Spectra of simulated lightning on Venus,Jupiter, and Titan

Laser-induced plasmas in various gas mixtures were used to simulate lightning in other planetary atmospheres. This method of simulation has the advantage of producing short-duration, high-temperature plasmas free from electrode contamination. The laser-induced plasma discharges in air are shown to accurately simulate terrestrial lightning and can be expected to simulate lightning spectra in other planetary atmospheres. Spectra from 240 to 880 nm are presented for simulated lightning in the atmospheres of Venus, Earth, Jupiter, and Titan. The spectra of lightning on the other giant planets are expected to be similar to that of Jupiter because the atmospheres of these planets are composed mainly of hydrogen and helium. The spectra of Venus and Titan show substantial amounts of radiation due to the presence of carbon atoms and ions and show CN Violet radiation. Although small amounts of CH₄ and NH₃ are present in the Jovian atmosphere, only emission from hydrogen and helium is observed. Most differences in the spectra can be understood in terms of the elemental ratios of the gas mixtures. Consequently, observations of the spectra of lightning on other planets should provide in situ estimates of the atmospheric and aerosol composition in the cloud layers in which lightning is occuring. In particular, the detection of inert gases such as helium should be possible and the relative abundance of these gases compared to major constituents might be determined.     

Adaptive fisheries management in Vietnam: The use of indicators and the introduction of a multi-disciplinary Marine Fisheries Specialist Team to support implementation

Vietnam is in the process of introducing adaptive management based on indicators and time-series to manage its marine fisheries. The development of indicator-based frameworks for fisheries management has accelerated in recent years. This article describes the suite of indicators being suggested or used in Vietnam including the data-collection system. The Vietnamese approach is supported by an institutional structure consisting of a multi-disciplinary advisory system to facilitate the process of using indicators and to introduce knowledge-based management. The article concludes by identifying current problems and weaknesses and by providing suggestions for future improvement of the system.     

Why chromatic imaging matters

During the last two decades, the first generation of beam combiners at the Very Large Telescope Interferometer has proved the importance of optical interferometry for high-angular resolution astrophysical studies in the near- and mid-infrared. With the advent of 4-beam combiners at the VLTI, the u ? v coverage per pointing increases significantly, providing an opportunity to use reconstructed images as powerful scientific tools. Therefore, interferometric imaging is already a key feature of the new generation of VLTI instruments, as well as for other interferometric facilities like CHARA and JWST. It is thus imperative to account for the current image reconstruction capabilities and their expected evolutions in the coming years. Here, we present a general overview of the current situation of optical interferometric image reconstruction with a focus on new wavelength-dependent information, highlighting its main advantages and limitations. As an Appendix we include several cookbooks describing the usage and installation of several state-of-the art image reconstruction packages. To illustrate the current capabilities of the software available to the community, we recovered chromatic images, from simulated MATISSE data, using the MCMC software SQUEEZE. With these images, we aim at showing the importance of selecting good regularization functions and their impact on the reconstruction.     

Mining spatial associations between daily activities and health using EMA–GPS data

The geographical explicit ecological momentary assessment (GEMA) data collection platform provides extremely rich geospatial datasets and is very promising to gain behavior insights linking mobility, activities, and health. However, the task of analyzing these large datasets effectively is not straightforward, because they often involve a large multivariable dimension and rich qualitative data formats. Responding to the call for innovative analytic approaches in GIScience, this article advocates the use of spatial association rule mining (SARM) to extract frequent associations among daily activities, daily mobility, and health, including both physical health (e.g. pain) and mental health (e.g. happiness). This inductive mining approach works robustly with large datasets and is suitable for both qualitative and quantitative studies. A novel visualization technique to analyze the mined rules is also developed and presented.     

Hydrogeochemical Features of Thermal Waters of South Trungbo (Central Vietnam)

The results of studying the features of the hydrogeological structure and chemical and isotope composition of thermal waters from the central part of Vietnam that are characterized by intense manifestations of intrusive magmatism are presented. It is established that low–and high–thermal waters with temperature varying within 30–85°C are developed in the area under study. The value of total mineralization of the hydrotherms ranges from 0.05 to 10.05 g/dm³. It is assumed that the circulation of thermal waters that are different in temperature and chemical composition occurs at two levels. The regular change of the hydrotherm composition in the direction from mineralized chloride sodium, including with increased Ca content, to fresh sodium bicarbonate is revealed. The ratio of δ¹⁸O–δ²H isotopes indicates that the water component is based on meteoric water. In the coastal areas, there is an isotope shift towards the ocean waters, which is also confirmed by the hydrogeochemical data. The key factors for forming the chemical composition of the thermal waters in South Trungbo are their genetic type, the interaction processes in the “water–rock–gas–organic substance” system, and their equilibrium–nonequilibrium state.     

Simplified formulae for designing coastal forest against tsunami run-up: one-dimensional approach

In the present study, laboratory experiments were conducted to validate the applicability of a numerical model based on one-dimensional nonlinear long-wave equations. The model includes drag and inertia resistance of trees to tsunami flow and porosity between trees and a simplified forest in a wave channel. It was confirmed that the water surface elevation and flow velocity by the numerical simulations agree well with the experimental results for various forest conditions of width and tree density. Further, the numerical model was applied to prototype conditions of a coastal forest of Pandanus odoratissimus to investigate the effects of forest conditions (width and tree density) and incident tsunami conditions (period and height) on run-up height and potential tsunami force. The modeling results were represented in curve-fit equations with the aim of providing simplified formulae for designing coastal forest against tsunamis. The run-up height and potential tsunami forces calculated by the curve-fit formulae and the numerical model agreed within ± 10% error.     

Flood-prone area mapping using machine learning techniques: a case study of Quang Binh province,Vietnam

Natural Hazards - Vietnam’s central coastal region is the most vulnerable and always at flood risk, severely affecting people’s livelihoods and socio-economic development. In...     

Adaptive neuro-fuzzy inference system coupled with shuffled frog leaping algorithm for predicting river streamflow time series

ABSTRACT

Accurate runoff forecasting plays a key role in catchment water management and water resources system planning. To improve the prediction accuracy, one needs to strive to develop a reliable and accurate forecasting model for streamflow. In this study, the novel combination of the adaptive neuro-fuzzy inference system (ANFIS) model with the shuffled frog-leaping algorithm (SFLA) is proposed. Historical streamflow data of two different rivers were collected to examine the performance of the proposed model. To evaluate the performance of the proposed ANFIS-SFLA model, six different scenarios for the model input–output architecture were investigated. The results show that the proposed ANFIS-SFLA model (R² = 0.88; NS = 0.88; RMSE = 142.30 (m³/s); MAE = 88.94 (m³/s); MAPE = 35.19%) significantly improved the forecasting accuracy and outperformed the classic ANFIS model (R² = 0.83; NS = 0.83; RMSE = 167.81; MAE = 115.83 (m³/s); MAPE = 45.97%). The proposed model could be generalized and applied in different rivers worldwide.