Environmental concentrations as ratios of random variables

Human-induced environmental change increasingly threatens the stability of socio-ecological systems. Careful statistical characterization of environmental concentrations is critical to quantify and predict the consequences of such changes on human and ecosystems conditions. However, while concentrations are naturally defined as the ratio between solute mass and solvent volume, they have rarely been treated as such, typically limiting the analysis to familiar distributions generically used for any other environmental variable. To address this gap, we propose a more general framework that leverages their definition explicitly as ratios of random variables. We show that the resulting models accurately describe the behavior of nitrate plus nitrite in US rivers and salt concentration in estuaries in the Everglades by accounting for heavy tails potentially emerging when the water volume fluctuates around low values. Models that preclude the presence of heavy tails and the related high probability of extreme concentrations could significantly undermine the accuracy of diagnostic frameworks and the effectiveness of mitigation interventions, especially for soil contamination characterized by a water volume (i.e., soil moisture) frequently approaching zero.

Railway Track Recognition Based on Radar Cross-Section Statistical Characterization Using mmWave Radar

The track settlement has a great influence on the safe operation of high-speed trains. The existing track settlement measurement approach requires sophisticated or expensive equipments, and the real-time performance is limited. To address the issue, an ultra-high resolution track settlement detection method is proposed by using millimeter wave radar based on frequency modulated continuous wave (FMCW). Firstly, by constructing the RCS statistical feature data set of multiple objects in the track settlement measurement environment, a directed acyclic graph-support vector machine (DAG-SVM) based method is designed to solve the problem of track recognition in multi-object scenes. Then, the adaptive chirp-z-transform (ACZT) algorithm is used to estimate the distance between the radar and the track surface, which realizes automatic real-time track settlement detection. An experimental platform has been constructed to verify the effectiveness of the proposed method. The experimental results show that the accuracy of track classification and identification is at least 95%, and the accuracy of track settlement measurement exceeds 0.5 mm, which completely meets the accuracy requirements of the railway system.

SELF v1.0: a minimal physical model for predicting time of freeze-up in lakes

Predicting the freezing time in lakes is achieved by means of complex mechanistic models or by simplified statistical regressions considering integral quantities. Here, we propose a minimal model (SELF) built on sound physical grounds that focuses on the pre-freezing period that goes from mixed conditions (lake temperature at 4 ∘C) to the formation of ice (0 ∘C at the surface) in dimictic lakes. The model is based on the energy balance involving the two main processes governing the inverse stratification dynamics: cooling of water due to heat loss and wind-driven mixing of the surface layer. They play opposite roles in determining the time required for ice formation and contribute to the large interannual variability observed in ice phenology. More intense cooling does indeed accelerate the rate of decrease of lake surface water temperature (LSWT), while stronger wind deepens the surface layer, increasing the heat capacity and thus reducing the rate of decrease of LSWT. A statistical characterization of the process is obtained with a Monte Carlo simulation considering random sequences of the energy fluxes. The results, interpreted through an approximate analytical solution of the minimal model, elucidate the general tendency of the system, suggesting a power law dependence of the pre-freezing duration on the energy fluxes. This simple yet physically based model is characterized by a single calibration parameter, the efficiency of the wind energy transfer to the change of potential energy in the lake. Thus, SELF can be used as a prognostic tool for the phenology of lake freezing.

The Relationship Between The Atlantic Multidecadal Oscillation and The Urucuia Aquifer System Recharge

This study investigates and detects links between the precipitation characteristics with meteorological systems and teleconnections around the Urucuia Aquifer System (UAS). Several studies show the influence of meteorological systems and teleconnections on the volume and intensity of precipitation in South America, mainly the Atlantic Multidecadal Oscillation (AMO), the El Niño South Oscillation (ENSO), and the Pacific Decadal Oscillations (PDO). Then, the precipitation series’ statistical characterization impacted the aquifer system’s recharge from 1973 to 2006. Monthly and annual series were analyzed and tested the correlation analysis with the indexes of the AMO, PDO, and ENSO. Finally, the series of maximum daily rainfall on the UAS was determined, and the 15 largest events were chosen to analyze the retroactive trajectories of air masses and thus try to estimate which atmospheric systems was acting and their origin. It concluded that the total annual precipitation data indicated a decreasing linear trend and that external climatic phenomena can influence precipitation characteristics. The correlation with the AMO index revealed a potential teleconectivity between climate circulation patterns with average annual precipitation over the UAS (p-value ≤ 0.03). Moreover, the analysing of precipitation trajectories observed a greater amount of specific humidity in the atmosphere during the AMO negative period concerning the AMO positive period. Also, the negative AMO phase’s trajectories had higher latitudes closer to the Intertropical Convergence Zone, as opposed to the positive AMO phase, where the trajectory altitudes were lower and closer to the Capricorn tropic.

An Alternative Statistical Characterization of TWDP Fading Model

Two-wave with diffuse power (TWDP) is one of the most promising models for the description of small-scale fading effects in 5G networks, which employs mmWave band, and in wireless sensor networks deployed in different cavity environments. However, its current statistical characterization has several fundamental issues. Primarily, conventional TWDP parameterization is not in accordance with the model’s underlying physical mechanisms. In addition, available TWDP expressions for PDF, CDF, and MGF are given either in integral or approximate forms, or as mathematically untractable closed-form expressions. Consequently, the existing TWDP statistical characterization does not allow accurate evaluation of system performance in all fading conditions for most modulation and diversity techniques. In this regard, physically justified TWDP parameterization is proposed and used for further calculations. Additionally, exact infinite-series PDF and CDF are introduced. Based on these expressions, the exact MGF of the SNR is derived in a form suitable for mathematical manipulations. The applicability of the proposed MGF for derivation of the exact average symbol error probability (ASEP) is demonstrated with the example of M-ary PSK modulation. The derived M-ary PSK ASEP expression is further simplified for large SNR values in order to obtain a closed-form asymptotic ASEP, which is shown to be applicable for SNR > 20 dB. All proposed expressions are verified by Monte Carlo simulation in a variety of TWDP fading conditions.

Assessing the Safety of Express Bus in Malaysia from Bus Operators’ Perspective

Express buses provide cheap and convenient services for long distance travelling. However, the safety aspect of express buses is a primary concern for passengers. The government and the private sector have contributed in improving the safety level of express buses. However, the accident and death rates involving express buses remains at a high level. There is a lack of detailed analysis regarding express bus accidents from the perspective of bus operators. Thus, this study was conducted to identify the causes of express bus accidents, characterize the statistical factors of express bus accidents and evaluate the safety of express buses in Malaysia from the perspectives of bus operators. The methodology consists of a survey conducted among staffs serving express bus operators located at the Terminal Bersepadu Selatan, Kuala Lumpur, Malaysia. The results showed that from bus operators’ perspective, road factors are the main contributors to the factors of occurrence of express bus accidents. In conclusion, the statistical characterization of accident causes has been determined and this can contribute in helping the bus operators and the community reduce express bus accidents and increase overall safety.