scholarly journals Dispersibility of the Pale Grass Blue Butterfly Zizeeria maha (Lepidoptera: Lycaenidae) Revealed by One-Individual Tracking in the Field: Quantitative Comparisons between Subspecies and between Sexes

Insects ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 122
Author(s):  
Atsuki Hiyama ◽  
Joji M. Otaki
Keyword(s):  
Moving Average ◽  
Dispersal Distance ◽  
Environmental Indicator ◽  
Adult Lifespan ◽  
Starting Point ◽  
Moving Average Model ◽  
Pale Grass Blue Butterfly ◽  
Individual Tracking ◽  
The One ◽  
Blue Butterfly

The pale grass blue butterfly Zizeeria maha (Lepidoptera: Lycaenidae) has been used as an environmental indicator species for radioactive pollution after the Fukushima nuclear accident. Here, based on the one-individual tracking method in the field, we examined dispersal-associated and other behavioral traits of this butterfly, focusing on two subspecies, Z. maha argia in mainland Japan and Z. maha okinawana in Okinawa. The accumulated distances in the adult lifespan were 18.9 km and 38.2 km in mainland and Okinawa males, respectively, and 15.0 km and 7.8 km in mainland and Okinawa females, respectively. However, the mean distance from the starting point was only 24.2 m and 21.1 m in the mainland and Okinawa males, respectively, and 13.7 m and 7.4 m in the mainland and Okinawa females, respectively. Some quantitative differences in resting and feeding were found between subspecies and between sexes. The ARIMA (autoregressive integrated moving average) model indicated that the dispersal distance was 52.3 m (99% confidence interval value of 706.6 m) from the starting point in mainland males. These results support the idea that despite some behavioral differences, both subspecies of this butterfly are suitable as an environmental indicator because of the small dispersal ranges.

scholarly journals Highway Speed Prediction Using Gated Recurrent Unit Neural Networks

2021 ◽  
Vol 11 (7) ◽  
pp. 3059
Author(s):  
Myeong-Hun Jeong ◽  
Tae-Young Lee ◽  
Seung-Bae Jeon ◽  
Minkyo Youm
Keyword(s):  
Neural Network ◽  
Intelligent Transportation Systems ◽  
Moving Average ◽  
Computational Cost ◽  
Nonlinear Problems ◽  
Transportation Systems ◽  
Mobility Data ◽  
Challenges And Opportunities ◽  
Moving Average Model ◽  
Gated Recurrent Unit

Movement analytics and mobility insights play a crucial role in urban planning and transportation management. The plethora of mobility data sources, such as GPS trajectories, poses new challenges and opportunities for understanding and predicting movement patterns. In this study, we predict highway speed using a gated recurrent unit (GRU) neural network. Based on statistical models, previous approaches suffer from the inherited features of traffic data, such as nonlinear problems. The proposed method predicts highway speed based on the GRU method after training on digital tachograph data (DTG). The DTG data were recorded in one month, giving approximately 300 million records. These data included the velocity and locations of vehicles on the highway. Experimental results demonstrate that the GRU-based deep learning approach outperformed the state-of-the-art alternatives, the autoregressive integrated moving average model, and the long short-term neural network (LSTM) model, in terms of prediction accuracy. Further, the computational cost of the GRU model was lower than that of the LSTM. The proposed method can be applied to traffic prediction and intelligent transportation systems.

scholarly journals Practices of sustainability and the enactment of their natures/cultures: Ecosystem services, rights of nature, and geoengineering

2021 ◽  
pp. 053901842199894
Author(s):  
Frank Adloff ◽  
Iris Hilbrich
Keyword(s):  
Ecosystem Services ◽  
Latin American ◽  
Social Systems ◽  
The Earth ◽  
Starting Point ◽  
Knowledge Cultures ◽  
Rights Of Nature ◽  
Value Of Nature ◽  
The One ◽  
And Control

Possible trajectories of sustainability are based on different concepts of nature. The article starts out from three trajectories of sustainability (modernization, transformation and control) and reconstructs one characteristic practice for each path with its specific conceptions of nature. The notion that nature provides human societies with relevant ecosystem services is typical of the path of modernization. Nature is reified and monetarized here, with regard to its utility for human societies. Practices of transformation, in contrast, emphasize the intrinsic ethical value of nature. This becomes particularly apparent in discourses on the rights of nature, whose starting point can be found in Latin American indigenous discourses, among others. Control practices such as geoengineering are based on earth-systemic conceptions of nature, in which no distinction is made between natural and social systems. The aim is to control the earth system as a whole in order for human societies to remain viable. Practices of sustainability thus show different ontological understandings of nature (dualistic or monistic) on the one hand and (implicit) ethics and sacralizations (anthropocentric or biocentric) on the other. The three reconstructed natures/cultures have different ontological and ethical affinities and conflict with each other. They are linked to very different knowledge cultures and life-worlds, which answer very differently to the question of what is of value in a society and in nature and how these values ought to be protected.

scholarly journals Multi-Channel Singular Spectrum Analysis on Geocenter Motion and Its Precise Prediction

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1403
Author(s):  
Xin Jin ◽  
Xin Liu ◽  
Jinyun Guo ◽  
Yi Shen
Keyword(s):  
Solid Earth ◽  
Spectrum Analysis ◽  
Mean Squared Error ◽  
Moving Average ◽  
Singular Spectrum Analysis ◽  
Singular Spectrum ◽  
Autoregressive Moving Average Model ◽  
Seasonal Characteristics ◽  
Geocenter Motion ◽  
Moving Average Model

Geocenter is the center of the mass of the Earth system including the solid Earth, ocean, and atmosphere. The time-varying characteristics of geocenter motion (GCM) reflect the redistribution of the Earth’s mass and the interaction between solid Earth and mass loading. Multi-channel singular spectrum analysis (MSSA) was introduced to analyze the GCM products determined from satellite laser ranging data released by the Center for Space Research through January 1993 to February 2017 for extracting the periods and the long-term trend of GCM. The results show that the GCM has obvious seasonal characteristics of the annual, semiannual, quasi-0.6-year, and quasi-1.5-year in the X, Y, and Z directions, the annual characteristics make great domination, and its amplitudes are 1.7, 2.8, and 4.4 mm, respectively. It also shows long-period terms of 6.09 years as well as the non-linear trends of 0.05, 0.04, and –0.10 mm/yr in the three directions, respectively. To obtain real-time GCM parameters, the MSSA method combining a linear model (LM) and autoregressive moving average model (ARMA) was applied to predict GCM for 2 years into the future. The precision of predictions made using the proposed model was evaluated by the root mean squared error (RMSE). The results show that the proposed method can effectively predict GCM parameters, and the prediction precision in the three directions is 1.53, 1.08, and 3.46 mm, respectively.

scholarly journals Analysis and prediction of polar motion using MSSA method

2021 ◽  
Vol 73 (1) ◽  
Author(s):  
Xin Jin ◽  
Xin Liu ◽  
Jinyun Guo ◽  
Yi Shen
Keyword(s):  
Polar Motion ◽  
Rotation Axis ◽  
Moving Average ◽  
Singular Spectrum Analysis ◽  
Autoregressive Moving Average ◽  
Rotational Axis ◽  
Autoregressive Moving Average Model ◽  
System Service ◽  
Moving Average Model ◽  
Polar Motion Prediction

AbstractPolar motion is the movement of the Earth's rotational axis relative to its crust, reflecting the influence of the material exchange and mass redistribution of each layer of the Earth on the Earth's rotation axis. To better analyze the temporally varying characteristics of polar motion, multi-channel singular spectrum analysis (MSSA) was used to analyze the EOP 14 C04 series released by the International Earth Rotation and Reference System Service (IERS) from 1962 to 2020, and the amplitude of the Chandler wobbles were found to fluctuate between 20 and 200 mas and decrease significantly over the last 20 years. The amplitude of annual oscillation fluctuated between 60 and 120 mas, and the long-term trend was 3.72 mas/year, moving towards N56.79 °W. To improve prediction of polar motion, the MSSA method combining linear model and autoregressive moving average model was used to predict polar motion with ahead 1 year, repeatedly. Comparing to predictions of IERS Bulletin A, the results show that the proposed method can effectively predict polar motion, and the improvement rates of polar motion prediction for 365 days into the future were approximately 50% on average.

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