The number of topics perplexity curve.

Three evident and meaningful characteristics of disruptive technology are the zeroing effect that causes sustaining technology useless for its remarkable and unprecedented progress, reshaping the landscape of technology and economy, and leading the future mainstream of technology system, all of which have profound impacts and positive influences. The identification of disruptive technology is a universally difficult task. Therefore, this paper aims to enhance the technical relevance of potential disruptive technology identification results and improve the granularity and effectiveness of potential disruptive technology identification topics. According to the life cycle theory, dividing the time stage, then constructing and analyzing the dynamic of technology networks to identify potential disruptive technology. Thereby, using the Latent Dirichlet Allocation (LDA) topic model further to clarify the topic content of potential disruptive technologies. This paper takes the large civil unmanned aerial vehicles (UAVs) as an example to prove the feasibility and effectiveness of the model. The results show that the potential disruptive technology in this field is the data acquisition, main equipment, and ground platform intelligence.</div

Intertopic distance map.

Three evident and meaningful characteristics of disruptive technology are the zeroing effect that causes sustaining technology useless for its remarkable and unprecedented progress, reshaping the landscape of technology and economy, and leading the future mainstream of technology system, all of which have profound impacts and positive influences. The identification of disruptive technology is a universally difficult task. Therefore, this paper aims to enhance the technical relevance of potential disruptive technology identification results and improve the granularity and effectiveness of potential disruptive technology identification topics. According to the life cycle theory, dividing the time stage, then constructing and analyzing the dynamic of technology networks to identify potential disruptive technology. Thereby, using the Latent Dirichlet Allocation (LDA) topic model further to clarify the topic content of potential disruptive technologies. This paper takes the large civil unmanned aerial vehicles (UAVs) as an example to prove the feasibility and effectiveness of the model. The results show that the potential disruptive technology in this field is the data acquisition, main equipment, and ground platform intelligence.</div

Potential disruptive technology identification flow chart.

Potential disruptive technology identification flow chart.</p

Tree Radial Growth Responses to Climate and Reservoir Impoundment in Valleys in Southwestern China

Southwestern China is a critical biodiversity hotspot area, and many large hydroelectric projects have been established in the valleys in the region. Tree growth in the valleys will be affected by both regional climate and reservoir impoundment. However, it remains unknown whether the radial growth of trees in the valleys has a common response pattern to the regional climate, and it is also unclear whether the response of radial growth to reservoir impoundment can be detected. In this study, we developed tree-ring width chronologies of Pinus yunnanensis Franch. collected at 11 sites with vertical and horizontal gradients to three hydroelectric reservoirs in three riverine valleys in southwestern China. We analyzed the radial growth responses to the regional climate from 1986 to 2017 by correlation with instrumental meteorological data. Tree growth responses to reservoir impoundment were investigated through spatial and temporal comparisons using the change in the Euclidean distance and difference test. We also distinguished their responses at tree-ring sites without influenced by reservoir impoundment including two sites in the valleys and seven sites at high elevations. The results showed that the climate conditions in May and the dry season before the growth season significantly limit the radial growth in the valleys, which is different to that at high-elevation areas in southwestern China. Growth variations in the valleys are related to elevations and the trees in similar slopes positions exhibit similar responses. For trees in the low slope positions, both variance and mean values of radial growth are affected by reservoir impoundment. Trees at relatively low sites (i.e., sites M2, R2, L2), rather than the trees close to the reservoirs (i.e., sites M1, R1, L1), respond more sensitively to reservoir impoundment

The calculation results of each IPC node location index.

The calculation results of each IPC node location index.</p

Potential disruptive technology topics.

Three evident and meaningful characteristics of disruptive technology are the zeroing effect that causes sustaining technology useless for its remarkable and unprecedented progress, reshaping the landscape of technology and economy, and leading the future mainstream of technology system, all of which have profound impacts and positive influences. The identification of disruptive technology is a universally difficult task. Therefore, this paper aims to enhance the technical relevance of potential disruptive technology identification results and improve the granularity and effectiveness of potential disruptive technology identification topics. According to the life cycle theory, dividing the time stage, then constructing and analyzing the dynamic of technology networks to identify potential disruptive technology. Thereby, using the Latent Dirichlet Allocation (LDA) topic model further to clarify the topic content of potential disruptive technologies. This paper takes the large civil unmanned aerial vehicles (UAVs) as an example to prove the feasibility and effectiveness of the model. The results show that the potential disruptive technology in this field is the data acquisition, main equipment, and ground platform intelligence.</div

The first stage of the technology network.

Three evident and meaningful characteristics of disruptive technology are the zeroing effect that causes sustaining technology useless for its remarkable and unprecedented progress, reshaping the landscape of technology and economy, and leading the future mainstream of technology system, all of which have profound impacts and positive influences. The identification of disruptive technology is a universally difficult task. Therefore, this paper aims to enhance the technical relevance of potential disruptive technology identification results and improve the granularity and effectiveness of potential disruptive technology identification topics. According to the life cycle theory, dividing the time stage, then constructing and analyzing the dynamic of technology networks to identify potential disruptive technology. Thereby, using the Latent Dirichlet Allocation (LDA) topic model further to clarify the topic content of potential disruptive technologies. This paper takes the large civil unmanned aerial vehicles (UAVs) as an example to prove the feasibility and effectiveness of the model. The results show that the potential disruptive technology in this field is the data acquisition, main equipment, and ground platform intelligence.</div