In this task, you are given a paragraph (from a research paper) and your task is to classify each sentence of the paragraph (assume n sentence) into the following categories: Background, Purpose, Method, Finding/Contribution, or Other. Return the output in this format: 1 - category of sentence 1, 2 - category of sentence 2, ..., n - category of sentence n; where each number indicates the order of the sentence. The categories can be identified using the following questions: 
 Background: - Why is this problem important? - What relevant works have been done before? - What did the previous works miss? - What are the high-level research questions? - How might this help other researchers?
 Purpose: - What specific things do the researchers want to do? - What specific knowledge do the researchers want to know? - What specific hypothesis do the researchers want to test?
 Method: - How did the researchers do it or find it out? - What are the procedures and steps of this research?
 Finding/Contribution: - What did the researchers find out? Did the proposed methods work? - Did things behave as the researchers expected?
Other: put every text fragment that does not fit into any of the categories above here. Put a sentence here if its not in English, is not part of the article, contains numbers and dates, is a caption of a figure or a table, is a formatting error, or you are not sure about it.

Input: Consider Input: Public Health jo urnal homepage: www .e lse vi er.co m/ pu he p u b l i c h e a l t h 1 5 0 ( 2 0 1 7 ) 1 4 9 e1 5 1.

Output: 1 - other, 2 - other


Input: Consider Input: The substantial winter influenza peak in temperate climates has lead to the hypothesis that cold and/or dry air is a causal factor in influenza variability. We examined the relationship between cold and/or dry air and daily influenza and pneumonia mortality in the cold season in the New York metropolitan area from 1975-2002. We conducted a retrospective study relating daily pneumonia and influenza mortality for New York City and surroundings from 1975-2002 to daily air temperature, dew point temperature (a measure of atmospheric humidity), and daily air mass type. We identified high mortality days and periods and employed temporal smoothers and lags to account for the latency period and the time between infection and death. Unpaired t-tests were used to compare high mortality events to non-events and nonparametric bootstrapped regression analysis was used to examine the characteristics of longer mortality episodes. We found a statistically significant (p = 0.003) association between periods of low dew point temperature and above normal pneumonia and influenza mortality 17 days later. The duration (r = 20.61) and severity (r = 20.56) of high mortality episodes was inversely correlated with morning dew point temperature prior to and during the episodes. Weeks in which moist polar air masses were common (air masses characterized by low dew point temperatures) were likewise followed by above normal mortality 17 days later (p = 0.019). This research supports the contention that cold, dry air may be related to influenza mortality and suggests that warning systems could provide enough lead time to be effective in mitigating the effects.

Output: 1 - background, 2 - purpose, 3 - method, 4 - method, 5 - method, 6 - finding, 7 - finding, 8 - finding, 9 - finding, 10 - finding, 11 - finding, 12 - finding


Input: Consider Input: To assess the risk of infectious bacterial aerosols leaking to the environment, the filtration efficiency of a biosafety level 3 (BSL-3) laboratory high-efficiency particulate (HEPA) filter was investigated using the aerosolized bacteria Serratia marcescens. The aerosol size was measured using an Andersen sampler. Eight first stage HEPA filters (numbered 1-8) were distributed in contaminated labs and exhausts from each of the first stage HEPA filters were aggregated and filtered through one second stage HEPA filter before being released to the environment. In total, 8 first-stage and 1 second-stage HEPA filters from the BSL-3 air purification system were analyzed. No S. marcescens was detected in first stage filters 1, 2, 4, 5, 7 and 8 and the second stage HEPA filter. The filtration efficiencies against aerosolized S. marcescens were >99.9999%. First stage filter numbers 3 and 6 had filtration efficiencies of 99.9825% and 99.9906%, respectively. When filter number 3 was replaced by a new filter and the bracket for filter number 6 was sealed, no aerosolized S. marcescens was detected in the filtered air. Our work suggests that the BSL-3 laboratory HEPA filter air purification system is effective against bacterial aerosols, with little to no bacterial leakage into the environment.


Output: 1 - purpose, 2 - method, 3 - method, 4 - method, 5 - method, 6 - finding, 7 - finding, 8 - finding, 9 - finding, 10 - finding, 11 - finding, 12 - finding, 13 - finding, 14 - finding