<|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:"Understanding the urban mobility community by taxi travel trajectory."
Abstract:"With the increase of urban population and the expansion of urban scale, understanding the urban structure could provide intellectual support for urban planning, traffic congestion, and even the spread of diseases. Little research has addressed the relationship between urban structure and human mobility. In this study, the community division method is applied to the itinerary network generated by taxi trajectory data, and the itinerary network is divided into several modules (called urban mobility communities) . Our results suggest that the urban mobility community has different associated characteristics with travel distance and administrative area. When the travel distance increases, many adjacent communities gradually merge into large ones in the central area, while the communities remain similar in the suburban area. Moreover, we observed some communities around some pivotal roads are distributed as ribbons. The quantitative analysis of community division results demonstrates a phase transition between urban mobility community and travel distance. In particular, inspired by heterogeneous travel distance distribution and community boundary restrictions, we first construct a model that reflects the non-trivial relationship between urban mobility community and travel distance and reveals the phase transition between them. Our study represents the first attempt to prove that human mobility and urban structure can be reflected by each other. (c) 2021 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:

Understanding the urban mobility community by taxi travel trajectory
With the increase of urban population and the expansion of urban scale, understanding the urban structure could provide intellectual support for urban planning, traffic congestion, and even the spread of diseases. Little research has addressed the relationship between urban structure and human mobility. In this study, the community division method is applied to the itinerary network generated by taxi trajectory data, and the itinerary network is divided into several modules (called urban mobility communities) . Our results suggest that the urban mobility community has different associated characteristics with travel distance and administrative area. When the travel distance increases, many adjacent communities gradually merge into large ones in the central area, while the communities remain similar in the suburban area. Moreover, we observed some communities around some pivotal roads are distributed as ribbons. The quantitative analysis of community division results demonstrates a phase transition between urban mobility community and travel distance. In particular, inspired by heterogeneous travel distance distribution and community boundary restrictions, we first construct a model that reflects the non-trivial relationship between urban mobility community and travel distance and reveals the phase transition between them. Our study represents the first attempt to prove that human mobility and urban structure can be reflected by each other. (c) 2021 Elsevier B.V. All rights reserved.