of degree distribution in the network (degree order). We integrated network degree distribution and degree order heterogeneities with a commonly used contact-based, directly transmitted disease model to quantify the effect of these two sources of heterogeneity on the infectious disease dynamics. Four conditions were simulated based on the combination of these two heterogeneities. Simulation results indicated that disease dynamics and individual contribution to new infections varied substantially among these four conditions under both parameter settings. Changes in the contact network had a greater effect on disease dynamics for pathogens with smaller basic reproduction number (i.e. R 0 , 2). 
 Title: Highly dynamic animal contact network and implications on disease transmission

Output: True


Input: Consider Input: Paragraph: Motivation: Understanding the relationship between the sequence, structure, binding energy, binding kinetics and binding thermodynamics of protein-protein interactions is crucial to understanding cellular signaling, the assembly and regulation of molecular complexes, the mechanisms through which mutations lead to disease, and protein engineering. Results: We present SKEMPI 2.0, a major update to our database of binding free energy changes upon mutation for structurally resolved protein-protein interactions. This version now contains manually curated binding data for 7085 mutations, an increase of 133%, including changes in kinetics for 1844 mutations, enthalpy and entropy changes for 443 mutations, and 440 mutations, which abolish detectable binding. 
 Title: Structural bioinformatics SKEMPI 2.0: an updated benchmark of changes in protein-protein binding energy, kinetics and thermodynamics upon mutation


Output: True