<|begin_of_text|><|start_header_id|>system<|end_header_id|>You are an expert on climate change, human mobility and migration. Answer the question truthfully.<|eot_id|><|start_header_id|>user<|end_header_id|>Here are the title and abstract of a scientific paper probably related to climate change, human mobility and migration..
Title:"ExMin: A routing metric for novel opportunity gain in Delay Tolerant Networks."
Abstract:"Delay Tolerant Networks (DTNs) are characterized by intermittently connected links formed by mobile nodes' probabilistic encounters. Most DTN routing techniques use the first encountered node who has smaller routing metric as a relay node. Prior work on DTN routing can be broadly classified into one which takes the minimum out of expected delays for all possible individual routing paths, referred to as MinEx, as a routing metric to decide the next hop relay node. Fundamentally, MinEx has no difference from the shortest path computation in conventional multi-hop networks, where a link weight is the expected inter-meeting time. However in DTNs, nodes meet intermittently by their mobility, hence the links formed from the meetings are probabilistic. In this environment, MinEx often fails to accurately estimate the actual delay since opportunism in nodes' intermittent meeting is not properly taken into account. In this paper, to exploit the true opportunism, we first propose a metric called ExMin which stochastically calculates the metric by taking the expectation of the minimum delays over all possible routes. We further show that ExMin can be computed online by relying only on local information sharing. Our extensive experiments involving three realistic network scenarios created by two vehicle traces (about 1500 Shanghai taxies and 500 San Francisco taxies) and one human mobility trace (93 KAIST students) show that ExMin outperforms MinEx by up to 30% under either of DTN environments allowing single-copy or multi-copies of a packet. (C) 2013 Elsevier B.V. All rights reserved.."
I have six questions you need to answer.
Q1: Is this article is about 'human migration mobility': 1 = yes; 0 = no. Answer with a number. Do not give a textual explanation.

Q2: What drivers of migration and mobility does the article study? 0 = 'other', 1 = 'climate', 2 = 'environment', 3 = 'economic', 4 = 'conflict', 5 = 'political', 6 = 'social', 7 = 'family'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q3: What is the overall sentiment of the article?:0 = 'neutral', 1 = 'negative', 2 = 'positive'. Answer with a number. Do not give a textual explanation.

Q4: What type of climate or environmental keywords are explicitly mentioned?:  0 = 'none', 1 = 'algal blooms', 2 = 'infestation', 3 = 'infectious diseases', 4 = 'ocean acidification', 5 = 'sea ice', 6 = 'acid rain', 7 = 'drought', 8 = 'cold wave', 9 = 'heat wave', 10 = 'glacial', 11 = 'wildfire', 12 = 'air pollution', 13 = 'biodiversity loss', 14 = 'coastal erosion', 15 = 'land degradation', 16 = 'deforestation', 17 = 'desertification', 18 = 'water pollution', 19 = 'diebacks', 20 = 'permafrost loss', 21 = 'sand mining', 22 = 'sea level rise', 23 = 'earthquake', 24 = 'tsunami', 25 = 'volcanic', 26 = 'flood', 27 = 'avalanche', 28 = 'landslide', 29 = 'downburst', 30 = 'thunderstorm', 31 = 'sandstorm', 32 = 'haze', 33 = 'storm', 34 = 'cyclone', 35 = 'blizzard', 36 = 'hail', 37 = 'snow', 38 = 'tornado', 39 = 'wind', 40 = 'hurricane', 41 = 'typhoon', 42 = 'other'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q5: What discipline does the article belong to?: 0 = 'other', 1 = 'social science', 2 = 'natural science', 3 = 'arts and humanities', 4 = 'multidiscipline and interdiscipline'. Answer with a number. Do not give a textual explanation.

Q6: Does the article apply quantitative and/or statistical analysis?: 0 = 'no', 1 = 'yes'. Answer with a number. Do not give a textual explanation.

Use the following template: 

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Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
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ExMin: A routing metric for novel opportunity gain in Delay Tolerant Networks
Delay Tolerant Networks (DTNs) are characterized by intermittently connected links formed by mobile nodes' probabilistic encounters. Most DTN routing techniques use the first encountered node who has smaller routing metric as a relay node. Prior work on DTN routing can be broadly classified into one which takes the minimum out of expected delays for all possible individual routing paths, referred to as MinEx, as a routing metric to decide the next hop relay node. Fundamentally, MinEx has no difference from the shortest path computation in conventional multi-hop networks, where a link weight is the expected inter-meeting time. However in DTNs, nodes meet intermittently by their mobility, hence the links formed from the meetings are probabilistic. In this environment, MinEx often fails to accurately estimate the actual delay since opportunism in nodes' intermittent meeting is not properly taken into account. In this paper, to exploit the true opportunism, we first propose a metric called ExMin which stochastically calculates the metric by taking the expectation of the minimum delays over all possible routes. We further show that ExMin can be computed online by relying only on local information sharing. Our extensive experiments involving three realistic network scenarios created by two vehicle traces (about 1500 Shanghai taxies and 500 San Francisco taxies) and one human mobility trace (93 KAIST students) show that ExMin outperforms MinEx by up to 30% under either of DTN environments allowing single-copy or multi-copies of a packet. (C) 2013 Elsevier B.V. All rights reserved.