<|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:"An enhanced community-based mobility model for distributed mobile social networks."
Abstract:"Simulation is fundamental tool for the evaluation and validation of the applications and protocols in Mobile Social Networks. However, the limited number of real user traces available and the imposed restrictions of the specific scenarios, make generalization very hard. Therefore, the need has been created for synthetic mobility models. The widely used Random Way-Point Mobility Model has been proven unable to capture characteristics of human mobility such as the social attraction. Consequently, in recent years mobility models based on social network theory, able to capture the temporal and spatial dependencies of mobile social networks, are being designed. In this paper the Enhanced Community Mobility Model (ECMM) is introduced. It follows preceding community-based approaches, that map communities to a topological space. Its main contribution is the introduction of new features, such as pause periods and group mobility encouragement, lacking for previous community-based mobility models. Additionally, ECMM enables researchers to arbitrarily select a social model as the trace generation process input, while at the same time generates traces with high conformance to that social network. A comparison between synthetic traces, generated by ECMM, other community-based models and a number of real ones is provided for validation.."
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 = [];
Q2 = [];
Q3 = [];
Q4 = [];
Q5 = [];
Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [1];
Q2 = [0];
Q3 = [0];
Q4 = [0];
Q5 = [];
Q6 = [1].
An enhanced community-based mobility model for distributed mobile social networks
Simulation is fundamental tool for the evaluation and validation of the applications and protocols in Mobile Social Networks. However, the limited number of real user traces available and the imposed restrictions of the specific scenarios, make generalization very hard. Therefore, the need has been created for synthetic mobility models. The widely used Random Way-Point Mobility Model has been proven unable to capture characteristics of human mobility such as the social attraction. Consequently, in recent years mobility models based on social network theory, able to capture the temporal and spatial dependencies of mobile social networks, are being designed. In this paper the Enhanced Community Mobility Model (ECMM) is introduced. It follows preceding community-based approaches, that map communities to a topological space. Its main contribution is the introduction of new features, such as pause periods and group mobility encouragement, lacking for previous community-based mobility models. Additionally, ECMM enables researchers to arbitrarily select a social model as the trace generation process input, while at the same time generates traces with high conformance to that social network. A comparison between synthetic traces, generated by ECMM, other community-based models and a number of real ones is provided for validation.