<|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:"A route planning mechanism for supermarket shuttle service based on taxi traces."
Abstract:"With the rapid growth of retailing during the modernization of China, there is an increasing demand to improve the service quality of supermarkets. The supermarket shuttle service can have a direct impact on extending supermarket access, increasing shared transports, and improving customers' satisfaction. However, it is an open problem to probe the exact locations of potential customers and optimize the route for shuttle service. In this paper, we propose a route planning mechanism for supermarket shuttle service based on exploring the pick-up/drop-off information from large scale taxi GPS traces. Taxi GPS traces can inform us the human mobility patterns related to point of interests. Compared with traditional customer survey to collect information, the proposed approach can provide a more easy-to-deploy, efficient and effective solution. Based on the rich locational information of potential customers, we detect the most suitable bus stops of shuttle and optimize the mutes to maximize the benefits for all stakeholders. The experimental results on real-life taxi data demonstrate the applicability as well as effectiveness of the proposed approach and exhibit promising performance of improve the quality of supermarket shuttle service.."
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 = [0];
Q2 = [];
Q3 = [];
Q4 = [];
Q5 = [];
Q6 = [1].
A route planning mechanism for supermarket shuttle service based on taxi traces
With the rapid growth of retailing during the modernization of China, there is an increasing demand to improve the service quality of supermarkets. The supermarket shuttle service can have a direct impact on extending supermarket access, increasing shared transports, and improving customers' satisfaction. However, it is an open problem to probe the exact locations of potential customers and optimize the route for shuttle service. In this paper, we propose a route planning mechanism for supermarket shuttle service based on exploring the pick-up/drop-off information from large scale taxi GPS traces. Taxi GPS traces can inform us the human mobility patterns related to point of interests. Compared with traditional customer survey to collect information, the proposed approach can provide a more easy-to-deploy, efficient and effective solution. Based on the rich locational information of potential customers, we detect the most suitable bus stops of shuttle and optimize the mutes to maximize the benefits for all stakeholders. The experimental results on real-life taxi data demonstrate the applicability as well as effectiveness of the proposed approach and exhibit promising performance of improve the quality of supermarket shuttle service.