<|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:"UrbanMobilitySense: A User-Centric Participatory Sensing System for Transportation Activity Surveys."
Abstract:"Transportation activity surveys collect the travel behavior of people, including when, where, and how they travel for urban planning purposes. Traditionally, transportation activity surveys are carried out using conventional questionaires, which are labor intensive and error prone. In this paper, we have developed a smartphone-based mobility sensing system, called UrbanMobilitySense, which captures human mobility information automatically to conduct transportation activity surveys. The UrbanMobilitySense system was designed to address two critical issues: 1) energy conservation and 2) privacy preservation. To optimize the energy utilization of smartphone, we avoid using the GPS sensor when the user is at long-stay places and filter out redundant data before data uploading. To preserve personal privacy, each smartphone maintains the user's long-stay places by two separate profiles: 1) private place profile and 2) public place profile. The former maintains the privacy-preserved places (e. g., home), whereas the latter maintains the public places (e. g., parks). We implement the UrbanMobilitySense system to conduct real-world transportation activity surveys, study the performance of our system through extensive experiments, and analyze the computational complexity of the proposed algorithms. The outcome of our work has been deployed in Singapore to support the Land Transport Authority's transportation activity surveys.."
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:
Q1 = [0];
Q2 = [];
Q3 = [];
Q4 = [];
Q5 = [1];
Q6 = [1].
UrbanMobilitySense: A User-Centric Participatory Sensing System for Transportation Activity Surveys
Transportation activity surveys collect the travel behavior of people, including when, where, and how they travel for urban planning purposes. Traditionally, transportation activity surveys are carried out using conventional questionaires, which are labor intensive and error prone. In this paper, we have developed a smartphone-based mobility sensing system, called UrbanMobilitySense, which captures human mobility information automatically to conduct transportation activity surveys. The UrbanMobilitySense system was designed to address two critical issues: 1) energy conservation and 2) privacy preservation. To optimize the energy utilization of smartphone, we avoid using the GPS sensor when the user is at long-stay places and filter out redundant data before data uploading. To preserve personal privacy, each smartphone maintains the user's long-stay places by two separate profiles: 1) private place profile and 2) public place profile. The former maintains the privacy-preserved places (e. g., home), whereas the latter maintains the public places (e. g., parks). We implement the UrbanMobilitySense system to conduct real-world transportation activity surveys, study the performance of our system through extensive experiments, and analyze the computational complexity of the proposed algorithms. The outcome of our work has been deployed in Singapore to support the Land Transport Authority's transportation activity surveys.