<|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:"Modelling mobile opportunistic networks - From mobility to structural and behavioural analysis."
Abstract:"In this work, we propose a modelling framework which captures the most fundamental behavioural and structural properties of mobile opportunistic networks from mobility to structural level. First, we introduce Spatio-TEmporal Parametric Stepping (STEPS) a simple parametric mobility model which can cover a large spectrum of human mobility patterns. STEPS abstracts the fundamental spatio-temporal behaviours of human mobility, i.e., preferential attachment and attractors, by using a power law to drive nodes' movement. We show that the model makes it possible to express key peer-to-peer properties of opportunistic networks such as inter-contact/contact time distributions. Leveraging on the expressive and modelling power of STEPS, we analyse how fundamental structural properties can emerge from the combination of elementary node's mobility behaviour. Specifically, we bring out one sufficient condition of the emergence of the famous small-world structure in opportunistic networks. We also show that this special dynamic network structure improves significantly the communication capacity of opportunistic networks. (C) 2014 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: 

Q1 = [];
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Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:

Modelling mobile opportunistic networks - From mobility to structural and behavioural analysis
In this work, we propose a modelling framework which captures the most fundamental behavioural and structural properties of mobile opportunistic networks from mobility to structural level. First, we introduce Spatio-TEmporal Parametric Stepping (STEPS) a simple parametric mobility model which can cover a large spectrum of human mobility patterns. STEPS abstracts the fundamental spatio-temporal behaviours of human mobility, i.e., preferential attachment and attractors, by using a power law to drive nodes' movement. We show that the model makes it possible to express key peer-to-peer properties of opportunistic networks such as inter-contact/contact time distributions. Leveraging on the expressive and modelling power of STEPS, we analyse how fundamental structural properties can emerge from the combination of elementary node's mobility behaviour. Specifically, we bring out one sufficient condition of the emergence of the famous small-world structure in opportunistic networks. We also show that this special dynamic network structure improves significantly the communication capacity of opportunistic networks. (C) 2014 Elsevier B.V. All rights reserved.