Communicating the amount of windstorm induced forest damage by the maximum wind gust speed in Finland

Abstract. Windstorms are natural disturbance agents in forests playing a role in natural forest regeneration. In Finland, the most severe individual windstorms have commonly damaged 2–4 million m3 of timber. In addition to financial losses caused to forest owners, windthrown trees have in many cases seriously disrupted the functionality of the national power grid. Communicating windstorm risks in duty forecasting is difficult. In this study, we aimed at developing windstorm impact estimates for forest damage in Finland to help the forecaster to improve communication of the risks of windstorms. We have compared the volume of forest damage caused by the most intense windstorms in Finland during the recent decade to the observed maximum inland wind gust speeds associated with the same windstorms. It was found out that the volume of forest damage follows approximately a power relation as a function of wind gust speed with a power of ∼10. This is a tentative estimate because of a short time series and small number of inspected windstorms. Moreover, also wind direction, location of the affected area and soil properties among other factors have an impact to the amount of damage as illustrated in our inspection. Despite the shortness of the time series, we believe that our results demonstrating the steep increase in the impacts of windstorms with an increasing windstorm intensity are valuable. However, more detailed investigations with longer time series are needed in order to more specifically communicate the windstorm risks and their impacts in boreal forests.

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A strategy for meta-analysis of short time series microarray datasets

Frontiers in Bioscience ◽

10.2741/3512 ◽

2009 ◽

Vol Volume (14) ◽

pp. 4058 ◽

Cited By ~ 2

Author(s):

Ruping Sun

Keyword(s):

Time Series ◽

Meta Analysis ◽

Short Time Series ◽

Microarray Datasets ◽

Short Time ◽

Time Series Microarray

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Identifying bidirectional total and non-linear information flow in functional corticomuscular coupling during a dorsiflexion task: a pilot study

Journal of NeuroEngineering and Rehabilitation ◽

10.1186/s12984-021-00872-w ◽

2021 ◽

Vol 18 (1) ◽

Author(s):

Tie Liang ◽

Qingyu Zhang ◽

Xiaoguang Liu ◽

Bin Dong ◽

Xiuling Liu ◽

...

Keyword(s):

Time Series ◽

Information Flow ◽

Gamma Band ◽

Motor Dysfunction ◽

Beta Band ◽

Short Time Series ◽

Information Interaction ◽

Stroke Group ◽

Short Time ◽

Maximal Information Coefficient

Abstract Background The key challenge to constructing functional corticomuscular coupling (FCMC) is to accurately identify the direction and strength of the information flow between scalp electroencephalography (EEG) and surface electromyography (SEMG). Traditional TE and TDMI methods have difficulty in identifying the information interaction for short time series as they tend to rely on long and stable data, so we propose a time-delayed maximal information coefficient (TDMIC) method. With this method, we aim to investigate the directional specificity of bidirectional total and nonlinear information flow on FCMC, and to explore the neural mechanisms underlying motor dysfunction in stroke patients. Methods We introduced a time-delayed parameter in the maximal information coefficient to capture the direction of information interaction between two time series. We employed the linear and non-linear system model based on short data to verify the validity of our algorithm. We then used the TDMIC method to study the characteristics of total and nonlinear information flow in FCMC during a dorsiflexion task for healthy controls and stroke patients. Results The simulation results showed that the TDMIC method can better detect the direction of information interaction compared with TE and TDMI methods. For healthy controls, the beta band (14–30 Hz) had higher information flow in FCMC than the gamma band (31–45 Hz). Furthermore, the beta-band total and nonlinear information flow in the descending direction (EEG to EMG) was significantly higher than that in the ascending direction (EMG to EEG), whereas in the gamma band the ascending direction had significantly higher information flow than the descending direction. Additionally, we found that the strong bidirectional information flow mainly acted on Cz, C3, CP3, P3 and CPz. Compared to controls, both the beta-and gamma-band bidirectional total and nonlinear information flows of the stroke group were significantly weaker. There is no significant difference in the direction of beta- and gamma-band information flow in stroke group. Conclusions The proposed method could effectively identify the information interaction between short time series. According to our experiment, the beta band mainly passes downward motor control information while the gamma band features upward sensory feedback information delivery. Our observation demonstrate that the center and contralateral sensorimotor cortex play a major role in lower limb motor control. The study further demonstrates that brain damage caused by stroke disrupts the bidirectional information interaction between cortex and effector muscles in the sensorimotor system, leading to motor dysfunction.

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Improved Lempel-Ziv Algorithm Based on Complexity Measurement of Short Time Series

Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007) ◽

10.1109/fskd.2007.357 ◽

2007 ◽

Cited By ~ 4

Author(s):

Feng-tao Liu ◽

Yong Tang

Keyword(s):

Time Series ◽

Short Time Series ◽

Complexity Measurement ◽

Short Time

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A reliable measure of similarity based on dependency for short time series: an application to gene expression networks

BMC Bioinformatics ◽

10.1186/1471-2105-10-270 ◽

2009 ◽

Vol 10 (1) ◽

pp. 270 ◽

Cited By ~ 1

Author(s):

Mônica G Campiteli ◽

Frederico M Soriani ◽

Iran Malavazi ◽

Osame Kinouchi ◽

Carlos AB Pereira ◽

...

Keyword(s):

Gene Expression ◽

Time Series ◽

Reliable Measure ◽

Short Time Series ◽

Measure Of Similarity ◽

Short Time

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LIMITATIONS OF THE PANEL REGRESSION MODEL APPLICATION: THE EXAMPLE OF THE WESTERN BALKAN COUNTRIES

ACTA ECONOMICA ◽

10.7251/ace2032151b ◽

2021 ◽

Vol 18 (32) ◽

Author(s):

Stanko Stanić ◽

Bojan Baškot

Keyword(s):

Time Series ◽

Regression Model ◽

Time Frame ◽

Panel Regression ◽

Time Dimension ◽

Data Set ◽

Short Time Series ◽

Western Balkan Region ◽

Balkan Region ◽

Short Time

Panel regression model may seem like an appealing solution in conditions of limited time series. This is often used as a shortcut to achieve deeper data set by setting several individual cases on the same time dimension, where cross units visually but not really multiply a time frame. Macroeconometrics of the Western Balkan region assumes short time series issue. Additionally, the structural brakes are numerous. Panel regression may seem like a solution, but there are some limitations that should be considered.

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