<|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:"Novel Multiplex Page Rank in Multilayer Networks."
Abstract:"Multilayer networks are described as complex networks in which each node is related to all other nodes in distinct layers. These layers form a class of cooperating and interacting networks. Examples of such multilayer networks are transport networks, where people can move from one city to another through various modes of transportation. The ranking of nodes in multilayer networks is one of the most challenging and demanding tasks on complex networks. Since pairs of nodes are related through various types of links in multilayers, the ranking of nodes should inevitably reveal the weights of nodes in all corresponding layers. In this paper, we exploit the concept of populations' random migration in a multiplex transport network to propose a new Multiplex PageRank centrality measure, where the effects of influence and feedback between networks on the centrality of nodes are directly considered. We apply the proposed measure to an artificial duplex network. Findings indicate that considering the network with multilayers helps uncover the rankings of nodes, which are different from the rankings in a monotonous network. Moreover, the Multiplex PageRank centrality measure of dynamical network models is discussed for further practical application and applied to an urban transport network. The results demonstrate the effectiveness of our measure in the dynamical network.."
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 = [];
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Q4 = [];
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Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [0];
Q2 = [];
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Q4 = [];
Q5 = [];
Q6 = [1].
Novel Multiplex Page Rank in Multilayer Networks
Multilayer networks are described as complex networks in which each node is related to all other nodes in distinct layers. These layers form a class of cooperating and interacting networks. Examples of such multilayer networks are transport networks, where people can move from one city to another through various modes of transportation. The ranking of nodes in multilayer networks is one of the most challenging and demanding tasks on complex networks. Since pairs of nodes are related through various types of links in multilayers, the ranking of nodes should inevitably reveal the weights of nodes in all corresponding layers. In this paper, we exploit the concept of populations' random migration in a multiplex transport network to propose a new Multiplex PageRank centrality measure, where the effects of influence and feedback between networks on the centrality of nodes are directly considered. We apply the proposed measure to an artificial duplex network. Findings indicate that considering the network with multilayers helps uncover the rankings of nodes, which are different from the rankings in a monotonous network. Moreover, the Multiplex PageRank centrality measure of dynamical network models is discussed for further practical application and applied to an urban transport network. The results demonstrate the effectiveness of our measure in the dynamical network.